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    <fireside:genDate>Thu, 05 Nov 2026 00:41:02 +0000</fireside:genDate>
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    <title>Teaching Python - Episodes Tagged with “Chatgpt”</title>
    <link>https://www.teachingpython.fm/tags/chatgpt</link>
    <pubDate>Fri, 02 Oct 2026 00:00:00 -0400</pubDate>
    <description>Teaching Python is a podcast about Python programming, computer science education, AI literacy, software development, cloud computing, cybersecurity, data, and how people learn technical skills. Hosted by Kelly Schuster-Paredes, Sean Tibor, and Julian Sequeira, the show is for educators, developers, technology leaders, and lifelong learners who want to better understand how Python connects to the wider world of computing. Episodes explore not only how people learn to code, but also how they build technical judgment, understand systems, evaluate AI-generated code, work with data, think about security, and move from beginner programming into real-world software development. About the Hosts Kelly Schuster-Paredes is a teacher who codes whose work has expanded from classroom computer science into AI strategy, curriculum design, professional learning, educational technology, and responsible technology adoption. Her background in Python and computer science education shapes her focus on learning, AI literacy, computational thinking, and what people need to understand in an AI-shaped world. Sean Tibor is Vice President of Infrastructure and Cloud at Pfizer and a former computer science teacher. He brings expertise in cloud computing, infrastructure, engineering operations, and technical leadership, connecting what people learn about computing with how large-scale systems are actually built, operated, secured, and maintained. Julian Sequiera is a technologist, Fractional CTO, and Senior Program Manager with more than 20 years of experience in infrastructure, cloud, engineering operations, and large-scale technology programs. He is also the co-founder of PyBites, a Python learning platform and community that has helped thousands of developers improve their Python and software development skills. What We Cover Python Programming and Computer Science Education: Learning Python, teaching programming, computational thinking, debugging, code literacy, and helping beginners build strong mental models. AI and AI Literacy: AI-assisted programming, evaluating AI-generated code, responsible AI use, human judgment, and what learners still need to understand when AI can produce code. Cloud, Infrastructure, and Cybersecurity: Systems, networks, deployment, security, reliability, architecture, and the operational side of software. Data and Software Engineering: APIs, databases, testing, maintainability, version control, software design, and moving from simple scripts to real-world applications. Learning and Technical Growth: How people learn difficult technical concepts, get unstuck, build confidence, and develop the judgment needed to use technology well. Expert Interviews: Conversations with educators, developers, engineers, researchers, technology leaders, and others shaping the future of computing and technical education. Teaching Python remains grounded in Python, but the conversation extends beyond syntax. The podcast explores the knowledge, skills, systems, and judgment people need to learn, build, and make responsible decisions with technology.</description>
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    <itunes:subtitle>We're two computer science educators learning and teaching Python</itunes:subtitle>
    <itunes:author>Sean Tibor and Kelly Paredes</itunes:author>
    <itunes:summary>Teaching Python is a podcast about Python programming, computer science education, AI literacy, software development, cloud computing, cybersecurity, data, and how people learn technical skills. Hosted by Kelly Schuster-Paredes, Sean Tibor, and Julian Sequeira, the show is for educators, developers, technology leaders, and lifelong learners who want to better understand how Python connects to the wider world of computing. Episodes explore not only how people learn to code, but also how they build technical judgment, understand systems, evaluate AI-generated code, work with data, think about security, and move from beginner programming into real-world software development. About the Hosts Kelly Schuster-Paredes is a teacher who codes whose work has expanded from classroom computer science into AI strategy, curriculum design, professional learning, educational technology, and responsible technology adoption. Her background in Python and computer science education shapes her focus on learning, AI literacy, computational thinking, and what people need to understand in an AI-shaped world. Sean Tibor is Vice President of Infrastructure and Cloud at Pfizer and a former computer science teacher. He brings expertise in cloud computing, infrastructure, engineering operations, and technical leadership, connecting what people learn about computing with how large-scale systems are actually built, operated, secured, and maintained. Julian Sequiera is a technologist, Fractional CTO, and Senior Program Manager with more than 20 years of experience in infrastructure, cloud, engineering operations, and large-scale technology programs. He is also the co-founder of PyBites, a Python learning platform and community that has helped thousands of developers improve their Python and software development skills. What We Cover Python Programming and Computer Science Education: Learning Python, teaching programming, computational thinking, debugging, code literacy, and helping beginners build strong mental models. AI and AI Literacy: AI-assisted programming, evaluating AI-generated code, responsible AI use, human judgment, and what learners still need to understand when AI can produce code. Cloud, Infrastructure, and Cybersecurity: Systems, networks, deployment, security, reliability, architecture, and the operational side of software. Data and Software Engineering: APIs, databases, testing, maintainability, version control, software design, and moving from simple scripts to real-world applications. Learning and Technical Growth: How people learn difficult technical concepts, get unstuck, build confidence, and develop the judgment needed to use technology well. Expert Interviews: Conversations with educators, developers, engineers, researchers, technology leaders, and others shaping the future of computing and technical education. Teaching Python remains grounded in Python, but the conversation extends beyond syntax. The podcast explores the knowledge, skills, systems, and judgment people need to learn, build, and make responsible decisions with technology.</itunes:summary>
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    <itunes:explicit>no</itunes:explicit>
    <itunes:keywords>Python, Python programming, learn Python, teaching Python, computer science education, coding education, programming for beginners, Python for beginners, computational thinking, code literacy, debugging, software development, software engineering, data science, artificial intelligence, AI literacy, AI-assisted coding, generative AI, machine learning, cybersecurity, cloud computing, cloud infrastructure, APIs, databases, systems thinking, technical education, STEM education, educational technology, edtech, curriculum design, instructional design, professional learning, teacher professional development, coding for students, computer science curriculum, physical computing, robotics, responsible AI, digital literacy, data literacy, technology leadership, developer education, technical coaching, lifelong learning, learning to code, teaching programming, real-world programming, coding with AI, Python podcast, computer science podcast, technology education podcast, programming podcast</itunes:keywords>
    <itunes:owner>
      <itunes:name>Sean Tibor and Kelly Paredes</itunes:name>
      <itunes:email>sean.tibor@gmail.com</itunes:email>
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<item>
  <title>Episode 163: How Do You Find Time to Keep Learning?</title>
  <link>https://www.teachingpython.fm/163</link>
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  <pubDate>Fri, 02 Oct 2026 00:00:00 -0400</pubDate>
  <author>Sean Tibor and Kelly Paredes</author>
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  <itunes:episode>163</itunes:episode>
  <itunes:title>How Do You Find Time to Keep Learning?</itunes:title>
  <itunes:episodeType>full</itunes:episodeType>
  <itunes:author>Sean Tibor and Kelly Paredes</itunes:author>
  <itunes:subtitle>Teaching Python started as a podcast about teaching programming in the classroom. But both the hosts and the world around Python have changed.

