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        <title><![CDATA[Computers Don't Byte]]></title>
        <link>https://app.springcast.fm/podcast/computers-dont-byte</link>
        <language>nl</language>
        <copyright><![CDATA[LIACS]]></copyright>
        <itunes:subtitle><![CDATA[Computer scientists who are at the forefront of their respected fields attempt to explain what on earth they're doing.]]></itunes:subtitle>
        <itunes:author>LIACS</itunes:author>
        <itunes:summary>
            <![CDATA[Computer scientists who are at the forefront of their respected fields attempt to explain what on earth they&#039;re doing.Computers don&#039;t byte is a series by the Leiden Institute of Advanced Computer Science (LIACS). Leading computer scientists from a variety of fields share their expertise and insights. Dive into the minds of these researchers and learn about real-world applications, the future of AI and related technologies and cutting-edge research. From chatbots to cybersecurity, from quantum to children&#039;s stories, each episode offers its own perspective on the changing landscape of computer science. Whether you&#039;re a seasoned professional or an aspiring enthusiast, this podcast offers knowledge and inspiration.Content: LIACSHost: Michiel van PoelgeestProduced by: Studio Onzichtbaar
            ]]>
        </itunes:summary>
        <itunes:owner>
            <itunes:name>LIACS</itunes:name>
            <itunes:email>hallo@studioonzichtbaar.nl</itunes:email>
        </itunes:owner>
        <itunes:type>episodic</itunes:type>
        <itunes:explicit>no</itunes:explicit>
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                                            <itunes:category text="Science"/>
                                                        <itunes:category text="Science">
                    <itunes:category
                        text="Mathematics"/>
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                            <description>
            <![CDATA[<p>Computer scientists who are at the forefront of their respected fields attempt to explain what on earth they're doing.</p><p>Computers don't byte is a series by the Leiden Institute of Advanced Computer Science (LIACS). Leading computer scientists from a variety of fields share their expertise and insights. Dive into the minds of these researchers and learn about real-world applications, the future of AI and related technologies and cutting-edge research. From chatbots to cybersecurity, from quantum to children's stories, each episode offers its own perspective on the changing landscape of computer science. Whether you're a seasoned professional or an aspiring enthusiast, this podcast offers knowledge and inspiration.</p><p>Content: <a href="https://liacs.leidenuniv.nl" target="_blank">LIACS</a></p><p>Host: Michiel van Poelgeest</p><p>Produced by: <a href="https://studioonzichtbaar.nl" target="_blank" style="font-family: sans-serif;">Studio Onzichtbaar</a></p>
            ]]>
        </description>
        <description_podcast_stripped>
            <![CDATA[Computer scientists who are at the forefront of their respected fields attempt to explain what on earth they're doing.Computers don't byte is a series by the Leiden Institute of Advanced Computer Science (LIACS). Leading computer scientists from a variety of fields share their expertise and insights. Dive into the minds of these researchers and learn about real-world applications, the future of AI and related technologies and cutting-edge research. From chatbots to cybersecurity, from quantum to children's stories, each episode offers its own perspective on the changing landscape of computer science. Whether you're a seasoned professional or an aspiring enthusiast, this podcast offers knowledge and inspiration.Content: LIACSHost: Michiel van PoelgeestProduced by: Studio Onzichtbaar
            ]]>
        </description_podcast_stripped>
                                                                            <item>
                    <episode_id>186747</episode_id>
                    <title>Mike Preuss: Beyond entertainment, the science of games</title>
                    <itunes:title>Mike Preuss: Beyond entertainment, the science of games
                    </itunes:title>
                    <link>https://app.springcast.fm/19948/preuss</link>
                    <description>
                        <![CDATA[<p>Game AI expert Mike Preuss takes us from the world of Go‑playing algorithms to cutting‑edge chemistry. Hear how Monte Carlo Tree Search, the technique behind AlphaGo, helped enable the first fully automated method for chemical retrosynthesis—an achievement published in Nature.<br><br>The Game Lab that Mike runs at LIACS improves game mechanics, collaborates across disciplines, and uses games for education, psychology, and even language learning. From smarter strategy units to serious games that train pilots, this episode shows why games—and game AI—matter far beyond entertainment.<br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p>
                        ]]>
                    </description>
                    <description_item_stripped>
                        <![CDATA[Game AI expert Mike Preuss takes us from the world of Go‑playing algorithms to cutting‑edge chemistry. Hear how Monte Carlo Tree Search, the technique behind AlphaGo, helped enable the first fully automated method for chemical retrosynthesis—an achievement published in Nature.The Game Lab that Mike runs at LIACS improves game mechanics, collaborates across disciplines, and uses games for education, psychology, and even language learning. From smarter strategy units to serious games that train pilots, this episode shows why games—and game AI—matter far beyond entertainment.Idea by Dimitra KouimtzidouResearch, planning & coordination by Marcel Tichelaar & Dimitra KouimtzidouInterview, production & editing by Michiel van Poelgeest
                        ]]>
                    </description_item_stripped>
                    <itunes:summary>
                        <![CDATA[<p>Game AI expert Mike Preuss takes us from the world of Go‑playing algorithms to cutting‑edge chemistry. Hear how Monte Carlo Tree Search, the technique behind AlphaGo, helped enable the first fully automated method for chemical retrosynthesis—an achievement published in Nature.<br><br>The Game Lab that Mike runs at LIACS improves game mechanics, collaborates across disciplines, and uses games for education, psychology, and even language learning. From smarter strategy units to serious games that train pilots, this episode shows why games—and game AI—matter far beyond entertainment.<br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p>
                        ]]>
                    </itunes:summary>
                    <itunes:subtitle><![CDATA[]]>
                    </itunes:subtitle>
                    <itunes:author>LIACS</itunes:author>
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                    <guid>https://app.springcast.fm/19948/preuss</guid>
                    <pubDate>Tue, 14 Apr 2026 05:00:00 +0200</pubDate>
                    <pubDate_friendly>Tuesday 14 Apr 2026</pubDate_friendly>
                    <pubDate_sortable>2026-04-14 05:00:00</pubDate_sortable>
                    <itunes:episode>23</itunes:episode>
                    <itunes:season>3</itunes:season>
                    <itunes:explicit>no</itunes:explicit>
                    <itunes:duration>0:18:08</itunes:duration>
                </item>
                                                <item>
                    <episode_id>186746</episode_id>
                    <title>Eleftheria Makri: Rethinking privacy in a data-driven world</title>
                    <itunes:title>Eleftheria Makri: Rethinking privacy in a data-driven world
                    </itunes:title>
                    <link>https://app.springcast.fm/19948/makri</link>
                    <description>
                        <![CDATA[<p>In this episode, assistant professor Eleftheria Makri takes us from a classic 1980s cryptography puzzle to today’s urgent questions about data privacy, secure computation, and the looming impact of quantum computing. Through clear examples—from billionaire dinner bills to medical diagnostics—she shows how we can extract useful insights from data without ever exposing the data itself.<br><br>Makri explains why privacy isn’t about secrecy but about control, and how secure computation can unlock collaboration in fields like healthcare and finance without exposing sensitive data. She also highlights the urgency of preparing for a post‑quantum world, where today’s encrypted information could become tomorrow’s open book.<br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p>
                        ]]>
                    </description>
                    <description_item_stripped>
                        <![CDATA[In this episode, assistant professor Eleftheria Makri takes us from a classic 1980s cryptography puzzle to today’s urgent questions about data privacy, secure computation, and the looming impact of quantum computing. Through clear examples—from billionaire dinner bills to medical diagnostics—she shows how we can extract useful insights from data without ever exposing the data itself.Makri explains why privacy isn’t about secrecy but about control, and how secure computation can unlock collaboration in fields like healthcare and finance without exposing sensitive data. She also highlights the urgency of preparing for a post‑quantum world, where today’s encrypted information could become tomorrow’s open book.Idea by Dimitra KouimtzidouResearch, planning & coordination by Marcel Tichelaar & Dimitra KouimtzidouInterview, production & editing by Michiel van Poelgeest
                        ]]>
                    </description_item_stripped>
                    <itunes:summary>
                        <![CDATA[<p>In this episode, assistant professor Eleftheria Makri takes us from a classic 1980s cryptography puzzle to today’s urgent questions about data privacy, secure computation, and the looming impact of quantum computing. Through clear examples—from billionaire dinner bills to medical diagnostics—she shows how we can extract useful insights from data without ever exposing the data itself.<br><br>Makri explains why privacy isn’t about secrecy but about control, and how secure computation can unlock collaboration in fields like healthcare and finance without exposing sensitive data. She also highlights the urgency of preparing for a post‑quantum world, where today’s encrypted information could become tomorrow’s open book.<br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p>
                        ]]>
                    </itunes:summary>
                    <itunes:subtitle><![CDATA[]]>
                    </itunes:subtitle>
                    <itunes:author>LIACS</itunes:author>
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                    <itunes:episodeType>full</itunes:episodeType>
                    <guid>https://app.springcast.fm/19948/makri</guid>
                    <pubDate>Tue, 31 Mar 2026 05:00:00 +0200</pubDate>
                    <pubDate_friendly>Tuesday 31 Mar 2026</pubDate_friendly>
                    <pubDate_sortable>2026-03-31 05:00:00</pubDate_sortable>
                    <itunes:episode>22</itunes:episode>
                    <itunes:season>3</itunes:season>
                    <itunes:explicit>no</itunes:explicit>
                    <itunes:duration>0:19:34</itunes:duration>
                </item>
                                                <item>
                    <episode_id>186341</episode_id>
                    <title>Henning Basold: from biology to rockets, the science of systems</title>
                    <itunes:title>Henning Basold: from biology to rockets, the science of systems
                    </itunes:title>
                    <link>https://app.springcast.fm/19948/henning-basold-from-biology-to-rockets-the-science-of-systems</link>
                    <description>
                        <![CDATA[<p>All systems are go! Assistant professor Henning Basold guides us through the fascinating world of systems—from the biological structures that make us who we are to the complex cyber‑physical systems behind rockets, trains, and self‑driving cars.  </p><p>How do category theory, logic, and formal verification help us understand, model, and secure the technologies we rely on every day. Why do systems fail? How can we prove they’re safe? And what does it take to describe the world mathematically? Tune in for a thought‑provoking journey into the hidden structures that shape the world around us.<br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p>
