Podcasts about Data science

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

This month, we explore how data science and AI are transforming the wine industry—from vineyard planting and grape harvesting to customer engagement. Can advanced technologies help winemakers enhance quality, promote sustainability, and better match wines to consumers—all while preserving the essential human touch? Might these innovations be applied to other products as well? Join us as we discuss these questions and more with industry leaders Kia Behnia, CEO and co-founder of Scout, and Katerina Axelsson, CEO and founder of Tastry. Pour yourself a glass and tune in as we uncork the intersection of data, AI, and the art of winemaking. Our Guests: Kia Behnia is CEO and co-founder of Scout, an AI-powered analytics platform built for precision viticulture, and proprietor of Kiatra Vineyards and Neotempo Wines.  Katerina Axelsson is CEO and founder of Tastry, a sensory-sciences company that blends advanced analytical chemistry, machine learning, and AI to predict consumer preferences—especially in wine.

A nostalgic dive into the rise and fall of true hacker culture - from MIT's curious tinkerers to today's hustle-obsessed "founders." Plus, why IRC was peak internet and what we lost when convenience killed community. For anyone who misses when coding was about elegance, not exits.RetryClaude can make mistakes. Please double-check responses. Interesting link https://www.twitch.tv/tsoding/about Sponsors DSH is proudly sponsored by Amethix Technologies. At the intersection of ethics and engineering, Amethix creates AI systems that don't just function—they adapt, learn, and serve. With a focus on dual-use innovation, Amethix is shaping a future where intelligent machines extend human capability, not replace it. Discover more at amethix.com   DSH is brought to you by Intrepid AI. From drones to satellites, Intrepid AI gives engineers and defense innovators the tools to prototype, simulate, and deploy autonomous systems with confidence. Whether it's in the sky, on the ground, or in orbit—if it's intelligent and mobile, Intrepid helps you build it. Learn more at intrepid.ai     ✨ Connect with us!

A statistician walks into a bar, and a comedy and art show begins. Creative work for scholars can extend beyond novel research and application. In today's episode of stats and stories, we see how the intersection between interest in statistics and art, as well as the intersection of statistics and comedy, with Dr Greg Matthews. Dr. Matthews is Associate Professor of Statistics and Director of the Center for Data Science and Consulting at Loyola University. He also is a data artist who developed and promoted the Data Art Show, which debuted at the 2016 Joint Statistical Meetings. He performs with the Uncontrolled Variables comedy troupe at the Lincoln Lodge in Chicago and you can see his data art, links to his comedy performance, and much more at his website, Stats in the Wild.

AI in software development sounds like a dream, faster coding, cleaner refactoring, and technical reports that actually make sense to stakeholders. But, what's the bad news in the classic good news/bad news scenario? Poisoned training data, compliance risks, and systems that are brittle and will not scale.  This week on Feds At The Edge, Alex Gromadzki, Assistant Director of Data Science at US GAO, and Steven Toy, Senior Director, Cloud Infrastructure for ICF, unpack the opportunities and pitfalls of generative AI in federal software development. From source-citing AI to data security in the software lifecycle, they reveal why small, testable use cases may be the smartest way forward.   Listen now on your favorite podcast platform to hear how federal leaders can balance innovation with responsibility as AI reshapes the software development life cycle.          

Rishard Rameez is the Co‑Founder and CEO of Zown, an AI‑powered real estate platform that makes homeownership more accessible and affordable. Zown was born from a viral Reddit post where Rishard shared his frustration over paying over $70K in real estate commissions. The outpouring of support inspired him to flip the model: instead of paying big commissions, Zown gives buyers significant upfront cash to help with their down payment and closing costs, while offering sellers flat fees. This customer‑first model has driven rapid growth, with Zown processing over $300 million in transactions and becoming Canada's fastest‑growing real estate brokerage. The platform has recently launched in California and continues expanding across North America. Rishard sparked a movement by transforming personal pain into an industry‑changing solution.(02:17) - The Broken Home Buying Process(03:02) - It All Started with a Viral Reddit Post (05:39) - Early Pivot from Flat Fee Model(14:59) - Unbundling Real Estate Services(18:06) - Feature: Blueprint - The Future of Real Estate - Register for 2025: The Premier Event for Industry Executives, Real Estate & Construction Tech Startups and VC's, at The Venetian, Las Vegas on Sep. 16th-18th, 2025.(19:00) - Feature: Meow - Business banking, with interest: Unlock a high-yield business checking account that pays up to 3.52%.(20:31) - Zone's Growth Journey(28:47) - Customer Acquisition Strategy(30:36) - Recent Seed Round(32:42) - Why Own vs. Rent a Home(34:52) - Collaboration Superpower: Muhammad and Jesus Christ

Celebrate a decade of innovation, learning, and connection in the Alteryx Community! In this special 10th anniversary episode of Alter Everything, we hear from you as we explore the stories and milestones that have defined the Alteryx Community over the past ten years. Hear firsthand accounts from users like you (maybe even you reading this) whose lives and careers have been transformed through mentorship, career advancement, or lifelong friendships. This episode highlights the power of Community in the world of data analytics. Join us as we honor the people, stories, and achievements that make the Alteryx Community truly special.Guests: Matt Rotundo, Engagement Engineer @Alteryx - @AlteryxMatt, LinkedInAlex Gross, Sr. Process Analyst @ Siemens - @grossal, LinkedInNicole Johnson, Sr. Manager Product Management @ Alteryx - @NicoleJ, LinkedInMatt Montgomery, Data Sherpa @ Montgomery Solutions - @mmontgomery, LinkedInCalvin Tang, Group Manager, Business Solutions & Enablement @ Prudential PLC - @Caltang, LinkedInSamantha Clifton, Sr. Sales Engineer @ Alteryx - @Samantha_Jayne, LinkedInLuke Cornetta, Sr. Director @ Alvarez and Marsal - @LukeC, LinkedInBen Stringer, Data Consultant @ Bulien - @BS_THE_ANALYST, LinkedInRoan Pilsworth, Data Consultant @ Bulien - @pilsner, LinkedInAlex Abi-Najm, Solutions and Enablement Lead @ Aimpoint Digital - @alexnajm, LinkedInShan Miralles, Quantitative Analyst @ JP Morgan Chase - @shancmiralles, LinkedInDan Menke, Community Ops Sr. Manager @ Alteryx - @DanM, LinkedInMegan Bowers, Sr. Content Manager @ Alteryx - @MeganBowers, LinkedInShow notes: Inspire ConferenceAlteryx ACE ProgramAdvent of CodeWeekly Challenges and Cloud QuestsAlteryx User GroupsAlteryx AcademyAlteryx Interactive LessonsAlteryx CertificationSparkEdRoad to Inspire Interested in sharing your feedback with the Alter Everything team? Take our feedback survey here!This episode was produced by Megan Bowers, Mike Cusic, and Matt Rotundo. Special thanks to Andy Uttley for the theme music.

The traditional career path of climbing the corporate ladder no longer appeals to many data scientists - who crave freedom and ownership of their work. Yet the leap from employment to independence can feel risky and uncertain, especially without a clear roadmap for success.In this episode, Daniel Bourke joins Dr. Genevieve Hayes to share his journey from machine learning engineer to successful independent data professional before age 30, revealing the practical steps and mindset shifts needed to transform technical skills into sustainable freedom.In this episode, you'll discover:Why embracing the "permissionless economy" is crucial for independent success [14:59]The power of "starting the job before you have it" [12:17]Why building your own website is the foundation for long-term independent success [24:35]A practical approach to opportunity selection that accelerates career momentum [17:27]Guest BioDaniel Bourke is the co-creator of Nutrify, an app described as “Shazam for food”, and teaches machine learning and deep learning at the Zero to Mastery Academy.LinksDaniel's websiteDaniel's YouTube channelConnect with Genevieve on LinkedInBe among the first to hear about the release of each new podcast episode by signing up HERE

In episode 29 of Recsperts, I welcome Craig Macdonald, Professor of Information Retrieval at the University of Glasgow, and Aleksandr “Sasha” Petrov, PhD researcher and former applied scientist at Amazon. Together, we dive deep into sequential recommender systems and the growing role of transformer models such as SASRec and BERT4Rec.Our conversation begins with their influential replicability study of BERT4Rec, which revealed inconsistencies in reported results and highlighted the importance of training objectives over architecture tweaks. From there, Craig and Sasha guide us through their award-winning research on making transformers for sequential recommendation with large corpora both more effective and more efficient. We discuss how recency sampling (RSS) reduces training times dramatically, and how gSASRec overcomes the problem of overconfidence in models trained with negative sampling. By generalizing the sigmoid function (gBCE), they were able to reconcile cross-entropy–based optimization results with negative sampling, matching the effectiveness of softmax approaches while keeping training scalable for large corpora.We also explore RecJPQ, their recent work on joint product quantization for item embeddings. This approach makes transformer-based sequential recommenders substantially faster at inference and far more memory-efficient for embeddings—while sometimes even improving effectiveness thanks to regularization effects. Towards the end, Craig and Sasha share their perspective on generative approaches like GPTRec, the promises and limits of large language models in recommendation, and what challenges remain for the future of sequential recommender systems.Enjoy this enriching episode of RECSPERTS – Recommender Systems Experts.Don't forget to follow the podcast and please leave a review.(00:00) - Introduction (04:09) - About Craig Macdonald (04:46) - About Sasha Petrov (13:48) - Tutorial on Transformers for Sequential Recommendations (19:24) - SASRec vs. BERT4Rec (21:25) - Replicability Study of BERT4Rec for Sequential Recommendation (32:52) - Training Sequential RecSys using Recency Sampling (40:01) - gSASRec for Reducing Overconfidence by Negative Sampling (01:00:51) - RecJPQ: Training Large-Catalogue Sequential Recommenders (01:21:37) - Generative Sequential Recommendation with GPTRec (01:29:12) - Further Challenges and Closing Remarks Links from the Episode:Craig Macdonald on LinkedInSasha Petrov on LinkedInSasha's WebsiteTutorial: Transformers for Sequential Recommendation (ECIR 2024)Tutorial Recording from ACM European Summer School in Bari (2024)Talk: Neural Recommender Systems (European Summer School in Information Retrieval 2024)Papers:Kang et al. (2018): Self-Attentive Sequential RecommendationSun et al. (2019): BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from TransformerPetrov et al. (2022): A Systematic Review and Replicability Study of BERT4Rec for Sequential RecommendationPetrov et al. (2022): Effective and Efficient Training for Sequential Recommendation using Recency SamplingPetrov et al. (2024): RSS: Effective and Efficient Training for Sequential Recommendation Using Recency Sampling (extended version)Petrov et al. (2023): gSASRec: Reducing Overconfidence in Sequential Recommendation Trained with Negative SamplingPetrov et al. (2025): Improving Effectiveness by Reducing Overconfidence in Large Catalogue Sequential Recommendation with gBCE lossPetrov et al. (2024): RecJPQ: Training Large-Catalogue Sequential RecommendersPetrov et al. (2024): Efficient Inference of Sub-Item Id-based Sequential Recommendation Models with Millions of ItemsRajput et al. (2023): Recommender Systems with Generative RetrievalPetrov et al. (2023): Generative Sequential Recommendation with GPTRecPetrov et al. (2024): Aligning GPTRec with Beyond-Accuracy Goals with Reinforcement LearningGeneral Links:Follow me on LinkedInFollow me on XSend me your comments, questions and suggestions to marcel.kurovski@gmail.comRecsperts WebsiteDisclaimer:Craig holds concurrent appointments as a Professor of Information Retrieval at University of Glasgow and as an Amazon Scholar. This podcast describes work performed at the University of Glasgow and is not associated with Amazon.

