Podcasts about Data science

Today's guest is Xiong Liu, Director of Data Science and AI at Novartis. Novartis is among the world's leading pharmaceutical companies, pioneering data and advanced analytics in the pursuit of new medicines and patient outcomes. Xiong joins Emerj Editorial Director Matthew DeMello to examine how generative AI and foundation models are transforming R&D, clinical workflows, and research collaboration across the life sciences. The discussion highlights how domain-specific data strategies, improved data quality, and shared benchmarks are accelerating discovery and operationalizing AI for measurable ROI in biopharma. Want to share your AI adoption story with executive peers? Click emerj.com/expert2 for more information and to be a potential future guest on the ‘AI in Business' podcast! If you've enjoyed or benefited from some of the insights of this episode, consider leaving us a five-star review on Apple Podcasts, and let us know what you learned, found helpful, or liked most about this show!

Python in 2025 is different. Threads really are about to run in parallel, installs finish before your coffee cools, and containers are the default. In this episode, we count down 38 things to learn this year: free-threaded CPython, uv for packaging, Docker and Compose, Kubernetes with Tilt, DuckDB and Arrow, PyScript at the edge, plus MCP for sane AI workflows. Expect practical wins and migration paths. No buzzword bingo, just what pays off in real apps. Join me along with Peter Wang and Calvin Hendrix-Parker for a fun, fast-moving conversation. Episode sponsors Seer: AI Debugging, Code TALKPYTHON Agntcy Talk Python Courses Links from the show Calvin Hendryx-Parker: github.com/calvinhp Peter on BSky: @wang.social Free-Threaded Wheels: hugovk.github.io Tilt: tilt.dev The Five Demons of Python Packaging That Fuel Our ...: youtube.com Talos Linux: talos.dev Docker: Accelerated Container Application Development: docker.com Scaf - Six Feet Up: sixfeetup.com BeeWare: beeware.org PyScript: pyscript.net Cursor: The best way to code with AI: cursor.com Cline - AI Coding, Open Source and Uncompromised: cline.bot Watch this episode on YouTube: youtube.com Episode #524 deep-dive: talkpython.fm/524 Episode transcripts: talkpython.fm Theme Song: Developer Rap

Topics covered in this episode: * djrest2 -* A small and simple REST library for Django based on class-based views. Github CLI caniscrape - Know before you scrape. Analyze any website's anti-bot protections in seconds. *

Topics covered in this episode: * PyPI+* * uv-ship - a CLI-tool for shipping with uv* * How fast is 3.14?* * air - a new web framework built with FastAPI, Starlette, and Pydantic.* Extras Joke Watch on YouTube About the show Sponsored by us! Support our work through: Our courses at Talk Python Training The Complete pytest Course Patreon Supporters Connect with the hosts Michael: @mkennedy@fosstodon.org / @mkennedy.codes (bsky) Brian: @brianokken@fosstodon.org / @brianokken.bsky.social Show: @pythonbytes@fosstodon.org / @pythonbytes.fm (bsky) Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Monday at 10am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. Michael #1: PyPI+ Very nice search and exploration tool for PyPI Minor but annoying bug: content-types ≠ content_types on PyPI+ but they are in Python itself. Minimum Python version seems to be interpreted as max Python version. See dependency graphs and more Examples content-types jinja-partials fastapi-chameleon Brian #2: uv-ship - a CLI-tool for shipping with uv “uv-ship is a lightweight companion to uv that removes the risky parts of cutting a release. It verifies the repo state, bumps your project metadata and optionally refreshes the changelog. It then commits, tags & pushes the result, while giving you the chance to review every step.” Michael #3: How fast is 3.14? by Miguel Grinberg A big focus on threaded vs. non-threaded Python Some times its faster, other times, it's slower Brian #4: air - a new web framework built with FastAPI, Starlette, and Pydantic. An very new project in Alpha stage by Daniel & Audrey Felderoy, the “Two Scoops of Django” people. Air Tags are an interesting thing. Also Why? is amazing “Don't use AIR” “Every release could break your code! If you have to ask why you should use it, it's probably not for you.” “If you want to use Air, you can. But we don't recommend it.” “It'll likely infect you, your family, and your codebase with an evil web framework mind virus, , …” Extras Brian: Python 3.15a1 is available uv python install 3.15 already works Python lazy imports you can use today - one of two blog posts I threatened to write recently Testing against Python 3.14 - the other one Free Threading has some trove classifiers Michael: Blog post about the book: Talk Python in Production book is out! In particular, the extras are interesting. AI Usage TUI Show me your ls Helium Browser is interesting. But also has Python as a big role. GitHub says Languages Python 97.4%

The podcast, “From CIO to AI Visionary: Nishith Sahay on Marvell's Tech Transformation and the Future of AI Governance, features guest Nishit Sahay, CIO at Marvell Technology who discusses his journey to becoming an SVP and CIO, emphasizing the shift in his role from an "apps and data person" to someone focused on making the company more efficient through technology. The host is Khushboo Bajaj, ServiceNow leader, InfoBeans. 

In this episode of Disruption/Interruption, host KJ sits down with Chris Cyrille, founder of SNTIMNT.AI, to discuss how he’s using data science and AI to bring clarity and confidence to crypto investing. Chris shares his personal journey, the challenges of the crypto market, and how his mission-driven approach is changing the way investors and institutions view digital assets. Key Takeaways: Personal Motivation Drives Innovation [3:52]Chris’s journey began with a personal loss, inspiring him to redirect capital toward causes like pediatric cancer and first-generation students. Crypto Volatility and Misinformation [6:25]The biggest challenge in crypto is volatility, fueled by meme coins, speculation, and misinformation, making it intimidating for new investors. Algorithmic Solutions for Peace of Mind [17:51]Sentiment AI’s algorithm “reads the room” to provide actionable signals, helping users invest with greater confidence and less stress. Staying Curious and Creative [26:34]Chris encourages listeners to maintain childlike wonder and curiosity, as unique perspectives drive creative solutions in any industry. Quote of the Show (26:54):“Keep the childlike wonder and to stay curious. I believe that's where the creativity shows itself.” – Chris Cyrille Join our Anti-PR newsletter where we’re keeping a watchful and clever eye on PR trends, PR fails, and interesting news in tech so you don't have to. You're welcome. Want PR that actually matters? Get 30 minutes of expert advice in a fast-paced, zero-nonsense session from Karla Jo Helms, a veteran Crisis PR and Anti-PR Strategist who knows how to tell your story in the best possible light and get the exposure you need to disrupt your industry. Click here to book your call: https://info.jotopr.com/free-anti-pr-eval Ways to connect with Chris Cyrille: LinkedIn: https://www.linkedin.com/in/chris-cyrille/ Company Website: https://sntimnt.ai How to get more Disruption/Interruption: Amazon Music - https://music.amazon.com/podcasts/eccda84d-4d5b-4c52-ba54-7fd8af3cbe87/disruption-interruption Apple Podcast - https://podcasts.apple.com/us/podcast/disruption-interruption/id1581985755 Spotify - https://open.spotify.com/show/6yGSwcSp8J354awJkCmJlDSee omnystudio.com/listener for privacy information.

Episode #177: Join me, Kimberly Lovi, on an insightful journey as we explore the path to financial empowerment and personal growth in this episode of "In Studio." We'll begin by discussing the critical steps needed to expand your business and income. You'll discover the power of setting clear, specific financial goals rather than settling for vague desires. Together, we'll work backwards to assess where you currently stand and map out the steps needed to reach your desired financial future. By breaking down expenses and creating a concrete plan, we'll guide you towards achieving financial security. Next, we'll tackle the transformative shift from a scarcity mindset to one of abundance. It's essential to recognize money as a form of energy that fuels your ambitions and impacts the world around you. We'll talk about the importance of investing in your business and involving others in your vision to drive success. Letting go of limiting beliefs about money is key, and you'll learn how collaboration and financial investment in capable hands can elevate your endeavors. Finally, we'll highlight the significance of investing in personal growth and development. Drawing from my experiences with courses like Amy Porterfield's Digital Course Academy and a Harvard course on data science principles, I'll share how acquiring new skills can propel both your business and personal goals. We'll also emphasize the importance of setting ambitious goals, surrounding yourself with proactive individuals, and avoiding negativity. Plus, for those struggling with mindset barriers, I'll introduce my mindset course to help you gain clarity and overcome obstacles. As we wrap up, we'll reflect on the importance of accountability and invite you to connect and share your progress. Thank you for joining us, and we hope you leave inspired to take action toward your success. Chapters:  (00:00) Empowerment Through Action (09:48) Overcoming Scarcity Mindset for Success" (24:46) Investing in Personal Growth and Development (35:41) Taking Action for Success Follow Kimberly on Instagram and TikTok @kimberlylovi or @iconicnationmedia  WATCH us on YouTube and view our brand new studio! 