                        ]]>
                    </description>
                    <description_item_stripped>
                        <![CDATA[All systems are go! Assistant professor Henning Basold guides us through the fascinating world of systems—from the biological structures that make us who we are to the complex cyber‑physical systems behind rockets, trains, and self‑driving cars.  How do category theory, logic, and formal verification help us understand, model, and secure the technologies we rely on every day. Why do systems fail? How can we prove they’re safe? And what does it take to describe the world mathematically? Tune in for a thought‑provoking journey into the hidden structures that shape the world around us.Idea by Dimitra KouimtzidouResearch, planning & coordination by Marcel Tichelaar & Dimitra KouimtzidouInterview, production & editing by Michiel van Poelgeest
                        ]]>
                    </description_item_stripped>
                    <itunes:summary>
                        <![CDATA[<p>All systems are go! Assistant professor Henning Basold guides us through the fascinating world of systems—from the biological structures that make us who we are to the complex cyber‑physical systems behind rockets, trains, and self‑driving cars.  </p><p>How do category theory, logic, and formal verification help us understand, model, and secure the technologies we rely on every day. Why do systems fail? How can we prove they’re safe? And what does it take to describe the world mathematically? Tune in for a thought‑provoking journey into the hidden structures that shape the world around us.<br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p>
                        ]]>
                    </itunes:summary>
                    <itunes:subtitle><![CDATA[]]>
                    </itunes:subtitle>
                    <itunes:author>LIACS</itunes:author>
                    <itunes:image
                        href="https://app.springcast.fm/storage/artwork/7022/19948/186341/Dd8NDNsGalrdM1mSG6CiSJO3KeqtcT8k038SslVj.jpg"/>
                    <enclosure
                        url="https://app.springcast.fm/download/186341/fRzJvjaM7dLS4K5zP1GbRdMjBubr1hJN.mp3"
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                    <itunes:episodeType>full</itunes:episodeType>
                    <guid>https://app.springcast.fm/19948/henning-basold-from-biology-to-rockets-the-science-of-systems</guid>
                    <pubDate>Mon, 16 Mar 2026 03:00:00 +0100</pubDate>
                    <pubDate_friendly>Monday 16 Mar 2026</pubDate_friendly>
                    <pubDate_sortable>2026-03-16 03:00:00</pubDate_sortable>
                    <itunes:episode>21</itunes:episode>
                    <itunes:season>3</itunes:season>
                    <itunes:explicit>no</itunes:explicit>
                    <itunes:duration>0:21:45</itunes:duration>
                </item>
                                                <item>
                    <episode_id>184908</episode_id>
                    <title>Rita Pucci: Reading the stripes, AI meets wildlife</title>
                    <itunes:title>Rita Pucci: Reading the stripes, AI meets wildlife
                    </itunes:title>
                    <link>https://app.springcast.fm/19948/rita-pucci-reading-the-stripes-ai-meets-wildlife</link>
                    <description>
                        <![CDATA[<p>What’s the difference between a zebra and a zebrafish? Assistant professor Rita Pucci, who works at both LIACS and Naturalis, brings together biodiversity and computer science. She’s developing a model that can recognise unique skin patterns of individual animals within a herd: a breakthrough that could transform how wildlife is monitored.</p><p>It could also reveal whether inbreeding is occurring—crucial information for species like zebras, where inbreeding can have devastating consequences. But before the model can reliably identify patterns in zebra coats, it first needs to learn how to generate patterns itself. And for that, it is trained on thousands of images of zebrafish.<br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p>
                        ]]>
                    </description>
                    <description_item_stripped>
                        <![CDATA[What’s the difference between a zebra and a zebrafish? Assistant professor Rita Pucci, who works at both LIACS and Naturalis, brings together biodiversity and computer science. She’s developing a model that can recognise unique skin patterns of individual animals within a herd: a breakthrough that could transform how wildlife is monitored.It could also reveal whether inbreeding is occurring—crucial information for species like zebras, where inbreeding can have devastating consequences. But before the model can reliably identify patterns in zebra coats, it first needs to learn how to generate patterns itself. And for that, it is trained on thousands of images of zebrafish.Idea by Dimitra KouimtzidouResearch, planning & coordination by Marcel Tichelaar & Dimitra KouimtzidouInterview, production & editing by Michiel van Poelgeest
                        ]]>
                    </description_item_stripped>
                    <itunes:summary>
                        <![CDATA[<p>What’s the difference between a zebra and a zebrafish? Assistant professor Rita Pucci, who works at both LIACS and Naturalis, brings together biodiversity and computer science. She’s developing a model that can recognise unique skin patterns of individual animals within a herd: a breakthrough that could transform how wildlife is monitored.</p><p>It could also reveal whether inbreeding is occurring—crucial information for species like zebras, where inbreeding can have devastating consequences. But before the model can reliably identify patterns in zebra coats, it first needs to learn how to generate patterns itself. And for that, it is trained on thousands of images of zebrafish.<br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p>
                        ]]>
                    </itunes:summary>
                    <itunes:subtitle><![CDATA[Scanning nature's barcode]]>
                    </itunes:subtitle>
                    <itunes:author>LIACS</itunes:author>
                    <itunes:image
                        href="https://app.springcast.fm/storage/artwork/7022/19948/184908/DZoEdMCPA4d5TVOVY9T0FYGtjIwIciWsgVNTagY8.jpg"/>
                    <enclosure
                        url="https://app.springcast.fm/download/184908/fPoeQM2rD1mvm5QvuoZToTN1ptOKKpxi.mp3"
                        length="55730176"
                        type="audio/mpeg"/>
                    <itunes:episodeType>full</itunes:episodeType>
                    <guid>https://app.springcast.fm/19948/rita-pucci-reading-the-stripes-ai-meets-wildlife</guid>
                    <pubDate>Mon, 02 Mar 2026 05:00:00 +0100</pubDate>
                    <pubDate_friendly>Monday 02 Mar 2026</pubDate_friendly>
                    <pubDate_sortable>2026-03-02 05:00:00</pubDate_sortable>
                    <itunes:episode>20</itunes:episode>
                    <itunes:season>3</itunes:season>
                    <itunes:explicit>no</itunes:explicit>
                    <itunes:duration>0:23:13</itunes:duration>
                </item>
                                                <item>
                    <episode_id>183577</episode_id>
                    <title>Arno Knobbe: Engineering Gold, the science behind Dutch speed skating</title>
                    <itunes:title>Arno Knobbe: Engineering Gold, the science behind Dutch speed skating
                    </itunes:title>
                    <link>https://app.springcast.fm/19948/arno-knobbe-engineering-gold-the-science-behind-dutch-speed-skating</link>
                    <description>
                        <![CDATA[<p>How can data help speed skaters push past their limits? Associate Professor Arno Knobbe specializes in sports data science. His research dives deep into the tiny details that can decide the outcome of a race. How and where do speed skaters find tenths of seconds to beat their rivals? <br><br>Arno's research helps olympic athletes study the 'corners' of the ice rink, where, as it turns out, every athlete needs a slightly different approach to glide through at top speed. And this isn’t just theory; his insights play a role at the 2026 Winter Olympics. </p><p>By collecting specific training data for each individual skater, Knobbe and his team can build the ultimate training schedule — one that ensures an athlete peaks at exactly the right moment: race day. And the impact goes far beyond elite sports. Even older adults wearing a smartwatch can benefit from the same principles, using data to better understand their health and daily activity.<br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p>
                        ]]>
                    </description>
                    <description_item_stripped>
                        <![CDATA[How can data help speed skaters push past their limits? Associate Professor Arno Knobbe specializes in sports data science. His research dives deep into the tiny details that can decide the outcome of a race. How and where do speed skaters find tenths of seconds to beat their rivals? Arno's research helps olympic athletes study the 'corners' of the ice rink, where, as it turns out, every athlete needs a slightly different approach to glide through at top speed. And this isn’t just theory; his insights play a role at the 2026 Winter Olympics. By collecting specific training data for each individual skater, Knobbe and his team can build the ultimate training schedule — one that ensures an athlete peaks at exactly the right moment: race day. And the impact goes far beyond elite sports. Even older adults wearing a smartwatch can benefit from the same principles, using data to better understand their health and daily activity.Idea by Dimitra KouimtzidouResearch, planning & coordination by Marcel Tichelaar & Dimitra KouimtzidouInterview, production & editing by Michiel van Poelgeest
                        ]]>
                    </description_item_stripped>
                    <itunes:summary>
                        <![CDATA[<p>How can data help speed skaters push past their limits? Associate Professor Arno Knobbe specializes in sports data science. His research dives deep into the tiny details that can decide the outcome of a race. How and where do speed skaters find tenths of seconds to beat their rivals? <br><br>Arno's research helps olympic athletes study the 'corners' of the ice rink, where, as it turns out, every athlete needs a slightly different approach to glide through at top speed. And this isn’t just theory; his insights play a role at the 2026 Winter Olympics. </p><p>By collecting specific training data for each individual skater, Knobbe and his team can build the ultimate training schedule — one that ensures an athlete peaks at exactly the right moment: race day. And the impact goes far beyond elite sports. Even older adults wearing a smartwatch can benefit from the same principles, using data to better understand their health and daily activity.<br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p>
                        ]]>
                    </itunes:summary>
                    <itunes:subtitle><![CDATA[Winter Olympics special]]>
                    </itunes:subtitle>
                    <itunes:author>LIACS</itunes:author>
                    <itunes:image
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                    <enclosure
                        url="https://app.springcast.fm/download/183577/fwEsXow82uL3hA0Khu7Gs6cmJf6sZZ63.mp3"
                        length="50366656"
                        type="audio/mpeg"/>
                    <itunes:episodeType>full</itunes:episodeType>
                    <guid>https://app.springcast.fm/19948/arno-knobbe-engineering-gold-the-science-behind-dutch-speed-skating</guid>
                    <pubDate>Mon, 16 Feb 2026 05:00:00 +0100</pubDate>
                    <pubDate_friendly>Monday 16 Feb 2026</pubDate_friendly>
                    <pubDate_sortable>2026-02-16 05:00:00</pubDate_sortable>
                    <itunes:episode>19</itunes:episode>
                    <itunes:season>3</itunes:season>
                    <itunes:explicit>no</itunes:explicit>
                    <itunes:duration>0:20:59</itunes:duration>
                </item>
                                                <item>
                    <episode_id>183421</episode_id>
                    <title>Joost Broekens and Thomas Moerland: AI, revolution or bubble?</title>
                    <itunes:title>Joost Broekens and Thomas Moerland: AI, revolution or bubble?
