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Today's clip is from episode 138 of the podcast, with Mélodie Monod, François-Xavier Briol and Yingzhen Li.During this live show at Imperial College London, Alex and his guests delve into the complexities and advancements in Bayesian deep learning, focusing on uncertainty quantification, the integration of machine learning tools, and the challenges faced in simulation-based inference.The speakers discuss their current projects, the evolution of Bayesian models, and the need for better computational tools in the field.Get the full discussion here.Attend Alex's tutorial at PyData Berlin: A Beginner's Guide to State Space Modeling Intro to Bayes Course (first 2 lessons free)Advanced Regression Course (first 2 lessons free)Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work!Visit our Patreon page to unlock exclusive Bayesian swag ;)TranscriptThis is an automatic transcript and may therefore contain errors. Please get in touch if you're willing to correct them.
Allegra Guinan of Lumiera helps leaders turn uncertainty about AI into confident, strategic leadership. In this conversation, she brings some actionable insights for navigating the hype and complexity of AI. The discussion covers challenges with implementing responsible AI practices, the growing importance of user experience and product thinking, and how leaders can focus on real-world business problems over abstract experimentation.Featuring:Allegra Guinan – LinkedInChris Benson – Website, LinkedIn, Bluesky, GitHub, XDaniel Whitenack – Website, GitHub, XLinks:LumieraSponsors:Shopify – The commerce platform trusted by millions. From idea to checkout, Shopify gives you everything you need to launch and scale your business—no matter your level of experience. Build beautiful storefronts, market with built-in AI tools, and tap into the platform powering 10% of all U.S. eCommerce. Start your one-dollar trial at shopify.com/practicalaiRegister for upcoming webinars here!
Au programme :Alexandre nous parle de la manière dont la tech et l'IA a fait évoluer son métier de radiologue depuis presque 20 ans.Infos :Animé par Patrick Beja (Bluesky, Instagram, Twitter, TikTok)Co-animé par AlexandreProduit par Patrick Beja (LinkedIn) et Fanny Cohen Moreau (LinkedIn).Musique libre de droit par Daniel BejaLe Rendez-vous Tech épisode 628 – Spécial : Tech et IA dans l'imagerie médicale---Liens :
Dan sits down with guests Mark Daniel Ward and Katie Sanders from The Data Mine at Purdue University to explore how higher education is evolving to meet the demands of the AI-driven workforce. They share how their program blends interdisciplinary learning, corporate partnerships, and real-world data science projects to better prepare students across 160+ majors. From AI chatbots to agricultural forecasting, they discuss the power of living-learning communities, how the data mine model is spreading to other institutions and what it reveals about the future of education, workforce development, and applied AI training.Featuring:Mark Daniel Ward – LinkedInKatie Sanders – LinkedInDaniel Whitenack – Website, GitHub, XLinks:The Data MineSponsors:Shopify – The commerce platform trusted by millions. From idea to checkout, Shopify gives you everything you need to launch and scale your business—no matter your level of experience. Build beautiful storefronts, market with built-in AI tools, and tap into the platform powering 10% of all U.S. eCommerce. Start your one-dollar trial at shopify.com/practicalaiRegister for upcoming webinars here!
On this episode, host Paul W. Grimm speaks with Professor Maura R. Grossman about the fundamentals of artificial intelligence and its growing influence on the legal system. They explore what AI is (and isn't), how machine learning and natural language processing work, and the differences between traditional automation and modern generative AI. In layman's terms, they discuss other key concepts, such as supervised and unsupervised learning, reinforcement training, and deepfakes, and other advances that have accelerated AI's development. Finally, they address a few potential risks of generative AI, including hallucinations, bias, and misuse in court, which sets the stage for a deeper conversation about legal implications on the next episode, "To Trust or Not to Trust: AI in Legal Practice." ABOUT THE HOSTJudge Paul W. Grimm (ret.) is the David F. Levi Professor of the Practice of Law and Director of the Bolch Judicial Institute at Duke Law School. From December 2012 until his retirement in December 2022, he served as a district judge of the United States District Court for the District of Maryland, with chambers in Greenbelt, Maryland. Click here to read his full bio.
Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!Intro to Bayes Course (first 2 lessons free)Advanced Regression Course (first 2 lessons free)Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work!Visit our Patreon page to unlock exclusive Bayesian swag ;)Takeaways:Bayesian deep learning is a growing field with many challenges.Current research focuses on applying Bayesian methods to neural networks.Diffusion methods are emerging as a new approach for uncertainty quantification.The integration of machine learning tools into Bayesian models is a key area of research.The complexity of Bayesian neural networks poses significant computational challenges.Future research will focus on improving methods for uncertainty quantification. Generalized Bayesian inference offers a more robust approach to uncertainty.Uncertainty quantification is crucial in fields like medicine and epidemiology.Detecting out-of-distribution examples is essential for model reliability.Exploration-exploitation trade-off is vital in reinforcement learning.Marginal likelihood can be misleading for model selection.The integration of Bayesian methods in LLMs presents unique challenges.Chapters:00:00 Introduction to Bayesian Deep Learning03:12 Panelist Introductions and Backgrounds10:37 Current Research and Challenges in Bayesian Deep Learning18:04 Contrasting Approaches: Bayesian vs. Machine Learning26:09 Tools and Techniques for Bayesian Deep Learning31:18 Innovative Methods in Uncertainty Quantification36:23 Generalized Bayesian Inference and Its Implications41:38 Robust Bayesian Inference and Gaussian Processes44:24 Software Development in Bayesian Statistics46:51 Understanding Uncertainty in Language Models50:03 Hallucinations in Language Models53:48 Bayesian Neural Networks vs Traditional Neural Networks58:00 Challenges with Likelihood Assumptions01:01:22 Practical Applications of Uncertainty Quantification01:04:33 Meta Decision-Making with Uncertainty01:06:50 Exploring Bayesian Priors in Neural Networks01:09:17 Model Complexity and Data Signal01:12:10 Marginal Likelihood and Model Selection01:15:03 Implementing Bayesian Methods in LLMs01:19:21 Out-of-Distribution Detection in LLMsThank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor,, Chad Scherrer,...