In this episode, Kelly and Julian reflect on what *Teaching Python* means in 2026, as Python increasingly sits inside a much larger computing landscape that includes AI, data, cybersecurity, cloud, software engineering, systems thinking, and automation.

They explore why Python still matters when AI can generate code, how the skills around programming are changing, and why reading, debugging, evaluating, testing, and modifying code may matter more than simply producing it. The conversation also looks at the changing role of the teacher, coach, and learner when AI can become another source of guidance.

Python is still here. But teaching Python now is increasingly about helping people understand, build, question, and make decisions with technology.</itunes:subtitle>
  <itunes:duration>52:40</itunes:duration>
  <itunes:explicit>no</itunes:explicit>
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  <description>&lt;p&gt;How do you keep learning when there never seems to be enough time?&lt;/p&gt;

&lt;p&gt;The answer may be less about finding more time and more about building learning into the way you already work, solve problems, use AI, and connect with other people.&lt;/p&gt;

&lt;p&gt;In Episode 163 of the Teaching Python Podcast, Sean Tibor, Kelly Schuster-Paredes, and Julian Sequeira discuss how they keep learning in a technology landscape shaped by rapid changes in AI, software development, and computing.&lt;/p&gt;

&lt;p&gt;They compare practical approaches to continuous learning, including building projects, using commutes and downtime, scheduling dedicated learning time, asking ChatGPT and Claude questions as they come up, watching webinars, reading, experimenting with new tools, and learning from professional networks.&lt;/p&gt;

&lt;p&gt;The conversation also explores what happens when you need to learn something you are not naturally interested in. They discuss adult learning, desirable difficulty, just-in-time learning, recursive learning, and why struggling with unfamiliar ideas can still be valuable even when AI can explain concepts instantly.&lt;/p&gt;

&lt;p&gt;Along the way, they talk about vibe coding, AI as a learning partner, professional development, technical communities, balancing creation and consumption, and setting boundaries so that continuous learning does not become constant burnout.&lt;/p&gt;

&lt;p&gt;If you are trying to keep up with AI, learn new technology, or continue developing technical skills without turning every spare moment into work, this episode offers a practical look at how learning can become part of everyday life.&lt;/p&gt;</description>
  <itunes:keywords>teaching python, continuous learning, recursive learning, lifelong learning, adult learning, learning how to learn, learning in technology, learning in tech, AI learning, AI for learning, learning with AI, keeping up with AI, keeping up with technology, learning new technology, ChatGPT for learning, Claude AI, AI learning partner, vibe coding, just-in-time learning, professional development, professional learning, technical skills, software development, coding, computer science, educational technology, edtech, digital literacy, AI literacy, knowledge work, productivity, time management, priority management, technical communities, professional networks, learning by building, project-based learning, desirable difficulty, burnout, work-life balance, technology careers, lifelong professional learning</itunes:keywords>
  <content:encoded>
    <![CDATA[<p>How do you keep learning when there never seems to be enough time?</p>