                    </itunes:title>
                    <link>https://app.springcast.fm/19948/joost-broekens-and-thomas-moerland-ai-revolution-or-a-bubble</link>
                    <description>
                        <![CDATA[<p>Associate Professor Joost Broekens and Assistant Professor Thomas Moerland explore the rapid rise of AI. Are we in the middle of a hype cycle, or is something truly transformative happening? And how do we keep these increasingly powerful systems safe? These questions—and more—drive this new CDB episode. </p><p>AI brings huge advantages, but not without trade‑offs. Is today’s AI revolution comparable to the invention of the steam engine? Cultural evolution is accelerating as knowledge fuels more knowledge, while humans become the limiting factor. Yet AI still mirrors us, shaped by human ideas and behavior. And doesn't the Turing test feel a bit outdated now that distinguishing AI agents from humans is becoming harder than ever.<br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p>
                        ]]>
                    </description>
                    <description_item_stripped>
                        <![CDATA[Associate Professor Joost Broekens and Assistant Professor Thomas Moerland explore the rapid rise of AI. Are we in the middle of a hype cycle, or is something truly transformative happening? And how do we keep these increasingly powerful systems safe? These questions—and more—drive this new CDB episode. AI brings huge advantages, but not without trade‑offs. Is today’s AI revolution comparable to the invention of the steam engine? Cultural evolution is accelerating as knowledge fuels more knowledge, while humans become the limiting factor. Yet AI still mirrors us, shaped by human ideas and behavior. And doesn't the Turing test feel a bit outdated now that distinguishing AI agents from humans is becoming harder than ever.Idea by Dimitra KouimtzidouResearch, planning & coordination by Marcel Tichelaar & Dimitra KouimtzidouInterview, production & editing by Michiel van Poelgeest
                        ]]>
                    </description_item_stripped>
                    <itunes:summary>
                        <![CDATA[<p>Associate Professor Joost Broekens and Assistant Professor Thomas Moerland explore the rapid rise of AI. Are we in the middle of a hype cycle, or is something truly transformative happening? And how do we keep these increasingly powerful systems safe? These questions—and more—drive this new CDB episode. </p><p>AI brings huge advantages, but not without trade‑offs. Is today’s AI revolution comparable to the invention of the steam engine? Cultural evolution is accelerating as knowledge fuels more knowledge, while humans become the limiting factor. Yet AI still mirrors us, shaped by human ideas and behavior. And doesn't the Turing test feel a bit outdated now that distinguishing AI agents from humans is becoming harder than ever.<br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p>
                        ]]>
                    </itunes:summary>
                    <itunes:subtitle><![CDATA[And who is winning the imitation game?]]>
                    </itunes:subtitle>
                    <itunes:author>LIACS</itunes:author>
                    <itunes:image
                        href="https://app.springcast.fm/storage/artwork/7022/19948/183421/D8goqZbwGkxizH7guQc7ZGI04ODA4AHIM7DpFF86.jpg"/>
                    <enclosure
                        url="https://app.springcast.fm/download/183421/RYKWfKCudBuDyFc6MzAdugWBVSONks4s.mp3"
                        length="98276416"
                        type="audio/mpeg"/>
                    <itunes:episodeType>full</itunes:episodeType>
                    <guid>https://app.springcast.fm/19948/joost-broekens-and-thomas-moerland-ai-revolution-or-a-bubble</guid>
                    <pubDate>Thu, 12 Feb 2026 05:00:00 +0100</pubDate>
                    <pubDate_friendly>Thursday 12 Feb 2026</pubDate_friendly>
                    <pubDate_sortable>2026-02-12 05:00:00</pubDate_sortable>
                    <itunes:episode>18</itunes:episode>
                    <itunes:season>3</itunes:season>
                    <itunes:explicit>no</itunes:explicit>
                    <itunes:duration>0:40:56</itunes:duration>
                </item>
                                                <item>
                    <episode_id>165384</episode_id>
                    <title>Evert van Nieuwenburg: Tiq Taq Toe, exploring quantum concepts through gameplay</title>
                    <itunes:title>Evert van Nieuwenburg: Tiq Taq Toe, exploring quantum concepts through gameplay
                    </itunes:title>
                    <link>https://app.springcast.fm/19948/evert</link>
                    <description>
                        <![CDATA[<p>What if a childhood game could unlock the mysteries of quantum mechanics? In this episode, we sit down with Assistant Professor Evert van Nieuwenburg to explore how Tiq Taq Toe is revolutionizing the way we learn physics. Through interactive gameplay, this innovative tool makes abstract quantum concepts more intuitive and engaging.  
</p><p>Whether you're a science enthusiast or just curious about learning through play, this episode offers a fascinating glimpse into a whole new way of thinking. Tune in and discover how simple moves can reveal the wonders of a complex universe.<br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p><p>
</p><p>
</p><p><br></p><p>
</p><p> </p>
                        ]]>
                    </description>
                    <description_item_stripped>
                        <![CDATA[What if a childhood game could unlock the mysteries of quantum mechanics? In this episode, we sit down with Assistant Professor Evert van Nieuwenburg to explore how Tiq Taq Toe is revolutionizing the way we learn physics. Through interactive gameplay, this innovative tool makes abstract quantum concepts more intuitive and engaging.  
Whether you're a science enthusiast or just curious about learning through play, this episode offers a fascinating glimpse into a whole new way of thinking. Tune in and discover how simple moves can reveal the wonders of a complex universe.Idea by Dimitra KouimtzidouResearch, planning & coordination by Marcel Tichelaar & Dimitra KouimtzidouInterview, production & editing by Michiel van Poelgeest


 
                        ]]>
                    </description_item_stripped>
                    <itunes:summary>
                        <![CDATA[<p>What if a childhood game could unlock the mysteries of quantum mechanics? In this episode, we sit down with Assistant Professor Evert van Nieuwenburg to explore how Tiq Taq Toe is revolutionizing the way we learn physics. Through interactive gameplay, this innovative tool makes abstract quantum concepts more intuitive and engaging.  
</p><p>Whether you're a science enthusiast or just curious about learning through play, this episode offers a fascinating glimpse into a whole new way of thinking. Tune in and discover how simple moves can reveal the wonders of a complex universe.<br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p><p>
</p><p>
</p><p><br></p><p>
</p><p> </p>
                        ]]>
                    </itunes:summary>
                    <itunes:subtitle><![CDATA[]]>
                    </itunes:subtitle>
                    <itunes:author>LIACS</itunes:author>
                    <itunes:image
                        href="https://app.springcast.fm/storage/artwork/7022/19948/165384/3TV17Rc3Ek3YjgBEeezLLy4efyd3238VgJ1Nz1LF.jpg"/>
                    <enclosure
                        url="https://app.springcast.fm/download/165384/ThZFuZBskefeUFthpGSZtTM1bi37r38e.mp3"
                        length="54046336"
                        type="audio/mpeg"/>
                    <itunes:episodeType>full</itunes:episodeType>
                    <guid>https://app.springcast.fm/19948/evert</guid>
                    <pubDate>Tue, 06 May 2025 02:00:00 +0200</pubDate>
                    <pubDate_friendly>Tuesday 06 May 2025</pubDate_friendly>
                    <pubDate_sortable>2025-05-06 02:00:00</pubDate_sortable>
                    <itunes:episode>17</itunes:episode>
                    <itunes:season>2</itunes:season>
                    <itunes:explicit>no</itunes:explicit>
                    <itunes:duration>0:22:31</itunes:duration>
                </item>
                                                <item>
                    <episode_id>161298</episode_id>
                    <title>Marco Spruit: Ai powered pets, a new indicator of elderly well-being?</title>
                    <itunes:title>Marco Spruit: Ai powered pets, a new indicator of elderly well-being?
                    </itunes:title>
                    <link>https://app.springcast.fm/19948/marco</link>
                    <description>
                        <![CDATA[<p>Can AI revolutionize elderly care? Professor Marco Spruit, an expert in translational data science, is developing Well-being AI—a smart pet robot that provides companionship while monitoring health through language markers. This technology could ease pressure on healthcare services by detecting early signs of decline and alerting caregivers. 
</p><p>Beyond professional care, these intelligent robots could also support informal caregivers. Imagine a situation where one partner begins to suffer from dementia—this technology would allow the other partner to remotely monitor their well-being, offering peace of mind and timely intervention. This way AI can be the key to a more sustainable and compassionate future for elderly care? <br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p><p>
</p><p>
</p><p><br></p>
                        ]]>
                    </description>
                    <description_item_stripped>
                        <![CDATA[Can AI revolutionize elderly care? Professor Marco Spruit, an expert in translational data science, is developing Well-being AI—a smart pet robot that provides companionship while monitoring health through language markers. This technology could ease pressure on healthcare services by detecting early signs of decline and alerting caregivers. 
Beyond professional care, these intelligent robots could also support informal caregivers. Imagine a situation where one partner begins to suffer from dementia—this technology would allow the other partner to remotely monitor their well-being, offering peace of mind and timely intervention. This way AI can be the key to a more sustainable and compassionate future for elderly care? Idea by Dimitra KouimtzidouResearch, planning & coordination by Marcel Tichelaar & Dimitra KouimtzidouInterview, production & editing by Michiel van Poelgeest


                        ]]>
                    </description_item_stripped>
                    <itunes:summary>
                        <![CDATA[<p>Can AI revolutionize elderly care? Professor Marco Spruit, an expert in translational data science, is developing Well-being AI—a smart pet robot that provides companionship while monitoring health through language markers. This technology could ease pressure on healthcare services by detecting early signs of decline and alerting caregivers. 
</p><p>Beyond professional care, these intelligent robots could also support informal caregivers. Imagine a situation where one partner begins to suffer from dementia—this technology would allow the other partner to remotely monitor their well-being, offering peace of mind and timely intervention. This way AI can be the key to a more sustainable and compassionate future for elderly care? <br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p><p>
</p><p>
</p><p><br></p>
                        ]]>
                    </itunes:summary>
                    <itunes:subtitle><![CDATA[]]>
                    </itunes:subtitle>
                    <itunes:author>LIACS</itunes:author>
                    <itunes:image
                        href="https://app.springcast.fm/storage/artwork/7022/19948/161298/QqOmtMKprlho9mgCBBI92udRRIk8ALpbCWM20Ie8.jpg"/>
                    <enclosure
                        url="https://app.springcast.fm/download/161298/zeD7HhKKeYbSDHlnXDnqRZac9OZYFhZo.mp3"
                        length="40566016"
                        type="audio/mpeg"/>
                    <itunes:episodeType>full</itunes:episodeType>
                    <guid>https://app.springcast.fm/19948/marco</guid>
                    <pubDate>Tue, 22 Apr 2025 02:00:00 +0200</pubDate>
                    <pubDate_friendly>Tuesday 22 Apr 2025</pubDate_friendly>
                    <pubDate_sortable>2025-04-22 02:00:00</pubDate_sortable>
                    <itunes:episode>16</itunes:episode>
                    <itunes:season>2</itunes:season>
                    <itunes:explicit>no</itunes:explicit>
                    <itunes:duration>0:16:54</itunes:duration>
                </item>
                                                <item>
                    <episode_id>164683</episode_id>
                    <title>Anna Kononova: Lenses for chip manufacturing, unveiling the complexity of their design</title>
                    <itunes:title>Anna Kononova: Lenses for chip manufacturing, unveiling the complexity of their design
                    </itunes:title>
                    <link>https://app.springcast.fm/19948/anna</link>
                    <description>
                        <![CDATA[<p>How can nature-inspired evolution help us create the perfect optical lens? Assistant Professor Anna Kononova explores this question in her research. High-tech industries, like computer chip manufacturers, require ultra-precise lenses to keep up with the demand for increasingly complex designs. 
</p><p>Anna uses evolutionary computing, a technique that mimics natural selection. Just as nature evolves the fittest species, computers generate and test many lens designs, keeping the best and refining them over generations. This approach helps create cutting-edge technology with incredible precision. <br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p><p>
</p><p>
</p><p><br></p>
                        ]]>
                    </description>
                    <description_item_stripped>
                        <![CDATA[How can nature-inspired evolution help us create the perfect optical lens? Assistant Professor Anna Kononova explores this question in her research. High-tech industries, like computer chip manufacturers, require ultra-precise lenses to keep up with the demand for increasingly complex designs. 