Topics covered in this episode: * pypistats.org was down, is now back, and there's a CLI* * State of Python 2025* * wrapt: A Python module for decorators, wrappers and monkey patching.* pysentry 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: pypistats.org was down, is now back, and there's a CLI pypistats.org is a cool site to check the download stats for Python packages. It was down for a while, like 3 weeks? A couple days ago, Hugo van Kemenade announced that it was back up. With some changes in stewardship “pypistats.org is back online!

We're bringing back one of our most downloaded episodes ever – a deep dive into how adverse events should be analyzed properly. This conversation with Jan Beyersmann and Kaspar Rufibach is packed with methodological insights and practical implications for statisticians working in clinical trials. Adverse event (AE) analysis has long been approached differently from efficacy analysis, often using overly simplistic methods that can bias results. In this episode, we discuss why that's a problem – and how the SAVVY collaboration (Survival analysis for AdVerse events with Varying follow-up times) is pushing the field forward. Together with academia and multiple pharma companies, this collaboration tackled the issue of AE analysis using real randomized trial data, not just simulations. The findings show how common methods can underestimate or overestimate event probabilities and how established statistical methods can be applied more consistently to ensure fair benefit–risk assessments. If you've ever wondered whether your approach to safety analysis is leading to misleading conclusions, this episode is a must-listen.

Co-taught by Prof. Wade Fagen-Ulmschneider (Grainger Engineering) and Prof. Karle Flanagan (Statistics), their CS/STAT 107 Data Science Discovery class is transforming the way students from 90+ majors approach data science. What's the secret to its wild success? - Real-world datasets - Hands-on, project-driven learning - Discovering how every major—from History to Finance—can be empowered by data! - And a wave of new X + DS degree programs putting Illinois students years ahead in the job market. Want to see where the future of education is headed? Hit play and dive into the one of the most exciting courses at Illinois— Data Science Discovery. 🔗 Explore more at: datasciencediscovery.org #DataScience #UIUC #IllinoisEngineering #Statistics #EducationInnovation #XplusDS #CSSTAT107 #CollegeMajors #CareerReady #DigitalFuture #StudentSuccess #BigTenChampions #STEM #HigherEd #MicroCredentials #pythonprogramming

Agentic AI programming is what happens when coding assistants stop acting like autocomplete and start collaborating on real work. In this episode, we cut through the hype and incentives to define “agentic,” then get hands-on with how tools like Cursor, Claude Code, and LangChain actually behave inside an established codebase. Our guest, Matt Makai, now VP of Developer Relations at DigitalOcean, creator of Full Stack Python and Plushcap, shares hard-won tactics. We unpack what breaks, from brittle “generate a bunch of tests” requests to agents amplifying technical debt and uneven design patterns. Plus, we also discuss a sane git workflow for AI-sized diffs. You'll hear practical Claude tips, why developers write more bugs when typing less, and where open source agents are headed. Hint: The destination is humans as editors of systems, not just typists of code. Episode sponsors Posit Talk Python Courses Links from the show Matt Makai: linkedin.com Plushcap Developer Content Analytics: plushcap.com DigitalOcean Gradient AI Platform: digitalocean.com DigitalOcean YouTube Channel: youtube.com Why Generative AI Coding Tools and Agents Do Not Work for Me: blog.miguelgrinberg.com AI Changes Everything: lucumr.pocoo.org Claude Code - 47 Pro Tips in 9 Minutes: youtube.com Cursor AI Code Editor: cursor.com JetBrains Junie: jetbrains.com Claude Code by Anthropic: anthropic.com Full Stack Python: fullstackpython.com Watch this episode on YouTube: youtube.com Episode #517 deep-dive: talkpython.fm/517 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

We speak with Carmen Best, Former Chief of Police Seattle at the World Police Summit 2025, held at the Dubai World Trade Centre 13-15 May. Carmen served with the Seattle Police Department for 28 years, beginning as an entry-level patrol officer and later becoming the first African American woman Chief of Police. Skilled in Public Safety, Infrastructure Security, Police Service, Law Enforcement, Police Administration, Management, Criminal Justice, and Crime Prevention. Carmen serves on the Leadership Council for the United Negro College Fund (UNCF), Seattle as well as a board member for United Way of King County, Young Women's Christian Association - King County, a member of the St. Jude Advisory Council for Seattle, and the Seattle University Criminal Justice Advisory Committee and member of the Human and Civil Rights Committee (HCRC) for the International Association of Chiefs of Police (IACP). A former member of the IACP Board of Directors - a group with which she maintains affiliation. Additionally, she is a contributor to MSNBC, CNBC and NBC News affiliates.MySecurity Media were media partners to the WPS 2025. #Worldpolicesummit #wps2025 #mysecuritytv

Dr. Rebecca Portnoff generates awareness of the threat landscape, enablers, challenges and solutions to the complex but addressable issue of online child sexual abuse.  Rebecca and Kimberly discuss trends in online child sexual abuse; pillars of impact and harm; how GenAI expands the threat landscape; personalized targeting and bespoke abuse; Thorn's Safety by Design Initiative; scalable prevention strategies; technical and legal barriers; standards, consensus and commitment; building better from the beginning; accountability as an innovative goal; and not confusing complex with unsolvable.  Dr. Rebecca Portnoff is the Vice President of Data Science at Thorn, a non-profit dedicated to protecting children from sexual abuse. Read Thorn's seminal Safety by Design paper, bookmark the Research Center to stay updated and support Thorn's critical work by donating here. Related Resources Thorn's Safety by Design Initiative (News): https://www.thorn.org/blog/generative-ai-principles/  Safety by Design Progress Reports: https://www.thorn.org/blog/thorns-safety-by-design-for-generative-ai-progress-reports/  Thorn + SIO AIG-CSAM Research (Report): https://cyber.fsi.stanford.edu/io/news/ml-csam-report  A transcript of this episode is here.

To mark our 50th episode, host Ross Katz brings back three visionary leaders—Dave Johnson (Dash Bio), Wolfgang Halter (Merck Life Science), and Jacob Oppenheim (RAVen)—together for a reflection on the evolution of biotech. They unpack the realities behind AI hype, the future of data-driven innovation, and what's really changing in drug development. ​​What You'll Learn in This Episode: >> Where real innovation is emerging across startups, big tech, and academia >> The biggest misconceptions about data in biotech—and why they persist >> What it takes to build trust in AI-powered biotech tools >> Why progress in biotech depends as much on execution as it does on breakthroughs >> How industry veterans see the future of automation, regulation, and global competition Meet Our Guests Dave Johnson is CEO and Co-Founder of Dash Bio and former Chief Data & AI Officer at Moderna. He's pioneering automation in clinical bioanalysis to accelerate drug development. Wolfgang Halter leads Data Science at Merck Life Science, developing tools like BayBE to optimize R&D through smarter data modeling and open-source innovation. Jacob Oppenheim is a Venture Partner at RAVen and co-founder of Fresnel. With a PhD in Biological Physics, he champions the transition to digital-native biopharma. About The Host Ross Katz is Principal and Data Science Lead at CorrDyn. Ross specializes in building intelligent data systems that empower biotech and healthcare organizations to extract insights and drive innovation. Connect with Our Guest: Sponsor: CorrDyn, a data consultancyConnect with Dave Johnson  on LinkedIn Connect with Wolfgang Halter on LinkedInConnect with Jacob Oppenheim on LinkedIn Connect with Us: Follow the podcast for more insightful discussions on the latest in biotech and data science.Subscribe and leave a review if you enjoyed this episode!Connect with Ross Katz on LinkedIn Sponsored by… This episode is brought to you by CorrDyn, the leader in data-driven solutions for biotech and healthcare. Discover how CorrDyn is helping organizations turn data into breakthroughs at CorrDyn.

Misfits Makin' It is the podcast component of the misfit comedy shows produced by Lauren LoGiudice. Show dates and info at www.laurenlogiudice.com In this Misfit Melodrama mini-episode of Misfits Makin' It Lauren speaks with scientist and comedian Andrea Jones-Rooy. The conversation explores the pressures to specialize, the importance of interdisciplinary thinking, and the realities of navigating comedy and performance as a misfit. Andrea shares insights on self-acceptance, resilience, and finding fulfillment by embracing multiple passions rather than conforming to traditional expectations. To submit your story leave a voicemail at 646-WANG-0-X-1 or go to www.laurenlogiudice.com/podcast. HOW TO SUPPORT THE PODCAST: Rate and review: Misfits trust other misfits to tell them what is good! Tell a friend: Word of mouth is the #1 way misfits learn about their next pod. Sponsor a podcast: Affordable for individuals and small businesses, also makes the perfect gift. Support this art directly with a podcast that's custom-tailored to you or your friends. Make it happen by reaching out to inthemidstprod@gmail.com. CONNECT WITH ANDREA JONES-ROOY: www.jonesrooy.com Instagram: @jonesrooy HOW TO SUPPORT THE PODCAST: Rate and review: Misfits trust other misfits to tell them what is good! Tell a friend: Work of mouth is the #1 way misfits like to learn about their next pod. Sponsor a podcast: Affordable for individuals and small businesses, also makes the perfect gift. Support this art directly with a podcast that's custom-tailored to you or your friends. Make it happen by reaching out to inthemidstprod@gmail.com. CONNECT WITH LAUREN LOGIUDICE: Instagram: @laurenlogi Twitter/TikTok/Threads: @laurenlogi Website: www.laurenlogiudice.com For more about the Honestly crowdfunding campaign visit: https://seedandspark.com/fund/honestly#story

The right book at the right time can completely transform your career trajectory, but many data professionals struggle to find resources that directly address their unique challenges of bridging technical expertise with business impact. While technical skills courses are abundant, guidance on becoming a strategic data leader remains scarce.In this Value Boost episode, Kashif Zahoor joins Dr. Genevieve Hayes to reveal how he transformed his entire data team's performance and culture through a simple but powerful approach: starting a BI book club that costs almost nothing but delivers enormous ROI.This episode reveals:How a weekly team book club transformed Kashif's data team [02:26]The "data concierge" concept that transforms dashboard builders into trusted business advisors [04:07]Why Data Insights Delivered by Mo Villagran is a team game-changer [08:28]The critical difference between fulfilling requests and solving underlying business problems [09:05]Guest BioKashif Zahoor is the Vice President of Business Intelligence at Influence Mobile and has extensive experience in data leadership.LinksConnect with Kashif on LinkedInData Insights Delivered (Amazon Australia)(Amazon US)The AI-Driven Leader (Amazon Australia)(Amazon US)Connect with Genevieve on LinkedInBe among the first to hear about the release of each new podcast episode by signing up HERE