Neste episódio brutalmente honesto, Ana Zucato compartilha a jornada da Noh, de um app genérico de divisão de contas que quebrou, até se tornar uma conta digital para casais que hoje cresce no boca a boca. Ana detalha como reposicionou o produto, o que realmente é Product-Market Fit (spoiler: não é uma sensação) e por que NPS é uma métrica superestimada.Discutimos:
Многие знают, что когда модели обучаются, где-то под капотом перемножаются матрицы и тензоры, и все это связано с дифференцированием. Мы с Денисом Степановым взялись за нелегкую задачу – разобраться, что же именно там происходит! Также ждем вас, ваши лайки, репосты и комменты в мессенджерах и соцсетях! Telegram-чат: https://t.me/podlodka Telegram-канал: https://t.me/podlodkanews Страница в Facebook: www.facebook.com/podlodkacast/ Twitter-аккаунт: https://twitter.com/PodcastPodlodka Ведущие в выпуске: Женя Кателла, Аня Симонова Полезные ссылки: Dive into Deep Learning Aston Zhang, Zachary C. Lipton, Mu Li, Alexander J. Smola (online book with code and formulas) https://d2l.ai/ https://www.amazon.com/s/ref=dp_byline_sr_book_2?ie=UTF8&field-author=Zachary+C.+Lipton&text=Zachary+C.+Lipton&sort=relevancerank&search-alias=books Micrograd by Andrej Karpathy https://github.com/karpathy/micrograd Andrej Karpathy builds GPT from scratch https://www.youtube.com/watch?v=kCc8FmEb1nY Scott Aaronson on LLM Watermarking https://www.youtube.com/watch?v=YzuVet3YkkA Annotated history of Modern AI and Deep Learning by Jurgen Schmidhuber https://people.idsia.ch/~juergen/deep-learning-history.html Probabilistic Machine Learning: An Introduction Kevin Patrick Murphy https://probml.github.io/pml-book/book1.html Probabilistic Machine Learning: Advanced Topics Kevin Patrick Murphy https://probml.github.io/pml-book/book2.html Pattern Recognition and Machine Learning Christopher Bishop https://www.microsoft.com/en-us/research/wp-content/uploads/2006/01/Bishop-Pattern-Recognition-and-Machine-Learning-2006.pdf Deep Learning: Foundations and Concepts Christopher Bishop, Hugh Bishop https://www.bishopbook.com/ Deep Learning Ian Goodfellow, Yoshua Bengio, Aaron Courville https://www.deeplearningbook.org/ Глубокое обучение: Погружение в мир нейронных сетей С. Николенко, А. Кадурин, Е. Архангельская https://www.k0d.cc/storage/books/AI,%20Neural%20Networks/%D0%93%D0%BB%D1%83%D0%B1%D0%BE%D0%BA%D0%BE%D0%B5%20%D0%BE%D0%B1%D1%83%D1%87%D0%B5%D0%BD%D0%B8%D0%B5%20(%D0%9D%D0%B8%D0%BA%D0%BE%D0%BB%D0%B5%D0%BD%D0%BA%D0%BE).pdf Gonzo-обзоры ML статей Григорий Сапунов, Алексей Тихонов https://t.me/gonzo_ML Machine Learning Street Talk podcast https://www.youtube.com/c/machinelearningstreettalk Feedforward NNs, Autograd, Backprop (Datalore report, Denis Stepanov) https://datalore.jetbrains.com/report/static/Ht_isxs4iB2.BNIqv-C3WUp/pEpNv2eMVU9tEkPsaboR9y Softmax Regression, Adversarial Attacks (Datalore report, Denis Stepanov) https://datalore.jetbrains.com/report/static/Ht_isxs4iB2.BNIqv-C3WUp/cIvd6zX1B5I3kULNiVCEyy Dual Numbers, PINN (Datalore report, Denis Stepanov) https://datalore.jetbrains.com/report/static/Ht_isxs4iB2.BNIqv-C3WUp/3oa1BNrPGpQ8uc82tCaz5d
Au programme :Dans cet épisode hors-série je vous propose une plongée dans les archives du RDV Tech on va remonter en octobre 2011 au moment de la mort de Steve Jobs. On en parlait dans le RDV Tech 71 avec au micro Guillaume Main, Olivier Frigara et Cédric Ingrand, une longue discussion de 45 minutes très intéressante, vous verrez que la qualité de certains invités n'est pas optimale mais c'est largement écoutable. Infos :Animé par Patrick Beja (Bluesky, Instagram, Twitter, TikTok)Produit par Patrick Beja (LinkedIn) et Fanny Cohen Moreau (LinkedIn).Musique libre de droit par Daniel Beja---Liens :
In this episode, hosts Lois Houston and Nikita Abraham, together with Senior Cloud Engineer Nick Commisso, break down the basics of artificial intelligence (AI). They discuss the differences between Artificial General Intelligence (AGI) and Artificial Narrow Intelligence (ANI), and explore the concepts of machine learning, deep learning, and generative AI. Nick also shares examples of how AI is used in everyday life, from navigation apps to spam filters, and explains how AI can help businesses cut costs and boost revenue. AI for You: https://mylearn.oracle.com/ou/course/ai-for-you/152601/252500 Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu Special thanks to Arijit Ghosh, David Wright, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode. ----------------------------------------------------------- Episode Transcript: 00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we'll bring you foundational training on the most popular Oracle technologies. Let's get started! 00:25 Nikita: Hello and welcome to the Oracle University Podcast. I'm Nikita Abraham, Team Lead of Editorial Services with Oracle University, and with me is Lois Houston, Director of Innovation Programs. Lois: Hi everyone! Welcome to a new season of the podcast. I'm so excited about this one because we're going to dive into the world of artificial intelligence, speaking to many experts in the field. Nikita: If you've been listening to us for a while, you probably know we've covered AI from a bunch of different angles. But this time, we're dialing it all the way back to basics. We wanted to create something for the absolute beginner, so no jargon, no assumptions, just simple conversations that anyone can follow. 01:08 Lois: That's right, Niki. You don't need to have a technical background or prior experience with AI to get the most out of these episodes. In our upcoming conversations, we'll break down the basics of AI, explore how it's shaping the world around us, and understand its impact on your business. Nikita: The idea is to give you a practical understanding of AI that you can use in your work, especially if you're in sales, marketing, operations, HR, or even customer service. 01:37 Lois: Today, we'll talk about the basics of AI with Senior Cloud Engineer Nick Commisso. Hi Nick! Welcome back to the podcast. Can you tell us about human intelligence and how it relates to artificial intelligence? And within AI, I know we have Artificial General Intelligence, or AGI, and Artificial Narrow Intelligence, or ANI. What's the difference between the two? Nick: Human intelligence is the intellectual capability of humans that allow us to learn new skills through observation and mental digestion, to think through and understand abstract concepts and apply reasoning, to communicate using language and understand non-verbal cues, such as facial expressions, tone variation, body language. We can handle objections and situations in real time, even in a complex setting. We can plan for short and long-term situations or projects. And we can create music, art, or invent something new or have original ideas. If machines can replicate a wide range of human cognitive abilities, such as learning, reasoning, or problem solving, we call