Anna uses evolutionary computing, a technique that mimics natural selection. Just as nature evolves the fittest species, computers generate and test many lens designs, keeping the best and refining them over generations. This approach helps create cutting-edge technology with incredible precision. Idea by Dimitra KouimtzidouResearch, planning & coordination by Marcel Tichelaar & Dimitra KouimtzidouInterview, production & editing by Michiel van Poelgeest


                        ]]>
                    </description_item_stripped>
                    <itunes:summary>
                        <![CDATA[<p>How can nature-inspired evolution help us create the perfect optical lens? Assistant Professor Anna Kononova explores this question in her research. High-tech industries, like computer chip manufacturers, require ultra-precise lenses to keep up with the demand for increasingly complex designs. 
</p><p>Anna uses evolutionary computing, a technique that mimics natural selection. Just as nature evolves the fittest species, computers generate and test many lens designs, keeping the best and refining them over generations. This approach helps create cutting-edge technology with incredible precision. <br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p><p>
</p><p>
</p><p><br></p>
                        ]]>
                    </itunes:summary>
                    <itunes:subtitle><![CDATA[]]>
                    </itunes:subtitle>
                    <itunes:author>LIACS</itunes:author>
                    <itunes:image
                        href="https://app.springcast.fm/storage/artwork/7022/19948/164683/cIfEcb9LLvhWUavMMNqY6smNcYuYWb4cKH3QPuOx.jpg"/>
                    <enclosure
                        url="https://app.springcast.fm/download/164683/2phlNZvrsATvX3zqJoN8gcXVHwD0suEg.mp3"
                        length="52886656"
                        type="audio/mpeg"/>
                    <itunes:episodeType>full</itunes:episodeType>
                    <guid>https://app.springcast.fm/19948/anna</guid>
                    <pubDate>Tue, 08 Apr 2025 02:00:00 +0200</pubDate>
                    <pubDate_friendly>Tuesday 08 Apr 2025</pubDate_friendly>
                    <pubDate_sortable>2025-04-08 02:00:00</pubDate_sortable>
                    <itunes:episode>15</itunes:episode>
                    <itunes:season>2</itunes:season>
                    <itunes:explicit>no</itunes:explicit>
                    <itunes:duration>0:22:02</itunes:duration>
                </item>
                                                <item>
                    <episode_id>162909</episode_id>
                    <title>Mitra Baratchi: Designing the perfect algorithm to understand the world</title>
                    <itunes:title>Mitra Baratchi: Designing the perfect algorithm to understand the world
                    </itunes:title>
                    <link>https://app.springcast.fm/19948/mitra</link>
                    <description>
                        <![CDATA[<p>Ever wondered how algorithms make sense of complex problems? In this episode, we dive deep into the art of designing algorithms with associate professor Mitra Baratchi. Exploring how computers process data, find connections, and deliver insights. 
</p><p>While algorithms can solve many challenges, there are limits to their accuracy. How can researchers identify these gaps and guide users toward the best solutions. How much should we rely on algorithms, and where does human expertise come in? <br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p><p>
</p><p>
</p><p><br></p>
                        ]]>
                    </description>
                    <description_item_stripped>
                        <![CDATA[Ever wondered how algorithms make sense of complex problems? In this episode, we dive deep into the art of designing algorithms with associate professor Mitra Baratchi. Exploring how computers process data, find connections, and deliver insights. 
While algorithms can solve many challenges, there are limits to their accuracy. How can researchers identify these gaps and guide users toward the best solutions. How much should we rely on algorithms, and where does human expertise come in? Idea by Dimitra KouimtzidouResearch, planning & coordination by Marcel Tichelaar & Dimitra KouimtzidouInterview, production & editing by Michiel van Poelgeest


                        ]]>
                    </description_item_stripped>
                    <itunes:summary>
                        <![CDATA[<p>Ever wondered how algorithms make sense of complex problems? In this episode, we dive deep into the art of designing algorithms with associate professor Mitra Baratchi. Exploring how computers process data, find connections, and deliver insights. 
</p><p>While algorithms can solve many challenges, there are limits to their accuracy. How can researchers identify these gaps and guide users toward the best solutions. How much should we rely on algorithms, and where does human expertise come in? <br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p><p>
</p><p>
</p><p><br></p>
                        ]]>
                    </itunes:summary>
                    <itunes:subtitle><![CDATA[]]>
                    </itunes:subtitle>
                    <itunes:author>LIACS</itunes:author>
                    <itunes:image
                        href="https://app.springcast.fm/storage/artwork/7022/19948/162909/S12kFF5tU3oaYtZkWH431yAwaveULlTKnehSTX9T.jpg"/>
                    <enclosure
                        url="https://app.springcast.fm/download/162909/WoDWP1EgBRnRmd1cRk6FTssM1vlROurN.mp3"
                        length="33346816"
                        type="audio/mpeg"/>
                    <itunes:episodeType>full</itunes:episodeType>
                    <guid>https://app.springcast.fm/19948/mitra</guid>
                    <pubDate>Tue, 25 Mar 2025 02:00:00 +0100</pubDate>
                    <pubDate_friendly>Tuesday 25 Mar 2025</pubDate_friendly>
                    <pubDate_sortable>2025-03-25 02:00:00</pubDate_sortable>
                    <itunes:episode>14</itunes:episode>
                    <itunes:season>2</itunes:season>
                    <itunes:explicit>no</itunes:explicit>
                    <itunes:duration>0:13:53</itunes:duration>
                </item>
                                                <item>
                    <episode_id>160993</episode_id>
                    <title>Peter van der Putten: Tamagotchi, a precursor to today’s human loved home robots</title>
                    <itunes:title>Peter van der Putten: Tamagotchi, a precursor to today’s human loved home robots
                    </itunes:title>
                    <link>https://app.springcast.fm/19948/peter</link>
                    <description>
                        <![CDATA[<p>How and why do humans form relationships with AI? This question lies at the core of Assistant Professor Peter van der Putten’s research. While AI sparks fear—raising concerns about its impact on our place in the universe—it also fascinates us, offering glimpses into an unknown future. 
</p><p>
</p><p>But can we truly bond with AI? It’s one thing to feel attached to a humanoid robot or a robotic pet, but what about a simple wooden cube with a moving face? In his study Common Locus, Peter explored just that. The results might surprise you—and reveal more about human nature than you’d expect. 
</p><p> 
</p><p>If you want to read more about the research project of Joost Mollen, Peter van der Putten, and Kate Darling: <a href="https://dl.acm.org/doi/10.1145/3563702" target="_blank">Bonding with a Couchsurfing Robot: The Impact of Common Locus on Human-Robot Bonding In-the-wild</a>. ACM Transactions on Human-Robot Interaction. 12, 1, Article 8, March 2023.   
</p><p>
</p><p>More information about Peter can be found here: <a href="https://liacs.leidenuniv.nl/~puttenpwhvander/" target="_blank">https://liacs.leidenuniv.nl/~puttenpwhvander/</a> <br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p><p>
</p><p>
</p><p><br></p>
                        ]]>
                    </description>
                    <description_item_stripped>
                        <![CDATA[How and why do humans form relationships with AI? This question lies at the core of Assistant Professor Peter van der Putten’s research. While AI sparks fear—raising concerns about its impact on our place in the universe—it also fascinates us, offering glimpses into an unknown future. 

But can we truly bond with AI? It’s one thing to feel attached to a humanoid robot or a robotic pet, but what about a simple wooden cube with a moving face? In his study Common Locus, Peter explored just that. The results might surprise you—and reveal more about human nature than you’d expect. 
 
If you want to read more about the research project of Joost Mollen, Peter van der Putten, and Kate Darling: Bonding with a Couchsurfing Robot: The Impact of Common Locus on Human-Robot Bonding In-the-wild. ACM Transactions on Human-Robot Interaction. 12, 1, Article 8, March 2023.   

More information about Peter can be found here: https://liacs.leidenuniv.nl/~puttenpwhvander/ Idea by Dimitra KouimtzidouResearch, planning & coordination by Marcel Tichelaar & Dimitra KouimtzidouInterview, production & editing by Michiel van Poelgeest


                        ]]>
                    </description_item_stripped>
                    <itunes:summary>
                        <![CDATA[<p>How and why do humans form relationships with AI? This question lies at the core of Assistant Professor Peter van der Putten’s research. While AI sparks fear—raising concerns about its impact on our place in the universe—it also fascinates us, offering glimpses into an unknown future. 
</p><p>
</p><p>But can we truly bond with AI? It’s one thing to feel attached to a humanoid robot or a robotic pet, but what about a simple wooden cube with a moving face? In his study Common Locus, Peter explored just that. The results might surprise you—and reveal more about human nature than you’d expect. 
</p><p> 
</p><p>If you want to read more about the research project of Joost Mollen, Peter van der Putten, and Kate Darling: <a href="https://dl.acm.org/doi/10.1145/3563702" target="_blank">Bonding with a Couchsurfing Robot: The Impact of Common Locus on Human-Robot Bonding In-the-wild</a>. ACM Transactions on Human-Robot Interaction. 12, 1, Article 8, March 2023.   
</p><p>
</p><p>More information about Peter can be found here: <a href="https://liacs.leidenuniv.nl/~puttenpwhvander/" target="_blank">https://liacs.leidenuniv.nl/~puttenpwhvander/</a> <br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p><p>
</p><p>
</p><p><br></p>
                        ]]>
                    </itunes:summary>
                    <itunes:subtitle><![CDATA[]]>
                    </itunes:subtitle>
                    <itunes:author>LIACS</itunes:author>
                    <itunes:image
                        href="https://app.springcast.fm/storage/artwork/7022/19948/160993/JCxRvMUAretOwnBKK21Y0IZAJ1hWlMzA9HfNvn1E.jpg"/>
                    <enclosure
                        url="https://app.springcast.fm/download/160993/7OpDzBbL9O4ufhnUdNhpxl97tiWaBcA0.mp3"
                        length="48326656"
                        type="audio/mpeg"/>
                    <itunes:episodeType>full</itunes:episodeType>
                    <guid>https://app.springcast.fm/19948/peter</guid>
                    <pubDate>Tue, 11 Mar 2025 02:00:00 +0100</pubDate>
                    <pubDate_friendly>Tuesday 11 Mar 2025</pubDate_friendly>
                    <pubDate_sortable>2025-03-11 02:00:00</pubDate_sortable>
                    <itunes:episode>13</itunes:episode>
                    <itunes:season>2</itunes:season>
                    <itunes:explicit>no</itunes:explicit>
                    <itunes:duration>0:20:08</itunes:duration>
                </item>
                                                <item>
                    <episode_id>159952</episode_id>
                    <title>Hao Wang: From Amsterdam to Paris, real-life applications of Pareto optimum</title>
                    <itunes:title>Hao Wang: From Amsterdam to Paris, real-life applications of Pareto optimum
                    </itunes:title>
                    <link>https://app.springcast.fm/19948/hao</link>
                    <description>
                        <![CDATA[<p>In this episode, LIACS Assistant Professor Hao Wang shares insights into multi-criteria optimization and the concept of the Pareto optimum. Discover how these powerful techniques, often used in decision-making and problem-solving, can help you plan the perfect trip.  