<p>The answer may be less about finding more time and more about building learning into the way you already work, solve problems, use AI, and connect with other people.</p>

<p>In Episode 163 of the Teaching Python Podcast, Sean Tibor, Kelly Schuster-Paredes, and Julian Sequeira discuss how they keep learning in a technology landscape shaped by rapid changes in AI, software development, and computing.</p>

<p>They compare practical approaches to continuous learning, including building projects, using commutes and downtime, scheduling dedicated learning time, asking ChatGPT and Claude questions as they come up, watching webinars, reading, experimenting with new tools, and learning from professional networks.</p>

<p>The conversation also explores what happens when you need to learn something you are not naturally interested in. They discuss adult learning, desirable difficulty, just-in-time learning, recursive learning, and why struggling with unfamiliar ideas can still be valuable even when AI can explain concepts instantly.</p>

<p>Along the way, they talk about vibe coding, AI as a learning partner, professional development, technical communities, balancing creation and consumption, and setting boundaries so that continuous learning does not become constant burnout.</p>

<p>If you are trying to keep up with AI, learn new technology, or continue developing technical skills without turning every spare moment into work, this episode offers a practical look at how learning can become part of everyday life.</p><p><a rel="payment" href="https://www.patreon.com/teachingpython">Support Teaching Python</a></p>]]>
  </content:encoded>
  <itunes:summary>
    <![CDATA[<p>How do you keep learning when there never seems to be enough time?</p>

<p>The answer may be less about finding more time and more about building learning into the way you already work, solve problems, use AI, and connect with other people.</p>

<p>In Episode 163 of the Teaching Python Podcast, Sean Tibor, Kelly Schuster-Paredes, and Julian Sequeira discuss how they keep learning in a technology landscape shaped by rapid changes in AI, software development, and computing.</p>

<p>They compare practical approaches to continuous learning, including building projects, using commutes and downtime, scheduling dedicated learning time, asking ChatGPT and Claude questions as they come up, watching webinars, reading, experimenting with new tools, and learning from professional networks.</p>

<p>The conversation also explores what happens when you need to learn something you are not naturally interested in. They discuss adult learning, desirable difficulty, just-in-time learning, recursive learning, and why struggling with unfamiliar ideas can still be valuable even when AI can explain concepts instantly.</p>

<p>Along the way, they talk about vibe coding, AI as a learning partner, professional development, technical communities, balancing creation and consumption, and setting boundaries so that continuous learning does not become constant burnout.</p>