it artificial general intelligence. Now, AGI is hypothetical for now, but when we apply AI to solve problems with specific, narrow objectives, we call it artificial narrow intelligence, or ANI. AGI is a hypothetical AI that thinks like a human. It represents the ultimate goal of artificial intelligence, which is a system capable of chatting, learning, and even arguing like us. If AGI existed, it would take the form like a robot doctor that accurately diagnoses and comforts patients, or an AI teacher that customizes lessons in real time based on each student's mood, pace, and learning style, or an AI therapist that comprehends complex emotions and provides empathetic, personalized support. ANI, on the other hand, focuses on doing one thing really well. It's designed to perform specific tasks by recognizing patterns and following rules, but it doesn't truly understand or think beyond its narrow scope. Think of ANI as a specialist. Your phone's face ID can recognize you instantly, but it can't carry on a conversation. Google Maps finds the best route, but it can't write you a poem. And spam filters catch junk mail, but it can't make you coffee. So, most of the AI you interact with today is ANI. It's smart, efficient, and practical, but limited to specific functions without general reasoning or creativity. 04:22 Nikita: Ok then what about Generative AI? Nick: Generative AI is a type of AI that can produce content such as audio, text, code, video, and images. ChatGPT can write essays, but it can't fact check itself. DALL-E creates art, but it doesn't actually know if it's good. Or AI song covers can create deepfakes like Drake singing "Baby Shark." 04:47 Lois: Why should I care about AI? Why is it important? Nick: AI is already part of your everyday life, often working quietly in the background. ANI powers things like navigation apps, voice assistants, and spam filters. Generative AI helps create everything from custom playlists to smart writing tools. And while AGI isn't here yet, it's shaping ideas about what the future might look like. Now, AI is not just a buzzword, it's a tool that's changing how we live, work, and interact with the world. So, whether you're using it or learning about it or just curious, it's worth knowing what's behind the tech that's becoming part of everyday life. 05:32 Lois: Nick, whenever people talk about AI, they also throw around terms like machine learning and deep learning. What are they and how do they relate to AI? Nick: As we shared earlier, AI is the ability of machines to imitate human intelligence. And Machine Learning, or ML, is a subset of AI where the algorithms are used to learn from past data and predict outcomes on new data or to identify trends from the past. Deep Learning, or DL, is a subset of machine learning that uses neural networks to learn patterns from complex data and make predictions or classifications. And Generative AI, or GenAI, on the other hand, is a specific application of DL focused on creating new content, such as text, images, and audio, by learning the underlying structure of the training data. 06:24 Nikita: AI is often associated with key domains like language, speech, and vision, right? So, could you walk us through some of the specific tasks or applications within each of these areas? Nick: Language-related AI tasks can be text related or generative AI. Text-related AI tasks use text as input, and the output can vary depending on the task. Some examples include detecting language, extracting entities in a text, extracting key phrases, and so on. 06:54 Lois: Ok, I get you. That's like translating text, where you can use a text translation tool, type your text in the box, choose your source and target language, and then click Translate. That would be an example of a text-related AI task. What about generative AI language tasks? Nick: These are generative, which means the output text is generated by the model. Some examples are creating text, like stories or poems, summarizing texts, and answering questions, and so on. 07:25 Nikita: What about speech and vision? Nick: Speech-related AI tasks can be audio related or generative AI. Speech-related AI tasks use audio or speech as input, and the output can vary depending on the task. For example, speech to text conversion, speaker recognition, or voice conversion, and so on. Generative AI tasks are generative, i.e., the output audio is generated by the model (for example, music composition or speech synthesis). Vision-related AI tasks can be image related or generative AI. Image-related AI tasks use an image as the input, and the output depends on the task. Some examples are classifying images or identifying objects in an image. Facial recognition is one of the most popular image-related tasks that's often used for surveillance and tracking people in real time. It's used in a lot of different fields, like security and biometrics, law enforcement, entertainment, and social media. For generative AI tasks, the output image is generated by the model. For example, creating an image from a textual description or generating images of specific style or high resolution, and so on. It can create extremely realistic new images and videos by generating original 3D models of objects, such as machine, buildings, medications, people and landscapes, and so much more. 08:58 Lois: This is so fascinating. So, now we know what AI is capable of. But Nick, what is AI good at? Nick: AI frees you to focus on creativity and more challenging parts of your work. Now, AI isn't magic. It's just very good at certain tasks. It handles work that's repetitive, time consuming, or too complex for humans, like processing data or spotting patterns in large data sets. AI can take over routine tasks that are essential but monotonous. Examples include entering data into spreadsheets, processing invoices, or even scheduling meetings, freeing up time for more meaningful work. AI can support professionals by extending their abilities. Now, this includes tools like AI-assisted coding for developers, real-time language translation for travelers or global teams, and advanced image analysis to help doctors interpret medical scans much more accurately. 10:00 Nikita: And what would you say is AI's sweet spot? Nick: That would be tasks that are both doable and valuable. A few examples of tasks that are feasible technically and have business value are things like predicting equipment failure. This saves downtime and the loss of business. Call center automation, like the routing of calls to the right person. This saves time and improves customer satisfaction. Document summarization and review. This helps save time for busy professionals. Or inspecting power lines. Now, this task is dangerous. By automating it, it protects human life and saves time. 10:48 Oracle University's Race to Certification 2025 is your ticket to free training and certification in today's hottest tech. Whether you're starting with Artificial Intelligence, Oracle Cloud Infrastructure, Multicloud, or Oracle Data Platform, this challenge covers it all! Learn more about your chance to win prizes and see your name on the Leaderboard by visiting education.oracle.com/race-to-certification-2025. That's education.oracle.com/race-to-certification-2025. 