Python's data stack is getting a serious GPU turbo boost. In this episode, Ben Zaitlen from NVIDIA joins us to unpack RAPIDS, the open source toolkit that lets pandas, scikit-learn, Spark, Polars, and even NetworkX execute on GPUs. We trace the project's origin and why NVIDIA built it in the open, then dig into the pieces that matter in practice: cuDF for DataFrames, cuML for ML, cuGraph for graphs, cuXfilter for dashboards, and friends like cuSpatial and cuSignal. We talk real speedups, how the pandas accelerator works without a rewrite, and what becomes possible when jobs that used to take hours finish in minutes. You'll hear strategies for datasets bigger than GPU memory, scaling out with Dask or Ray, Spark acceleration, and the growing role of vector search with cuVS for AI workloads. If you know the CPU tools, this is your on-ramp to the same APIs at GPU speed. Episode sponsors Posit Talk Python Courses Links from the show RAPIDS: github.com/rapidsai Example notebooks showing drop-in accelerators: github.com Benjamin Zaitlen - LinkedIn: linkedin.com RAPIDS Deployment Guide (Stable): docs.rapids.ai RAPIDS cuDF API Docs (Stable): docs.rapids.ai Asianometry YouTube Video: youtube.com cuDF pandas Accelerator (Stable): docs.rapids.ai Watch this episode on YouTube: youtube.com Episode #516 deep-dive: talkpython.fm/516 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: pyx - optimized backend for uv * Litestar is worth a look* * Django remake migrations* * django-chronos* Extras Joke Watch on YouTube About the show Python Bytes 445 Sponsored by Sentry: pythonbytes.fm/sentry - Python Error and Performance Monitoring 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: pyx - optimized backend for uv via John Hagen (thanks again) I'll be interviewing Charlie in 9 days on Talk Python → Sign up (get notified) of the livestream here. Not a PyPI replacement, more of a middleware layer to make it better, faster, stronger. pyx is a paid service, with maybe a free option eventually. Brian #2: Litestar is worth a look James Bennett Michael brought up Litestar in episode 444 when talking about rewriting TalkPython in Quart James brings up scaling - Litestar is easy to split an app into multiple files Not using pydantic - You can use pydantic with Litestar, but you don't have to. Maybe attrs is right for you instead. Michael brought up Litestar seems like a “more batteries included” option. Somewhere between FastAPI and Django. Brian #3: Django remake migrations Suggested by Bruno Alla on BlueSky In response to a migrations topic last week django-remake-migrations is a tool to help you with migrations and the docs do a great job of describing the problem way better than I did last week “The built-in squashmigrations command is great, but it only work on a single app at a time, which means that you need to run it for each app in your project. On a project with enough cross-apps dependencies, it can be tricky to run.” “This command aims at solving this problem, by recreating all the migration files in the whole project, from scratch, and mark them as applied by using the replaces attribute.” Also of note The package was created with Copier Michael brought up Copier in 2021 in episode 219 It has a nice comparison table with CookieCutter and Yoeman One difference from CookieCutter is yml vs json. I'm actually not a huge fan of handwriting either. But I guess I'd rather hand write yml. So I'm thinking of trying Copier with my future project template needs. Michael #4: django-chronos Django middleware that shows you how fast your pages load, right in your browser. Displays request timing and query counts for your views and middleware. Times middleware, view, and total per request (CPU and DB). Extras Brian: Test & Code 238: So Long, and Thanks for All the Fish after 10 years, this is the goodbye episode Michael: Auto-activate Python virtual environment for any project with a venv directory in your shell (macOS/Linux): See gist. Python 3.13.6 is out. Open weight OpenAI models Just Enough Python for Data Scientists Course The State of Python 2025 article by Michael Joke: python is better than java

Bob Rudis, VP Data Science from GreyNoise, is sharing some insights into their work on "Early Warning Signals: When Attacker Behavior Precedes New Vulnerabilities." New research reveals a striking trend: in 80% of cases, spikes in malicious activity against enterprise edge technologies like VPNs and firewalls occurred weeks before related CVEs were disclosed. The report breaks down this “6-week critical window,” highlighting which vendors show the strongest early-warning patterns and offering tactical steps defenders can take when suspicious spikes emerge. These findings reveal how early attacker activity can be transformed into actionable intelligence, enabling defenders to anticipate and neutralize threats before vulnerabilities are publicly disclosed. Complete our annual ⁠⁠⁠audience survey⁠⁠⁠ before August 31. The research can be found here: Early Warning Signals: When Attacker Behavior Precedes New Vulnerabilities Learn more about your ad choices. Visit megaphone.fm/adchoices

Bob Rudis, VP Data Science from GreyNoise, is sharing some insights into their work on "Early Warning Signals: When Attacker Behavior Precedes New Vulnerabilities." New research reveals a striking trend: in 80% of cases, spikes in malicious activity against enterprise edge technologies like VPNs and firewalls occurred weeks before related CVEs were disclosed. The report breaks down this “6-week critical window,” highlighting which vendors show the strongest early-warning patterns and offering tactical steps defenders can take when suspicious spikes emerge. These findings reveal how early attacker activity can be transformed into actionable intelligence, enabling defenders to anticipate and neutralize threats before vulnerabilities are publicly disclosed. Complete our annual ⁠⁠⁠audience survey⁠⁠⁠ before August 31. The research can be found here: Early Warning Signals: When Attacker Behavior Precedes New Vulnerabilities Learn more about your ad choices. Visit megaphone.fm/adchoices

A young computer scientist and two colleagues show that searches within data structures called hash tables can be much faster than previously deemed possible. The story How Undergraduate Upends a 40-Year-Old Data Science Conjecture first appeared on Quanta Magazine.

In this episode of Elixir Wizards, host Sundi Myint chats with SmartLogic engineers and fellow Wizards Dan Ivovich and Charles Suggs about the practical tooling that surrounds Elixir in a consultancy setting. We dig into how standardized dev environments, sensible scaffolding, and clear observability help teams ship quickly across many client projects without turning every app into a snowflake. Join us for a grounded tour of what's working for us today (and what we've retired), plus how we evaluate new tech (including AI) through a pragmatic, Elixir-first lens. Key topics discussed in this episode: Standardizing across projects: why consistent environments matter in consultancy work Nix (and flakes) for reproducible dev setups and faster onboarding Igniter to scaffold common patterns (auth, config, workflows) without boilerplate drift Deployment approaches: OTP releases, runtime config, and Ansible playbooks Frontend pipeline evolution: from Brunch/Webpack to esbuild + Tailwind Observability in practice: Prometheus metrics and Grafana dashboards Handling time-series and sensor data When Explorer can be the database Picking the right tool: Elixir where it shines, integrations where it counts Using AI with intention: code exploration, prototypes, and guardrails for IP/security Keeping quality high across multiple codebases: tests, telemetry, and sensible conventions Reducing context-switching costs with shared patterns and playbooks Links mentioned: http://smartlogic.io https://nix.dev/ https://github.com/ash-project/igniter Elixir Wizards S13E01 Igniter with Zach Daniel https://youtu.be/WM9iQlQSFg https://github.com/elixir-explorer/explorer Elixir Wizards S14E09 Explorer with Chris Grainger https://youtu.be/OqJDsCF0El0 Elixir Wizards S14E08 Nix with Norbert (Nobbz) Melzer https://youtu.be/yymUcgy4OAk https://jqlang.org/ https://github.com/BurntSushi/ripgrep https://github.com/resources/articles/devops/ci-cd https://prometheus.io/ https://capistranorb.com/ https://ansible.com/  https://hexdocs.pm/phoenix/releases.html https://brunch.io/ https://webpack.js.org/loaders/css-loader/ https://tailwindcss.com/ https://sass-lang.com/dart-sass/ https://grafana.com/ https://pragprog.com/titles/passweather/build-a-weather-station-with-elixir-and-nerves/ https://www.datadoghq.com/ https://sqlite.org/ Elixir Wizards S14E06 SDUI at Cars.com with Zack Kayser https://youtu.be/nloRcgngTk https://github.com/features/copilot https://openai.com/codex/ https://www.anthropic.com/claude-code YouTube Video: Vibe Coding TEDCO's RFP https://youtu.be/i1ncgXZJHZs Blog: https://smartlogic.io/blog/how-i-used-ai-to-vibe-code-a-website-called-for-in-tedco-rfp/ Blog: https://smartlogic.io/blog/from-vibe-to-viable-turning-ai-built-prototypes-into-market-ready-mvps/ https://www.thriftbooks.com/w/eragon-by-christopher-paolini/246801 https://tidewave.ai/ !! We Want to Hear Your Thoughts *!!* Have questions, comments, or topics you'd like us to discuss in our season recap episode? Share your thoughts with us here: https://forms.gle/Vm7mcYRFDgsqqpDC9

In today's episode, I sit down with AraOluwa Odelowo, Ara is a rising junior at Rice University, where she studies Economics, Data Science, and Financial Computation & Modeling. She's also a Division I track and field athlete who's passionate about integrating faith, discipline, and excellence across all areas of life. At Rice, Ara has been actively involved in both leadership and service, and she brings a thoughtful perspective on navigating college as a high-achieving student. She's excited to share her journey, especially what she wishes she knew before college, with students exploring their next steps. Ara also welcomes connections from professionals who are passionate about mentorship and building diverse pipelines into business, tech, and leadership.

Many data scientists begin their careers expecting to influence strategic decisions, only to find themselves trapped as "data order takers" - endlessly running reports and responding to requests without understanding their business impact. This reactive approach limits career growth and earning potential, keeping even experienced professionals from reaching their strategic potential.In this episode, Kashif Zahoor joins Dr. Genevieve Hayes to share his journey from data order taker to strategic business partner, revealing a practical framework that any data professional can use to transform their role and accelerate their career growth.You'll learn:The three-step framework for evolving from order taker to strategic partner: amplify efficiency, deliver measurable value, and partner first, analyze second [06:21]Why understanding your company's financial model is crucial for demonstrating real business impact [10:57]The mindset shift from waiting for requests to proactively identifying and solving business problems [19:33]How building trust through consistent delivery opens doors to bigger strategic conversations [17:04]Guest BioKashif Zahoor is the Vice President of Business Intelligence at Influence Mobile and has extensive experience in data leadership.LinksConnect with Kashif on LinkedInConnect with Genevieve on LinkedInBe among the first to hear about the release of each new podcast episode by signing up HERE

How does a particle physicist end up shaping the UK Government's approach to artificial intelligence? In this thought‑provoking episode, Andrew Grill sits down with Dr Laura Gilbert CBE, former Director of Data Science at 10 Downing Street and now the Senior Director of AI at the Tony Blair Institute.Laura's unique career path, from academic research in physics to the heart of policymaking, gives her a rare perspective on how governments can use emerging technologies not just efficiently, but humanely. She shares candid insights into how policy teams think about digital transformation, why the public sector faces very different challenges to private industry, and how to avoid technology that dehumanises decision‑making.Drawing on examples from her work in Whitehall, Laura discusses the realities of forecasting in AI, the danger of “buzzword chasing”, and why the next breakthrough in Artificial General Intelligence might well come from an unexpected player, possibly from within government itself.This is a conversation for anyone curious about the intersection of science, policy, ethics, and technology, and how they can combine to make government more responsive, transparent, and human-centred.What You'll Learn in This EpisodeHow Laura Gilbert moved from particle physics research into government AI leadershipThe strategic role of AI in shaping modern policy and public servicesWhy forecasting in AI is harder than it looks—and how this impacts decision‑makersThe balance between technical capability and human‑centred governanceWhy governments must look beyond the tech giants for innovative solutionsLessons from the Evidence House and AI for Public Good programmesResourcesTony Blair Global Institute WebsiteUK Government AI IncubatorLaura on LinkedInRaindrop.io bookmarking appThanks for listening to Digitally Curious. You can buy the book that showcases these episodes at curious.click/orderYour Host is Actionable Futurist® Andrew GrillFor more on Andrew - what he speaks about and recent talks, please visit ActionableFuturist.com Andrew's Social ChannelsAndrew on LinkedIn@AndrewGrill on Twitter @Andrew.Grill on InstagramKeynote speeches hereOrder Digitally Curious