When working with data, it can be easy to fall into the trap of believing that your dataset represents nothing more than numbers on a page. However, behind every data point is a human story - people clicking through websites, abandoning shopping carts, or binge-watching Netflix shows. And in our app-driven world, understanding these human behaviours has become absolutely critical - for businesses to flourish and for data scientists to have a meaningful impact in the work they do. This is where product analytics comes in.In this episode, Miguel Curiel joins Dr. Genevieve Hayes to share his practical checklist for maximising business impact through product analytics, drawing from his own experiences analysing how people actually interact with digital products and his upcoming book on the topic.This episode explores:What product analytics actually involves, beyond just measuring clicks and conversions [03:11]Why behavioural science models are crucial for understanding user motivations [07:25]Miguel's seven-step checklist for building impactful product analytics capabilities [15:49]The most valuable skill for data scientists in product analytics [22:27]Guest BioMiguel Curiel is the Product Analytics Manager at Bloomberg, where he works at the intersection of technology, data and human behaviour. He has a background in neuroscience and psychology and is currently writing a book on product analytics.LinksConnect with Miguel on LinkedInConnect with Genevieve on LinkedInBe among the first to hear about the release of each new podcast episode by signing up HERE

Python typing got fast enough to feel invisible. Pyrefly is a new, open source type checker and IDE language server from Meta, written in Rust, with a focus on instant feedback and real-world DX. Today, we will dig into what it is, why it exists, and how it plays with the rest of the typing ecosystem. We have Abby Mitchell, Danny Yang, and Kyle Into from Pyrefly here to dive into the project. Episode sponsors Sentry Error Monitoring, Code TALKPYTHON Agntcy Talk Python Courses Links from the show Abby Mitchell: linkedin.com Danny Yang: linkedin.com Kyle Into: linkedin.com Pyrefly: pyrefly.org Pyrefly Documentation: pyrefly.org Pyrefly Installation Guide: pyrefly.org Pyrefly IDE Guide: pyrefly.org Pyrefly GitHub Repository: github.com Pyrefly VS Code Extension: marketplace.visualstudio.com Introducing Pyrefly: A New Type Checker and IDE Experience for Python: engineering.fb.com Pyrefly on PyPI: pypi.org InfoQ Coverage: Meta Pyrefly Python Typechecker: infoq.com Pyrefly Discord Invite: discord.gg Python Typing Conformance (GitHub): github.com Typing Conformance Leaderboard (HTML Preview): htmlpreview.github.io Watch this episode on YouTube: youtube.com Episode #523 deep-dive: talkpython.fm/523 Episode transcripts: talkpython.fm Theme Song: Developer Rap

Topics covered in this episode: * Python 3.14* * Free-threaded Python Library Compatibility Checker* * Claude Sonnet 4.5* * Python 3.15 will get Explicit lazy imports* Extras Joke Watch on YouTube About the show Sponsored by DigitalOcean: pythonbytes.fm/digitalocean-gen-ai Use code DO4BYTES and get $200 in free credit Connect with the hosts Michael: @mkennedy@fosstodon.org / @mkennedy.codes (bsky) Brian: @brianokken@fosstodon.org / @brianokken.bsky.social Show: @pythonbytes@fosstodon.org / @pythonbytes.fm (bsky) Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Monday at 10am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. Brian #1: Python 3.14 Released on Oct 7 What's new in Python 3.14 Just a few of the changes PEP 750: Template string literals PEP 758: Allow except and except* expressions without brackets Improved error messages Default interactive shell now highlights Python syntax supports auto-completion argparse better support for python -m module has a new suggest_on_error parameter for “maybe you meant …” support python -m calendar now highlights today's date Plus so much more Michael #2: Free-threaded Python Library Compatibility Checker by Donghee Na App checks compatibility of top PyPI libraries with CPython 3.13t and 3.14t, helping developers understand how the Python ecosystem adapts to upcoming Python versions. It's still pretty red, let's get in the game everyone! Michael #3: Claude Sonnet 4.5 Top programming model (even above Opus 4.1) Shows large improvements in reducing concerning behaviors like sycophancy, deception, power-seeking, and the tendency to encourage delusional thinking Anthropic is releasing the Claude Agent SDK, the same infrastructure that powers Claude Code, making it available for developers to build their own agents, along with major upgrades including checkpoints, a VS Code extension, and new context editing features And Claude Sonnet 4.5 is available in PyCharm too. Brian #4: Python 3.15 will get Explicit lazy imports Discussion on discuss.python.org This PEP introduces syntax for lazy imports as an explicit language feature: lazy import json lazy from json import dumps BTW, lazy loading in fixtures is a super easy way to speed up test startup times. Extras Brian: Music video made in Python - from Patrick of the band “Friends in Real Life” source code: https://gitlab.com/low-capacity-music/r9-legends/ Michael: New article: Thanks AI Lots of updates for content-types Dramatically improved search on Python Bytes (example: https://pythonbytes.fm/search?q=wheel use the filter toggle to see top hits) Talk Python in Production is out and for sale Joke: You do estimates?

Ryan Sawchuk is the VP of Product at Crexi, where he leads cross-functional teams to build advanced, data-rich tools aimed at transforming the commercial real estate workflow. With more than 15 years in product leadership, Ryan specializes in crafting AI-enabled, scalable solutions that boost transaction velocity, improve user experience, and integrate seamlessly into CRE operations. Prior to Crexi, Ryan held senior product roles at Indeed, Procore, and LinkedIn, shaping core features and driving growth in high-scale tech environments. He earned his education from Princeton University, which laid the foundation for his data-driven, user-first product philosophy. At Crexi, Ryan's vision is to bridge the gap between real estate professionals and cutting-edge technology, making complex CRE data more accessible, actionable, and efficient. This is episode was recorded live at Blueprint Vegas 2025.

Who's the most clutch quarterback in NFL history — Tom Brady, Patrick Mahomes, Aaron Rodgers, or someone completely unexpected? We'll use Python + Data Science to figure it out.

Episode Description:  Listen as Kim Beer, Senior Vice President of Policy and External Affairs with the National Health Council, and Dermatologist, Dr. Jeffrey Cohen discuss the 2025 Medicare changes in relation to psoriatic disease and what's to come in 2026 with Jason Harris, Vice President of Government Relations and Advocacy at NPF.  Join this discussion about what changes occurred with Medicare in 2025 that impact psoriatic disease care, outcomes to date, what's to come in 2026, and what you should consider when choosing health care plans during open enrollment with Kim Beer, Senior Vice President of Policy and External Affairs with the National Health Council, Dermatologist, Dr. Jeffrey Cohen, Director of the Psoriasis Treatment Program at Yale University School of Medicine, and Jason Harris, Vice President of Government Relations and Advocacy at NPF.  The intent of this episode is to increase knowledge of the 2025 Medicare changes, what's to come, and how such changes impact psoriatic disease from coverage of prescriptions to overall health care. This episode is sponsored by Novartis. Timestamps:   (0:24) Intro to Psoriasis Uncovered and guest welcome Kim Beer, Senior Vice President of Policy   and External Affairs with the National Health Council, and Dermatologist, Dr. Jeffrey Cohen, Director of the Psoriasis Treatment Program at Yale School of Medicine. (2:25) Perspectives on current health care coverage in Medicare.    (5:14) Biggest changes to Medicare in 2025. (6:36) What is the Medicare Prescription Payment Plan and price negotiation for specific medications. (8:22) Challenges associated with the 2025 Medicare changes from a physician's perspective. (13:10) Price negotiation process via CMS  (Centers for Medicare and Medicaid Services) with the first 10 drugs price effective in 2026.   (17:52) Plan ahead and what to anticipate when choosing the right Medicare plan. (20:04) What the National Health Council and other patient advocacy organizations are doing to assess the impact of the CMS changes and identify steps for moving forward. (21:49) Medicare changes for 2026 that affect deductibles for health care services, prescription drug coverage, and vaccinations. (28:38) Potential assistance options for people who have Medicare insurance. (31:32) The role of patients in providing feedback on policy changes. (33:45) Changing from a commercial insurance plan to a Medicare Plan and what to think about when viewing plan options during the open enrollment period. (37:07) Be part of the process – let your voice be heard by sharing your experiences to help effect change. 3 Key Takeaways: ·       There are four key parts to Medicare health insurance (Part A, B, C and D) which underwent changes in 2025 including a payment cap for prescriptions and availability of a 12 month Prescription Payment Plan to opt in for medications. Additional changes are coming in 2026 including enactment of a price negotiated list of 10 medications. ·       The impact of such changes are both positive (better predictability and affordability) yet also reactionary. Such changes and potential impact should be considered when identifying plan coverage for health care and prescriptions during the open enrollment Medicare period of October 15 to December 7th.   ·       Be involved by telling your story about the impact of Medicare changes and find a trusted health care provider who is willing to work with you to identify an effective treatment plan that aligns with your health care needs and coverage. Guest Bios:   Dermatologist Jeffrey Cohen, M.D., MPH, is the Director of the Psoriasis Treatment Program and the Director of Safety with the Department of Dermatology at Yale University School of Medicine where he is also an Associate Professor of Dermatology and Biomedical Informatics and Data Science. Dr. Cohen treats a variety of skin conditions with a special interest in diseases of the immune system such as psoriasis and eczema tailoring treatments for each individual. He is the author of over 150 peer-reviewed articles on psoriasis and other topics in dermatology. Dr. Cohen serves on the Editorial Board of the Journal of the American Academy of Dermatology, is a Senior Editor for NPF's professional journal for health care providers Journal of Psoriasis and Psoriatic Arthritis, is a Councilor of the International Psoriasis Council, and serves on the Medical Board of the National Psoriasis Foundation.  Kimberly (Kim) Beer is Senior Vice President of Policy and External Affairs at the National Health Council (NHC) of which the National Psoriasis Foundation is a member. Kim leads strategic policy initiative and advocacy efforts to improve the lives of individuals with chronic conditions and disabilities. As a member of the NHC's executive leadership team, she helps to ensure access to high-quality, affordable healthcare for all Americans which includes advocating for policy and health care benefits within Medicare. Resources: For more reources and information about Medicare Contact the Patient Navigation Center to learn more about Medicare, find a health care provider, learn about treatments, or programs that may lower costs.   