11:30 Nikita: Welcome back! Now one big way AI is helping businesses today is by cutting costs, right? Can you give us some examples of this? Nick: Now, AI can contribute to cost reduction in several key areas. For instance, chatbots are capable of managing up to 50% of customer queries. This significantly reduces the need for manual support, thereby lowering operational costs. AI can streamline workflows, for example, reducing invoice processing time from 10 days to just 1 hour. This leads to substantial savings in both time and resources. In addition to cost savings, AI can also support revenue growth. One way is enabling personalization and upselling. Platforms like Netflix use AI-driven recommendation systems to influence user choices. This not only enhances the user experience, but it also increases the engagement and the subscription revenue. Or unlocking new revenue streams. AI technologies, such as generative video tools and virtual influencers, are creating entirely new avenues for advertising and branded content, expanding business opportunities in emerging markets. 12:50 Lois: Wow, saving money and boosting bottom lines. That's a real win! But Nick, how is AI able to do this? Nick: Now, data is what teaches AI. Just like we learn from experience, so does AI. It learns from good examples, bad examples, and sometimes even the absence of examples. The quality and variety of data shape how smart, accurate, and useful AI becomes. Imagine teaching a kid to recognize animals using only pictures of squirrels that are labeled dogs. That would be very confusing at the dog park. AI works the exact same way, where bad data leads to bad decisions. With the right data, AI can be powerful and accurate. But with poor or biased data, it can become unreliable and even misleading. AI amplifies whatever you feed it. So, give it gourmet data, not data junk food. AI is like a chef. It needs the right ingredients. It needs numbers for predictions, like will this product sell? It needs images for cool tricks like detecting tumors, and text for chatting, or generating excuses for why you'd be late. Variety keeps AI from being a one-trick pony. Examples of the types of data are numbers, or machine learning, for predicting things like the weather. Text or generative AI, where chatbots are used for writing emails or bad poetry. Images, or deep learning, can be used for identifying defective parts in an assembly line, or an audio data type to transcribe a dictation from a doctor to a text. 14:35 Lois: With so much data available, things can get pretty confusing, which is why we have the concept of labeled and unlabeled data. Can you help us understand what that is? Nick: Labeled data are like flashcards, where everything has an answer. Spam filters learned from emails that are already marked as junk, and X-rays are marked either normal or pneumonia. Let's say we're training AI to tell cats from dogs, and we show it a hundred labeled pictures. Cat, dog, cat, dog, etc. Over time, it learns, hmm fluffy and pointy ears? That's probably a cat. And then we test it with new pictures to verify. Unlabeled data is like a mystery box, where AI has to figure it out itself. Social media posts, or product reviews, have no labels. So, AI clusters them by similarity. AI finding trends in unlabeled data is like a kid sorting through LEGOs without instructions. No one tells them which blocks will go together. 15:36 Nikita: With all the data that's being used to train AI, I'm sure there are issues that can crop up too. What are some common problems, Nick? Nick: AI's performance depends heavily on the quality of its data. Poor or biased data leads to unreliable and unfair outcomes. Dirty data includes errors like typos, missing values, or duplicates. For example, an age record as 250, or NA, can confuse the AI. And a variety of data cleaning techniques are available, like missing data can be filled in, or duplicates can be removed. AI can inherit human prejudices if the data is unbalanced. For example, a hiring AI may favor one gender if the past three hires were mostly male. Ensuring diverse and representative data helps promote fairness. Good data is required to train better AI. Data could be messy, and needs to be processed before to train AI. 16:39 Nikita: Thank you, Nick, for sharing your expertise with us. To learn more about AI, go to mylearn.oracle.com and search for the AI for You course. As you complete the course, you'll find skill checks that you can attempt to solidify your learning. Lois: In our next episode, we'll dive deep into fundamental AI concepts and terminologies. Until then, this is Lois Houston… Nikita: And Nikita Abraham signing off! 17:05 That's all for this episode of the Oracle University Podcast. If you enjoyed listening, please click Subscribe to get all the latest episodes. We'd also love it if you would take a moment to rate and review us on your podcast app. See you again on the next episode of the Oracle University Podcast.
We unpack how AI is reshaping hiring decisions, shifting job roles, and creating new expectations for professionals — from engineers to marketers. They explore the rise of AI-assisted teams, the growing compensation bubble, why continuous learning is now table stakes, and how some service providers are quietly riding the AI wave.Featuring:Chris Benson – Website, LinkedIn, Bluesky, GitHub, XDaniel Whitenack – Website, GitHub, XSponsors:Outshift by Cisco: AGNTCY is an open source collective building the Internet of Agents. It's a collaboration layer where AI agents can communicate, discover each other, and work across frameworks. For developers, this means standardized agent discovery tools, seamless protocols for inter-agent communication, and modular components to compose and scale multi-agent workflows."Register for upcoming webinars here!
Au programme :OpenAI, Perplexity et même Proton : ils profitent de l'été pour continuer à lancer toujours plus de solutions par intelligence artificielleVibe coding et no code : des possibilités toujours plus grandes de faire du développer sans saisir de ligne de code… pour toujours plus de risques ?Réflexion de l'été : les smartphones sont-ils de parasites ?Infos :Animé par Guillaume Vendé (Bluesky, Mastodon, Threads, Instagram, TikTok, YouTube, techcafe.fr)Co-animé par Benoît Curdy (X, Niptech)Co-animé par Baptiste Freydt (X, Niptech)Produit par Patrick Beja (LinkedIn) et Fanny Cohen Moreau (LinkedIn).Musique libre de droit par Daniel BejaLe Rendez-vous Tech épisode 627 – Les agents IA ne prennent pas de vacances---Liens :