<p>If you are trying to keep up with AI, learn new technology, or continue developing technical skills without turning every spare moment into work, this episode offers a practical look at how learning can become part of everyday life.</p><p><a rel="payment" href="https://www.patreon.com/teachingpython">Support Teaching Python</a></p>]]>
  </itunes:summary>
</item>
<item>
  <title>Episode 113: ChatGPT and Studying Teachers</title>
  <link>https://www.teachingpython.fm/113</link>
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  <pubDate>Mon, 31 Jul 2023 08:00:00 -0400</pubDate>
  <author>Sean Tibor and Kelly Paredes</author>
  <enclosure url="https://aphid.fireside.fm/d/1437767933/c8ea6bdf-0c80-46e7-a00a-639d7dc2be91/8b0570d1-29db-45bb-b796-4f075d9f1743.mp3" length="67708588" type="audio/mpeg"/>
  <itunes:episode>113</itunes:episode>
  <itunes:title>ChatGPT and Studying Teachers</itunes:title>
  <itunes:episodeType>full</itunes:episodeType>
  <itunes:author>Sean Tibor and Kelly Paredes</itunes:author>
  <itunes:subtitle>This week we are joined by Philip Guo and Sam Lau, researchers at the University of California, San Diego. Philip and Sam have recently published research on how computer science instructors use artificial intelligence tools like ChatGPT and GitHub Copilot in their classrooms. Join us to learn more about the data behind how generative AI is changing the way we teach computer science and coding.</itunes:subtitle>
  <itunes:duration>56:25</itunes:duration>
  <itunes:explicit>no</itunes:explicit>
  <itunes:image href="https://cdn.fireside.fm/file/fireside-images-2024/podcasts/images/c/c8ea6bdf-0c80-46e7-a00a-639d7dc2be91/episodes/8/8b0570d1-29db-45bb-b796-4f075d9f1743/cover.jpg?v=1"/>
  <description>&lt;p&gt;This week we are joined by Philip Guo and Sam Lau, researchers at the University of California, San Diego. Philip and Sam have recently published research on how computer science instructors use artificial intelligence tools like ChatGPT and GitHub Copilot in their classrooms. Join us to learn more about the data behind how generative AI is changing the way we teach computer science and coding.&lt;/p&gt;&lt;p&gt;Special Guests: Philip Guo and Sam Lau.&lt;/p&gt;</description>
  <itunes:keywords>python,teaching,chatgpt,github copilot</itunes:keywords>
  <content:encoded>
    <![CDATA[<p>This week we are joined by Philip Guo and Sam Lau, researchers at the University of California, San Diego. Philip and Sam have recently published research on how computer science instructors use artificial intelligence tools like ChatGPT and GitHub Copilot in their classrooms. Join us to learn more about the data behind how generative AI is changing the way we teach computer science and coding.</p><p>Special Guests: Philip Guo and Sam Lau.</p><p><a rel="payment" href="https://www.patreon.com/teachingpython">Support Teaching Python</a></p><p>Links:</p><ul><li><a title="sam lau" rel="nofollow" href="https://www.samlau.me/">sam lau
</a></li><li><a title="AI Code Generation Tools Study" rel="nofollow" href="https://www.samlau.me/pubs/cs-instructors-adapting-to-chatgpt-copilot-ai-tools_ICER-2023.pdf">AI Code Generation Tools Study
</a> &mdash; From "Ban It Till We Understand It" to "Resistance is Futile": How University Programming Instructors Plan to Adapt as More Students Use AI Code Generation and Explanation Tools such as ChatGPT and GitHub Copilot
</li><li><a title="Pandas Tutor: Using Pyodide to Teach Data Science at Scale | Pyodide blog" rel="nofollow" href="https://blog.pyodide.org/posts/pandastutor/">Pandas Tutor: Using Pyodide to Teach Data Science at Scale | Pyodide blog
</a> &mdash; Hi, we’re Sam Lau and Philip Guo, and we teach data science classes at UC San Diego. In this guest post we’ll tell you about our free educational tool, Pandas Tutor, that helps students learn data science using the popular pandas library. The above screenshot shows how you can use it to write Python and pandas code in a web-based editor and see visualizations of what your code does step-by-step.
</li><li><a title="Pandas Tutor - visualize Python pandas code" rel="nofollow" href="https://pandastutor.com/">Pandas Tutor - visualize Python pandas code
</a> &mdash; Pandas Tutor lets you write Python pandas code in your browser and see how it transforms your data step-by-step. (If you use R, try Tidy Data Tutor. To visualize general Python, Java, C, C++, and JavaScript code, try Python Tutor.)
</li><li><a title="Teaching Programming in the Age of ChatGPT" rel="nofollow" href="https://www.oreilly.com/radar/teaching-programming-in-the-age-of-chatgpt/">Teaching Programming in the Age of ChatGPT
</a> &mdash; How computing instructors plan to adapt to ChatGPT, GitHub Copilot, and other AI coding assistants (ICER 2023 paper)
</li><li><a title="Real-Real-World Programming with ChatGPT" rel="nofollow" href="https://www.oreilly.com/radar/real-real-world-programming-with-chatgpt/">Real-Real-World Programming with ChatGPT
</a> &mdash; Taking AI Far Beyond Small Self-Contained Coding Tasks
</li></ul>]]>
  </content:encoded>
  <itunes:summary>
    <![CDATA[<p>This week we are joined by Philip Guo and Sam Lau, researchers at the University of California, San Diego. Philip and Sam have recently published research on how computer science instructors use artificial intelligence tools like ChatGPT and GitHub Copilot in their classrooms. Join us to learn more about the data behind how generative AI is changing the way we teach computer science and coding.</p><p>Special Guests: Philip Guo and Sam Lau.</p><p><a rel="payment" href="https://www.patreon.com/teachingpython">Support Teaching Python</a></p><p>Links:</p><ul><li><a title="sam lau" rel="nofollow" href="https://www.samlau.me/">sam lau
</a></li><li><a title="AI Code Generation Tools Study" rel="nofollow" href="https://www.samlau.me/pubs/cs-instructors-adapting-to-chatgpt-copilot-ai-tools_ICER-2023.pdf">AI Code Generation Tools Study
</a> &mdash; From "Ban It Till We Understand It" to "Resistance is Futile": How University Programming Instructors Plan to Adapt as More Students Use AI Code Generation and Explanation Tools such as ChatGPT and GitHub Copilot
</li><li><a title="Pandas Tutor: Using Pyodide to Teach Data Science at Scale | Pyodide blog" rel="nofollow" href="https://blog.pyodide.org/posts/pandastutor/">Pandas Tutor: Using Pyodide to Teach Data Science at Scale | Pyodide blog
</a> &mdash; Hi, we’re Sam Lau and Philip Guo, and we teach data science classes at UC San Diego. In this guest post we’ll tell you about our free educational tool, Pandas Tutor, that helps students learn data science using the popular pandas library. The above screenshot shows how you can use it to write Python and pandas code in a web-based editor and see visualizations of what your code does step-by-step.
</li><li><a title="Pandas Tutor - visualize Python pandas code" rel="nofollow" href="https://pandastutor.com/">Pandas Tutor - visualize Python pandas code
</a> &mdash; Pandas Tutor lets you write Python pandas code in your browser and see how it transforms your data step-by-step. (If you use R, try Tidy Data Tutor. To visualize general Python, Java, C, C++, and JavaScript code, try Python Tutor.)
</li><li><a title="Teaching Programming in the Age of ChatGPT" rel="nofollow" href="https://www.oreilly.com/radar/teaching-programming-in-the-age-of-chatgpt/">Teaching Programming in the Age of ChatGPT
</a> &mdash; How computing instructors plan to adapt to ChatGPT, GitHub Copilot, and other AI coding assistants (ICER 2023 paper)
</li><li><a title="Real-Real-World Programming with ChatGPT" rel="nofollow" href="https://www.oreilly.com/radar/real-real-world-programming-with-chatgpt/">Real-Real-World Programming with ChatGPT
</a> &mdash; Taking AI Far Beyond Small Self-Contained Coding Tasks
</li></ul>]]>
  </itunes:summary>
</item>
<item>
  <title>Episode 103: ChatGPT and Learning</title>
  <link>https://www.teachingpython.fm/103</link>
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  <pubDate>Thu, 05 Jan 2023 08:00:00 -0500</pubDate>
  <author>Sean Tibor and Kelly Paredes</author>
  <enclosure url="https://aphid.fireside.fm/d/1437767933/c8ea6bdf-0c80-46e7-a00a-639d7dc2be91/ba186cf5-7a60-4799-9997-4fb5ef54d067.mp3" length="59486286" type="audio/mpeg"/>
  <itunes:episode>103</itunes:episode>
  <itunes:title>ChatGPT and Learning</itunes:title>
  <itunes:episodeType>full</itunes:episodeType>
  <itunes:author>Sean Tibor and Kelly Paredes</itunes:author>
  <itunes:subtitle>In this episode of Teaching Python, Kelly and Sean consider the potential effects of ChatGPT on computer science education. They explore the question of whether ChatGPT will assist or hinder the learning process, and consider ways in which this innovative artificial intelligence tool might be used beneficially.</itunes:subtitle>
  <itunes:duration>49:34</itunes:duration>
  <itunes:explicit>no</itunes:explicit>
  <itunes:image href="https://cdn.fireside.fm/file/fireside-images-2024/podcasts/images/c/c8ea6bdf-0c80-46e7-a00a-639d7dc2be91/episodes/b/ba186cf5-7a60-4799-9997-4fb5ef54d067/cover.jpg?v=1"/>
  <description>&lt;p&gt;This episode description was written by ChatGPT. What do you think?&lt;/p&gt;