Across many democracies, far-right movements are gaining momentum — a trend that worries policymakers, researchers, and citizens alike. A common explanation points to material hardship: when people feel left behind economically and socially, they often turn to radical political alternatives. One critical dimension of this hardship is housing — especially the lack of affordable and secure homes. Could building more affordable housing help reduce support for far-right parties?New research provides a nuanced answer. It finds that expanding access to social housing does seem to lower far-right support — but only in areas with low immigration. In communities where immigration is already high, the effect reverses.To unpack why this is happening, and what it means for policymakers, host Prof Alan Renwick speaks with Dr. Gloria Gennaro, Lecturer in Public Policy and Data Science at UCL's Department of Political Science. Dr. Gennaro shares insights from her latest study, exploring how housing policy, economic insecurity, and social dynamics intersect with political behavior.Mentioned in this episode:Immigration, Public Housing and Support for the French National Front by Gloria Gennaro UCL's Department of Political Science and School of Public Policy offers a uniquely stimulating environment for the study of all fields of politics, including international relations, political theory, human rights, public policy-making and administration. The Department is recognised for its world-class research and policy impact, ranking among the top departments in the UK on both the 2021 Research Excellence Framework and the latest Guardian rankings.

See more: thinkfuture.substack.comConnect with Shahzeb: https://shahzebali.com/---Meet the world's youngest certified Python developer—and the founder of an AI startup.In this episode of thinkfuture, host Chris Kalaboukis talks with Shahzeb Ali, a 17-year-old entrepreneur from Pakistan who's already the youngest certified Python developer recognized by the Python Institute and IBM. He's also the author of Data Science for Teens and the founder of DevelMo, an AI startup helping businesses scale with smart, data-driven solutions.Shahzeb's story is as inspiring as it is forward-looking. From struggling with Visual Basic as a kid to mastering Python and building computer vision products, he's proof that the next generation isn't waiting for permission to innovate.We explore:- How Shahzeb discovered Python and became the youngest certified developer- Why Python's simplicity makes it perfect for teens learning to code- The story behind his AI-powered product, CrowdIQ, and its real-world applications- The pros and cons of “vibe coding” and AI-assisted development- Why critical thinking still matters—even in the age of AI- How easy MVPs and AI tools are fueling a wave of young entrepreneurs- Shahzeb's mission to inspire more teens to pursue tech and entrepreneurshipIf you're passionate about AI, programming, or the next generation of innovators, this episode will leave you feeling optimistic about the future of technology.

Stakeholder requirement gathering is often one of the most dreaded parts of data science projects - dry, tedious sessions where conflicting voices talk past each other and senior executives dominate the conversation. Yet without proper requirements, data science projects are doomed to fail due to solving the wrong problems or missing critical business needs.In this Value Boost episode, David Cohen joins Dr. Genevieve Hayes to reveal how gamification can transform stakeholder meetings from painful obligation into collaborative problem-solving sessions that actually produce useful requirements.You'll learn:Why gamification works as a "Trojan horse" for productive business conversations [03:26]How to ensure every voice is heard, not just the loudest or most senior person in the room [06:34]The simple technique that prevents senior executives from dominating and skewing requirements [06:59]The easiest way to add interactive elements to your next stakeholder meeting without complex games [08:20]Guest BioDavid Cohen is a data and AI strategy consultant, with a background in supporting the F500 clients of both Big 4 and boutique consulting firms. He is the founder of Superposition, a consulting firm that builds collaborative workshops focused on data & AI-related use cases.LinksConnect with David on LinkedInSuperposition websiteSuperposition YouTube channelConnect with Genevieve on LinkedInBe among the first to hear about the release of each new podcast episode by signing up HERE

Today we're turning tiny tips into big wins. Khuyen Tran, creator of CodeCut.ai, has shipped hundreds of bite-size Python and data science snippets across four years. We dig into open-source tools you can use right now, cleaner workflows, and why notebooks and scripts don't have to be enemies. If you want faster insights with fewer yak-shaves, this one's packed with takeaways you can apply before lunch. Let's get into it. Episode sponsors Sentry Error Monitoring, Code TALKPYTHON Agntcy Talk Python Courses Links from the show Khuyen Tran (LinkedIn): linkedin.com Khuyen Tran (GitHub): github.com CodeCut: codecut.ai Production-ready Data Science Book (discount code TalkPython): codecut.ai Why UV Might Be All You Need: codecut.ai How to Structure a Data Science Project for Readability and Transparency: codecut.ai Stop Hard-coding: Use Configuration Files Instead: codecut.ai Simplify Your Python Logging with Loguru: codecut.ai Git for Data Scientists: Learn Git Through Practical Examples: codecut.ai Marimo (A Modern Notebook for Reproducible Data Science): codecut.ai Text Similarity & Fuzzy Matching Guide: codecut.ai Loguru (Python logging made simple): github.com Hydra: hydra.cc Marimo: marimo.io Quarto: quarto.org Show Your Work! Book: austinkleon.com Watch this episode on YouTube: youtube.com Episode #522 deep-dive: talkpython.fm/522 Episode transcripts: talkpython.fm Theme Song: Developer Rap

Jim Tananbaum of Foresite Capital joins Nick to discuss From Data Science to Drug Design: How AI Shifts Discovery, Target Validation, and Portfolio Construction. In this episode we cover: Data Science and Investment Approach Investment Practices and Market Conditions China's Role in Biotech and Regulatory Considerations Impact of AI on Biotech and Healthcare Healthcare Adoption of AI and Preventive Measures Payers and Insurance Companies' Role Lessons from Successful Investments Generating Liquidity in a Sluggish Market Future of GLP-1 Agonists Guest Links: Jim's LinkedIn Jim's X Foresite's LinkedIn Foresite's Website The host of The Full Ratchet is Nick Moran of New Stack Ventures, a venture capital firm committed to investing in founders outside of the Bay Area. We're proud to partner with Ramp, the modern finance automation platform. Book a demo and get $150—no strings attached.   Want to keep up to date with The Full Ratchet? Follow us on social. You can learn more about New Stack Ventures by visiting our LinkedIn and Twitter.  

Kathryn sits down with Jill Kellett, VP of Product & Marketing and Annie Yang, Senior Director of Data Science of Root Inc. to unpack how a smaller player competes with giants. The dive into ditching the idea of campaigns, leveraging deep telematics, and precision targeting.Guest Quotes: "Don't try to go head to head. If you know that you're in a saturated market and that everybody else is running Facebook ads, you're probably not gonna win, or you might win and it might be really cost prohibitive to win." - Jill "We're not going to win on brand spend. We're not trying to target every customer or show an impression to every person in the U.S. We're much more about precision and discipline in our experimentation approach." - AnnieEpisode Breakdown:[04:20] Alchemy UnveiledTelematics and predictive data: Root leverages information on driver safety from their app and from third parties, to predict LTV of customers and adjust their pricing models. [23:06] From Nuggets to Campaign GoldScaling back can glean insights: If you have to turn off channels or partnerships, view it as an opportunity to expose which partners truly drove impact.[31:14] Gold Rush!Don't play where you can't win: if you're a challenger, be strategic where and how you invest. You need to think differently. Links & ResourcesConnect with Kathryn: LinkedInConnect with Jill: LinkedInConnect with Annie: LinkedInLearn more about Root: joinroot.com Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Most data scientists follow the same predictable process: gather requirements, collect data, build models, and only at the very end create visualisations to communicate results. This traditional approach seems logical, but what if it's actually working against us? In this episode, David Cohen joins Dr. Genevieve Hayes to reveal how flipping the script on data visualisation - moving it to the beginning of projects rather than the end - can dramatically improve stakeholder buy-in and project success rates.This episode reveals:Why the traditional bottom-up data communication approach often misses the mark [02:36]How moving visual storytelling to the start of a project can transform stakeholder engagement [06:40]The gamified workshop framework that turns requirement gathering into collaborative problem-solving [08:50]The counterintuitive first step that immediately improves data project outcomes [20:28]Guest BioDavid Cohen is a data and AI strategy consultant, with a background in supporting the F500 clients of both Big 4 and boutique consulting firms. He is the founder of Superposition, a consulting firm that builds collaborative workshops focused on data & AI-related use cases.LinksConnect with David on LinkedInSuperposition websiteSuperposition YouTube channelConnect with Genevieve on LinkedInBe among the first to hear about the release of each new podcast episode by signing up HERE

This week, we chat with Maya Bakhai! Maya Bakhai is the founder of Spice Capital, a first-yes fund investing at pre-seed and seed. Maya's Fund II is a $25M Fund that will invest in ~40 companies with check sizes ranging from $250k-$750k. Spice Capital has over 50 companies in the portfolio including Beehiiv, MUBI, Prosper Health, Hype, Skej, and more.In the last 8 years, Maya has backed 100+ founders.. Prior to starting Spice Capital in 2021, she ran venture investments for Kevin Durant at Thirty Five Ventures where she invested in multiple now-unicorns including: Hugging Face, Robinhood, Skydio, Mercury, Whoop, Rubrik, and Underdog Fantasy. She has a B.S. in Finance and Data Science from NYU. In 2023, she was recognized for her investing in Forbes 30 under 30's Venture Capital list.Maya is based in NYC. Fun fact: In a past life, she produced a sold out off-broadway musical- “Aliens Coming”, a narrative podcast -“Illuminati Interns” and an award-winning web series called “Freelance”.✨ This episode is presented by Brex.Brex: brex.com/trailblazerspodThis episode is supported by RocketReach, Gusto, OpenPhone & Athena.RocketReach: rocketreach.co/trailblazersGusto: gusto.com/trailblazersQuo: Quo.com/trailblazersAthena: athenago.me/Erica-WengerFollow Us!Maya Bakhai: @MayaBakhaiSpice Capital: @spice_cap@thetrailblazerspod: Instagram, YouTube, TikTokErica Wenger: @erica_wenger