Traditional software expects 100% passing tests. In LLM-powered systems, that's not just unrealistic — it's a feature, not a bug. Eric Ma leads research data science in Moderna's data science and AI group, and over breakfast at SciPy we explored why AI products break the old rules, what skills different personas bring (and miss), and how to keep systems alive after the launch hype fades. You'll hear the clink of coffee cups, the murmur of SciPy in the background, and the occasional bite of frittata as we talk (hopefully also a feature, not a bug!) We talk through: • The three personas — and the blind spots each has when shipping AI systems • Why “perfect” tests can be a sign you're testing the wrong thing • Development vs. production observability loops — and why you need both • How curiosity about failing data separates good builders from great ones • Ways large organizations can create space for experimentation without losing delivery focus If you want to build AI products that thrive in the messy real world, this episode will help you embrace the chaos — and make it work for you. LINKS Eric' Website (https://ericmjl.github.io/) More about the workshops Eric and Hugo taught at SciPy (https://hugobowne.substack.com/p/stress-testing-llms-evaluation-frameworks) Upcoming Events on Luma (https://lu.ma/calendar/cal-8ImWFDQ3IEIxNWk)

What if your code was crash-proof? That's the value prop for a framework called Temporal. Temporal is a durable execution platform that enables developers to build scalable applications without sacrificing productivity or reliability. The Temporal server executes units of application logic called Workflows in a resilient manner that automatically handles intermittent failures, and retries failed operations. We have Mason Egger from Temporal on to dive into durable execution. Episode sponsors Posit PyBay Talk Python Courses Links from the show Just Enough Python for Data Scientists Course: talkpython.fm Temporal Durable Execution Platform: temporal.io Temporal Learn Portal: learn.temporal.io Temporal GitHub Repository: github.com Temporal Python SDK GitHub Repository: github.com What Is Durable Execution, Temporal Blog: temporal.io Mason on Bluesky Profile: bsky.app Mason on Mastodon Profile: fosstodon.org Mason on Twitter Profile: twitter.com Mason on LinkedIn Profile: linkedin.com X Post by @skirano: x.com Temporal Docker Compose GitHub Repository: github.com Building a distributed asyncio event loop (Chad Retz) - PyTexas 2025: youtube.com Watch this episode on YouTube: youtube.com Episode #515 deep-dive: talkpython.fm/515 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: Coverage.py regex pragmas * Python of Yore* * nox-uv* * A couple Django items* Extras Joke Watch on YouTube About the show Sponsored by DigitalOcean: pythonbytes.fm/digitalocean-gen-ai Use code DO4BYTES and get $200 in free credit Connect with the hosts Michael: @mkennedy@fosstodon.org / @mkennedy.codes (bsky) Brian: @brianokken@fosstodon.org / @brianokken.bsky.social Show: @pythonbytes@fosstodon.org / @pythonbytes.fm (bsky) Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Monday at 10am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. Brian #1: Coverage.py regex pragmas Ned Batchelder The regex implementation of how coverage.py recognizes pragmas is pretty amazing. It's extensible through plugins covdefaults adds a bunch of default exclusions, and also platform- and version-specific comment syntaxes. coverage-conditional-plugin gives you a way to create comment syntaxes for entire files, for whether other packages are installed, and so on. A change from last year (as part of coverage.py 7.6 allows multiline regexes, which let's us do things like: Exclude an entire file with A(?s:.*# pragma: exclude file.*)Z Allow start and stop delimiters with # no cover: start(?s:.*?)# no cover: stop Exclude empty placeholder methods with ^s*(((async )?def .*?)?)(s*->.*?)?:s*)?...s*(#|$) See Ned's article for explanations of these Michael #2: Python of Yore via Matthias Use YORE: ... comments to highlight CPython version dependencies. # YORE: EOL 3.8: Replace block with line 4. if sys.version_info < (3, 9): from astunparse import unparse else: from ast import unparse Then check when they go out of support: $ yore check --eol-within '5 months' ./src/griffe/agents/nodes/_values.py:11: Python 3.8 will reach its End of Life within approx. 4 months Even fix them with fix . Michael #3: nox-uv via John Hagen What nox-uv does is make it very simple to install uv extras and/or dependency groups into a nox session's virtual environment. The versions installed are constrained by uv's lockfile meaning that everything is deterministic and pinned. Dependency groups make it very easy to install only want is necessary for a session (e.g., only linting dependencies like Ruff, or main dependencies + mypy for type checking). Brian #4: A couple Django items Stop Using Django's squashmigrations: There's a Better Way Johnny Metz Resetting migrations is sometimes the right thing. Overly simplified summary: delete migrations and start over dj-lite Adam Hill Use SQLite in production with Django “Simplify deploying and maintaining production Django websites by using SQLite in production. dj-lite helps enable the best performance for SQLite for small to medium-sized projects. It requires Django 5.1+.” Extras Brian: Test & Code 237: FastAPI Cloud with Sebastian Ramirez will be out later today pythontest.com: pytest fixtures nuts and bolts - revisited A blog series that I wrote a long time ago. I've updated it into more managable bite-sized pieces, updated and tested with Python 3.13 and pytest 8 Michael: New course: Just Enough Python for Data Scientists My live stream about uv is now on YouTube Cursor CLI: Built to help you ship, right from your terminal. Joke: Copy/Paste

Enterprise AI leaders from C3 AI, Resolve AI, and Scale AI reveal how Fortune 100 companies are successfully scaling agentic AI from pilots to production and share secrets for successful AI transformation.Topics Include:Panel introduces three AI leaders from Resolve AI, C3 AI, and Scale AIResolve AI builds autonomous site reliability engineers for production incident responseC3 AI provides full-stack platform for developing enterprise agentic AI workflowsScale AI helps Fortune 100 companies adopt agents with private data integrationMoving from AI pilots to production requires custom solutions, not shrink-wrap softwareSuccess demands working directly with customers to understand their specific workflowsAll enterprise AI solutions need well-curated access to internal data and resourcesSoftware engineering has permanently shifted to agentic coding with no going backAI agents rapidly improving in reasoning, tool use, and contextual understandingIndustry moving from simple co-pilots to agents solving complex multi-step problemsSpiros coins new concept: evolving from "systems of record" to "systems of knowledge"Democratized development platforms let enterprises declare their own agent workflowsSemantic business layers enable agents to understand domain-specific enterprise operationsTrust and observability remain major barriers to enterprise agent adoptionOversight layers essential for agents making longer-horizon autonomous business decisionsPerformance tracking and calibration systems needed like MLOps for reasoning chainsCEO-level top-down support required for successful AI transformation initiativesTraditional per-seat SaaS pricing models completely broken for agentic AI solutionsIndustry shifting toward outcome-based and work-completion pricing models insteadReal examples shared: agent collaboration in production engineering and sales automationParticipants:Nikhil Krishnan – SVP & Chief Technology Officer, Data Science, C3 AISpiros Xanthos – Founder and CEO, Resolve AIVijay Karunamurthy – Head of Engineering, Product and Design / Field Chief Technology Officer, Scale AIAndy Perkins – GM, US ISV Sales – Data, Analytics, GenAI, Amazon Web ServicesFurther Links:C3 – Website – AWS MarketplaceResolve AI – Website – AWS MarketplaceScale AI – Website – AWS MarketplaceSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

In this special replay of one of our all-time most popular episodes, we dive deep into one of the most debated topics in the pharmaceutical industry: R vs SAS. Together with Thomas Neitmann and my co-host Sam Gardner, we compare these two powerful statistical programming tools from multiple angles — ease of learning, day-to-day usability, community support, visualization capabilities, regulatory acceptance, and more. Whether you are a seasoned SAS programmer, an R enthusiast, or someone deciding which tool to focus on, this conversation will give you valuable insights into where each shines, where they struggle, and how the industry is evolving.