&lt;hr&gt;

&lt;p&gt;In this episode of the Teaching Python podcast, Kelly and Sean delve into the topic of ChatGPT and its potential impact on computer science education. &lt;a href="https://openai.com/blog/chatgpt/" rel="nofollow noopener"&gt;ChatGPT&lt;/a&gt; is a new artificial intelligence tool developed by OpenAI that has generated a lot of buzz in the tech industry. The hosts consider both the potential benefits and drawbacks of using ChatGPT in the classroom, and discuss how it could be used to enhance the learning experience.&lt;/p&gt;

&lt;p&gt;One of the key points they address is the question of whether ChatGPT will be a helpful or harmful addition to computer science education. On the one hand, ChatGPT has the potential to be a powerful teaching aid, providing students with a unique and engaging way to learn. On the other hand, there are concerns that the use of ChatGPT could lead to a reduction in critical thinking skills, as students may rely too heavily on the tool for solutions.&lt;/p&gt;

&lt;p&gt;Ultimately, Kelly and Sean argue that ChatGPT has the potential to be a valuable resource for educators, but it is important to use it in a balanced and mindful way. They suggest that incorporating ChatGPT into the curriculum in combination with other teaching methods could be an effective way to maximize its benefits and minimize any negative effects. If you are interested in learning more about ChatGPT and its potential applications in education, be sure to check out the linked resources.&lt;/p&gt;</description>
  <itunes:keywords>ChatGPT, artificial intelligence, computer science education, teaching aid, critical thinking, learning resource, education technology</itunes:keywords>
  <content:encoded>
    <![CDATA[<p>This episode description was written by ChatGPT. What do you think?</p>

<hr>

<p>In this episode of the Teaching Python podcast, Kelly and Sean delve into the topic of ChatGPT and its potential impact on computer science education. <a href="https://openai.com/blog/chatgpt/" rel="nofollow noopener">ChatGPT</a> is a new artificial intelligence tool developed by OpenAI that has generated a lot of buzz in the tech industry. The hosts consider both the potential benefits and drawbacks of using ChatGPT in the classroom, and discuss how it could be used to enhance the learning experience.</p>

<p>One of the key points they address is the question of whether ChatGPT will be a helpful or harmful addition to computer science education. On the one hand, ChatGPT has the potential to be a powerful teaching aid, providing students with a unique and engaging way to learn. On the other hand, there are concerns that the use of ChatGPT could lead to a reduction in critical thinking skills, as students may rely too heavily on the tool for solutions.</p>