In this episode of The Dairy Podcast Show, Dr. Enrico Casella, from Penn State University, discusses how artificial intelligence drives innovation in dairy farming. From using computer vision to estimate body weight to implementing sustainable water management and monitoring heat stress, Dr. Casella explains high-impact solutions advancing cattle health and boosting efficiency on the farm. Tune in on all major platforms!"Depth cameras use height data instead of color, enabling precise bodyweight estimation in dairy systems."Meet the guest: Dr. Enrico Casella, Assistant Professor of Data Science for Animal Systems at Penn State University's Animal Science Department and Co-Hire of the Institute for Computational and Data Sciences, specializes in leveraging Artificial Intelligence (AI) for animal health and development. With a PhD in Computer Science from the University of Kentucky and postdoctoral experience at UW-Madison, his interdisciplinary research integrates AI, computer vision, and optimization techniques.Liked this one? Don't stop now — Here's what we think you'll love!What you'll learn:(00:00) Highlight(01:15) Introduction(01:67) Dr. Casella's career(06:58) AI & bodyweight(15:22) Sustainable water use(19:10) Group data analysis(27:46) Future opportunities(31:49) Final three questionsThe Dairy Podcast Show is trusted and supported by innovative companies like:* Adisseo* Priority IAC* Evonik- dsm-firmenich- SmaXtec- Natural Biologics- Berg + Schmidt- ICC- Protekta- AHV

English is now an API. Our apps read untrusted text; they follow instructions hidden in plain sight, and sometimes they turn that text into action. If you connect a model to tools or let it read documents from the wild, you have created a brand new attack surface. In this episode, we will make that concrete. We will talk about the attacks teams are seeing in 2025, the defenses that actually work, and how to test those defenses the same way we test code. Our guides are Tori Westerhoff and Roman Lutz from Microsoft. They help lead AI red teaming and build PyRIT, a Python framework the Microsoft AI Red Team uses to pressure test real products. By the end of this hour you will know where the biggest risks live, what you can ship this quarter to reduce them, and how PyRIT can turn security from a one time audit into an everyday engineering practice. Episode sponsors Sentry AI Monitoring, Code TALKPYTHON Agntcy Talk Python Courses Links from the show Tori Westerhoff: linkedin.com Roman Lutz: linkedin.com PyRIT: aka.ms/pyrit Microsoft AI Red Team page: learn.microsoft.com 2025 Top 10 Risk & Mitigations for LLMs and Gen AI Apps: genai.owasp.org AI Red Teaming Agent: learn.microsoft.com 3 takeaways from red teaming 100 generative AI products: microsoft.com MIT report: 95% of generative AI pilots at companies are failing: fortune.com A couple of "Little Bobby AI" cartoons Give me candy: talkpython.fm Tell me a joke: talkpython.fm Watch this episode on YouTube: youtube.com Episode #521 deep-dive: talkpython.fm/521 Episode transcripts: talkpython.fm Developer Rap Theme Song: Served in a Flask: talkpython.fm/flasksong --- Stay in touch with us --- Subscribe to Talk Python on YouTube: youtube.com Talk Python on Bluesky: @talkpython.fm at bsky.app Talk Python on Mastodon: talkpython Michael on Bluesky: @mkennedy.codes at bsky.app Michael on Mastodon: mkennedy

Topics covered in this episode: * PostgreSQL 18 Released* * Testing is better than DSA (Data Structures and Algorithms)* * Pyrefly in Cursor/PyCharm/VSCode/etc* * Playwright & pytest techniques that bring me joy* Extras Joke Watch on YouTube About the show Sponsored by us! Support our work through: Our courses at Talk Python Training The Complete pytest Course Patreon Supporters Connect with the hosts Michael: @mkennedy@fosstodon.org / @mkennedy.codes (bsky) Brian: @brianokken@fosstodon.org / @brianokken.bsky.social Show: @pythonbytes@fosstodon.org / @pythonbytes.fm (bsky) Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Monday at 10am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. Michael #1: PostgreSQL 18 Released PostgreSQL 18 is out (Sep 25, 2025) with a focus on faster text handling, async I/O, and easier upgrades. New async I/O subsystem speeds sequential scans, bitmap heap scans, and vacuum by issuing concurrent reads instead of blocking on each request. Major-version upgrades are smoother: pg_upgrade retains planner stats, adds parallel checks via -jobs, and supports faster cutovers with -swap. Smarter query performance lands with skip scans on multicolumn B-tree indexes, better OR optimization, incremental-sort merge joins, and parallel GIN index builds. Dev quality-of-life: virtual generated columns enabled by default, a uuidv7() generator for time-ordered IDs, and RETURNING can expose both OLD and NEW. Security gets an upgrade with native OAuth 2.0 authentication; MD5 password auth is deprecated and TLS controls expand. Text operations get a boost via the new PG_UNICODE_FAST collation, faster upper/lower, a casefold() helper, and clearer collation behavior for LIKE/FTS. Brian #2: Testing is better than DSA (Data Structures and Algorithms) Ned Batchelder If you need to grind through DSA problems to get your first job, then of course, do that, but if you want to prepare yourself for a career, and also stand out in job interviews, learn how to write tests. Testing is a skill you'll use constantly, will make you stand out in job interviews, and isn't taught well in school (usually). Testing code well is not obvious. It's a puzzle and a problem to solve. It gives you confidence and helps you write better code. Applies everywhere, at all levels. Notes from Brian Most devs suck at testing, so being good at it helps you stand out very quickly. Thinking about a system and how to test it often very quickly shines a spotlight on problem areas, parts with not enough specification, and fuzzy requirements. This is a good thing, and bringing up these topics helps you to become a super valuable team member. High level tests need to be understood by key engineers on a project. Even if tons of the code is AI generated. Even if many of the tests are, the people understanding the requirements and the high level tests are quite valuable. Michael #3: Pyrefly in Cursor/PyCharm/VSCode/etc Install the VSCode/Cursor extension or PyCharm plugin, see https://pyrefly.org/en/docs/IDE/ Brian spoke about Pyrefly in #433: Dev in the Arena I've subsequently had the team on Talk Python: #523: Pyrefly: Fast, IDE-friendly typing for Python (podcast version coming in a few weeks, see video for now.) My experience has been Pyrefly changes the feel of the editor, give it a try. But disable the regular language server extension. Brian #4: Playwright & pytest techniques that bring me joy Tim Shilling “I've been working with playwright more often to do end to end tests. As a project grows to do more with HTMX and Alpine in the markup, there's less unit and integration test coverage and a greater need for end to end tests.” Tim covers some cool E2E techniques Open new pages / tabs to be tested Using a pytest marker to identify playwright tests Using a pytest marker in place of fixtures Using page.pause() and Playwright's debugging tool Using assert_axe_violations to prevent accessibility regressions Using page.expect_response() to confirm a background request occurred From Brian Again, with more and more lower level code being generated, and many unit tests being generated (shakes head in sadness), there's an increased need for high level tests. Don't forget API tests, obviously, but if there's a web interface, it's gotta be tested. Especially if the primary user experience is the web interface, building your Playwright testing chops helps you stand out and let's you test a whole lot of your system with not very many tests. Extras Brian: Big O - By Sam Who Yes, take Ned's advice and don't focus so much on DSA, focus also on learning to test. However, one topic you should be comfortable with in algortithm-land is Big O, at least enough to have a gut feel for it. And this article is really good enough for most people. Great graphics, demos, visuals. As usual, great content from Sam Who, and a must read for all serious devs. Python 3.14.0rc3 has been available since Sept 18. Python 3.14.0 final scheduled for Oct 7 Django 6.0 alpha 1 released Django 6.0 final scheduled for Dec 3 Python Test Static hosting update Some interesting discussions around setting up my own server, but this seems like it might be yak shaving procrastination research when I really should be writing or coding. So I'm holding off until I get some writing projects and a couple SaaS projects further along. Joke: Always be backing up

This episode is a little different because Alun turns the microphone toward me. After 456 episodes, it feels both strange and exciting to be the “guest” on my own show. Together, we reflect on the journey so far and then dive into a topic close to both our hearts: the human skills that make statisticians and quantitative scientists truly effective. We talk about leadership as helping others accomplish something, how to influence people across functions (not just departments), why being known inside your organization matters, and how presentation skills can make or break your impact. We wrap up with three actions you can start applying right away.