Dhruv Agrawal is CEO and president of Aether Biomedical. Discover Dhruv's unique journey from studying medicine in New Delhi to creating life-changing bionic limbs. Under his leadership, Aether Biomedical has achieved significant milestones, including CE certification and FDA registration for its Zeus V1 bionic limb. Dhruv shares his personal story of transitioning from medical school to MedTech innovation, the obstacles faced and lessons learned as a young entrepreneur, and the hope and inspiration of seeing Aether's prosthetics transform lives, especially in war-torn regions.   Guest links: https://www.aetherbiomedical.com | https://www.linkedin.com/company/aether-biomedical | https://www.instagram.com/aether_biomedical/  Charity supported: ASPCA Interested in being a guest on the show or have feedback to share? Email us at theleadingdifference@velentium.com.  PRODUCTION CREDITS Host & Editor: Lindsey Dinneen Producer: Velentium Medical   EPISODE TRANSCRIPT Episode 061 - Dhruv Agrawal Dhruv Agrawal [00:00:00] Lindsey Dinneen: Hi, I'm Lindsey and I'm talking with MedTech industry leaders on how they change lives for a better world. [00:00:09] Diane Bouis: The inventions and technologies are fascinating and so are the people who work with them. [00:00:15] Frank Jaskulke: There was a period of time where I realized, fundamentally, my job was to go hang out with really smart people that are saving lives and then do work that would help them save more lives. [00:00:28] Diane Bouis: I got into the business to save lives and it is incredibly motivating to work with people who are in that same business, saving or improving lives. [00:00:38] Duane Mancini: What better industry than where I get to wake up every day and just save people's lives. [00:00:42] Lindsey Dinneen: These are extraordinary people doing extraordinary work, and this is The Leading Difference. Hello, and welcome back to another episode of The Leading Difference podcast. I'm your host, Lindsey, and today I'm excited to introduce you to my guest, Dhruv Agrawal. Dhruv is the CEO and president of the management board of Aither Biomedical. He studied medicine in New Delhi before dropping out to pursue a bachelor's in business management. He also has a postgraduate diploma in Medical Device Development Regulatory Affairs from University of California Irvine, and a Master's in Data Science from the University of London. Under his leadership, Aither Biomedical has achieved CE certification and FDA registration for the Zeus V1 bionic limb, and established distribution across nine European countries, the US, and India. Additionally, Aither has raised over 12.5 million US dollars in private capital from leading VCs and has been a part of multiple European grants and research programs for an additional 6.5 million US dollars in non-dilutive capital. All right. Well, thank you so much for being here. Welcome to the show. I'm so excited to speak with you today. [00:01:49] Dhruv Agrawal: it's a pleasure to be here, Lindsey. Thank you so much for inviting me. [00:01:52] Lindsey Dinneen: Of course, of course. Well, I would love, if you wouldn't mind just starting by sharing a little bit about yourself and your background and what led you to Med Tech. [00:02:02] Dhruv Agrawal: Yeah, absolutely. So I'm Dhruv Agrawal. I'm the CEO of Aither Biomedical. We are a company based out of Poznan in Poland, so on the western part of Poland. It's a little bit chilly here. As a company, we are a team of about 55 people right now, currently present in the US, Europe, Middle East, as well as India. And we focus on making bionic hands for upper limb amputees. [00:02:25] Lindsey Dinneen: Amazing. Yes. So I wanna get into everything amazing that your company does, but going back for just a little bit, in your own personal history, can you share a little bit about maybe growing up and what experiences led you to think, "Hey, in the future, maybe I wanna do X, Y, and Z." [00:02:43] Dhruv Agrawal: Mm-hmm. So first of all, entrepreneurship was never a plan for me. I didn't even knew that there was a thing called an entrepreneur until I was easily into high school. Both my parents are doctors. My dad's a pediatrician, mom's a gynecologist, and as it happens in India, if your parents are doctors, you kind of know that you have to become a doctor as well. So I went to the coaching classes to pre, to prepare for medical entrance examinations. I actually met my co-founder there about 10 years ago. We both got into medical school. I was generally comfortable with medicine, you know, growing up in a hospital with doctor parents around. So I was generally comfortable in a clinical setting, but I realized that I was much more interested in the technological aspect of medicine rather than the clinical aspect of it. And that was when I was getting into the second year of my university. And luckily my dad, for my 18th birthday, bought me a 3D printer, like a very simple 3D printer from China as my 18th birthday gift. 'cause I was really wanting to get into that world. And that's where the story begins. So even till today, my dad jokingly says that that's the worst gift he has ever bought for me, because that made me drop out of medical school. [00:03:57] Lindsey Dinneen: Oh no. Okay, so you were given this gift and you started, I imagine, tinkering with it, learning how to use it. So tell me about that. [00:04:06] Dhruv Agrawal: Yeah, the thing with my co-founder as well, even though we went to the same medical university, we were not really friends in the first year. We were just colleagues. But when I got this 3D printer, it was like one of those things that you assemble, you get a kit and you assemble. And I was asking around people in my university and they were like, "Come on, what are you doing? Like, I don't wanna come to your apartment to assemble a 3D printer." And my co-founder was the first one who said yes to coming down and assembling that printer with me. So that's how our friendship essentially started in the university, even though we had known each other for three years by that point. And then we started, of course, by very basic things like printing mobile phone covers and key chains and we were just in awe with the fact that I have something in my room, in a studio apartment, where I can just build physical things, right? And this was back in 2018, so 3D printer was not such a consumer product where, you know, if it was of course used in industry, but it was not something that you would imagine having at your home, at least not in India. And then we actually found out that there's a society called Enable, which is an NGO that makes very simple basic prosthetic designs for kids. So we started by printing those and started going to some amputee clinics around and trialing that out with patients, just purely out of technical curiosity. We didn't really had a draw towards amputation, so to speak. We were more driven by the technical curiosity of, you know, it sounds interesting to make a prostatic hand. So that was the beginning. And then slowly, slowly things happened very organically that we went from wanting to 3D print basic things to starting a biomedical innovation club in our university, to incorporating a company in India, then to coming all the way over to Poland and now having 55 people. [00:05:49] Lindsey Dinneen: Holy cow. That's an amazing story. Thank you for sharing about that. So, okay, so, so you started off with this curiosity, like, "Hey, let's see what we could do with this printer and, and how we can make it work for people." And I love that your initial pull with it was to actually provide something that does help people. So that's obviously a core value, something that you hold very dear. So can you speak a little bit more, did you have sort of any personal experience or within your family or what led you to say, "You know what, hey, I've got this really cool tool at my disposal. Let me start using it by actually doing something that helps others." [00:06:27] Dhruv Agrawal: I mean, the honest answer, I would love to say I had some personal experience, but the honest answer is no, not, not really. I don't have one of those stories where I can tell you that, like I met an amputee 15 years ago, 20 years ago, and have had that motivation for that time. It was just pure technical curiosity to begin with. But of course, as we started building basic devices and giving it out to people and seeing the response of what a very simple, you know, $50 thing can do for a person who's missing a limb in an impoverished family in a village in India, that's a very powerful thing. So at that point, we realized that we started getting more and more close to upper limb amputation as a field, as a clinical specialty within itself. Of course, both me and my co-founder coming from medical school growing up in family of medicals, we've always had it in our heart to work in the clinical side of things. We've always liked working around, helping people get healthier and better. But amputation specifically was an area that we were very lucky that we found as an area of interest that developed within the both of us. [00:07:31] Lindsey Dinneen: Yeah, of course. Okay, so, so you started printing these limbs, and then you realized, "Oh my goodness, there's such a need for this. There's so much opportunity here to really help people." So, so tell me a little bit about the evolution over time of how you have made it better and better, more technologically advanced, more ergonomic, all the things that go into that. Can you speak a little bit to that learning curve and process? [00:07:56] Dhruv Agrawal: Mm-hmm. Yeah, it was a very long learning curve because not only did, me and my co-founder had zero background in business. We were 18-year-old, 19-year-old kids, right? We were just teenagers and we really had no idea what we wanted to do. And not only that, we also were not engineers, so we didn't have any engineering experience or expertise either. So everything that we did in the very beginning, at least, was self-taught. I just knew I had an inclination towards electronics and programming. My co-founder was much more towards mechanical CAD design and things like that. So we started learning these courses for free on edX and Coursera and all these, you know, MOOC platforms. And that's how we built up the very first prototype of the product by getting some small grants here and there in India. Of course, the situation is very different right now. We have R&D team of 30 people, very experienced, a few PhDs here and there. So I don't really design anymore in my day-to-day life, but that's how we started. And same was the side of the journey of coming from India to Poland. Again, that was not something that was planned at all. We had no experience in business. We had no experience in raising funding or raising money and things like that. We just learned on the go, applied to over a hundred different programs 'cause most of the investors said no to us back then in 2018 to funding 'cause why would they say yes? And we looked at like, "Okay, can we get some grants and things like that?" Applied to over a hundred programs. Luckily got selected in this program in Poland, which was like a $50,000 program back in 2018 and decided, "Yeah, let's try that place out." And came to Poland. I literally came with a backpack with stuff for two months 'cause there was a plan, come for the grant, stay for two months, go back to my family in India, and it's been seven years since then. [00:09:44] Lindsey Dinneen: Oh, there you go. Oh my goodness. That's great. So Poland, and you get along it sounds like just fine. Excellent. Excellent. Okay, so, I really appreciate you sharing about, especially, you were both so young and but so eager. It sounds like just, "Yes, let's learn, let's develop the skills that we need to along the way." I would imagine though, coming into it, perhaps that young and not having as much business experience, or, or any really in, in the past, I-- something that I really admired when I was kind of looking through your LinkedIn profile was when you post, a lot of times you share stories about areas that, that may be considered I, I guess mistakes or stumbling blocks or things that, that you've overcome on your path. And I would love if you would share maybe just a couple of things that come to mind, as an early founder, because your story is amazing and unique, but there are lots of other founders too who find themselves in similar situations where they're like, "Whoof, I've got this great idea. I know what I want, but here's maybe what I should look out for to avoid." could you share a little bit about that? [00:10:49] Dhruv Agrawal: Yeah, absolutely. I mean, the first thing is mistakes are unavoidable, right? it doesn't matter whether you're coming from a background of a medical school dropout, or if you have 10, 15, 20 years of corporate experience and things like that. 'Cause I do find myself thinking a lot about, you know, wouldn't it have been better if I would've graduated and then did a MBA and then started a company? Yes, it might have been better, but the things that I deal with in my day-to-day life in the startup, I don't think this is taught anywhere. So the first and foremost thing, which is of importance, is that mistakes are unavoidable. It's okay to make mistakes. The biggest learning that I have is mistakes are unavoidable, but it's up to you to be decisive enough to pivot as quickly as possible. So don't look back at the mistakes that we have made, because one of the worst things that we have done in this company, or where we have failed the most, or where we have seen that like, "Ah, this is where we could have done things better," are not about making a wrong decision. They were just about being indecisive and being in a dilemma for a long, long time. It would've been far better if we would've made certain decisions quickly, gotten feedback and quickly pivoted, instead of just being in a dilemma and trying to balance two sides for a long time period. An example of that would be when we launched the first version of our product into the market, we realized that we had made some errors from the point of view of what should be the feature set in this product. And so, for example, the product was available only in a medium size hand in terms of the dimensions, but majority of the market is for a small size hand. So at that point we couldn't really just miniaturize things because there's a physical limitation. So at that point we had to make a decision of do we scrap this thing completely and build a new hand from scratch that starts with a small hand and then has a medium sized option as a grow up? Or do we continue to work on the medium sized hand, and then launch a small sized hand separately? Finally, we decided to do the second option. But looking back again, I, I don't think it would've been better or worse either way. I think both of these options are fair. It's just the fact that we spent over nine months going back and forth between, "Okay, let's continue putting our efforts in energy into the medium sized that we have right now" versus, "Okay, this month we are now suddenly feeling, ah, that's not gonna work out. Let's start building the second version." So that dilemma of indecision is probably the worst thing that you can do. Just make a decision, own up to it, move on. If it works out, great, if it not, if it doesn't work out, you're gonna have learnings and you'll be stronger at the end of the day. So that's, I would be an I would say would be an example of one of the key errors that we made. [00:13:23] Lindsey Dinneen: Yeah. Well, thank you for being willing to share that, and that's such valuable advice and feedback. And so, as you recognize this and go, "Okay, so that didn't work as planned, or in the way that I would prefer," what did you end up deciding? How do you go now, moving forward, when you are in a position of "I have a major decision to make. I feel like both options have value and merit." How do you end up deciding, "Okay, I I'm not gonna leave this just in this hazy middle ground, I'm gonna make a decision." How do you go about that now differently? [00:13:54] Dhruv Agrawal: I think the first and foremost thing that entrepreneurs, or anybody who wants to build a new product, or anybody who just wants to build something new, is be very, very, very honest with yourself about, "Am I solving a real problem?" As founders, as creators, as developers, it is so easy to go into that mindset of you find a problem that you can relate to or you somehow think that this is a real problem. It doesn't matter what feedback you're going to get. You're going to convert that feedback, or create a narrative or story from that feedback, that is going to align with the impression that you have built in your own head about what the real problem is. So one thing that we really do right now is just focus on problem market fit at the very early stages of launching a new software, building a new product, building the next version of the hand, or whatever else we do is really try to question, "Are we solving a real problem?" And in a completely unbiased manner, "Do people agree with me that I am solving a real problem?" So that's what I would say would be a primary thing that we do differently right now. Of course at this point, we start getting users involved much earlier into our development process. That is something that we did not do in the past, and hence the surprise that we got at that point. So we start involving users, different stakeholders, and things like that much earlier, but at the same time, I would say that it's not to say that I would penalize myself for the historical decisions that I took. We did the best that we could potentially with the resources that were available at that point. Now we have much more resources so we can do all these things. So don't feel pressured to do everything on day one. You know, start with something, move forward and build that maturity as you grow. [00:15:38] Lindsey Dinneen: Oh, I love that. That's excellent advice. Thank you for sharing. Yeah, so you know that's a great segue and I love the fact that you were talking about the end user and the importance. And it's so funny because of course, ultimately your goal is to help these end users and improve their quality of life and whatnot. But to your point, it does get easy to get so bogged down in the details of what you're creating and innovating that perhaps you forget sort of the bigger picture at times. So, speaking of these end users, can you share any stories that might stand out to you as really reinforcing to you that, "Hey, gosh, I am in the right industry, doing the right thing at the right time." [00:16:17] Dhruv Agrawal: Yeah, no, absolutely. So we have had many phenomenal end users that have reiterated our belief in the product that we are building, the problems that we are solving, the company, and the organization that we are building as a whole. I mean, generally speaking, patients change their devices every three to five years, and that's really our entry point of getting a device into the hands of the patients. But even with those, a patient is using another prosthetic device, they start using ours, they will see a step change in the functionality, and that's always empowering. But the most interesting stories are where we have really seen patients who, for example, congenital amputees tried a prosthetic device 10 years ago, 15 years ago, and then made a decision to live their life without any prosthetic device. So got used to a life for 15, 20, 25 years of living a life without a prosthetic device, just with an amputated limb or a limb difference. And then, we come in with our product, they see it, they use it, and they are ready to adopt that again. And that's a much powerful validation for us because somebody who has used a device, looked at all the advancements over the last two decades, decided actively decided to not use any of those advancements, and looks at our product and says, "Ah, this really solves the problems that I was waiting for someone to solve for the last two decades." Like we had this situation with a very famous Polish guy, Marek Kamiński, who is the youngest Polish person to go to both poles, North Pole and the South Pole, and he's a bilateral amputee on legs and he has a unilateral amputation to one arm. He has not used a prosthetic device in, I think 15 or 20 years, something like that. So for a very long timeframe. He met with an ambassador of ours and was finally convinced after 15 long years to give another try. And we fitted him over three months ago and he's been performing phenomenally with the device and he's so happy with that. So those are the moments that really give us more confidence or give us a boost of confidence in the product that we are building and the company that we are building. [00:18:19] Lindsey Dinneen: That's incredible. Wow. What a story. Yeah, and I love hearing those kinds of stories and that just to reinforce, " Hey, you really are making a difference." And I'm sure that helps on the days that are a little bit harder, a little trickier, you know, it helps to have that to hold onto, so you know your impact goes so far beyond even the places that you've mentioned before. I was reading about how you've worked with the Open Dialogue Foundation and there's been some work in Ukraine, and I'm wondering if you could share a little bit about perhaps that collaboration, and or some of the other exciting collaborations you have going on with these amazing organizations all over the world. [00:18:54] Dhruv Agrawal: Absolutely. I mean, the work that we do in Ukraine is something which is very close to our heart and what you just mentioned a moment ago, it's exactly that type of work that keeps us going on the hardest of days. I have so many amazing stories from the patients who have been fitted with our device 'cause at this point in the last year or so, we have already fitted over a hundred patients with our bionic hands in Ukraine. We primarily work with Superhumans, which is NGO based out of Kyiv, a great place, really the mecca for prosthetics at this point, I would say. They're doing a phenomenal job of getting these patients in, rehabilitating them, fitting them with our device and then training them on how to use the device. In fact, even supporting them in the post rehabilitation, acquainting them to back to the real world as well. And we send teams of doctors from the US, from Poland, to Ukraine to actually fit these devices to patients. And we have had a lot of success stories come out of it. We have people who have amputations, even at the level of shoulder who are amputated all the way up to the shoulder or four quarter amputation, and they are successfully able to live a independent life with our device. I think the best story that I've had, or the part that really made me tear up, was when one of the soldiers got fitted with our device and his really, really big wish was to be able to do the first, to dance with his wife, with both hands. And I got to see that and it was, it was the most amazing feeling ever. [00:20:20] Lindsey Dinneen: Oh my goodness. Yes. I don't know how you couldn't just have the waterfall start with that kind of story. That's incredible. Thank you for sharing about that. So, as you look toward the company's future and your own, what are you excited about moving forward? [00:20:34] Dhruv Agrawal: I mean, we are currently in the process of getting a new version of our hand in the market, which has all the learnings of the last four years or so. So we are definitely really excited about that. You have to keep in mind when we launched the first product, we didn't even have enough money to-- because prosthetics are expensive-- so we didn't really have had enough money to buy our competitor devices, or the devices from the past to look around to see, touch, feel, how they are built. Everything that we built was purely out of our imagination and based on what we could find on the internet. And, you know, go visit a doctor who fits these devices, have that 10, 15 minutes to look around that device, and so on and so on. I mean, four years later, now we have the experience of fitting close to seven, 800 patients with our device. All that feedback that has gone into the next version product that we are gonna be building. So very excited about that. We continue to develop the software platform, so we are not just a company that is focused on providing a device to the patient, but we provide an entire software platform that's like a digital twin for the patient. So it supports the patients throughout their end-to-end journey. Because it's not just about giving a device to the patient, but it's all about can we improve their quality of life? Can the patient pick up a glass of water? Can he tie his shoelaces? Can he water a plant? Can he do the activities that he really wants to do? And from that perspective, the software platform that we continue to build focuses on things like adherence, occupational therapy, physical therapy, monitoring of the usage of the device. Because the thing in prosthetics industry is, the day you give the device to the patient is not the day you have won the battle. That's the day the battle actually begins, 'cause now it's all about making sure that you deliver on the promise of helping him get better quality of life. [00:22:20] Lindsey Dinneen: Yeah. Yeah. I'm sure that's an exciting challenge, but it's a continually evolving challenge too. And there's probably variations, I would imagine, on people embracing the technology a little bit differently and how you handle all that. Yeah. Excellent. Well that is a very exciting future and it's so much fun to hear about, and you know, you've had a great career so far. I'm sure it's wildly different than what you may have imagined as a kid. But what a cool gift that you're bringing to the world. You've been recognized quite a bit. You're 30 under 30 for Europe, and you've been involved in lots of different cool organizations. You've been a TEDx speaker. What are some of those moments like, have they been surreal? Is it just like, "Oh, thank you." Just confirmation that, hey, you are on the right tracker. What are those kinds of moments like for you? [00:23:08] Dhruv Agrawal: I mean, definitely the first round of funding that we raised in Poland was was a huge check mark for us, because it's that moment at which you realize, "Ah, somebody wants to give me money and somebody wants to give me a quarter of a million dollars." I've never seen that much money together on a single bank account or in any way, shape or form, right? I come from a normal middle class family. We don't have that. So, that was definitely the first micro checkpoint, let's say. I mean, both the things that you mentioned, the TEDx thing, the Forbes 30 Under 30 thing, coming from a background in India where these things are really important, although they're not so important for me as a person, but they're much more important for some reason to my parents and to society. It is a different place. We put a lot of emphasis on these types of things. So from six, seven years ago, looking at these lists coming out or looking at, "Oh, this cool guy spoke on a TEDx talk, sending him an email about, 'Do you want to be an advisor in my company? I'll give you 5% shares,'" and so on and so on, to actually doing those things by yourself, that's definitely pretty well as well. But again, at the end of the day, there is nothing better than seeing a new patient get fitted with the hand, seeing the reaction of their family members. They have a daughter, they have a son who they hold their hand for the first time. They hug their wife. I mean, just, just being around amputees and patients who use your device, something that you built and that helps them get better at their daily life, that's, I would say, the most rewarding thing ever. [00:24:39] Lindsey Dinneen: Yeah, of course. That's, that's wonderful. Yeah. So, oh my goodness, this is so great and very inspirational, but pivoting the conversation a little bit just for fun. Imagine that you were to be offered a million dollars-- speaking of those wonderful sums of money-- to teach a masterclass on anything you want. It can be something within your industry, but doesn't have to be, what would you choose to teach? [00:25:03] Dhruv Agrawal: I have two topics in mind. One is I would probably teach a masterclass on pitching, especially for first time founders. I think that is something which I'm good at, and we have obviously raised a pretty decent amount of capital up 'till now. So that would be the one thing that I would say. So kind of a combination of pitching and starting a startup for the first time, especially in the field of hardware, medical devices, things like that. And the second thing that I would really like to talk about is just probably trying to put my thoughts together and making a masterclass on how to never give up, because I think that that's a very underrated quality. But that's a very important quality. There have been complex times in the history of our company where we have felt that like, "Ah, this might be it." But it's all about what you do in those moments and how you go beyond those. I think it's all about that. [00:25:47] Lindsey Dinneen: Yeah, absolutely. And how do you wish to be remembered after you leave this world? [00:25:53] Dhruv Agrawal: Just as a positive change maker. I really would like all these patients that we are helping and giving these devices to. I, I just want to be a small part of their lives. Just as I was part of the life of the veteran who got married, I, I just wanna ha have those small moments club together amongst these different individuals that we are privileged to work with. [00:26:13] Lindsey Dinneen: Hmm. Yes, of course. Wonderful. And then final question, what is one thing that makes you smile every time you see or think about it? [00:26:22] Dhruv Agrawal: Oh, that's very simple. Patients getting fitted with our device. Today we see a patient getting fitted with our device, and that smile on their face and things like that. And, you know, that's even much bigger, much more interesting in Ukraine because many times when you go to these hospitals, and when I go to these hospitals in Ukraine, you have to understand that these people have gone through a lot. These soldiers who are putting their body on the line for their country. There, of course, there's a certain sort of low morale that they have when they're amputated and when they're in these hospitals and things like that where they don't really think that there is ever a possibility for them to regain something back. And you go in there and you show them a bionic hand, and they're not sure if this thing works, and you put the electrodes on them and they open the hand or close it for the first time, and then you suddenly see those expressions change from like, "Ah, what has happened to me?" to, "Oh, what can I achieve?" That is also an amazing feeling. [00:27:16] Lindsey Dinneen: Yeah. Oh, I love that. What an amazing gift to be able to help somebody bridge that gap and witness it. How cool is that? Oh, well, I think this is incredible. I am so grateful for you and your co-founder for starting this company and just being able to give so many people hope and new life, really, just a new way of experiencing life. So thank you for all of the incredible work you're doing. I'm so excited to continue to follow your work, support your work, as I'm sure all of our listeners are as well. So, gosh, I just really appreciate you sharing all of your advice and stories and wisdom with us. So thanks again so much for being here. [00:27:55] Dhruv Agrawal: Of course, Lindsey, thank so much for having me. [00:27:56] Lindsey Dinneen: Of course, of course. And we are honored to be making a donation on your behalf as a thank you for your time today to the American Society for the Prevention of Cruelty to Animals, which is dedicated to preventing animal cruelty in the United States. We really appreciate you choosing that organization to support and thank you just again, so very much for your time here today. I just wish you continued success as you work to change lives for a better world. And thank you also so much to our listeners, and if you're feeling as inspired as I am right now, I'd love it if you share this episode with a colleague or two and we'll catch you next time. [00:28:43] Ben Trombold: The Leading Difference is brought to you by Velentium. Velentium is a full-service CDMO with 100% in-house capability to design, develop, and manufacture medical devices from class two wearables to class three active implantable medical devices. Velentium specializes in active implantables, leads, programmers, and accessories across a wide range of indications, such as neuromodulation, deep brain stimulation, cardiac management, and diabetes management. Velentium's core competencies include electrical, firmware, and mechanical design, mobile apps, embedded cybersecurity, human factors and usability, automated test systems, systems engineering, and contract manufacturing. Velentium works with clients worldwide, from startups seeking funding to established Fortune 100 companies. Visit velentium.com to explore your next step in medical device development.