<p>Ultimately, Kelly and Sean argue that ChatGPT has the potential to be a valuable resource for educators, but it is important to use it in a balanced and mindful way. They suggest that incorporating ChatGPT into the curriculum in combination with other teaching methods could be an effective way to maximize its benefits and minimize any negative effects. If you are interested in learning more about ChatGPT and its potential applications in education, be sure to check out the linked resources.</p><p><a rel="payment" href="https://www.patreon.com/teachingpython">Support Teaching Python</a></p><p>Links:</p><ul><li><a title="ChatGPT: Optimizing Language Models for Dialogue" rel="nofollow" href="https://openai.com/blog/chatgpt/">ChatGPT: Optimizing Language Models for Dialogue
</a> &mdash; We’ve trained a model called ChatGPT which interacts in a conversational way. The dialogue format makes it possible for ChatGPT to answer followup questions, admit its mistakes, challenge incorrect premises, and reject inappropriate requests. ChatGPT is a sibling model to InstructGPT, which is trained to follow an instruction in a prompt and provide a detailed response.
</li><li><a title="Aligning Language Models to Follow Instructions" rel="nofollow" href="https://openai.com/blog/instruction-following/">Aligning Language Models to Follow Instructions
</a> &mdash; We’ve trained language models that are much better at following user intentions than GPT-3 while also making them more truthful and less toxic, using techniques developed through our alignment research. These InstructGPT models, which are trained with humans in the loop, are now deployed as the default language models on our API.
</li><li><a title="Proximal Policy Optimization" rel="nofollow" href="https://openai.com/blog/openai-baselines-ppo/">Proximal Policy Optimization
</a> &mdash; We’re releasing a new class of reinforcement learning algorithms, Proximal Policy Optimization (PPO), which perform comparably or better than state-of-the-art approaches while being much simpler to implement and tune. PPO has become the default reinforcement learning algorithm at OpenAI because of its ease of use and good performance.
</li><li><a title="ChatGPT Equivalent Is Open-Source, But it Is of No Use to Developers" rel="nofollow" href="https://www.analyticsinsight.net/chatgpt-equivalent-is-open-source-but-it-is-of-no-use-to-developers/">ChatGPT Equivalent Is Open-Source, But it Is of No Use to Developers
</a> &mdash; It seems like the first open-source&nbsp;ChatGPT&nbsp;equivalent has emerged. It is an application of RLHF (Reinforcement Learning with Human Feedback) built on top of&nbsp;Google’s PaLM architecture, which has 540 billion parameters. PaLM + RLHF, ChatGPT Equivalent is open-source now, it is a text-generating model that acts similarly to&nbsp;ChatGPT,&nbsp;was provided by the developer in charge of reverse engineering closed-sourced AI systems like Meta’s Make-A-Video. It is characterized as a work in progress. 
</li><li><a title="How AI Is Changing The Way Students Learn" rel="nofollow" href="https://www.forbes.com/sites/forbestechcouncil/2022/09/20/how-ai-is-changing-the-way-students-learn/?sh=1cb887f97338">How AI Is Changing The Way Students Learn
</a> &mdash; In the education landscape, technology is rapidly changing. AI and machine learning, in particular, are now impacting the education sector in numerous ways. In fact, despite some commonly held beliefs, the use of AI in education goes beyond grading student assessments, and this technology can greatly benefit both educators and students.
</li><li><a title="Brian Bourque on Twitter: " rel="nofollow" href="https://twitter.com/bbourque/status/1610144728514809857?s=12">Brian Bourque on Twitter: 
</a> &mdash; "ChatGPT will revolutionize how non-technical folks build products. Here's an example (I put this together in 2 min, so yeah, it's crappy):" / Twitter
</li><li><a title="Can Anti-Plagiarism Tools Detect When AI Chatbots Write Student Essays? | EdSurge News" rel="nofollow" href="https://www.edsurge.com/news/2022-12-21-can-anti-plagiarism-tools-detect-when-ai-chatbots-write-student-essays">Can Anti-Plagiarism Tools Detect When AI Chatbots Write Student Essays? | EdSurge News
</a> &mdash; After its launch last month, ChatGPT, the latest chatbot released by OpenAI, made the rounds online.