</p><p>Whether you’re balancing cost, travel time, and comfort or choosing between destinations, learn how mathematical models can guide you toward the best possible choices. Tune in for a new episode that bridges research and real-life experiences.<br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p><p>
</p><p>
</p><p><br></p><p> </p>
                        ]]>
                    </description>
                    <description_item_stripped>
                        <![CDATA[In this episode, LIACS Assistant Professor Hao Wang shares insights into multi-criteria optimization and the concept of the Pareto optimum. Discover how these powerful techniques, often used in decision-making and problem-solving, can help you plan the perfect trip.  
Whether you’re balancing cost, travel time, and comfort or choosing between destinations, learn how mathematical models can guide you toward the best possible choices. Tune in for a new episode that bridges research and real-life experiences.Idea by Dimitra KouimtzidouResearch, planning & coordination by Marcel Tichelaar & Dimitra KouimtzidouInterview, production & editing by Michiel van Poelgeest

 
                        ]]>
                    </description_item_stripped>
                    <itunes:summary>
                        <![CDATA[<p>In this episode, LIACS Assistant Professor Hao Wang shares insights into multi-criteria optimization and the concept of the Pareto optimum. Discover how these powerful techniques, often used in decision-making and problem-solving, can help you plan the perfect trip.  
</p><p>Whether you’re balancing cost, travel time, and comfort or choosing between destinations, learn how mathematical models can guide you toward the best possible choices. Tune in for a new episode that bridges research and real-life experiences.<br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p><p>
</p><p>
</p><p><br></p><p> </p>
                        ]]>
                    </itunes:summary>
                    <itunes:subtitle><![CDATA[]]>
                    </itunes:subtitle>
                    <itunes:author>LIACS</itunes:author>
                    <itunes:image
                        href="https://app.springcast.fm/storage/artwork/7022/19948/159952/mRTBWFWbSlhFG1xv04CcrpbGH0ZBQ4yJVQVrxYiJ.jpg"/>
                    <enclosure
                        url="https://app.springcast.fm/download/159952/C7NHbsMtppvR1GyXX4CWg8o277gOwqVu.mp3"
                        length="42926656"
                        type="audio/mpeg"/>
                    <itunes:episodeType>full</itunes:episodeType>
                    <guid>https://app.springcast.fm/19948/hao</guid>
                    <pubDate>Tue, 25 Feb 2025 02:00:00 +0100</pubDate>
                    <pubDate_friendly>Tuesday 25 Feb 2025</pubDate_friendly>
                    <pubDate_sortable>2025-02-25 02:00:00</pubDate_sortable>
                    <itunes:episode>12</itunes:episode>
                    <itunes:season>2</itunes:season>
                    <itunes:explicit>no</itunes:explicit>
                    <itunes:duration>0:17:53</itunes:duration>
                </item>
                                                <item>
                    <episode_id>158416</episode_id>
                    <title>Lu Cao: Hay Fever, how AI improves pollen monitoring</title>
                    <itunes:title>Lu Cao: Hay Fever, how AI improves pollen monitoring
                    </itunes:title>
                    <link>https://app.springcast.fm/19948/lu</link>
                    <description>
                        <![CDATA[<p>The hay fever season lasts longer than it used to because of climate change. LIACS Assistant Professor Lu Cao explains how machine learning and AI can help to easier count pollen in the air. This improves the accuracy and efficiency of pollen monitoring, a critical tool for understanding seasonal allergies, air quality, and climate impact.    
</p><p>Discover how AI-driven technologies can improve the accuracy and efficiency of pollen monitoring, providing valuable insights for municipal governments. With better data, policymakers can adjust their strategies on public green spaces, balancing ecological benefits with the needs of residents affected by allergies. <br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p><p>
</p><p>
</p><p><br></p>
                        ]]>
                    </description>
                    <description_item_stripped>
                        <![CDATA[The hay fever season lasts longer than it used to because of climate change. LIACS Assistant Professor Lu Cao explains how machine learning and AI can help to easier count pollen in the air. This improves the accuracy and efficiency of pollen monitoring, a critical tool for understanding seasonal allergies, air quality, and climate impact.    
Discover how AI-driven technologies can improve the accuracy and efficiency of pollen monitoring, providing valuable insights for municipal governments. With better data, policymakers can adjust their strategies on public green spaces, balancing ecological benefits with the needs of residents affected by allergies. Idea by Dimitra KouimtzidouResearch, planning & coordination by Marcel Tichelaar & Dimitra KouimtzidouInterview, production & editing by Michiel van Poelgeest


                        ]]>
                    </description_item_stripped>
                    <itunes:summary>
                        <![CDATA[<p>The hay fever season lasts longer than it used to because of climate change. LIACS Assistant Professor Lu Cao explains how machine learning and AI can help to easier count pollen in the air. This improves the accuracy and efficiency of pollen monitoring, a critical tool for understanding seasonal allergies, air quality, and climate impact.    
</p><p>Discover how AI-driven technologies can improve the accuracy and efficiency of pollen monitoring, providing valuable insights for municipal governments. With better data, policymakers can adjust their strategies on public green spaces, balancing ecological benefits with the needs of residents affected by allergies. <br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p><p>
</p><p>
</p><p><br></p>
                        ]]>
                    </itunes:summary>
                    <itunes:subtitle><![CDATA[]]>
                    </itunes:subtitle>
                    <itunes:author>LIACS</itunes:author>
                    <itunes:image
                        href="https://app.springcast.fm/storage/artwork/7022/19948/158416/4hmsymdRHK8QnqEuCi6kPGWVygJ1FxshoxaIEWe1.png"/>
                    <enclosure
                        url="https://app.springcast.fm/download/158416/LPRKMtkBPK9vKa0tLptVxdy5vGRnMwOC.mp3"
                        length="38266816"
                        type="audio/mpeg"/>
                    <itunes:episodeType>full</itunes:episodeType>
                    <guid>https://app.springcast.fm/19948/lu</guid>
                    <pubDate>Tue, 11 Feb 2025 02:00:00 +0100</pubDate>
                    <pubDate_friendly>Tuesday 11 Feb 2025</pubDate_friendly>
                    <pubDate_sortable>2025-02-11 02:00:00</pubDate_sortable>
                    <itunes:episode>11</itunes:episode>
                    <itunes:season>2</itunes:season>
                    <itunes:explicit>no</itunes:explicit>
                    <itunes:duration>0:15:56</itunes:duration>
                </item>
                                                <item>
                    <episode_id>157817</episode_id>
                    <title>Joost Broekens: Robots &amp; Emotions, are we moving from AI to EI?</title>
                    <itunes:title>Joost Broekens: Robots &amp; Emotions, are we moving from AI to EI?
                    </itunes:title>
                    <link>https://app.springcast.fm/19948/robots-emotions-are-we-moving-from-ai-to-ei</link>
                    <description>
                        <![CDATA[<p>Can robots feel joy or guilt? Can they have emotions at all? Today, we dive into the fascinating world of "affective" computing with Associate Professor Joost Broekens, a leading expert in the field. But what exactly is affective computing?</p><p>We also tackle the ethical challenges of AI-emotion interaction, exploring topics like the European AI Act, which bans emotion recognition in education and the workplace. Are these new technologies transforming artificial intelligence into emotional intelligence?<br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p><p>
</p><p><br></p>
                        ]]>
                    </description>
                    <description_item_stripped>
                        <![CDATA[Can robots feel joy or guilt? Can they have emotions at all? Today, we dive into the fascinating world of "affective" computing with Associate Professor Joost Broekens, a leading expert in the field. But what exactly is affective computing?We also tackle the ethical challenges of AI-emotion interaction, exploring topics like the European AI Act, which bans emotion recognition in education and the workplace. Are these new technologies transforming artificial intelligence into emotional intelligence?Idea by Dimitra KouimtzidouResearch, planning & coordination by Marcel Tichelaar & Dimitra KouimtzidouInterview, production & editing by Michiel van Poelgeest

                        ]]>
                    </description_item_stripped>
                    <itunes:summary>
                        <![CDATA[<p>Can robots feel joy or guilt? Can they have emotions at all? Today, we dive into the fascinating world of "affective" computing with Associate Professor Joost Broekens, a leading expert in the field. But what exactly is affective computing?</p><p>We also tackle the ethical challenges of AI-emotion interaction, exploring topics like the European AI Act, which bans emotion recognition in education and the workplace. Are these new technologies transforming artificial intelligence into emotional intelligence?<br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p><p>
</p><p><br></p>
                        ]]>
                    </itunes:summary>
                    <itunes:subtitle><![CDATA[with Associate Professor Joost Broekens]]>
                    </itunes:subtitle>
                    <itunes:author>LIACS</itunes:author>
                    <itunes:image
                        href="https://app.springcast.fm/storage/artwork/7022/19948/157817/Y08LZ1ltFU8WUhAhmht8kLZRfHPKHVx0gCAnIbcr.png"/>
                    <enclosure
                        url="https://app.springcast.fm/download/157817/k5NI3IcryKRxlPJUrCw1KxL7bn8JcyHH.mp3"
                        length="48391936"
                        type="audio/mpeg"/>
                    <itunes:episodeType>full</itunes:episodeType>
                    <guid>https://app.springcast.fm/19948/robots-emotions-are-we-moving-from-ai-to-ei</guid>
                    <pubDate>Tue, 28 Jan 2025 02:00:00 +0100</pubDate>
                    <pubDate_friendly>Tuesday 28 Jan 2025</pubDate_friendly>
                    <pubDate_sortable>2025-01-28 02:00:00</pubDate_sortable>
                    <itunes:episode>10</itunes:episode>
                    <itunes:season>2</itunes:season>
                    <itunes:explicit>no</itunes:explicit>
                    <itunes:duration>0:20:09</itunes:duration>
                </item>
                                                <item>
                    <episode_id>104367</episode_id>
                    <title>Vedran Dunjko: Next level computing, exploring the world of quantum</title>
                    <itunes:title>Vedran Dunjko: Next level computing, exploring the world of quantum
                    </itunes:title>
                    <link>https://app.springcast.fm/19948/vedran-dunjko</link>
                    <description>
                        <![CDATA[<p>Professor Vedran Dunjko leads the Applied Quantum Algorithms group at Leiden University. His research focuses on quantum computing, which uses quantum effects to greatly improve computation. This could lead to much more powerful computers. Developing a working quantum computer is an ongoing effort, bringing both exciting possibilities and potential security risks because of its superior computing abilities.<br><br>Much of what a quantum computer can achieve remains a mystery, even to experts like Dunjko. Essentially, the quantum computer is a solution in search of a problem. Nonetheless, Dunjko is confident in its potential applications, particularly in the field of quantum physics.  <br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p><p>
</p><p><br></p>
                        ]]>
                    </description>
                    <description_item_stripped>
                        <![CDATA[Professor Vedran Dunjko leads the Applied Quantum Algorithms group at Leiden University. His research focuses on quantum computing, which uses quantum effects to greatly improve computation. This could lead to much more powerful computers. Developing a working quantum computer is an ongoing effort, bringing both exciting possibilities and potential security risks because of its superior computing abilities.Much of what a quantum computer can achieve remains a mystery, even to experts like Dunjko. Essentially, the quantum computer is a solution in search of a problem. Nonetheless, Dunjko is confident in its potential applications, particularly in the field of quantum physics.  Idea by Dimitra KouimtzidouResearch, planning & coordination by Marcel Tichelaar & Dimitra KouimtzidouInterview, production & editing by Michiel van Poelgeest

                        ]]>
                    </description_item_stripped>
                    <itunes:summary>
                        <![CDATA[<p>Professor Vedran Dunjko leads the Applied Quantum Algorithms group at Leiden University. His research focuses on quantum computing, which uses quantum effects to greatly improve computation. This could lead to much more powerful computers. Developing a working quantum computer is an ongoing effort, bringing both exciting possibilities and potential security risks because of its superior computing abilities.<br><br>Much of what a quantum computer can achieve remains a mystery, even to experts like Dunjko. Essentially, the quantum computer is a solution in search of a problem. Nonetheless, Dunjko is confident in its potential applications, particularly in the field of quantum physics.  <br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p><p>
</p><p><br></p>
                        ]]>
                    </itunes:summary>
                    <itunes:subtitle><![CDATA[]]>
                    </itunes:subtitle>
                    <itunes:author>LIACS</itunes:author>
                    <itunes:image
                        href="https://app.springcast.fm/storage/artwork/7022/19948/104367/6iZOgJWo27syaJd1TCT9syTqo2RnI8YDPQDFA5Yf.png"/>
                    <enclosure
                        url="https://app.springcast.fm/download/104367/YtkxhVY687ytqjz4WuLoa0rIvAu8IbZh.mp3"
                        length="54286336"
                        type="audio/mpeg"/>
                    <itunes:episodeType>full</itunes:episodeType>
                    <guid>https://app.springcast.fm/19948/vedran-dunjko</guid>
                    <pubDate>Tue, 02 Jul 2024 02:00:00 +0200</pubDate>
                    <pubDate_friendly>Tuesday 02 Jul 2024</pubDate_friendly>
                    <pubDate_sortable>2024-07-02 02:00:00</pubDate_sortable>
                    <itunes:episode>9</itunes:episode>
                    <itunes:season>1</itunes:season>
                    <itunes:explicit>no</itunes:explicit>
                    <itunes:duration>0:22:37</itunes:duration>
                </item>
                                                <item>
                    <episode_id>104366</episode_id>
                    <title>Hazel Doughty: Video Understanding, a step towards the real world</title>
                    <itunes:title>Hazel Doughty: Video Understanding, a step towards the real world
                    </itunes:title>
                    <link>https://app.springcast.fm/19948/hazel-doughty</link>
                    <description>
                        <![CDATA[<p>Assistant Professor Hazel Doughty specializes in computer vision, aiming to enable computers to automatically understand visual content. Her research focuses on video understanding, where thousands of videos with text descriptions are fed to the computer. Her project, "From What to How," seeks to advance computers from identifying actions to understanding how they are performed, though this is currently limited by insufficient data. 