In this episode of Beyond the Thesis with Papa PhD, host David Mendes sits down with Dr. Karina do Santos Machado, a trailblazing young scientist from Brazil whose journey exemplifies the power of collaboration and open science in the global South. Karina shares her path from a childhood fascination with computers to becoming a principal investigator leading cutting-edge drug discovery research with global impact, all from her home base in Rio Grande.   Facing the challenges of limited funding, infrastructure hurdles, and fewer resources common to universities in developing countries, Karina highlights how resourcefulness and community spirit have been fundamental to her success. Collaboration is not only a choice but a necessity in the Brazilian scientific landscape. By building networks both within her institution and internationally, Karina has leveraged open science initiatives to propel her team onto the world stage, including successful participation in global drug discovery challenges such as Conscience's CACHE initiative for COVID-19 therapeutics.   As Karina explains, open science has been key in providing access to critical data, software, and partnerships, democratizing opportunities for smaller labs like hers. Her story is a testament to how determined scientists, even from under-resourced environments, can foster innovation and make tangible contributions to global health.   Karina dos Santos Machado holds a degree in Computer Engineering from the Universidade Federal de Rio Grande and a Master's and Ph.D. in Computer Science from the Pontifícia Universidade Católica of Rio Grande do Sul. Between 2018 and 2019, she worked as a postdoctoral fellowship in the NANO-D research group at INRIA in Grenoble, France. She is currently a Lecturer at FURG, working in the graduate programs in Health Sciences and Computer Science, where she coordinates the Computational Biology Laboratory. Her research focuses primarily on Bioinformatics and Data Science, including the following topics: Genomics, Machine Learning, Virtual Drug Screening, Molecular Docking, and Molecular Dynamics.   Three Inspiring Take-aways from my conversation with Karina: Collaboration is a Superpower: In environments where resources are scarce, building bridges—within your university and beyond—makes it possible to tackle complex scientific problems. Don't hesitate to ask for help, offer your expertise, and create interdisciplinary teams; together, you go further. Open Science Levels the Field: By embracing open-source tools, sharing data, and participating in global challenges, you can give your work international visibility and validation, regardless of your location or funding status. Open science isn't just a philosophy; it's a passport to global research networks and impact. Your Local Challenges Have Global Resonance: The unique scientific questions you face in your community, like drug resistance in tuberculosis, are shared by the worldwide research community. Your perspective and commitment to real-world problems can drive both local solutions and contribute to advancing science on a global scale.   Karina's journey proves that with innovation, community, and openness, you can thrive and lead in science, no matter where you start.  If you're curious about AI, biosciences, or just want to see how resilient, creative science happens outside the “usual” power centers, this episode is a must-listen. Reach out to Karina on LinkedIn, and check out the episode for more wisdom! Let's build a more open, global scientific community together.  See the resources section below for Daria Levina's links! This episode's resources: X | Karina Machado CONSCIENCE | Webpage CACHE Challenges | Webpage Thank you, Karina Machado! If you enjoyed this conversation with Karina, let her know by clicking the link below and leaving her a message on Linkedin: Send Karina Machado a thank you message on Linkedin! Click here to share your key take-away from this interview with David! Leave a review on Podchaser ! Support the show !   You might also like the following episodes: Daria Levina – Behind the Scenes of Graduate Admissions Morgan Foret – Demystifying Industry Careers Tina Persson –Leaving Academia and Embracing Industry Sylvie Lahaie – Navigating Stress and Anxiety in Graduate School