Unser heutiger Gast wurde in Dresden geboren, studierte Computerlinguistik in Leipzig und Saarbrücken und promovierte später an der Stanford University – betreut von keinem Geringeren als Andrew Ng und Chris Manning. Seine Dissertation wurde als beste Informatik-Promotion ausgezeichnet. Nach Stationen bei Microsoft und Siemens gründete er sein erstes Unternehmen: MetaMind, ein Deep-Learning-Startup, das 2016 von Salesforce übernommen wurde. Dort war er anschließend Chief Scientist, leitete große Forschungsteams und trieb die KI-Strategie des Konzerns maßgeblich voran. Heute ist er Gründer und CEO von you.com, einer KI-basierten Suchmaschine, die als datenschutzfreundliche, transparente und anpassbare Alternative zu klassischen Anbietern auftritt, mit einem starken Fokus auf Nutzendenkontrolle und verantwortungsvoller KI. Zudem investiert er über seinen Fonds AI+X in KI-Startups weltweit. Seine wissenschaftlichen Arbeiten zählen zu den meistzitierten im Bereich NLP und Deep Learning, über 170.000 Mal, und viele seiner Ideen haben die Entwicklung heutiger Sprachmodelle mitgeprägt. Ein herzliches Dankeschön an Adrian Locher, CEO und Gründer von Merantix, für die Vermittlung dieses Gesprächs. Seit über acht Jahren beschäftigen wir uns in diesem Podcast mit der Frage, wie Arbeit den Menschen stärkt, statt ihn zu schwächen. In 500 Gesprächen mit über 600 Menschen haben wir darüber gesprochen, was sich für sie geändert hat, und was sich noch ändern muss. Wie können wir verhindern, dass KI-Systeme nur effizienter, aber nicht gerechter werden und worauf kommt es bei der Gestaltung wirklich an? Welche Rolle spielt Transparenz, wenn es um Vertrauen in KI geht, besonders in sensiblen Anwendungen wie Suche, Bildung oder Arbeit? Und was braucht es, um KI so zu entwickeln, dass sie unsere Fähigkeiten erweitert, statt sie zu ersetzen? Fest steht: Für die Lösung unserer aktuellen Herausforderungen brauchen wir neue Impulse. Daher suchen wir weiter nach Methoden, Vorbildern, Erfahrungen, Tools und Ideen, die uns dem Kern von New Work näherbringen. Darüber hinaus beschäftigt uns von Anfang an die Frage, ob wirklich alle Menschen das finden und leben können, was sie im Innersten wirklich, wirklich wollen. Ihr seid bei On the Way to New Work – heute mit Richard Socher. [Hier](https://linktr.ee/onthewaytonewwork) findet ihr alle Links zum Podcast und unseren aktuellen Werbepartnern
Neste episódio do Product Guru's, Paulo Chiodi conversa com Iago Maciel, especialista em produto com passagens por Ambev e experiências atuais no Vale do Silício. Iago compartilha sua jornada de reinvenção profissional, onde mergulhou no ecossistema de IA em São Francisco para entender como a inteligência artificial está moldando o futuro dos produtos digitais.A conversa aborda temas como segurança em produtos de IA, mudanças de mentalidade na gestão de produtos, o papel controverso do “Product Builder”, estratégias para integração de times técnicos e jurídicos, e como os PMs podem se tornar mais estratégicos. Iago também compartilha ferramentas práticas, como o uso de dados sintéticos, evaluations e o uso do Manus para pesquisas complexas. Um episódio indispensável para quem quer liderar na nova era da tecnologia.// Onde encontrar o convidado: Iago Macielhttps://www.linkedin.com/in/iagomsouza/// Recado Importante: O futuro dos produtos digitais já começou e a Inteligência Artificial é parte do time.A PM3 acaba de lançar a Formação em Gestão de Produtos de IA: um curso pensado para Product Managers que querem criar, delegar e inovar com mais inteligência. Muito além dos prompts: você vai aprender a liderar produtos baseados em IA, dominar temas como Machine Learning, Deep Learning e IA Generativa, e aplicar novas formas de discovery, experimentação e validação.Prepare-se para o mercado que mais cresce no mundo e torne-se o PM que lidera a transformação.Acesse o link e saiba mais: https://go.pm3.com.br/ProductGurus-AI-Specialist/// Outros parceiros:Codando sem Codar - A maior comunidade de AI (Vibe) Coding do Brasilhttps://codandosemcodar.com.br/?utm_campaign=pg_podcastCurling - Do treinamento à criação de soluções com IA, estamos em cada etapa. https://www.usecurling.com/// Nesse episódio abordamos: A segurança em IA precisa ser discutida desde a concepção do produto. PMs devem parar de delegar completamente dados e segurança aos times técnicos. Produtos com IA demandam novas formas de validação, como evaluations. Dados sintéticos ajudam no treino de modelos mesmo sem base real. Prompt injection é uma ameaça real para produtos com IA. O PM moderno precisa entender do modelo de negócio e do P&L. A função “Product Builder” é mais buzzword do que papel real no Brasil. A IA está democratizando o desenvolvimento de produtos, mas exige direção. O uso de ferramentas como Manus acelera pesquisas e benchmarking. PMs devem liderar a estratégia de adoção de IA nas empresas, não só seguir tendências./// Capítulos00:00 Abertura01:30 Sabático no Vale: por que largar tudo e estudar IA02:36 Eventos e aprendizado com o ecossistema de startups03:49 O hype dos engenheiros de IA e o mercado atual05:41 Segurança em IA: por que ninguém fala sobre isso08:07 Mentalidade de produto na era da IA10:40 Casos de uso, riscos e prompt injection13:04 Estratégias de dados e feedback loops em IA14:48 O risco real de modelos de IA mal treinados17:21 Casos jurídicos e discriminação por IA nos EUA18:31 A polêmica do Product Builder22:55 Diferença entre maturidade de PMs no Brasil e EUA27:42 O que o PM precisa desaprender com IA32:20 O “jogo do Tigrinho” das automações e uso consciente36:09 A pandemia e a perda de protagonismo do PM38:32 Como se tornar um PM mais estratégico com IA41:00 Como usar IA como mentor de negócios43:23 A importância da curiosidade como soft skill46:41 Liderança de adoção de IA nas empresas48:01 Como conversar com jurídico, segurança e engenharia52:40 Ferramentas práticas e dicas de prompt55:37 Uso avançado do Manus para pesquisa multistep58:22 Encerramento e links úteis na descrição
In this episode, Chris sits down with Igor Nikitin, CEO and co-founder of Nice Technologies, to explore how AI and modern engineering practices are transforming the actuarial field and setting the stage for the future of actuarial modeling. We discuss the introduction of programming into insurance pricing workflows, and how their Python-based calc engine, AI copilots, and DevOps-inspired workflows are enabling actuaries to collaborate more effectively across teams while accelerating innovation. Featuring:Igor Nikitin – LinkedInChris Benson – Website, LinkedIn, Bluesky, GitHub, XLinks:Nice TechnologiesSponsors:Shopify – The commerce platform trusted by millions. From idea to checkout, Shopify gives you everything you need to launch and scale your business—no matter your level of experience. Build beautiful storefronts, market with built-in AI tools, and tap into the platform powering 10% of all U.S. eCommerce. Start your one-dollar trial at shopify.com/practicalai