</p><p>
</p><p>Ultimately, her goal is for computers to independently analyze videos and comprehend methods used in various tasks. This would allow for the creation of assistive videos for activities like for instance proper CPR techniques. 
<br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p><p><br></p><p><br></p>
                        ]]>
                    </description>
                    <description_item_stripped>
                        <![CDATA[Assistant Professor Hazel Doughty specializes in computer vision, aiming to enable computers to automatically understand visual content. Her research focuses on video understanding, where thousands of videos with text descriptions are fed to the computer. Her project, "From What to How," seeks to advance computers from identifying actions to understanding how they are performed, though this is currently limited by insufficient data. 

Ultimately, her goal is for computers to independently analyze videos and comprehend methods used in various tasks. This would allow for the creation of assistive videos for activities like for instance proper CPR techniques. 
Idea by Dimitra KouimtzidouResearch, planning & coordination by Marcel Tichelaar & Dimitra KouimtzidouInterview, production & editing by Michiel van Poelgeest
                        ]]>
                    </description_item_stripped>
                    <itunes:summary>
                        <![CDATA[<p>Assistant Professor Hazel Doughty specializes in computer vision, aiming to enable computers to automatically understand visual content. Her research focuses on video understanding, where thousands of videos with text descriptions are fed to the computer. Her project, "From What to How," seeks to advance computers from identifying actions to understanding how they are performed, though this is currently limited by insufficient data. 
</p><p>
</p><p>Ultimately, her goal is for computers to independently analyze videos and comprehend methods used in various tasks. This would allow for the creation of assistive videos for activities like for instance proper CPR techniques. 
<br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p><p><br></p><p><br></p>
                        ]]>
                    </itunes:summary>
                    <itunes:subtitle><![CDATA[]]>
                    </itunes:subtitle>
                    <itunes:author>LIACS</itunes:author>
                    <itunes:image
                        href="https://app.springcast.fm/storage/artwork/7022/19948/104366/Wo31XHaXndkE1oJLRo4jv6VaBsqT0UtKSDWMxpoY.png"/>
                    <enclosure
                        url="https://app.springcast.fm/download/104366/fenzWk8iTAiI3Zwn541p2JcmWed6uifJ.mp3"
                        length="44366656"
                        type="audio/mpeg"/>
                    <itunes:episodeType>full</itunes:episodeType>
                    <guid>https://app.springcast.fm/19948/hazel-doughty</guid>
                    <pubDate>Tue, 18 Jun 2024 02:00:00 +0200</pubDate>
                    <pubDate_friendly>Tuesday 18 Jun 2024</pubDate_friendly>
                    <pubDate_sortable>2024-06-18 02:00:00</pubDate_sortable>
                    <itunes:episode>8</itunes:episode>
                    <itunes:season>1</itunes:season>
                    <itunes:explicit>no</itunes:explicit>
                    <itunes:duration>0:18:29</itunes:duration>
                </item>
                                                <item>
                    <episode_id>104171</episode_id>
                    <title>Jan van Rijn: Robustness, unveiling the black box of AI</title>
                    <itunes:title>Jan van Rijn: Robustness, unveiling the black box of AI
                    </itunes:title>
                    <link>https://app.springcast.fm/19948/jan-van-rijn</link>
                    <description>
                        <![CDATA[<p>Assistant Professor Jan van Rijn is at the forefront of research into the trustworthiness of AI systems. His work focuses on the field of machine learning, with a particular emphasis on exploring and enhancing the robustness of AI systems. Robustness is a critical component in building trustworthy machines, such as self-driving cars, where reliable performance is paramount.<br><br>Jan and his team are dedicated to developing techniques that make verification models for testing robustness more efficient. However, significant challenges remain. One of the primary obstacles is the sheer size of current AI systems, like ChatGPT, which are too large to be efficiently verified using existing methods. <br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p><p><br></p>
                        ]]>
                    </description>
                    <description_item_stripped>
                        <![CDATA[Assistant Professor Jan van Rijn is at the forefront of research into the trustworthiness of AI systems. His work focuses on the field of machine learning, with a particular emphasis on exploring and enhancing the robustness of AI systems. Robustness is a critical component in building trustworthy machines, such as self-driving cars, where reliable performance is paramount.Jan and his team are dedicated to developing techniques that make verification models for testing robustness more efficient. However, significant challenges remain. One of the primary obstacles is the sheer size of current AI systems, like ChatGPT, which are too large to be efficiently verified using existing methods. Idea by Dimitra KouimtzidouResearch, planning & coordination by Marcel Tichelaar & Dimitra KouimtzidouInterview, production & editing by Michiel van Poelgeest
                        ]]>
                    </description_item_stripped>
                    <itunes:summary>
                        <![CDATA[<p>Assistant Professor Jan van Rijn is at the forefront of research into the trustworthiness of AI systems. His work focuses on the field of machine learning, with a particular emphasis on exploring and enhancing the robustness of AI systems. Robustness is a critical component in building trustworthy machines, such as self-driving cars, where reliable performance is paramount.<br><br>Jan and his team are dedicated to developing techniques that make verification models for testing robustness more efficient. However, significant challenges remain. One of the primary obstacles is the sheer size of current AI systems, like ChatGPT, which are too large to be efficiently verified using existing methods. <br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p><p><br></p>
                        ]]>
                    </itunes:summary>
                    <itunes:subtitle><![CDATA[]]>
                    </itunes:subtitle>
                    <itunes:author>LIACS</itunes:author>
                    <itunes:image
                        href="https://app.springcast.fm/storage/artwork/7022/19948/104171/m0ByczVcUF11xzFGByPsfYIFBcD9Wh6bqInJil5w.png"/>
                    <enclosure
                        url="https://app.springcast.fm/download/104171/MW8EBhEjqN527ER5ZBiTNQDZdUpoAG7n.mp3"
                        length="39046336"
                        type="audio/mpeg"/>
                    <itunes:episodeType>full</itunes:episodeType>
                    <guid>https://app.springcast.fm/19948/jan-van-rijn</guid>
                    <pubDate>Tue, 04 Jun 2024 02:00:00 +0200</pubDate>
                    <pubDate_friendly>Tuesday 04 Jun 2024</pubDate_friendly>
                    <pubDate_sortable>2024-06-04 02:00:00</pubDate_sortable>
                    <itunes:episode>7</itunes:episode>
                    <itunes:season>1</itunes:season>
                    <itunes:explicit>no</itunes:explicit>
                    <itunes:duration>0:16:16</itunes:duration>
                </item>
                                                <item>
                    <episode_id>104133</episode_id>
                    <title>Tessa Verhoef: Robots, a way to better understand humans</title>
                    <itunes:title>Tessa Verhoef: Robots, a way to better understand humans
                    </itunes:title>
                    <link>https://app.springcast.fm/19948/tessa-verhoef-robots-a-way-to-better-understand-humans</link>
                    <description>
                        <![CDATA[<p>Assistant Professor Tessa Verhoef has a passion for robotics and is dedicated to improving the human-likeness of robots, for instance by looking into their use of language.</p><p>Her journey began with Kismet, a robot designed to convey emotions and engage in human-like interactions. While her expertise involves AI and robotics, she also delves into language evolution, exploring how languages form and transform over time. <br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p><p><br></p>
                        ]]>
                    </description>
                    <description_item_stripped>
                        <![CDATA[Assistant Professor Tessa Verhoef has a passion for robotics and is dedicated to improving the human-likeness of robots, for instance by looking into their use of language.Her journey began with Kismet, a robot designed to convey emotions and engage in human-like interactions. While her expertise involves AI and robotics, she also delves into language evolution, exploring how languages form and transform over time. Idea by Dimitra KouimtzidouResearch, planning & coordination by Marcel Tichelaar & Dimitra KouimtzidouInterview, production & editing by Michiel van Poelgeest
                        ]]>
                    </description_item_stripped>
                    <itunes:summary>
                        <![CDATA[<p>Assistant Professor Tessa Verhoef has a passion for robotics and is dedicated to improving the human-likeness of robots, for instance by looking into their use of language.</p><p>Her journey began with Kismet, a robot designed to convey emotions and engage in human-like interactions. While her expertise involves AI and robotics, she also delves into language evolution, exploring how languages form and transform over time. <br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p><p><br></p>
                        ]]>
                    </itunes:summary>
                    <itunes:subtitle><![CDATA[]]>
                    </itunes:subtitle>
                    <itunes:author>LIACS</itunes:author>
                    <itunes:image
                        href="https://app.springcast.fm/storage/artwork/7022/19948/104133/fDISymXdoK6hx1F0yD3nZWAGzfThFLyb5WiGiwBR.png"/>
                    <enclosure
                        url="https://app.springcast.fm/download/104133/gR8szV8EuiUgZQhWFoc6PtLOkTQh7oFc.mp3"
                        length="43869376"
                        type="audio/mpeg"/>
                    <itunes:episodeType>full</itunes:episodeType>
                    <guid>https://app.springcast.fm/19948/tessa-verhoef-robots-a-way-to-better-understand-humans</guid>
                    <pubDate>Mon, 20 May 2024 02:00:00 +0200</pubDate>
                    <pubDate_friendly>Monday 20 May 2024</pubDate_friendly>
                    <pubDate_sortable>2024-05-20 02:00:00</pubDate_sortable>
                    <itunes:episode>6</itunes:episode>
                    <itunes:season>1</itunes:season>
                    <itunes:explicit>no</itunes:explicit>
                    <itunes:duration>0:18:16</itunes:duration>
                </item>
                                                <item>
                    <episode_id>94390</episode_id>
                    <title>Rob van Nieuwpoort: Efficient computing, a journey starting with a Commodore 64</title>
                    <itunes:title>Rob van Nieuwpoort: Efficient computing, a journey starting with a Commodore 64
                    </itunes:title>
                    <link>https://app.springcast.fm/19948/rob-van-nieuwpoort-titel</link>
                    <description>