Nathan Herz is the Co‑Founder and COO of Paraspot AI, a New York‑based AI company backed by RE Angels, ffVC, 97212 Ventures, SaaS Ventures & Aroundtown that applies advanced computer vision to automate property inspections for Single-family, Multifamily, Hospitality, and Logistics operators. Paraspot's platform reduces inspection costs and time, empowering operators to manage assets efficiently remotely. Since co-founding the company in 2020, Nathan has been instrumental in scaling operations, leading sales strategy, and building key client relationships.(01:28) - Nathan's Real Estate Journey & Birth of Paraspot(06:15) - Challenges & Innovations in Property Inspections(10:17) - AI-Powered Inspections(18:07) - Latest Property Management Regulation in CA & NY(21:05) - 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.(22:38) - Founder Timing & Persistence(25:58) - New Audio Feature for Inspections(28:32) - Single Family vs. Multifamily Market Fit(37:31) - New Partnership Announcement with DepositCloud(39:52) - Collaboration Superpower: Nathan's grandpa & Ryan Serhant

Even the most compelling data presentation can fail if it runs headfirst into your stakeholders' cognitive blind spots. Decision makers who claim to be "data-driven" often unconsciously filter information through their existing beliefs, leaving brilliant insights ignored or dismissed.In this Value Boost episode, Dr. Russell Walker joins Dr. Genevieve Hayes to reveal practical techniques for identifying and overcoming the cognitive biases that sabotage data-driven decision making.This episode reveals:How confirmation bias transforms data analysis into a "numerical Rorschach test" where stakeholders see only what confirms their existing beliefs [02:59]The "verbal jujitsu" technique that acknowledges preconceptions without confrontation, allowing stakeholders to save face while guiding them toward data-driven conclusions [03:47]Why recency bias makes yesterday's angry customer complaint outweigh months of systematic data analysis in executive decision making [05:24]The pre-meeting strategy that helps you anticipate and prepare for stakeholder blind spots before they derail your presentation [07:00]Guest BioDr Russell Walker is the principal consultant at Walker Associates, which specialises in data science education and healthcare analytics, and previously served as a professor at DeVry University, where he co-founded the university's business intelligence and analytics program. He holds a PhD in business administration with a specialty in computer science.LinksRussell's WebsiteConnect with Russell on LinkedInConnect with Genevieve on LinkedInBe among the first to hear about the release of each new podcast episode by signing up HERE

Heart failure remains one of the most urgent challenges in health care, affecting millions of individuals and imposing a significant burden on families and the broader health system. Although guideline-directed medical therapy (GDMT) has been shown to improve clinical outcomes and reduce hospitalizations, adoption of these therapies remains suboptimal nationwide. Addressing this treatment gap is essential not only for enhancing survival and quality of life but also for mitigating the rising economic impact of heart failure as its prevalence continues to increase. Gluckman also led the session “Addressing Underuse of Guideline-Directed Medical Therapy in Heart Failure” at the July 9 Institute for Value-Based Medicine® (IVBM) event in Garden Grove, CA, where he addressed the need for integrated approaches to drive sustainable, system-level change in cardiovascular care. On this episode of Managed Care Cast, Ty Gluckman, MD, MHA, FACC, FAHA, FASPC—a practicing cardiologist at Providence Heart Institute in Portland, Oregon, and medical director of Providence's Center for Cardiovascular Analytics, Research, and Data Science—discusses strategies to improve GDMT implementation. The conversation explores opportunities for payers and providers, the potential of remote patient monitoring and digital health tools, and the role of value-based care models in supporting optimal therapy. Emphasis is placed on the importance of aligning clinical guidelines with managed care policies to drive meaningful improvements in patient outcomes.

We were promised robot butlers and got Roombas that cry under the couch. In this brutally honest (and slightly hilarious) episode, Francesco dives into why the robot revolution fizzled, why your dishwasher still needs you, and how robotics became more YouTube circus than household helper. Spoiler: It's not the tech – it's us.   Sponsors DSH is proudly sponsored by Amethix Technologies. At the intersection of ethics and engineering, Amethix creates AI systems that don't just function—they adapt, learn, and serve. With a focus on dual-use innovation, Amethix is shaping a future where intelligent machines extend human capability, not replace it. Discover more at amethix.com   DSH is brought to you by Intrepid AI. From drones to satellites, Intrepid AI gives engineers and defense innovators the tools to prototype, simulate, and deploy autonomous systems with confidence. Whether it's in the sky, on the ground, or in orbit—if it's intelligent and mobile, Intrepid helps you build it. Learn more at intrepid.ai     ✨ Connect with us!

Topics covered in this episode: rumdl - A Markdown Linter written in Rust * Coverage 7.10.0: patch* * aioboto3* * You might not need a Python class* Extras Joke Watch on YouTube About the show 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: rumdl - A Markdown Linter written in Rust via Owen Lamont Supports toml file config settings Install via uv tool install rumdl. ⚡️ Built for speed with Rust - significantly faster than alternatives

Listen to this interview with Whitney Pratt – an actuary who leads a team of data scientists – about similarities and differences of the two fields and how we can better work together.  If you are an actuary wanting to know more about data science, or trying to choose between the two career paths, this is a must listen!

In this special replay episode — the top 3 most downloaded of all time — I'm again joined by Stuart McGuire as we explore The Chimp Paradox by Professor Steve Peters. This book provides a simple yet powerful model for understanding how our brain works — and how it often works against us if we're not aware of it. Whether in meetings, under pressure, or dealing with self-doubt, understanding your inner “chimp” can help you manage emotions, lead with clarity, and avoid the traps that keep so many statisticians and scientists stuck. This episode remains a favorite because it strikes at the core of how we think, react, and lead — especially in high-stakes scientific and business environments.

Games typically involve some combination of math, chance, strategy, and skill. In this two part mini-series, the Klaviyo Data Science Podcast investigates the role of math in games and how our relationship to them is changing given the increasing number of sophisticated AI Agents that can often beat us at our favorite games.This podcast additionally covers concepts ranging from what makes a game ‘Solved', to how the early development of Game Theory was influenced by the Cold War.The team also touches on a topic that will be expanded on in the next episode: why AI Agents are so sophisticated at certain games (e.g. Go), while struggling with other games (e.g. no stakes poker or basketball).When they invent the robot LeBron James, it will be the end of human society.- Michael LawsonFor more details, check out the ⁠⁠⁠full writeup on Medium⁠⁠⁠!