Dave, Esmee, and Rob take a moment to look back on the wild ride that was Season 4—revisiting the themes that sparked the biggest conversations and the guests who left a lasting impression. They also reveal what's on their summer to-do lists and drop a few juicy hints about what's coming in Season 5. Get ready—it's going to be even bigger and bolder.Thank you to all our listeners and guests for joining us in Season 4 - have a great summer and we will see you in September!TLDR:00:40 Season 4 by the numbers – and a fun mix-up with round figures03:20 Reflecting on standout topics and memorable guests03:42 Scaling AI: Hyperscaler narratives, tech momentum, and the adoption gap13:18 Ethics in the AI era – how organizations can and must stay grounded18:12 The human factor: Why “human-in-the-loop” matters more than ever27:29 Sovereignty in tech – geopolitics, shifting narratives, and the rise of Sovereign AI37:16 A deep dive into Telco – highlights from our dedicated mini-series53:48 2025 tech trends with Gene Kim55:33 Listener Q&A: Daniel Delicate on Cynefin vs. IT operating models1:01:44 Andrea Kis on keeping humanity in fast-paced tech1:06:09 Ezhil Suresh on how we prep and record our podcast with top-tier guests1:11:38 John Eaton-Griffin on how guests have shaped our thinking1:17:19 A word from our co-host1:19:57 Looking ahead to Season 5: AAA episodes, new industry mini-series, and Hyperscaler events1:22:09 Meet our new AI companions: Substack and the Cloud Realities chatbot1:23:40 What's next for us this summerHostsDave Chapman: https://www.linkedin.com/in/chapmandr/Esmee van de Giessen: https://www.linkedin.com/in/esmeevandegiessen/Rob Kernahan: https://www.linkedin.com/in/rob-kernahan/ProductionMarcel van der Burg: https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman: https://www.linkedin.com/in/chapmandr/SoundBen Corbett: https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett: https://www.linkedin.com/in/louis-corbett-087250264/'Cloud Realities' is an original podcast from Capgemini
Au programme :Cette semaine je vous propose un épisode "crossover" pour découvrir mon autre podcast, le RDV Jeux.C'est l'épisode 370, où on traite de la stratégie de Microsoft / Xbox, de l'équation impossible entre gros jeux gamers et jeux mobiles, et de nos jeux du moment. Enjoy!Plus d'infos : https://frenchspin.fr/2024/10/microsoft-na-quune-solution-rdv-jeux/Infos :Animé par Patrick Beja (Bluesky, Instagram, Twitter, TikTok)Produit par Patrick Beja (LinkedIn) et Fanny Cohen Moreau (LinkedIn).Musique libre de droit par Daniel Beja---Liens :
A startup brasileira Avra criou um modelo fundacional próprio de IA para apoiar clientes do mercado financeiro a analisar e conceder crédito para PMEs. A startup já captou US$ 2 milhões em financiamento de venture capital e foi reconhecida, pela AWS, como uma das três empresas mais inovadoras da América Latina na criação de modelos fundacionais. Viviane Meister, CEO, e Bruno Alano, CTO, ambos cofundadores da Avra, explicam o que fazem e provam que o Brasil pode, sim, competir globalmente no terreno da IA.Links do episódio:O site da AvraA página do LinkedIn de Viviane MeisterA página do LinkedIn de Bruno AlanoPessoa inspiradora: Shivani Siroya, fundadora e CEO da Tala, a startup de microcrédito que entrou para a lista de 2025 das 50 Top Fintechs globais da Forbes.O blog/livro "Neural Networks and DeepLearning", criado por Michael NielsenO livro "The Master Switch: The Rise and Fall of Information Empires", de Tim WuO livro "Visionários", de Steven JohnsonO livro "Inteligência artificial a nosso favor: Como manter o controle sobre a tecnologia", de Stuart Russell A The Shift é uma plataforma de conteúdo que descomplica os contextos da inovação disruptiva e da economia digital.Visite o site www.theshift.info e assine a newsletter
The rise of structure software fueled globalization by streamlining operations across borders. Now, Cloud and AI are accelerating this momentum, enabling faster innovation, smarter decision-making, and scalable growth. By modernizing ERP with intelligent technologies, organizations can stay agile, competitive, and ready for the next wave of global transformation.This week, Dave, Esmee and Rob talk to Timo Elliott, Innovation Evangelist at SAP, to explore how SAP is driving globalization—and how organizations can accelerate innovation through the power of Cloud and AI. TLDR00:55 Introduction of Timo Elliott02:40 Rob shares his confusion about misleading online ads08:06 In-depth conversation with Timo46:32 Rethinking control in enterprise systems1:00:00 Brunch at a Paris café or joining an event?GuestTimo Elliott: https://www.linkedin.com/in/timoelliott/HostsDave Chapman: https://www.linkedin.com/in/chapmandr/Esmee van de Giessen: https://www.linkedin.com/in/esmeevandegiessen/Rob Kernahan: https://www.linkedin.com/in/rob-kernahan/ProductionMarcel van der Burg: https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman: https://www.linkedin.com/in/chapmandr/SoundBen Corbett: https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett: https://www.linkedin.com/in/louis-corbett-087250264/'Cloud Realities' is an original podcast from Capgemini
In this episode of Practical AI, Chris and Daniel explore the fascinating world of agentic AI for drone and robotic swarms, which is Chris's passion and professional focus. They unpack how autonomous vehicles (UxV), drones (UaV), and other autonomous multi-agent systems can collaborate without centralized control while exhibiting complex emergent behavior with agency and self-governance to accomplish a mission or shared goals. Chris and Dan delve into the role of AI real-time inference and edge computing to enable complex agentic multi-model autonomy, especially in challenging environments like disaster zones and remote industrial operations.Featuring:Chris Benson – Website, LinkedIn, Bluesky, GitHub, XDaniel Whitenack – Website, GitHub, XLinks:ROS - Robotic Operating SystemGazeboHugging Face Agents CourseSwarm Robotics | WikipediaChris's definition of Swarming:Swarming occurs when numerous independent fully-autonomous multi-agentic platforms exhibit highly-coordinated locomotive and emergent behaviors with agency and self-governance in any domain (air, ground, sea, undersea, space), functioning as a single independent logical distributed decentralized decisioning entity for purposes of C3 (command, control, communications) with human operators on-the-loop, to implement actions that achieve strategic, tactical, or operational effects in the furtherance of a mission.© 2025 Chris BensonSponsors:Outshift by Cisco: AGNTCY is an open source collective building the Internet of Agents. It's a collaboration layer where AI agents can communicate, discover each other, and work across frameworks. For developers, this means standardized agent discovery tools, seamless protocols for inter-agent communication, and modular components to compose and scale multi-agent workflows.