Alex, a sophomore at a university in Pittsburgh, started toying with the chatbot about a week after it was released, after finding out about it on Twitter. Within a couple of days, he got really excited by the quality of the writing it produced. The chatbot was good, he says—really good. (“Alex” is the name that this person provided to EdSurge. He only agreed to speak anonymously, for fear of repercussions for admitting to academic dishonesty.)
</li><li><a title="Will ChatGPT Kill the Student Essay? - The Atlantic" rel="nofollow" href="https://www.theatlantic.com/technology/archive/2022/12/chatgpt-ai-writing-college-student-essays/672371/">Will ChatGPT Kill the Student Essay? - The Atlantic
</a> &mdash; Nobody is prepared for how AI will transform academia.
</li><li><a title="ChatGPT for Google - Chrome Web Store" rel="nofollow" href="https://chrome.google.com/webstore/detail/chatgpt-for-google/jgjaeacdkonaoafenlfkkkmbaopkbilf">ChatGPT for Google - Chrome Web Store
</a> &mdash; Display ChatGPT response alongside Google Search results
This is an open-source extension that show response from ChatGPT alongside Google and other search engines
</li><li><a title="ZohaibAhmed/chatgpt-api: This repo is unofficial ChatGPT api. It is based on Daniel Gross&#39;s WhatsApp GPT" rel="nofollow" href="https://github.com/ZohaibAhmed/chatgpt-api">ZohaibAhmed/chatgpt-api: This repo is unofficial ChatGPT api. It is based on Daniel Gross's WhatsApp GPT
</a> &mdash; It uses playwright and chromium to open browser and parse html.
It is an unoffical api for development purpose only.
</li><li><a title="lencx/ChatGPT: 🔮 ChatGPT Desktop Application (Mac, Windows and Linux)" rel="nofollow" href="https://github.com/lencx/ChatGPT">lencx/ChatGPT: 🔮 ChatGPT Desktop Application (Mac, Windows and Linux)
</a> &mdash; This is a major and exciting update. It works like a Telegram bot command and helps you quickly populate custom models to make chatgpt work the way you want it to. This project has taken a lot of my spare time, so if it helps you, please help spread the word or star it would be a great encouragement to me. I hope I can keep updating it and adding more interesting features.
</li><li><a title="ChatGPT Tutorial - A Crash Course on Chat GPT for Beginners - YouTube" rel="nofollow" href="https://www.youtube.com/watch?v=JTxsNm9IdYU">ChatGPT Tutorial - A Crash Course on Chat GPT for Beginners - YouTube
</a> &mdash; This ChatGPT Tutorial is a Crash Course on Chat GPT for Beginners. With the increase in popularity, ChatGPT is still unknown to many people. In this video, I will provide a crash course on different ways to use ChatGPT.
</li></ul>]]>
  </content:encoded>
  <itunes:summary>
    <![CDATA[<p>This episode description was written by ChatGPT. What do you think?</p>

<hr>

<p>In this episode of the Teaching Python podcast, Kelly and Sean delve into the topic of ChatGPT and its potential impact on computer science education. <a href="https://openai.com/blog/chatgpt/" rel="nofollow noopener">ChatGPT</a> is a new artificial intelligence tool developed by OpenAI that has generated a lot of buzz in the tech industry. The hosts consider both the potential benefits and drawbacks of using ChatGPT in the classroom, and discuss how it could be used to enhance the learning experience.</p>

<p>One of the key points they address is the question of whether ChatGPT will be a helpful or harmful addition to computer science education. On the one hand, ChatGPT has the potential to be a powerful teaching aid, providing students with a unique and engaging way to learn. On the other hand, there are concerns that the use of ChatGPT could lead to a reduction in critical thinking skills, as students may rely too heavily on the tool for solutions.</p>