In this episode of Crazy Wisdom, host Stewart Alsop sits down with astrologer and researcher C.T. Lucero for a wide-ranging conversation that weaves through ancient astrology, the evolution of calendars, the intersection of science and mysticism, and the influence of digital tools like AI on symbolic interpretation. They explore the historical lineage from Hellenistic Greece to the Persian golden age, discuss the implications of the 2020 Saturn-Jupiter conjunction, touch on astrocartography, and reflect on the information age's shifting paradigms. For more on the guest's work, check out ctlucero.com.Check out this GPT we trained on the conversationTimestamps00:00 Stewart Alsop introduces C.T. Lucero; they begin discussing time cycles and the metaphor of Monday as an unfolding future.05:00 Astrology's historical roots in Hellenistic Greece and Persian Baghdad; the transmission and recovery of ancient texts.10:00 The role of astrology in medicine and timing; predictive precision and interpreting symbolic calendars.15:00 Scientism vs. astrological knowledge; the objective reliability of planetary movement compared to shifting cultural narratives.20:00 Use of AI and large language models in astrology; the limits and future potential of automation in interpretation.25:00 Western vs. Vedic astrology; the sidereal vs. tropical zodiac debate and cultural preservation of techniques.30:00 Christianity, astrology, and the problem of idolatry; Jesus' position in relation to celestial knowledge.35:00 The Saturn-Jupiter conjunction of 2020; vaccine rollout and election disputes as symbolic markers.40:00 The Mayan Venus calendar and its eight-year cycle; 2020 as the true “end of the world.”45:00 Media manipulation, air-age metaphors, and digital vs. analog paradigms; the rise of new empires.50:00 Astrocartography and relocation charts; using place to understand personal missions.Key InsightsAstrology as a Temporal Framework: C.T. Lucero presents astrology not as mysticism but as a sophisticated calendar system rooted in observable planetary cycles. He compares astrological timekeeping to how we intuitively understand days of the week—Sunday indicating rest, Monday bringing activity—arguing that longer astrological cycles function similarly on broader scales.Historical Continuity and Translation: The episode traces astrology's lineage from Hellenistic Greece through Persian Baghdad and into modernity. Lucero highlights the massive translation efforts over the past 30 years, particularly by figures like Benjamin Dykes, which have recovered lost knowledge and corrected centuries of transcription errors, contributing to what he calls astrology's third golden age.Cultural and Linguistic Barriers to Knowledge: Lucero and Alsop discuss how language borders—historically with Latin and Greek, and now digitally with regional languages—have obscured access to valuable knowledge. This extends to old medical practices and astrology, which were often dismissed simply because their documentation wasn't widely accessible.Astrology vs. Scientism: Lucero critiques scientism for reducing prediction to material mechanisms while ignoring symbolic and cyclical insights that astrology offers. He stresses astrology's predictive power lies in pattern recognition and contextual interpretation, not in deterministic forecasts.Astrology and the Digital Age: AI and LLMs are starting to assist astrologers by generating interpretations and extracting planetary data, though Lucero points out that deep symbolic synthesis still exceeds AI's grasp. Specialized astrology AIs are emerging, built by domain experts for richer, more accurate analysis.Reevaluating Vedic and Mayan Systems: Lucero asserts that Western and Vedic astrology share a common origin, and even the Mayan Venus calendar may reflect the same underlying system. While the Indian tradition preserved techniques lost in the West, both traditions illuminate astrology's adaptive yet consistent core.2020 as a Historical Turning Point: According to Lucero, the Saturn-Jupiter conjunction of December 2020 marked the start of a 20-year societal cycle and the end of a Mayan Venus calendar “day.” He links this to transformative events like the vaccine rollout and U.S. election, framing them as catalysts for long-term shifts in trust, governance, and culture.

Building AI agents that actually get things done is harder than it looks. Demetrios, Paul, and Dmitri break down what makes agents effective—from smart planning and memory to treating tools, systems, and even people as components. They cover the "react" loop, budgeting for long tasks, sandboxing, and learning from experience. It's a sharp, practical look at what it really takes to design useful, adaptive AI agents.Guest speakers:Paul van der Boor - VP AI at Prosus GroupDmitri Jarnikov - Senior Director of Data Science at Prosus GroupHost:Demetrios Brinkmann - Founder of MLOps Community~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExploreJoin our Slack community [https://go.mlops.community/slack]Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)] Sign up for the next meetup: [https://go.mlops.community/register]MLOps Swag/Merch: [https://shop.mlops.community/]

Durga Suresh-Menon, PhD - Head of School: New England Innovation Academy. This is episode 776 of Teaching Learning Leading, K12, an audio podcast. Durga Suresh-Menon, Ph.D., is Head of School at New England Innovation Academy.  An energizing, dynamic and growth-minded educator with a record of inclusive leadership and passionate storytelling, Dr. Suresh-Menon joins NEIA with over two decades of collaborative higher-education experience, academic program development and a unique understanding of what makes students successful. She has a rich background in higher education, leadership, curriculum development, and academic excellence.  Before joining NEIA, she served as Dean of the School of Computing and Data Science and Dean of Graduate Education at Wentworth Institute of Technology, as well as an Associate Professor, where she led efforts to implement progressive learning strategies and interdisciplinary curriculum that promoted innovation and global awareness.  She is recognized for her work fostering a culture of growth, development and innovation, ensuring that a STEAM curriculum remains aligned with the ever-evolving technological landscape and industry demands.  Fluent in multiple languages, Dr. Suresh-Menon loves to connect with tech-minded students and parents from all backgrounds and brings a global perspective and collaborative spirit to NEIA's academic community. What an awesome conversation! So much to think about! Thanks for listening! Thanks for sharing! Before you go... You could help support this podcast by Buying Me A Coffee. Not really buying me something to drink but clicking on the link on my home page at https://stevenmiletto.com for Buy Me a Coffee or by going to this link Buy Me a Coffee. This would allow you to donate to help the show address the costs associated with producing the podcast from upgrading gear to the fees associated with producing the show. That would be cool. Thanks for thinking about it.  Hey, I've got another favor...could you share the podcast with one of your friends, colleagues, and family members? Hmmm? What do you think? Thank you! You are AWESOME! Connect and Learn More: https://neiacademy.org/ durga.suresh-menon@neiacademy.org https://www.instagram.com/hello.neia/?hl=en https://www.linkedin.com/in/durga-suresh-menon/ Length - 37:41

What happens when precarious urban cultural laborers take data collection, laws, and policymaking into their own hands? Buskers have been part of our cities for hundreds of years, but they remain invisible to governments and in datasets. From nuisance to public art, this cultural practice can help us understand the politics of data collection, archives, regulatory frameworks, and urban planning. Busking also responds to underlying questions on the boundaries of the rights to the city, and who has a voice in shaping how our cities are planned and governed.A transnational exploration of street performance, Urban Music Governance examines the intricate limits of legality, data visibility, and resistance from the perspective of those working at the social and regulatory margins of society. Based on a decade of fieldwork in Rio de Janeiro and Montreal, this book offers a lively account of why such an often-overlooked practice matters today.By investigating the role of busking in contemporary society, Urban Music Governance presents an original interdisciplinary study that exposes how power dynamics in policymaking decide issues of access—and exclusion—around us, above and below ground. Jess Reia is an Assistant Professor of Data Science at the University of Virginia, USA, working on data justice, technology policy, and urban governance. Alex Hallbom is a Registered Professional Planner in British Columbia, Canada. He sits on the editorial board of Plan Canada, the professional publication for planners in Canada. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/new-books-network

Topics covered in this episode: * Open Source Security work isn't “Special”* * uv v0.8* * Extra, Extra, Extra* Announcing Toad - a universal UI for agentic coding in the terminal 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: Open Source Security work isn't “Special” Seth Larson It seems like security is special in a sense that we don't want just anyone working on the security aspect of a project. We just want the trusted maintainers, right? Seth is arguing that this is the wrong mindset It makes more sense that we maybe have security experts contribute to many projects, and that someone working on security for just one project doesn't benefit from scale. “Maintainers don't see how other projects are triaging vulnerabilities and can't learn from each other. They can't compare notes on what they are seeing and whether they are doing the right thing. Isolation in security work breeds a culture of fear. Fear of doing the wrong thing and making your users unsafe.” “These “security contributors” could be maintainers or contributors of other open source projects that know about security, they could be foundations offering up resources to their ecosystem, or engineers at companies helping their dependency graph.” But how do we build trust in these individuals? Meeting in person works. But there are other ways as well. I'd personally love to have someone contact me about a project of mine regarding a security problem or process that the project could/should follow. Especially if I could see other projects I trust already trusting this individual to work on the other projects. Michael #2: uv v0.8 Changes Install Python executables into a directory on the PATH Register Python versions with the Windows Registry Prompt before removing an existing directory in uv venv Bump --python-platform linux to manylinux_2_28 Make uv_build the default build backend in uv init And many more And uv v0.8.1 Lots of enhancements. And uv v0.8.2 And uv v0.8.3 Adds Add CPython 3.14.0rc1 Brian #3: Extra, Extra, Extra fstrings.wtf - Armin Ronacher Python 3.14 release candidate 1 is go! Django turns 20, with parties mkdocs-redirects I'm Tired of Talking About AI - Paddy Carver Michael #4: Announcing Toad - a universal UI for agentic coding in the terminal by Will McGugan A universal front-end for AI in the terminal. Watch the video. Joke: Heaviest objects in the universe And … Cloud Architects 2025 “They send us our cloud bills in scientific notation… “

In this episode of the Real Estate Pro Show, host Erika interviews Adam Eldibany founder of Home Builder, who shares his journey from data science to real estate financing. Adam discusses the evolution of his company, the challenges of data quality in real estate, and the importance of relationships in the industry. He also shares success stories from clients and offers advice for new investors, emphasizing the impact of technology on the future of real estate financing. Professional Real Estate Investors - How we can help you: Investor Fuel Mastermind:  Learn more about the Investor Fuel Mastermind, including 100% deal financing, massive discounts from vendors and sponsors you're already using, our world class community of over 150 members, and SO much more here: http://www.investorfuel.com/apply   Investor Machine Marketing Partnership:  Are you looking for consistent, high quality lead generation? Investor Machine is America's #1 lead generation service professional investors. Investor Machine provides true ‘white glove' support to help you build the perfect marketing plan, then we'll execute it for you…talking and working together on an ongoing basis to help you hit YOUR goals! Learn more here: http://www.investormachine.com   Coaching with Mike Hambright:  Interested in 1 on 1 coaching with Mike Hambright? Mike coaches entrepreneurs looking to level up, build coaching or service based businesses (Mike runs multiple 7 and 8 figure a year businesses), building a coaching program and more. Learn more here: https://investorfuel.com/coachingwithmike   Attend a Vacation/Mastermind Retreat with Mike Hambright: Interested in joining a “mini-mastermind” with Mike and his private clients on an upcoming “Retreat”, either at locations like Cabo San Lucas, Napa, Park City ski trip, Yellowstone, or even at Mike's East Texas “Big H Ranch”? Learn more here: http://www.investorfuel.com/retreat   Property Insurance: Join the largest and most investor friendly property insurance provider in 2 minutes. Free to join, and insure all your flips and rentals within minutes! There is NO easier insurance provider on the planet (turn insurance on or off in 1 minute without talking to anyone!), and there's no 15-30% agent mark up through this platform!  Register here: https://myinvestorinsurance.com/   New Real Estate Investors - How we can work together: Investor Fuel Club (Coaching and Deal Partner Community): Looking to kickstart your real estate investing career? Join our one of a kind Coaching Community, Investor Fuel Club, where you'll get trained by some of the best real estate investors in America, and partner with them on deals! You don't need $ for deals…we'll partner with you and hold your hand along the way! Learn More here: http://www.investorfuel.com/club   —--------------------

Every year the core developers of Python convene in person to focus on high priority topics for CPython and beyond. This year they met at PyCon US 2025. Those meetings are closed door to keep focused and productive. But we're lucky that Seth Michael Larson was in attendance and wrote up each topic presented and the reactions and feedback to each. We'll be exploring this year's Language Summit with Seth. It's quite insightful to where Python is going and the pressing matters. Episode sponsors Seer: AI Debugging, Code TALKPYTHON Sentry AI Monitoring, Code TALKPYTHON Talk Python Courses Links from the show Seth on Mastodon: @sethmlarson@fosstodon.org Seth on Twitter: @sethmlarson Seth on Github: github.com Python Language Summit 2025: pyfound.blogspot.com WheelNext: wheelnext.dev Free-Threaded Wheels: hugovk.github.io Free-Threaded Python Compatibility Tracking: py-free-threading.github.io PEP 779: Criteria for supported status for free-threaded Python: discuss.python.org PyPI Data: py-code.org Senior Engineer tries Vibe Coding: youtube.com Watch this episode on YouTube: youtube.com Episode #514 deep-dive: talkpython.fm/514 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