Au programme :Le parcours de Jeff, de la France et l'informatique aux États-Unis et l'investissementInfos :Animé par Patrick Beja (Bluesky, Instagram, Twitter, TikTok)Co-animé par Jeff ClavierProduit par Patrick Beja (LinkedIn) et Fanny Cohen Moreau (LinkedIn).Musique libre de droit par Daniel BejaLe Rendez-vous Tech épisode626 - Spécial : Portrait de Jeff Clavier---Liens :
Are we on the brink of advertising becoming too smart for its own good, or is Deep Learning finally getting us closer to what customers actually want? Agility requires us to constantly evaluate how technology like AI reshapes the relationships between brands and consumers—sometimes for better, sometimes for far more complex. The advertising landscape is shifting under our feet, with new rules, new tech, and frankly, a lot of new guesswork.Today we're going to talk about how Deep Learning and AI are impacting advertising effectiveness, personalization, and the future of advertising—with or without cookies. To help me discuss this topic, I'd like to welcome Jaysen Gillespie, VP, Global Head of Analytics and Product Marketing at RTB House. About Jaysen Gillespie Jaysen is a Southern California analytics pro with 15+ years in tech leadership. Currently holding the position of VP, Global Head of Product Marketing and Analytics at RTB House, he turns data into insights that drive relevant decisions. He is an experienced speaker and content creator, simplifying complex ideas and making them easily consumable and applicable. For Jaysen, analytics isn't just interesting—it's essential. Resources RTB House: https://www.rtbhouse.com https://www.rtbhouse.com The Agile Brand podcast is brought to you by TEKsystems. Learn more here: https://www.teksystems.com/versionnextnow Catch the future of e-commerce at eTail Boston, August 11-14, 2025. Register now: https://bit.ly/etailboston and use code PARTNER20 for 20% off for retailers and brandsDon't Miss MAICON 2025, October 14-16 in Cleveland - the event bringing together the brights minds and leading voices in AI. Use Code AGILE150 for $150 off registration. Go here to register: https://bit.ly/agile150" Connect with Greg on LinkedIn: https://www.linkedin.com/in/gregkihlstromDon't miss a thing: get the latest episodes, sign up for our newsletter and more: https://www.theagilebrand.showCheck out The Agile Brand Guide website with articles, insights, and Martechipedia, the wiki for marketing technology: https://www.agilebrandguide.com The Agile Brand is produced by Missing Link—a Latina-owned strategy-driven, creatively fueled production co-op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. https://www.missinglink.company
GreenOps is a cultural transformation that empowers developers to turn emissions data into meaningful action, bridging the communication gap with ESG teams and exposing the critical truth that cloud cost and carbon cost are not the same, which fundamentally reshapes how we approach sustainable IT.This week, Dave, Esmee and Rob talk to James Hall, Head of GreenOps at Green Pixie, to unpack the real state of GreenOps today—and why we've only just scratched the surface. TLDR 01:57 Rob is confused about AGI 06:11 Cloud conversation with James Hall 22:10 Esmee as media archeologist, found GreenOps is 50 years old 30:46 Having some drinks in the summer Guest James Hall: https://www.linkedin.com/in/james-f-hall/ Hosts Dave Chapman: https://www.linkedin.com/in/chapmandr/ Esmee van de Giessen: https://www.linkedin.com/in/esmeevandegiessen/ Rob Kernahan: https://www.linkedin.com/in/rob-kernahan/Production Marcel van der Burg: https://www.linkedin.com/in/marcel-vd-burg/ Dave Chapman: https://www.linkedin.com/in/chapmandr/ Sound Ben Corbett: https://www.linkedin.com/in/ben-corbett-3b6a11135/ Louis Corbett: https://www.linkedin.com/in/louis-corbett-087250264/'Cloud Realities' is an original podcast from Capgemini
Au programme :En ce mois de juillet 2025 je vous propose une plongée dans les archives du RDV Tech on va remonter juste de quelques années pour se repencher sur le début de quelque chose qui bouleverse beaucoup de choses ces dernières années, l'arrivée de ChatGPT fin 2022. On en parlait dans le RDV Tech 490 le 6 décembre 2022 avec au micro avec moi Korben et Cedric de Luca, avec le début de la version conversationnelle de ChatGPT pour le grand public, on était impressionnés par la génération de textes. Infos :Animé par Patrick Beja (Bluesky, Instagram, Twitter, TikTok)Produit par Patrick Beja (LinkedIn) et Fanny Cohen Moreau (LinkedIn).Musique libre de droit par Daniel Beja---Liens :
In the first episode of an "AI in the shadows" theme, Chris and Daniel explore the increasing concerning world of agentic misalignment. Starting out with a reminder about hallucinations and reasoning models, they break down how today's models only mimic reasoning, which can lead to serious ethical considerations. They unpack a fascinating (and slightly terrifying) new study from Anthropic, where agentic AI models were caught simulating blackmail, deception, and even sabotage — all in the name of goal completion and self-preservation. Featuring:Chris Benson – Website, LinkedIn, Bluesky, GitHub, XDaniel Whitenack – Website, GitHub, XLinks:Agentic Misalignment: How LLMs could be insider threatsHugging Face Agents CourseRegister for upcoming webinars here!
Are the AI models you use today imposters?Please watch the intro video we did before this: https://www.youtube.com/watch?v=o1q6Hhz0MAgIn this episode, hosts Dr. Tim Scarfe and Dr. Duggar are joined by AI researcher Prof. Kenneth Stanley and MIT PhD student Akash Kumar to discuss their fascinating paper, "Questioning Representational Optimism in Deep Learning."Imagine you ask two people to draw a perfect skull. One is a brilliant artist who understands anatomy, the other is a machine that just traces the image. Both drawings look identical, but the artist understands what a skull is—they know where the mouth is, how the jaw works, and that it's symmetrical. The machine just has a tangled mess of lines that happens to form the right picture.An AI with an elegant representation, has the building blocks to generate truly new ideas.The Path Is the Goal: As Kenneth Stanley puts it, "it matters not just where you get, but how you got there". Two students can ace a math test, but the one who truly understands the concepts—instead of just memorizing formulas—is the one who will go on to make new discoveries.The show is a mixture of 3 separate recordings we have done, the original Patreon warmup with Tim/Kenneth, the Tim/Keith "Steakhouse" recorded after the main interview, then the main interview with Kenneth/Akarsh/Keith/Tim. Feel free to skip around. We had to edit this in a rush as we are travelling next week but it's reasonably cleaned up. TOC:00:00:00 Intro: Garbage vs. Amazing Representations00:05:42 How Good Representations Form00:11:14 Challenging the "Bitter Lesson"00:18:04 AI Creativity & Representation Types00:22:13 Steakhouse: Critiques & Alternatives00:28:30 Steakhouse: Key Concepts & Goldilocks Zone00:39:42 Steakhouse: A Sober View on AI Risk00:43:46 Steakhouse: The Paradox of Open-Ended Search00:47:58 Main Interview: Paper Intro & Core Concepts00:56:44 Main Interview: Deception and Evolvability01:36:30 Main Interview: Reinterpreting Evolution01:56:16 Main Interview: Impostor Intelligence02:11:15 Main Interview: Recommendations for AI ResearchREFS:Questioning Representational Optimism in Deep Learning:The Fractured Entangled Representation HypothesisAkarsh Kumar, Jeff Clune, Joel Lehman, Kenneth O. Stanleyhttps://arxiv.org/pdf/2505.11581Kenneth O. Stanley, Joel LehmanWhy Greatness Cannot Be Planned: The Myth of the Objectivehttps://amzn.to/44xLaXKOriginal show with Kenneth from 4 years ago:https://www.youtube.com/watch?v=lhYGXYeMq_EKenneth Stanley is SVP Open Endedness at Lila Scienceshttps://x.com/kenneth0stanleyAkarsh Kumar (MIT)https://akarshkumar.com/AND... Kenneth is HIRING (this is an OPPORTUNITY OF A LIFETIME!)Research Engineer: https://job-boards.greenhouse.io/lila/jobs/7890007002Research Scientist: https://job-boards.greenhouse.io/lila/jobs/8012245002TRANSCRIPT:https://app.rescript.info/public/share/W_T7E1OC2Wj49ccqlIOOztg2MJWaaVbovTeyxcFEQdU
Hello à tous et toutes ! Retour à l'audio pour cet édito "public" où je vous détaille le programme de l'été pour tous les podcasts (et je vous parle aussi des raisons de ce break).Passez d'excellentes vacances, et on se retrouve en septembre.