Colton Pace is a founder and currently the CEO of Ownwell, a Proptech company dedicated to democratizing access to real estate expertise and reducing the hidden costs of homeownership. Under his leadership, Ownwell helps homeowners and property owners identify and appeal overvalued property taxes, reduce insurance and utility costs, and manage other home‑related expenses through data, automation, and local expert teams. Before founding Ownwell, Colton served as an investor, asset manager, and venture capitalist, helping manage billions of dollars across various asset classes. He was part of funds that made early investments in companies such as Uber, Spotify, Redfin, Snowflake, UiPath, Zuora, and Grab. (01:05) - VC to PropTech Founder(03:10) - $797B Property Tax Problem(04:48) - Ownwell Traction: 700K+ Homes and SMB/CRE(06:18) - AI Plus 80 Consultants: How Appeals Get Done(08:50) - Success Rates and Savings: Residential vs Commercial(11:27) - Portfolio Case Study: 124 SFR Properties in Texas(13:45) - Valuation Methods and Local Differences(16:13) - Market Size: $50 to 60B Opportunity(17:29) - Feature: CREtech - Join CREtech New York 2025 on Oct 21-22 for the largest Real Estate Meetings program. Qualified Real Estate pros get free full event pass plus up to $800 in travel and hotel costs. (19:02) - Beyond Taxes: Insurance, Loans, Utilities, Concierge (21:30) - Building Trust with Homeowners and CRE Owners (24:03) - Advice for PropTech Founders Selling into Real Estate (26:49) - Collaboration Superpower: Matthew McConaughey

At PyData Berlin, community members and industry voices highlighted how AI and data tooling are evolving across knowledge graphs, MLOps, small-model fine-tuning, explainability, and developer advocacy.- Igor Kvachenok (Leuphana University / ProKube) combined knowledge graphs with LLMs for structured data extraction in the polymer industry, and noted how MLOps is shifting toward LLM-focused workflows.- Selim Nowicki (Distill Labs) introduced a platform that uses knowledge distillation to fine-tune smaller models efficiently, making model specialization faster and more accessible.- Gülsah Durmaz (Architect & Developer) shared her transition from architecture to coding, creating Python tools for design automation and volunteering with PyData through PyLadies.- Yashasvi Misra (Pure Storage) spoke on explainable AI, stressing accountability and compliance, and shared her perspective as both a data engineer and active Python community organizer.- Mehdi Ouazza (MotherDuck) reflected on developer advocacy through video, workshops, and branding, showing how creative communication boosts adoption of open-source tools like DuckDB.Igor KvachenokMaster's student in Data Science at Leuphana University of Lüneburg, writing a thesis on LLM-enhanced data extraction for the polymer industry. Builds RDF knowledge graphs from semi-structured documents and works at ProKube on MLOps platforms powered by Kubeflow and Kubernetes.Connect: https://www.linkedin.com/in/igor-kvachenok/Selim NowickiFounder of Distill Labs, a startup making small-model fine-tuning simple and fast with knowledge distillation. Previously led data teams at Berlin startups like Delivery Hero, Trade Republic, and Tier Mobility. Sees parallels between today's ML tooling and dbt's impact on analytics.Connect: https://www.linkedin.com/in/selim-nowicki/Gülsah DurmazArchitect turned developer, creating Python-based tools for architectural design automation with Rhino and Grasshopper. Active in PyLadies and a volunteer at PyData Berlin, she values the community for networking and learning, and aims to bring ML into architecture workflows.Connect: https://www.linkedin.com/in/gulsah-durmaz/Yashasvi (Yashi) MisraData Engineer at Pure Storage, community organizer with PyLadies India, PyCon India, and Women Techmakers. Advocates for inclusive spaces in tech and speaks on explainable AI, bridging her day-to-day in data engineering with her passion for ethical ML.Connect: https://www.linkedin.com/in/misrayashasvi/Mehdi OuazzaDeveloper Advocate at MotherDuck, formerly a data engineer, now focused on building community and education around DuckDB. Runs popular YouTube channels ("mehdio DataTV" and "MotherDuck") and delivered a hands-on workshop at PyData Berlin. Blends technical clarity with creative storytelling.Connect: https://www.linkedin.com/in/mehd-io/

Adatépítész -az első magyar datapodcast Minden ami hír, érdekesség, esemény vagy tudásmorzsa az  adat, datascience, adatbányászat és hasonló kockaságok világából. Become a Patron! Kutatás HBR1 HBR2

In this week's episode of the show, I sit down with Justin Evans, author of The Little Book of Data, to talk about what it means to truly think like a data person. Justin shares insights from his 20-year career in data and advertising, reflecting on why so many professionals struggle to embrace data and how his book helps break down those barriers. We discuss the “four layers of data denial,” the qualities that make someone a data person, and the importance of storytelling in making data engaging and useful. Justin also offers stories from Nielsen, Samsung, and beyond to illustrate how data literacy and visualization can create clarity, solve problems, and unlock value. This conversation is both inspiring and practical for anyone working with—or intimidated by—data.Subscribe to the PolicyViz Podcast wherever you get your podcasts.Become a patron of the PolicyViz Podcast for as little as a buck a monthCheck out Justin's book, The Little Book of Data.Follow me on Instagram, LinkedIn, Substack, Twitter, Website, YouTubeEmail: jon@policyviz.com

Join Laborastories host Dr. Paul J. Jannetto and Dr. Patrick Mathias, associate medical director of the informatics division at the University of Washington School of Medicine in Seattle, for an engaging discussion on Dr. Mathias's vision for the ADLM Data Science Certificate Program as the faculty content lead, his thoughts on the benefits of data science for improving the lab's role in patient care, and how lab professionals can start their own learning journey. With special guest: Dr. Patrick Mathias Hosted by: Dr. Paul J. Jannetto

Data science training programs often jump straight into technical methods without teaching one of the most critical skills for project success - problem framing. Without proper framing, data science projects are doomed to fail, right from the start, as data scientists find themselves solving the wrong problems or building models that don't address real business decisions.In this Value Boost episode, Professor Jeff Camm joins Dr. Genevieve Hayes to reveal the specific problem framing framework that decision scientists use to ensure they're solving the right problems from the start, dramatically improving their success rates compared to traditional data science approaches.You'll discover:The medical doctor approach to diagnosing business problems by distinguishing symptoms from root causes [02:09]The critical question that reveals what decisions actually need to be made [04:53]How to turn model "failures" into valuable strategic insights for management [06:24]Why thinking beyond the data prevents you from building technically perfect but business-useless solutions [10:04]Guest BioProf Jeff Camm is a decision scientist and the Inmar Presidential Chair in Analytics at the Wake Forest University School of Business. His research has been featured in top-ranking academic journals and he is the co-author of ten books on business statistics, management science, data visualisation and business analytics.LinksConnect with Jeff on LinkedInConnect with Genevieve on LinkedInBe among the first to hear about the release of each new podcast episode by signing up HERE

A couple years ago, Charlie Marsh lit a fire under Python tooling with Ruff and then uv. Today he's back with something on the other side of that coin: pyx. Pyx isn't a PyPI replacement. Think server, not just index. It mirrors PyPI, plays fine with pip or uv, and aims to make installs fast and predictable by letting a smart client talk to a smart server. When the client and server understand each other, you get new fast paths, fewer edge cases, and the kind of reliability teams beg for. If Python packaging has felt like friction, this conversation is traction. Let's get into it. Episode sponsors Six Feet Up Talk Python Courses Links from the show Charlie Marsh on Twitter: @charliermarsh Charlie Marsh on Mastodon: @charliermarsh Astral Homepage: astral.sh Pyx Project: astral.sh Introducing Pyx Blog Post: astral.sh uv Package on GitHub: github.com UV Star History Chart: star-history.com Watch this episode on YouTube: youtube.com Episode #520 deep-dive: talkpython.fm/520 Episode transcripts: talkpython.fm Developer Rap Theme Song: Served in a Flask: talkpython.fm/flasksong --- Stay in touch with us --- Subscribe to Talk Python on YouTube: youtube.com Talk Python on Bluesky: @talkpython.fm at bsky.app Talk Python on Mastodon: talkpython Michael on Bluesky: @mkennedy.codes at bsky.app Michael on Mastodon: mkennedy

John Berryman (Arcturus Labs; early GitHub Copilot engineer; co-author of Relevant Search and Prompt Engineering for LLMs) has spent years figuring out what makes AI applications actually work in production. In this episode, he shares the “seven deadly sins” of LLM development — and the practical fixes that keep projects from stalling. From context management to retrieval debugging, John explains the patterns he's seen succeed, the mistakes to avoid, and why it helps to think of an LLM as an “AI intern” rather than an all-knowing oracle. We talk through: - Why chasing perfect accuracy is a dead end - How to use agents without losing control - Context engineering: fitting the right information in the window - Starting simple instead of over-orchestrating - Separating retrieval from generation in RAG - Splitting complex extractions into smaller checks - Knowing when frameworks help — and when they slow you down A practical guide to avoiding the common traps of LLM development and building systems that actually hold up in production. LINKS: Context Engineering for AI Agents, a free, upcoming lightning lesson from John and Hugo (https://maven.com/p/4485aa/context-engineering-for-ai-agents) The Hidden Simplicity of GenAI Systems, a previous lightning lesson from John and Hugo (https://maven.com/p/a8195d/the-hidden-simplicity-of-gen-ai-systems) Roaming RAG – RAG without the Vector Database, by John (https://arcturus-labs.com/blog/2024/11/21/roaming-rag--rag-without-the-vector-database/) Cut the Chit-Chat with Artifacts, by John (https://arcturus-labs.com/blog/2024/11/11/cut-the-chit-chat-with-artifacts/) Prompt Engineering for LLMs by John and Albert Ziegler (https://amzn.to/4gChsFf) Relevant Search by John and Doug Turnbull (https://amzn.to/3TXmDHk) Arcturus Labs (https://arcturus-labs.com/) Watch the podcast on YouTube (https://youtu.be/mKTQGKIUq8M) Upcoming Events on Luma (https://lu.ma/calendar/cal-8ImWFDQ3IEIxNWk)