                        <![CDATA[<p>Rob van Nieuwpoort is Professor of Efficient Computing and eScience at LIACS. His research focuses mainly on augmenting the efficiency of software and applications. But it also tackles the challenges posed by large-scale simulations housed within data centers. In this era where the demand for storage capacity skyrockets, reaching a point where accommodating all data becomes impossible. </p><p>In the 1960s, Moore's Law predicted the doubling of transistors on a chip every 2 years. Our current times finds us confronted with the constraints of chip capacity. And that is a fundamental problem for the future. But fortunately, Rob Van Nieuwpoort sees solutions.<br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p>
                        ]]>
                    </description>
                    <description_item_stripped>
                        <![CDATA[Rob van Nieuwpoort is Professor of Efficient Computing and eScience at LIACS. His research focuses mainly on augmenting the efficiency of software and applications. But it also tackles the challenges posed by large-scale simulations housed within data centers. In this era where the demand for storage capacity skyrockets, reaching a point where accommodating all data becomes impossible. In the 1960s, Moore's Law predicted the doubling of transistors on a chip every 2 years. Our current times finds us confronted with the constraints of chip capacity. And that is a fundamental problem for the future. But fortunately, Rob Van Nieuwpoort sees solutions.Idea by Dimitra KouimtzidouResearch, planning & coordination by Marcel Tichelaar & Dimitra KouimtzidouInterview, production & editing by Michiel van Poelgeest
                        ]]>
                    </description_item_stripped>
                    <itunes:summary>
                        <![CDATA[<p>Rob van Nieuwpoort is Professor of Efficient Computing and eScience at LIACS. His research focuses mainly on augmenting the efficiency of software and applications. But it also tackles the challenges posed by large-scale simulations housed within data centers. In this era where the demand for storage capacity skyrockets, reaching a point where accommodating all data becomes impossible. </p><p>In the 1960s, Moore's Law predicted the doubling of transistors on a chip every 2 years. Our current times finds us confronted with the constraints of chip capacity. And that is a fundamental problem for the future. But fortunately, Rob Van Nieuwpoort sees solutions.<br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p>
                        ]]>
                    </itunes:summary>
                    <itunes:subtitle><![CDATA[]]>
                    </itunes:subtitle>
                    <itunes:author>LIACS</itunes:author>
                    <itunes:image
                        href="https://app.springcast.fm/storage/artwork/7022/19948/94390/5dIp0Wn8s2I6yxdVms3FkrN2mL9TyB6lY9U3Hyde.png"/>
                    <enclosure
                        url="https://app.springcast.fm/download/94390/gh2QbmVA8ya3NBR5JOHnwU9t4qBPea4L.mp3"
                        length="42951616"
                        type="audio/mpeg"/>
                    <itunes:episodeType>full</itunes:episodeType>
                    <guid>https://app.springcast.fm/19948/rob-van-nieuwpoort-titel</guid>
                    <pubDate>Mon, 06 May 2024 01:00:00 +0200</pubDate>
                    <pubDate_friendly>Monday 06 May 2024</pubDate_friendly>
                    <pubDate_sortable>2024-05-06 01:00:00</pubDate_sortable>
                    <itunes:episode>5</itunes:episode>
                    <itunes:season>1</itunes:season>
                    <itunes:explicit>no</itunes:explicit>
                    <itunes:duration>0:17:53</itunes:duration>
                </item>
                                                <item>
                    <episode_id>92816</episode_id>
                    <title>Joost Batenburg: detecting fingerprints with tomography (digital archaeology)</title>
                    <itunes:title>Joost Batenburg: detecting fingerprints with tomography (digital archaeology)
                    </itunes:title>
                    <link>https://app.springcast.fm/19948/joost-batenburg-detecting-fingerprints-with-tomography-digital-archaeology</link>
                    <description>
                        <![CDATA[<p>Enter the realm of tomography, the work field of 'digital archaeologist' Professor Joost Batenburg. Tomography is a technique to peer into objects without taking them apart, akin to the familiar CT scan. Two-dimensional images are converted into three-dimensional images using algorithms. </p><p>Now Professor Batenburg has created a portable device that goes around objects, capturing their insides. No longer constrained by size, this device unveils the unseen, revealing secrets within sculptures and artifacts. This provides art historians with a wealth of valuable information about the creation of these artworks.  <br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p>
                        ]]>
                    </description>
                    <description_item_stripped>
                        <![CDATA[Enter the realm of tomography, the work field of 'digital archaeologist' Professor Joost Batenburg. Tomography is a technique to peer into objects without taking them apart, akin to the familiar CT scan. Two-dimensional images are converted into three-dimensional images using algorithms. Now Professor Batenburg has created a portable device that goes around objects, capturing their insides. No longer constrained by size, this device unveils the unseen, revealing secrets within sculptures and artifacts. This provides art historians with a wealth of valuable information about the creation of these artworks.  Idea by Dimitra KouimtzidouResearch, planning & coordination by Marcel Tichelaar & Dimitra KouimtzidouInterview, production & editing by Michiel van Poelgeest
                        ]]>
                    </description_item_stripped>
                    <itunes:summary>
                        <![CDATA[<p>Enter the realm of tomography, the work field of 'digital archaeologist' Professor Joost Batenburg. Tomography is a technique to peer into objects without taking them apart, akin to the familiar CT scan. Two-dimensional images are converted into three-dimensional images using algorithms. </p><p>Now Professor Batenburg has created a portable device that goes around objects, capturing their insides. No longer constrained by size, this device unveils the unseen, revealing secrets within sculptures and artifacts. This provides art historians with a wealth of valuable information about the creation of these artworks.  <br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p>
                        ]]>
                    </itunes:summary>
                    <itunes:subtitle><![CDATA[]]>
                    </itunes:subtitle>
                    <itunes:author>LIACS</itunes:author>
                    <itunes:image
                        href="https://app.springcast.fm/storage/artwork/7022/19948/92816/VmVjqCLWAcqFJcC0hks0mTGcIVvWzI8TQ2p0yXO5.png"/>
                    <enclosure
                        url="https://app.springcast.fm/download/92816/louMeQ35KQViuQ3DaBzrJQLvfTxLWzoG.mp3"
                        length="35836096"
                        type="audio/mpeg"/>
                    <itunes:episodeType>full</itunes:episodeType>
                    <guid>https://app.springcast.fm/19948/joost-batenburg-detecting-fingerprints-with-tomography-digital-archaeology</guid>
                    <pubDate>Tue, 23 Apr 2024 01:00:00 +0200</pubDate>
                    <pubDate_friendly>Tuesday 23 Apr 2024</pubDate_friendly>
                    <pubDate_sortable>2024-04-23 01:00:00</pubDate_sortable>
                    <itunes:episode>4</itunes:episode>
                    <itunes:season>1</itunes:season>
                    <itunes:explicit>no</itunes:explicit>
                    <itunes:duration>0:14:55</itunes:duration>
                </item>
                                                <item>
                    <episode_id>90451</episode_id>
                    <title>Max van Duijn: using language as a window on the mind</title>
                    <itunes:title>Max van Duijn: using language as a window on the mind
                    </itunes:title>
                    <link>https://app.springcast.fm/19948/max-van-duijn</link>
                    <description>
                        <![CDATA[<p>Assistant professor Max van Duijn combines cognitive science with Artificial Intelligence (AI). His research is on children’s stories and the question if they have a so-called Theory of Mind. This is the ability to understand the mental state of somebody else and use this information to explain and predict human behavior. </p><p>But here's the twist: Max's research not only applies to the exploration of storytelling but also serves as a test for AI. With the data collection, he and his team investigate uncharted territory: Does AI possess a mind? Can entities like ChatGPT truly empathize? <br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p>
                        ]]>
                    </description>
                    <description_item_stripped>
                        <![CDATA[Assistant professor Max van Duijn combines cognitive science with Artificial Intelligence (AI). His research is on children’s stories and the question if they have a so-called Theory of Mind. This is the ability to understand the mental state of somebody else and use this information to explain and predict human behavior. But here's the twist: Max's research not only applies to the exploration of storytelling but also serves as a test for AI. With the data collection, he and his team investigate uncharted territory: Does AI possess a mind? Can entities like ChatGPT truly empathize? Idea by Dimitra KouimtzidouResearch, planning & coordination by Marcel Tichelaar & Dimitra KouimtzidouInterview, production & editing by Michiel van Poelgeest
                        ]]>
                    </description_item_stripped>
                    <itunes:summary>
                        <![CDATA[<p>Assistant professor Max van Duijn combines cognitive science with Artificial Intelligence (AI). His research is on children’s stories and the question if they have a so-called Theory of Mind. This is the ability to understand the mental state of somebody else and use this information to explain and predict human behavior. </p><p>But here's the twist: Max's research not only applies to the exploration of storytelling but also serves as a test for AI. With the data collection, he and his team investigate uncharted territory: Does AI possess a mind? Can entities like ChatGPT truly empathize? <br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p>
                        ]]>
                    </itunes:summary>
                    <itunes:subtitle><![CDATA[]]>
                    </itunes:subtitle>
                    <itunes:author>LIACS</itunes:author>
                    <itunes:image
                        href="https://app.springcast.fm/storage/artwork/7022/19948/90451/sVlGlMKMaFAMgvj6isTJj5K0KJUjohWJSvY62cVy.png"/>
                    <enclosure
                        url="https://app.springcast.fm/download/90451/3Gx0FiHbdwqRA9pusYtSyJOM0iKLLCfj.mp3"
                        length="44806336"
                        type="audio/mpeg"/>
                    <itunes:episodeType>full</itunes:episodeType>
                    <guid>https://app.springcast.fm/19948/max-van-duijn</guid>
                    <pubDate>Tue, 09 Apr 2024 01:00:00 +0200</pubDate>
                    <pubDate_friendly>Tuesday 09 Apr 2024</pubDate_friendly>
                    <pubDate_sortable>2024-04-09 01:00:00</pubDate_sortable>
                    <itunes:episode>3</itunes:episode>
                    <itunes:season>1</itunes:season>
                    <itunes:explicit>no</itunes:explicit>
                    <itunes:duration>0:18:40</itunes:duration>
                </item>
                                                <item>
                    <episode_id>90672</episode_id>
                    <title>Niki van Stein:  can explainable AI save lives?</title>
                    <itunes:title>Niki van Stein:  can explainable AI save lives?