<p>Ultimately, Kelly and Sean argue that ChatGPT has the potential to be a valuable resource for educators, but it is important to use it in a balanced and mindful way. They suggest that incorporating ChatGPT into the curriculum in combination with other teaching methods could be an effective way to maximize its benefits and minimize any negative effects. If you are interested in learning more about ChatGPT and its potential applications in education, be sure to check out the linked resources.</p><p><a rel="payment" href="https://www.patreon.com/teachingpython">Support Teaching Python</a></p><p>Links:</p><ul><li><a title="ChatGPT: Optimizing Language Models for Dialogue" rel="nofollow" href="https://openai.com/blog/chatgpt/">ChatGPT: Optimizing Language Models for Dialogue
</a> &mdash; We’ve trained a model called ChatGPT which interacts in a conversational way. The dialogue format makes it possible for ChatGPT to answer followup questions, admit its mistakes, challenge incorrect premises, and reject inappropriate requests. ChatGPT is a sibling model to InstructGPT, which is trained to follow an instruction in a prompt and provide a detailed response.
</li><li><a title="Aligning Language Models to Follow Instructions" rel="nofollow" href="https://openai.com/blog/instruction-following/">Aligning Language Models to Follow Instructions
</a> &mdash; We’ve trained language models that are much better at following user intentions than GPT-3 while also making them more truthful and less toxic, using techniques developed through our alignment research. These InstructGPT models, which are trained with humans in the loop, are now deployed as the default language models on our API.
</li><li><a title="Proximal Policy Optimization" rel="nofollow" href="https://openai.com/blog/openai-baselines-ppo/">Proximal Policy Optimization
</a> &mdash; We’re releasing a new class of reinforcement learning algorithms, Proximal Policy Optimization (PPO), which perform comparably or better than state-of-the-art approaches while being much simpler to implement and tune. PPO has become the default reinforcement learning algorithm at OpenAI because of its ease of use and good performance.
</li><li><a title="ChatGPT Equivalent Is Open-Source, But it Is of No Use to Developers" rel="nofollow" href="https://www.analyticsinsight.net/chatgpt-equivalent-is-open-source-but-it-is-of-no-use-to-developers/">ChatGPT Equivalent Is Open-Source, But it Is of No Use to Developers
</a> &mdash; It seems like the first open-source&nbsp;ChatGPT&nbsp;equivalent has emerged. It is an application of RLHF (Reinforcement Learning with Human Feedback) built on top of&nbsp;Google’s PaLM architecture, which has 540 billion parameters. PaLM + RLHF, ChatGPT Equivalent is open-source now, it is a text-generating model that acts similarly to&nbsp;ChatGPT,&nbsp;was provided by the developer in charge of reverse engineering closed-sourced AI systems like Meta’s Make-A-Video. It is characterized as a work in progress. 
</li><li><a title="How AI Is Changing The Way Students Learn" rel="nofollow" href="https://www.forbes.com/sites/forbestechcouncil/2022/09/20/how-ai-is-changing-the-way-students-learn/?sh=1cb887f97338">How AI Is Changing The Way Students Learn
</a> &mdash; In the education landscape, technology is rapidly changing. AI and machine learning, in particular, are now impacting the education sector in numerous ways. In fact, despite some commonly held beliefs, the use of AI in education goes beyond grading student assessments, and this technology can greatly benefit both educators and students.
</li><li><a title="Brian Bourque on Twitter: " rel="nofollow" href="https://twitter.com/bbourque/status/1610144728514809857?s=12">Brian Bourque on Twitter: 
</a> &mdash; "ChatGPT will revolutionize how non-technical folks build products. Here's an example (I put this together in 2 min, so yeah, it's crappy):" / Twitter
</li><li><a title="Can Anti-Plagiarism Tools Detect When AI Chatbots Write Student Essays? | EdSurge News" rel="nofollow" href="https://www.edsurge.com/news/2022-12-21-can-anti-plagiarism-tools-detect-when-ai-chatbots-write-student-essays">Can Anti-Plagiarism Tools Detect When AI Chatbots Write Student Essays? | EdSurge News
</a> &mdash; After its launch last month, ChatGPT, the latest chatbot released by OpenAI, made the rounds online.

Alex, a sophomore at a university in Pittsburgh, started toying with the chatbot about a week after it was released, after finding out about it on Twitter. Within a couple of days, he got really excited by the quality of the writing it produced. The chatbot was good, he says—really good. (“Alex” is the name that this person provided to EdSurge. He only agreed to speak anonymously, for fear of repercussions for admitting to academic dishonesty.)
</li><li><a title="Will ChatGPT Kill the Student Essay? - The Atlantic" rel="nofollow" href="https://www.theatlantic.com/technology/archive/2022/12/chatgpt-ai-writing-college-student-essays/672371/">Will ChatGPT Kill the Student Essay? - The Atlantic
</a> &mdash; Nobody is prepared for how AI will transform academia.
</li><li><a title="ChatGPT for Google - Chrome Web Store" rel="nofollow" href="https://chrome.google.com/webstore/detail/chatgpt-for-google/jgjaeacdkonaoafenlfkkkmbaopkbilf">ChatGPT for Google - Chrome Web Store
</a> &mdash; Display ChatGPT response alongside Google Search results
This is an open-source extension that show response from ChatGPT alongside Google and other search engines
</li><li><a title="ZohaibAhmed/chatgpt-api: This repo is unofficial ChatGPT api. It is based on Daniel Gross&#39;s WhatsApp GPT" rel="nofollow" href="https://github.com/ZohaibAhmed/chatgpt-api">ZohaibAhmed/chatgpt-api: This repo is unofficial ChatGPT api. It is based on Daniel Gross's WhatsApp GPT
</a> &mdash; It uses playwright and chromium to open browser and parse html.
It is an unoffical api for development purpose only.
</li><li><a title="lencx/ChatGPT: 🔮 ChatGPT Desktop Application (Mac, Windows and Linux)" rel="nofollow" href="https://github.com/lencx/ChatGPT">lencx/ChatGPT: 🔮 ChatGPT Desktop Application (Mac, Windows and Linux)
</a> &mdash; This is a major and exciting update. It works like a Telegram bot command and helps you quickly populate custom models to make chatgpt work the way you want it to. This project has taken a lot of my spare time, so if it helps you, please help spread the word or star it would be a great encouragement to me. I hope I can keep updating it and adding more interesting features.
</li><li><a title="ChatGPT Tutorial - A Crash Course on Chat GPT for Beginners - YouTube" rel="nofollow" href="https://www.youtube.com/watch?v=JTxsNm9IdYU">ChatGPT Tutorial - A Crash Course on Chat GPT for Beginners - YouTube
</a> &mdash; This ChatGPT Tutorial is a Crash Course on Chat GPT for Beginners. With the increase in popularity, ChatGPT is still unknown to many people. In this video, I will provide a crash course on different ways to use ChatGPT.
</li></ul>]]>
  </itunes:summary>
</item>
  </channel>
</rss>