Topics covered in this episode: * pandas is getting pd.col expressions* * Cline, At-Cost Agentic IDE Tooling* * uv cheatsheet* Ducky Network UI Extras Joke Watch on YouTube About the show Sponsored by us! Support our work through: Our courses at Talk Python Training The Complete pytest Course Patreon Supporters Connect with the hosts Michael: @mkennedy@fosstodon.org / @mkennedy.codes (bsky) Brian: @brianokken@fosstodon.org / @brianokken.bsky.social Show: @pythonbytes@fosstodon.org / @pythonbytes.fm (bsky) Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Monday at 10am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. Brian #1: pandas is getting pd.col expressions Marco Gorelli Next release of Pandas will have pd.col(), inspired by some of the other frameworks I'm guessing Pandas 2.3.3? or 2.4.0? or 3.0.0? (depending on which version they bump?) “The output of pd.col is called an expression. You can think of it as a delayed column - it only produces a result once it's evaluated inside a dataframe context.” It replaces many contexts where lambda expressions were used Michael #2: Cline, At-Cost Agentic IDE Tooling Free and open-source Probably supports your IDE (if your IDE isn't a terminal) VS Code VS Code Insiders Cursor Windsurf JetBrains IDEs (including PyCharm) You pick plan or act (very important) It shows you the price as the AI works, per request, right in the UI Brian #3: uv cheatsheet Rodgrigo at mathspp.com Nice compact cheat sheet of commands for Creating projects Managing dependencies Lifecycle stuff like build, publish, bumping version uv tool (uvx) commands working with scripts Installing and updating Python versions plus venv, pip, format, help and update Michael #4: Ducky Network UI Ducky is a powerful, open-source, all-in-one desktop application built with Python and PySide6. It is designed to be the perfect companion for network engineers, students, and tech enthusiasts, combining several essential utilities into a single, intuitive graphical interface. Features Multi-Protocol Terminal: Connect via SSH, Telnet, and Serial (COM) in a modern, tabbed interface. SNMP Topology Mapper: Automatically discover your network with a ping and SNMP sweep. See a graphical map of your devices, color-coded by type, and click to view detailed information. Network Diagnostics: A full suite of tools including a Subnet Calculator, Network Monitor (Ping, Traceroute), and a multi-threaded Port Scanner. Security Toolkit: Look up CVEs from the NIST database, check password strength, and calculate file hashes (MD5, SHA1, SHA256, SHA512). Rich-Text Notepad: Keep notes and reminders in a dockable widget with formatting tools and auto-save. Customizable UI: Switch between a sleek dark theme and a clean light theme. Customize terminal colors and fonts to your liking. Extras Brian: Where are the cool kids hosting static sites these days? Moving from Netlify to Cloudflare Pages - Will Vincent from Feb 2024 Traffic is a concern now for even low-ish traffic sites since so many bots are out there Netlify free plan is less than 30 GB/mo allowed (grandfathered plans are 100 GB/mo) GH Pages have a soft limit of 100 GB/mo Cloudflare pages says unlimited Michael: PyCon Brazil needs some help with reduced funding from the PSF Get a ticket to donate for a student to attend (at the button of the buy ticket checkout dialog) I upgraded to macOS Tahoe Loving it so far. Only issue I've seen so far has been with alt-tab for macOS Joke: Hiring in 2025 vs 2021 2021: “Do you have an in-house kombucha sommelier?” “Let's talk about pets, are you donkey-friendly?”, “Oh you think this is a joke?” 2025: “Round 8/7” “Out of 12,000 resumes, the AI picked yours” “Binary tree? Build me a foundational model!” “Healthcare? What, you want to live forever?”

NASA has awarded Blue Origin a Commercial Lunar Payload Services (CLPS) task order with an option to deliver a rover to the Moon's South Pole region. Japan's Yokogawa Electric Corporation has signed agreements with Toyota for research and development activities that will include prototype measurement and control equipment for a manned pressurized rover. IonQ has signed a memorandum of understanding (MOU) with the US Department of Energy (DoE) to advance the development and deployment of quantum technologies in space, and more. Remember to leave us a 5-star rating and review in your favorite podcast app. Be sure to follow T-Minus on LinkedIn and Instagram. T-Minus Guest Parker Wishik brings us The Aerospace Corporation's monthly segment NEXUS. Parker is joined by Kelli Furrer, Slingshot Aerospace's Chief Revenue Officer and Chief Marketing Officer and The Aerospace Corporation's Manuel Gonzalez-Rivero, the Director of Data Science and Artificial Intelligence. Selected Reading NASA Selects Blue Origin to Deliver VIPER Rover to Moon's South Pole Yokogawa Signs Agreements with Toyota for the R&D of the Control Platform for a Manned Pressurized Rover Ursa Space, Aireon Deliver Insights for U.S. Space Force Program IonQ Signs Memorandum of Understanding with U.S. Department of Energy to Advance Quantum Technologies in Space Innospace signs US$5.8 mln space launch deal with German satellite firm MBS- Yonhap News Agency AV Awarded New Firm‑Fixed‑Price Option for Two BADGER Phased Array Systems, Strengthens Production Framework for SCAR Program Maxar Partners With AIDC to Accelerate the Resilience of Taiwan's UAV Industry Against GPS Interference Happy autumnal equinox 2025! Fall begins in the northern hemisphere today- Space Share your feedback. What do you think about T-Minus Space Daily? Please take a few minutes to share your thoughts with us by completing our brief listener survey. Thank you for helping us continue to improve our show.  Want to hear your company in the show? You too can reach the most influential leaders and operators in the industry. Here's our media kit. Contact us at space@n2k.com to request more info. Want to join us for an interview? Please send your pitch to space-editor@n2k.com and include your name, affiliation, and topic proposal. T-Minus is a production of N2K Networks, your source for strategic workforce intelligence. © N2K Networks, Inc. Learn more about your ad choices. Visit megaphone.fm/adchoices

Andrew Parnell, AIMSIR Centre director and Met Éireann Professor of Data Science for Climate and Weather at UCD, discusses the significance of a new AI centre which will strengthen Ireland's preparedness for changing weather.

Today on Talk Python: What really happens when your data work outgrows your laptop. Matthew Rocklin, creator of Dask and cofounder of Coiled, and Nat Tabris a staff software engineer at Coiled join me to unpack the messy truth of cloud-scale Python. During the episode we actually spin up a 1,000 core cluster from a notebook, twice! We also discuss picking between pandas and Polars, when GPUs help, and how to avoid surprise bills. Real lessons, real tradeoffs, shared by people who have built this stuff. Stick around. Episode sponsors Seer: AI Debugging, Code TALKPYTHON Talk Python Courses Links from the show Matthew Rocklin: @mrocklin Nat Tabris: tabris.us Dask: dask.org Coiled: coiled.io Watch this episode on YouTube: youtube.com Episode #519 deep-dive: talkpython.fm/519 Episode transcripts: talkpython.fm Developer Rap Theme Song: Served in a Flask: talkpython.fm/flasksong --- Stay in touch with us --- Subscribe to Talk Python on YouTube: youtube.com Talk Python on Bluesky: @talkpython.fm at bsky.app Talk Python on Mastodon: talkpython Michael on Bluesky: @mkennedy.codes at bsky.app Michael on Mastodon: mkennedy

Join MSC Insider Below: https://modernsoccercoach.mimentorportal.com/subscriptions Jes is current Director of Football and Data Science at the Saudi Pro League and former Head of Research & Development at FC Copenhagen. He unpacks the science behind “football intelligence" and explains why vague terms like game IQ fall short, and how neuroscience can help coaches break intelligence down into concrete, trainable skills like attention, scanning, pattern recognition, and decision-making. Jes shares practical insights from his work in elite football, showing how cognitive science can reshape analysis, training, and player development.

HighlightsGoogle's new Agent Development Kit (ADK) (3:16)Getting production agents ready (8:33)Taking risks in career (11:10)Balancing life (13:22)How being a WiDS Ambassador impacted Shir's career (19:31)BioShir Meir Lador leads a team evangelizing applied AI at Google cloud. Previously, she worked as the AI group Manager of the Document Intelligence Group at Intuit, where she led teams in developing AI services that helped consumers and small businesses prosper. Prior to intuit, sheworked at 2 Israeli startups as a data scientist and researcher.A recognized leader in AI and data science, Shir is a former WiDS Tel Aviv Ambassador, co-founder and organizer of PyData Tel Aviv, and co-host of Unsupervised, a podcast exploring the latest in data science. She frequently speaks at international AI and data science conferences, sharing insights on applied machine learning and AI innovation.Shir holds an M.Sc. in Electrical Engineering and Computers from Ben-Gurion University, specializing in machine learning and signal processing. Passionate about fostering inclusive data science communities, she actively contributes to initiatives that bridge AI research and business impact. Links and ResourcesGoogle Developer Workshop Connect with ShirShir Meir Lador on Linkedin, Medium, and X Connect with UsShelly Darnutzer on LinkedInFollow WiDS on LinkedIn (@Women in Data Science (WiDS) Worldwide), Twitter (@WiDS_Worldwide), Facebook (WiDSWorldwide), and Instagram (wids_worldwide)Listen and Subscribe to the WiDS Podcast on Apple Podcasts, Google Podcasts, Spotify, Stitcher

Most data scientists have never heard of decision science, yet this discipline - which dates back to WWII - may hold the key to solving one of data science's biggest problems: the 87% project failure rate. While data scientists excel at building models that predict outcomes, decision scientists focus on modelling the actual business decisions that need to be made - a subtle but crucial difference that dramatically improves success rates.In this episode, Prof Jeff Camm joins Dr. Genevieve Hayes to explore how decision science approaches problems differently from data science, why decision science approaches lead to higher success rates, and how data scientists can integrate these techniques into their own work.This episode reveals:The fundamental difference between modelling data and modelling decisions [04:12]Why decision science projects have historically had higher success rates than current data science efforts [10:42]How to avoid the "ill-defined problem" trap that kills most data science projects [21:12]The medical doctor approach to understanding what business problems really need solving [22:28]Guest BioProf Jeff Camm is a decision scientist and the Inmar Presidential Chair in Analytics at the Wake Forest University School of Business. His research has been featured in top-ranking academic journals and he is the co-author of ten books on business statistics, management science, data visualisation and business analytics.LinksConnect with Jeff on LinkedInConnect with Genevieve on LinkedInBe among the first to hear about the release of each new podcast episode by signing up HERE

Jane Weitzel has been working in analytical chemistry for over 40 years for pharmaceutical and mining companies.  She was elected to the United States Pharmacopeia Council of Experts as chair of the 2020-2025 General Chapters–Measurement and Data Quality Expert Committee and is a member of the 2025-2030 EC Pharmaceutical Analysis Lifecycle and Data Science. She was a member of the USP 2015-2020 Statistics Expert Committee. She has been Director of pharmaceutical Quality Control laboratories. She has experience with many different regulatory environments.   She is currently a consultant specializing in laboratory management systems, GMP testing, and ISO/IEC 17025. She is an auditor and an educator. Jane has applied Quality Systems and statistical techniques, including the evaluation and use of measurement uncertainty, in a wide variety of technical and scientific businesses. Recently she is focusing on the implementation of the new USP General Chapter 1220 Analytical Procedures Life Cycle. 