                    </itunes:title>
                    <link>https://app.springcast.fm/19948/niki</link>
                    <description>
                        <![CDATA[<p>Niki van Stein is assistant professor at LIACS. Her research focuses on explainable artificial intelligence (AI), with a specific focus on the maritime sector. At a time when modern marine vessels are evolving into complex supercomputers on water, AI plays a crucial role in efficiently managing maintenance tasks.</p><p>However, the key to success lies in the ability of these AI systems to be understandable to both maintenance workers and crew on board. This is where Niki's research comes in: she aims to make AI accessible and understandable to everyone involved in ship maintenance.<br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p>
                        ]]>
                    </description>
                    <description_item_stripped>
                        <![CDATA[Niki van Stein is assistant professor at LIACS. Her research focuses on explainable artificial intelligence (AI), with a specific focus on the maritime sector. At a time when modern marine vessels are evolving into complex supercomputers on water, AI plays a crucial role in efficiently managing maintenance tasks.However, the key to success lies in the ability of these AI systems to be understandable to both maintenance workers and crew on board. This is where Niki's research comes in: she aims to make AI accessible and understandable to everyone involved in ship maintenance.Idea by Dimitra KouimtzidouResearch, planning & coordination by Marcel Tichelaar & Dimitra KouimtzidouInterview, production & editing by Michiel van Poelgeest
                        ]]>
                    </description_item_stripped>
                    <itunes:summary>
                        <![CDATA[<p>Niki van Stein is assistant professor at LIACS. Her research focuses on explainable artificial intelligence (AI), with a specific focus on the maritime sector. At a time when modern marine vessels are evolving into complex supercomputers on water, AI plays a crucial role in efficiently managing maintenance tasks.</p><p>However, the key to success lies in the ability of these AI systems to be understandable to both maintenance workers and crew on board. This is where Niki's research comes in: she aims to make AI accessible and understandable to everyone involved in ship maintenance.<br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p>
                        ]]>
                    </itunes:summary>
                    <itunes:subtitle><![CDATA[]]>
                    </itunes:subtitle>
                    <itunes:author>LIACS</itunes:author>
                    <itunes:image
                        href="https://app.springcast.fm/storage/artwork/7022/19948/90672/wkEDYi3DlwYYqmqbKDlj7KoFXGAxcVd5OAHOtnnK.png"/>
                    <enclosure
                        url="https://app.springcast.fm/download/90672/Rwn9aM7wqfH5FLTfHLHOWr0eGvdCcwL2.mp3"
                        length="35446336"
                        type="audio/mpeg"/>
                    <itunes:episodeType>full</itunes:episodeType>
                    <guid>https://app.springcast.fm/19948/niki</guid>
                    <pubDate>Tue, 26 Mar 2024 01:00:00 +0100</pubDate>
                    <pubDate_friendly>Tuesday 26 Mar 2024</pubDate_friendly>
                    <pubDate_sortable>2024-03-26 01:00:00</pubDate_sortable>
                    <itunes:episode>2</itunes:episode>
                    <itunes:season>1</itunes:season>
                    <itunes:explicit>no</itunes:explicit>
                    <itunes:duration>0:14:46</itunes:duration>
                </item>
                                                <item>
                    <episode_id>90443</episode_id>
                    <title>Suzan Verberne: the future of chatbots is human</title>
                    <itunes:title>Suzan Verberne: the future of chatbots is human
                    </itunes:title>
                    <link>https://app.springcast.fm/19948/suzan-verberne-the-future-of-chatbots-is-human</link>
                    <description>
                        <![CDATA[<p>Professor Suzan Verberne talks about her research on search engines and chatbots. She explains the difference between search engines such as Google, and large language models like ChatGPT. </p><p>Furthermore, contrary to what many people think, Dutch as a language is much 'bigger' than you might expect. As a country we produce vast amounts of text. But will this help LLMs to adapt to local needs? Or do humans simply need to understand this technology better, in order to make full use of it?<br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p><p><br></p>
                        ]]>
                    </description>
                    <description_item_stripped>
                        <![CDATA[Professor Suzan Verberne talks about her research on search engines and chatbots. She explains the difference between search engines such as Google, and large language models like ChatGPT. Furthermore, contrary to what many people think, Dutch as a language is much 'bigger' than you might expect. As a country we produce vast amounts of text. But will this help LLMs to adapt to local needs? Or do humans simply need to understand this technology better, in order to make full use of it?Idea by Dimitra KouimtzidouResearch, planning & coordination by Marcel Tichelaar & Dimitra KouimtzidouInterview, production & editing by Michiel van Poelgeest
                        ]]>
                    </description_item_stripped>
                    <itunes:summary>
                        <![CDATA[<p>Professor Suzan Verberne talks about her research on search engines and chatbots. She explains the difference between search engines such as Google, and large language models like ChatGPT. </p><p>Furthermore, contrary to what many people think, Dutch as a language is much 'bigger' than you might expect. As a country we produce vast amounts of text. But will this help LLMs to adapt to local needs? Or do humans simply need to understand this technology better, in order to make full use of it?<br><br>Idea by Dimitra Kouimtzidou<br>Research, planning & coordination by Marcel Tichelaar & Dimitra Kouimtzidou<br>Interview, production & editing by Michiel van Poelgeest</p><p><br></p>
                        ]]>
                    </itunes:summary>
                    <itunes:subtitle><![CDATA[Chatbots vs Large Language Models]]>
                    </itunes:subtitle>
                    <itunes:author>LIACS</itunes:author>
                    <itunes:image
                        href="https://app.springcast.fm/storage/artwork/7022/19948/90443/PHpr8PKuNl4wQfxAUicIHkSDj02NjcamnlS4nRA9.png"/>
                    <enclosure
                        url="https://app.springcast.fm/download/90443/HgDHD2hBdxoyEzjXYepNWvwSKbIRTann.mp3"
                        length="36686656"
                        type="audio/mpeg"/>
                    <itunes:episodeType>full</itunes:episodeType>
                    <guid>https://app.springcast.fm/19948/suzan-verberne-the-future-of-chatbots-is-human</guid>
                    <pubDate>Tue, 12 Mar 2024 01:00:00 +0100</pubDate>
                    <pubDate_friendly>Tuesday 12 Mar 2024</pubDate_friendly>
                    <pubDate_sortable>2024-03-12 01:00:00</pubDate_sortable>
                    <itunes:episode>1</itunes:episode>
                    <itunes:season>1</itunes:season>
                    <itunes:explicit>no</itunes:explicit>
                    <itunes:duration>0:15:17</itunes:duration>
                </item>
                                                <item>
                    <episode_id>89929</episode_id>
                    <title>Introducing: Computers Don&#039;t Byte</title>
                    <itunes:title>Introducing: Computers Don&#039;t Byte
                    </itunes:title>
                    <link>https://app.springcast.fm/19948/trailer</link>
                    <description>
                        <![CDATA[<p>Leading computer scientists from a variety of fields share their expertise and insights. Dive into the minds of these researchers and learn about real-world applications, the future of AI and related technologies and cutting-edge research. From chatbots to cybersecurity, from quantum to children's stories, each episode offers its own perspective on the changing landscape of computer science. Whether you're a seasoned professional or an aspiring enthusiast, our podcast offers knowledge and inspiration. Listen to these bright minds shaping the digital world.</p><p>Content: <a href="https://liacs.leidenuniv.nl" target="_blank">LIACS</a> (Leiden University)</p><p>Host: Michiel van Poelgeest</p><p>Produced by: <a href="https://studioonzichtbaar.nl" target="_blank">Studio Onzichtbaar</a></p>
                        ]]>
                    </description>
                    <description_item_stripped>
                        <![CDATA[Leading computer scientists from a variety of fields share their expertise and insights. Dive into the minds of these researchers and learn about real-world applications, the future of AI and related technologies and cutting-edge research. From chatbots to cybersecurity, from quantum to children's stories, each episode offers its own perspective on the changing landscape of computer science. Whether you're a seasoned professional or an aspiring enthusiast, our podcast offers knowledge and inspiration. Listen to these bright minds shaping the digital world.Content: LIACS (Leiden University)Host: Michiel van PoelgeestProduced by: Studio Onzichtbaar
                        ]]>
                    </description_item_stripped>
                    <itunes:summary>
                        <![CDATA[<p>Leading computer scientists from a variety of fields share their expertise and insights. Dive into the minds of these researchers and learn about real-world applications, the future of AI and related technologies and cutting-edge research. From chatbots to cybersecurity, from quantum to children's stories, each episode offers its own perspective on the changing landscape of computer science. Whether you're a seasoned professional or an aspiring enthusiast, our podcast offers knowledge and inspiration. Listen to these bright minds shaping the digital world.</p><p>Content: <a href="https://liacs.leidenuniv.nl" target="_blank">LIACS</a> (Leiden University)</p><p>Host: Michiel van Poelgeest</p><p>Produced by: <a href="https://studioonzichtbaar.nl" target="_blank">Studio Onzichtbaar</a></p>
                        ]]>
                    </itunes:summary>
                    <itunes:subtitle><![CDATA[]]>
                    </itunes:subtitle>
                    <itunes:author>LIACS</itunes:author>
                    <itunes:image
                        href="https://app.springcast.fm/storage/artwork/7022/19948/upqGNZIzfciiZdbTP5bFU49l1c0aZvxJqzAWzKD9.png"/>
                    <enclosure
                        url="https://app.springcast.fm/download/89929/6Y0LObbvIsu3D3FPaCRpPGMxMHZWPfVo.mp3"
                        length="5326336"
                        type="audio/mpeg"/>
                    <itunes:episodeType>trailer</itunes:episodeType>
                    <guid>https://app.springcast.fm/19948/trailer</guid>
                    <pubDate>Mon, 04 Mar 2024 01:00:00 +0100</pubDate>
                    <pubDate_friendly>Monday 04 Mar 2024</pubDate_friendly>
                    <pubDate_sortable>2024-03-04 01:00:00</pubDate_sortable>
                    <itunes:episode>0.5</itunes:episode>
                    <itunes:season>1</itunes:season>
                    <itunes:explicit>no</itunes:explicit>
                    <itunes:duration>0:02:13</itunes:duration>
                </item>
                        </channel>
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