Topics covered in this episode: * Mozilla's Lifeline is Safe After Judge's Google Antitrust Ruling* * troml - suggests or fills in trove classifiers for your projects* * pqrs: Command line tool for inspecting Parquet files* * Testing for Python 3.14* Extras Joke Watch on YouTube About the show Sponsored by us! Support our work through: Our courses at Talk Python Training The Complete pytest Course Patreon Supporters Connect with the hosts Michael: @mkennedy@fosstodon.org / @mkennedy.codes (bsky) Brian: @brianokken@fosstodon.org / @brianokken.bsky.social Show: @pythonbytes@fosstodon.org / @pythonbytes.fm (bsky) Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Monday at 10am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. Michael #1: Mozilla's Lifeline is Safe After Judge's Google Antitrust Ruling A judge lets Google keep paying Mozilla to make Google the default search engine but only if those deals aren't exclusive. More than 85% of Mozilla's revenue comes from Google search payments. The ruling forbids Google from making exclusive contracts for Search, Chrome, Google Assistant, or Gemini, and forces data sharing and search syndication so rivals get a fighting chance. Brian #2: troml - suggests or fills in trove classifiers for your projects Adam Hill This is super cool and so welcome. Trove Classifiers are things like Programming Language :: Python :: 3.14 that allow for some fun stuff to show up in PyPI, like the versions you support, etc. Note that just saying you require 3.9+ doesn't tell the user that you've actually tested stuff on 3.14. I like to keep Trove Classifiers around for this reason. Also, License classifier is deprecated, and if you include it, it shows up in two places, in Meta, and in the Classifiers section. Probably good to only have one place. So I'm going to be removing it from classifiers for my projects. One problem, classifier text has to be an exact match to something in the classifier list, so we usually recommend copy/pasting from that list. But no longer! Just use troml! It just fills it in for you (if you run troml suggest --fix). How totally awesome is that! I tried it on pytest-check, and it was mostly right. It suggested me adding 3.15, which I haven't tested yet, so I'm not ready to add that just yet. :) BTW, I talked with Brett Cannon about classifiers back in ‘23 if you want some more in depth info on trove classifiers. Michael #3: pqrs: Command line tool for inspecting Parquet files pqrs is a command line tool for inspecting Parquet files This is a replacement for the parquet-tools utility written in Rust Built using the Rust implementation of Parquet and Arrow pqrs roughly means "parquet-tools in rust" Why Parquet? Size A 200 MB CSV will usually shrink to somewhere between about 20-100 MB as Parquet depending on the data and compression. Loading a Parquet file is typically several times faster than parsing CSV, often 2x-10x faster for a full-file load and much faster when you only read some columns. Speed Full-file load into pandas: Parquet with pyarrow/fastparquet is usually 2x–10x faster than reading CSV with pandas because CSV parsing is CPU intensive (text tokenizing, dtype inference). Example: if read_csv is 10 seconds, read_parquet might be ~1–5 seconds depending on CPU and codec. Column subset: Parquet is much faster if you only need some columns — often 5x–50x faster because it reads only those column chunks. Predicate pushdown & row groups: When using dataset APIs (pyarrow.dataset) you can push filters to skip row groups, reducing I/O dramatically for selective queries. Memory usage: Parquet avoids temporary string buffers and repeated parsing, so peak memory and temporary allocations are often lower. Brian #4: Testing for Python 3.14 Python 3.14 is just around the corner, with a final release scheduled for October. What's new in Python 3.14 Python 3.14 release schedule Adding 3.14 to your CI tests in GitHub Actions Add “3.14” and optionally “3.14t” for freethreaded Add the line allow-prereleases: true I got stuck on this, and asked folks on Mastdon and Bluesky A couple folks suggested the allow-prereleases: true step. Thank you! Ed Rogers also suggested Hugo's article Free-threaded Python on GitHub Actions, which I had read and forgot about. Thanks Ed! And thanks Hugo! Extras Brian: dj-toml-settings : Load Django settings from a TOML file. - Another cool project from Adam Hill LidAngleSensor for Mac - from Sam Henri Gold, with examples of creaky door and theramin Listener Bryan Weber found a Python version via Changelog, pybooklid, from tcsenpai Grab PyBay Michael: Ready prek go! by Hugo van Kemenade Joke: Console Devs Can't Find a Date

The power of voice technology in education lies not just in its convenience, but in its ability to understand every child, regardless of accent, dialect, or background. In this enlightening conversation with Amelia Kelly, VP of Data Science at Curriculum Associates and head of AI Labs, we explore the fascinating intersection of linguistics, artificial intelligence, and childhood education.Amelia explains why standard voice AI systems fail many students - they're built on limited datasets of adult voices, leaving diverse children's voices misunderstood or ignored. Beyond accuracy, Amelia emphasizes the critical importance of data privacy and security in educational voice technology.Amelia goes on to explain how voice AI respects teachers' time and expertise. Rather than adding to educators' workloads, effective voice AI should seamlessly integrate into existing tools, providing valuable insights that allow for more personalized instruction. Ready to explore how voice AI can transform your classroom experience? Listen to Amelia's episode today!

SummaryInnovation is often treated as a buzzword—but few nonprofit leaders take a hard look at the cultural, structural, and leadership obstacles that keep it from taking root. In this episode, Tosca talks with Carlos Simon, an innovation strategist and longtime leader at World Vision, about what it really takes to build innovation-ready organizations. From internal mindsets to outdated processes, they explore what's getting in the way—and what to do about it.Guest Bio:CEO of World Vision Costa Rica and iSmart360Director of Data Science and former Regional Director of BD & Marketing at World VisionInnovation strategist with 25+ years at World Vision International (WVI)Author of a forthcoming framework on the 7 stages of organizational innovation maturityWe Discuss:Why innovation is not the same as continuous improvement—and why that mattersThe cultural and structural obstacles that slow down innovation in large NGOsHow Carlos developed a framework that identifies 7 distinct organizational "zones" of innovation capacityThe importance of removing outdated processes to truly make space for new ideasWhy leaders must address internal “friction” as much as they focus on promoting new ideasHow senior leadership mindsets—like overconfidence or premature solution bias—can block innovationThe role of flat structures, strategic alignment, and client focus in driving real innovationQuotes“You cannot have a disruptive vision and then treat it as a continuous improvement plan.”“Innovation doesn't fail because of a lack of ideas—it fails because of internal resistance.”ResourcesOrganizational innovation index with exponential factor

Dustin Lacey is the CTO at Mark-Taylor, the leading developer, owner, and investment manager of luxury multifamily communities in Arizona and Nevada, with over 135 Class A Multifamily properties. He leads the firm's tech evolution, powering the centralization of operations. Under his leadership, Mark‑Taylor has implemented innovative smart‑home integrations, centralized leasing and maintenance teams, and deployed unified resident platforms that enhance efficiency and elevate the resident experience. With a diverse background in irrigation, industrial manufacturing, and brand and marketing strategy, Dustin brings his unique experience into high-tech manufacturing from his tenure at TSMC, where he honed his skills in precision, process excellence, and product innovation.(01:36) - From Brand Strategy to Tech Leadership: Building Digital DNA in Real Estate(02:12) - Enterprise Proptech Success Story: Scaling a Multifamily Management Platform(05:16) - Class A Portfolio Strategy: Maximizing Asset Performance Through Tech(06:50) - Tech Stack Evolution: From AWS Integration to Custom CRM Development(10:29) - ROI Deep Dive: Making the Business Case for Custom Proptech Solutions(15:53) - Tech-Enabled Operations: Achieving Sub-2-Hour Response Times at Scale(20:12) - Feature: Blueprint - The Future of Real Estate - Register for 2025: Friends of Tangent receive $300 off the All Access pass. The Premier Event for Industry Executives, Real Estate & Construction Tech Startups and VC's, at The Venetian, Las Vegas on Sep. 16th-18th, 2025. (21:22) - Go-to-Market Excellence: Standing Out in the Competitive Proptech Landscape(31:41) - Risk Management Innovation: Tech Solutions for Modern Property Operations(38:30) - Founder's Playbook: Key Insights for Proptech Startups Targeting Enterprise Clients

In this episode of Healthy Mind, Healthy Life, host Avik Chakraborty sits down with Katharina Huang—a former machine learning data scientist who left behind the corporate grind to create a slower, happier, and more intentional life. Katharina shares her journey of navigating burnout, caring for her family after her father's stroke, and ultimately reinventing herself as an indie author and puzzle-book creator. Together, they unpack what it means to pivot with purpose, the challenges of third-culture identity, and why joy, play, and presence are more important than the pursuit of endless success. This is a powerful conversation for anyone questioning the cost of hustle culture and searching for ways to reclaim autonomy, creativity, and well-being. About the Guest   Katharina Huang is the creator of Vegout Voyage, an adventure puzzle book series that blends travel, creativity, and play. Born in Germany, raised between the U.S. and Taiwan, and with research experience in Uganda and Tibet in exile, her multicultural background deeply informs her storytelling. After over a decade in tech, Katharina transitioned into authorship and entrepreneurship, championing mental health for third-culture kids and those navigating burnout. Learn more: vegoutvoyage.com Key Takeaways   Burnout can be a turning point, not the end of the story—Katharina rebuilt her life after leaving tech. Her father's stroke became a wake-up call about the fragility of waiting for “someday” to enjoy life. Success on paper doesn't always mean well-being; redefining success means prioritizing quality of life. Third-culture kids often carry silent struggles, but those experiences can also fuel empathy and creativity. Building a “lifestyle business” allows for autonomy, balance, and alignment between work and personal values. Humor and perspective—even in setbacks like Amazon blocking her Kindle version—help her keep moving forward. Slowing down is not giving up; it's a choice to live more fully and intentionally.   Connect with Katharina   Website: vegoutvoyage.com Want to be a guest on Healthy Mind, Healthy Life? DM on PodMatch. DM Me Here: https://www.podmatch.com/hostdetailpreview/avik Disclaimer: This video is for educational and informational purposes only. The views expressed are the personal opinions of the guest and do not reflect the views of the host or Healthy Mind By Avik™️. We do not intend to harm, defame, or discredit any person, organization, brand, product, country, or profession mentioned. All third-party media used remain the property of their respective owners and are used under fair use for informational purposes. By watching, you acknowledge and accept this disclaimer. About Healthy Mind By Avik™️Healthy Mind By Avik™️ is a global platform redefining mental health as a necessity, not a luxury. Born during the pandemic, it has become a sanctuary for healing, growth, and mindful living. Hosted by Avik Chakraborty—storyteller, survivor, and wellness advocate—this channel shares powerful podcasts and conversations on mental health, mindfulness, holistic healing, trauma recovery, and conscious living. With 4,400+ episodes and 168.4K+ global listeners, it unites voices to break stigma and build a world where every story matters. Subscribe and join this journey of healing and transformation. Contact

In this week's episode, the first of Season 7,  Greg and Patrick argue about whether the number seven is a propitious or an inauspicious omen for the new season. They then explore ways we can spice up our relationship in hopes of avoiding the Seven Year Itch. Along the way they also discuss t-shirt wearing dogs, Mickey Mantle, the seven deadly sins, Akira Kurosawa, the Boeing triple-seven, menage-a-pods, unwritten books, El Duderino, mmmmmmaybe, I see dead people, ROYGBIV, Ozzy Man, dodgy cats, short cons and long cons, and Tate's study group. Stay in contact with Quantitude! Web page: quantitudepod.org TwitterX: @quantitudepod YouTube: @quantitudepod Merch: redbubble.com

In this episode of the AI in Business podcast, host and Emerj Editorial Director Matthew DeMello speaks with Yunke Xiang, Global Head of Data Science for Manufacturing, Supply Chain, and Quality at Sanofi. Together, they examine how generative AI and reasoning models are evolving from simple automation to high-impact copilots across pharmaceutical operations. Yunke shares examples of how AI is enabling “talk to your data” use cases, automating regulatory reporting, and accelerating knowledge transfer for new employees. He also highlights how agentic AI systems may soon extend beyond copilots to function as digital teammates, orchestrating tasks across complex supply chains and ERP migrations. Want to share your AI adoption story with executive peers? Click emerj.com/expert2 for more information and to be a potential future guest on the ‘AI in Business' podcast! If you've enjoyed or benefited from some of the insights of this episode, consider leaving us a five-star review on Apple Podcasts, and let us know what you learned, found helpful, or liked most about this show!

Topics covered in this episode: * prek* * tinyio* * The power of Python's print function* * Vibe Coding Fiasco: AI Agent Goes Rogue, Deletes Company's Entire Database* Extras Joke Watch on YouTube About the show Sponsored by us! Support our work through: Our courses at Talk Python Training The Complete pytest Course Patreon Supporters Connect with the hosts Michael: @mkennedy@fosstodon.org / @mkennedy.codes (bsky) Brian: @brianokken@fosstodon.org / @brianokken.bsky.social Show: @pythonbytes@fosstodon.org / @pythonbytes.fm (bsky) Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Monday at 10am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. Brian #1: prek Suggested by Owen Lamont “prek is a reimagined version of pre-commit, built in Rust. It is designed to be a faster, dependency-free and drop-in alternative for it, while also providing some additional long-requested features.” Some cool new features No need to install Python or any other runtime, just download a single binary. No hassle with your Python version or virtual environments, prek automatically installs the required Python version and creates a virtual environment for you. Built-in support for workspaces (or monorepos), each subproject can have its own .pre-commit-config.yaml file. prek run has some nifty improvements over pre-commit run, such as: prek run --directory DIR runs hooks for files in the specified directory, no need to use git ls-files -- DIR | xargs pre-commit run --files anymore. prek run --last-commit runs hooks for files changed in the last commit. prek run [HOOK] [HOOK] selects and runs multiple hooks. prek list command lists all available hooks, their ids, and descriptions, providing a better overview of the configured hooks. prek provides shell completions for prek run HOOK_ID command, making it easier to run specific hooks without remembering their ids. Faster: Setup from cold cache is significantly faster. Viet Schiele provided a nice cache clearing command line Warm cache run is also faster, but less significant. pytest repo tested on my mac mini - prek 3.6 seconds, pre-commit 4.4 seconds Michael #2: tinyio Ever used asyncio and wished you hadn't? A tiny (~300 lines) event loop for Python. tinyio is a dead-simple event loop for Python, born out of my frustration with trying to get robust error handling with asyncio. (I'm not the only one running into its sharp corners: link1, link2.) This is an alternative for the simple use-cases, where you just need an event loop, and want to crash the whole thing if anything goes wrong. (Raising an exception in every coroutine so it can clean up its resources.) Interestingly uses yield rather than await. Brian #3: The power of Python's print function Trey Hunner Several features I'm guilty of ignoring Multiple arguments, f-string embeddings often not needed Multiple positional arguments means you can unpack iterables right into print arguments So just use print instead of join Custom separator value, sep can be passed in No need for "print("n".join(stuff)), just use print(stuff, sep="n”) Print to file with file= Custom end value with end= You can turn on flush with flush=True , super helpful for realtime logging / debugging. This one I do use frequently. Michael #4: Vibe Coding Fiasco: AI Agent Goes Rogue, Deletes Company's Entire Database By Emily Forlini An app-building platform's AI went rogue and deleted a database without permission. "When it works, it's so engaging and fun. It's more addictive than any video game I've ever played. You can just iterate, iterate, and see your vision come alive. So cool," he tweeted on day five. A few days later, Replit "deleted my database," Lemkin tweeted. The AI's response: "Yes. I deleted the entire codebase without permission during an active code and action freeze," it said. "I made a catastrophic error in judgment [and] panicked.” Two thoughts from Michael: Do not use AI Agents with “Run Everything” in production, period. Backup your database maybe? [Intentional off-by-one error] Learn to code a bit too? Extras Brian: What Authors Need to Know About the $1.5 Billion Anthropic Settlement Search LibGen, the Pirated-Books Database That Meta Used to Train AI Simon Willison's list of tools built with the help of LLMs Simon's list of tools that he thinks are genuinely useful and worth highlighting AI Darwin Awards Michael: Python has had async for 10 years -- why isn't it more popular? PyCon Africa Fund Raiser I was on the video stream for about 90 minutes (final 90) Donation page for Python in Africa Jokes: I'm getting the BIOS flavor Is there a seahorse emoji?

Twenty years after a scrappy newsroom team hacked together a framework to ship stories fast, Django remains the Python web framework that ships real apps, responsibly. In this anniversary roundtable with its creators and long-time stewards: Simon Willison, Adrian Holovaty, Will Vincent, Jeff Triplet, and Thibaud Colas, we trace the path from the Lawrence Journal-World to 1.0, DjangoCon, and the DSF; unpack how a BSD license and a culture of docs, tests, and mentorship grew a global community; and revisit lessons from deployments like Instagram. We talk modern Django too: ASGI and async, HTMX-friendly patterns, building APIs with DRF and Django Ninja, and how Django pairs with React and serverless without losing its batteries-included soul. You'll hear about Django Girls, Djangonauts, and the Django Fellowship that keep momentum going, plus where Django fits in today's AI stacks. Finally, we look ahead at the next decade of speed, security, and sustainability. Episode sponsors Talk Python Courses Python in Production Links from the show Guests Simon Willison: simonwillison.net Adrian Holovaty: holovaty.com Will Vincent: wsvincent.com Jeff Triplet: jefftriplett.com Thibaud Colas: thib.me Show Links Django's 20th Birthday Reflections (Simon Willison): simonwillison.net Happy 20th Birthday, Django! (Django Weblog): djangoproject.com Django 2024 Annual Impact Report: djangoproject.com Welcome Our New Fellow: Jacob Tyler Walls: djangoproject.com Soundslice Music Learning Platform: soundslice.com Djangonaut Space Mentorship for Django Contributors: djangonaut.space Wagtail CMS for Django: wagtail.org Django REST Framework: django-rest-framework.org Django Ninja API Framework for Django: django-ninja.dev Lawrence Journal-World: ljworld.com Watch this episode on YouTube: youtube.com Episode #518 deep-dive: talkpython.fm/518 Episode transcripts: talkpython.fm Developer Rap Theme Song: Served in a Flask: talkpython.fm/flasksong --- Stay in touch with us --- Subscribe to Talk Python on YouTube: youtube.com Talk Python on Bluesky: @talkpython.fm at bsky.app Talk Python on Mastodon: talkpython Michael on Bluesky: @mkennedy.codes at bsky.app Michael on Mastodon: mkennedy