Quantum computing in 2025 is rapidly advancing toward commercialization, with breakthroughs in algorithms, scalable hardware, and cloud-based quantum services driving real-world applications across finance, healthcare, logistics, and cybersecurityThis week, Dave, Esmee, and Rob dive into the cutting edge of quantum computing with Catherine Vollgraff Heidweiller, Quantum AI PM at Google, and James Goeders, Head of Product for Google Quantum AI, exploring how far we've come since our June 2023 Quantumania! episode and what to expect from Willow—the bold fusion of quantum, AI, digital integration, deployment, and the broader tech ecosystem.TLDR00:46 Meet Catherine and James – intros and backgrounds02:22 Rob is confused about students using AI09:40 Deep dive with Catherine and James on the current state and future of Quantum48:01 Quantum isn't just tech—it's a whole new way of thinking1:01:37 Seize the moment and bringing external users onto quantum hardwareGuestCatherine Vollgraff Heidweiller: https://www.linkedin.com/in/cmv-vollgraffheidweiller/James Goeders: https://www.linkedin.com/in/james-goeders-8876a7164/HostsDave Chapman: https://www.linkedin.com/in/chapmandr/Esmee van de Giessen: https://www.linkedin.com/in/esmeevandegiessen/Rob Kernahan: https://www.linkedin.com/in/rob-kernahan/ProductionMarcel van der Burg: https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman: https://www.linkedin.com/in/chapmandr/SoundBen Corbett: https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett: https://www.linkedin.com/in/louis-corbett-087250264/'Cloud Realities' is an original podcast from Capgemini
In this episode, we sit down with Joey Conway to explore NVIDIA's open source AI, from the reasoning-focused Nemotron models built on top of Llama, to the blazing-fast Parakeet speech model. We chat about what makes open foundation models so valuable, how enterprises can think about deploying multi-model strategies, and why reasoning is becoming the key differentiator in real-world AI applications.Featuring:Joey Conway – LinkedInChris Benson – Website, LinkedIn, Bluesky, GitHub, XLinks:Llama Nemotron UltraNVIDIA Llama Nemotron Ultra Open Model Delivers Groundbreaking Reasoning AccuracyIndependent analysis of AIParakeet ModelParakeet LeaderboardTry the Llama-3.1-Nemotron-Ultra-253B-v1 model here and here
Au programme :IA vs auteurs: première victoire des LLMFairphone Gen 6, une première réussite?TikTok et Instagram bientôt sur votre télé?Le reste de l'actualitéInfos :Animé par Patrick Beja (Bluesky, Instagram, Twitter, TikTok)Co-animé par Jérôme Keinborg (Bluesky).Co-animé par Cédric de LucaProduit par Patrick Beja (LinkedIn) et Fanny Cohen Moreau (LinkedIn).Musique libre de droit par Daniel BejaLe Rendez-vous Tech épisode 625 – L'important c'est le chemin ET la destination – Victoire légale des LLM, Fairphone Gen 6, TikTok & Insta sur TV---Liens :
Can AI-driven autonomy reduce harm, or does it risk dehumanizing decision-making? In this “AI Hot Takes & Debates” series episode, Daniel and Chris dive deep into the ethical crossroads of AI, autonomy, and military applications. They trade perspectives on ethics, precision, responsibility, and whether machines should ever be trusted with life-or-death decisions. It's a spirited back-and-forth that tackles the big questions behind real-world AI.Featuring:Chris Benson – Website, GitHub, LinkedIn, XDaniel Whitenack – Website, GitHub, XLinks:The Concept of "The Human" in the Critique of Autonomous WeaponsOn the Pitfalls of Technophilic Reason: A Commentary on Kevin Jon Heller's “The Concept of ‘the Human' in the Critique of Autonomous Weapons”Sponsors:Outshift by Cisco: AGNTCY is an open source collective building the Internet of Agents. It's a collaboration layer where AI agents can communicate, discover each other, and work across frameworks. For developers, this means standardized agent discovery tools, seamless protocols for inter-agent communication, and modular components to compose and scale multi-agent workflows.
The telecom industry is undergoing a fundamental transformation. This shift is creating new business opportunities and services but also brings significant challenges in transformation and modernization. In this special bonus episode, building on our Reimagining Telecoms mini-series, we dive into the current opportunities shaping today's dynamic telco landscape.This week, Dave, Esmee and Rob talk to Vivek Badrinath, Director General of the GSMA about the current opportunities shaping today's dynamic telco landscape and the role of GSMA. TLDR01:38 Introduction to Vivek and the bonus episode03:48 In-depth conversation with Vivek Badrinath42:13 Can empathy become a strategic KPI in telecom?47:20 Event in Uzbekistan and doubling down on the digital ecosystem GuestVivek Badrinath: https://www.linkedin.com/in/vivekbadrinath/HostsDave Chapman: https://www.linkedin.com/in/chapmandr/Esmee van de Giessen: https://www.linkedin.com/in/esmeevandegiessen/Rob Kernahan: https://www.linkedin.com/in/rob-kernahan/ ProductionMarcel van der Burg: https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman: https://www.linkedin.com/in/chapmandr/with Praveen Shankar: https://www.linkedin.com/in/praveen-shankar-capgemini/SoundBen Corbett: https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett: https://www.linkedin.com/in/louis-corbett-087250264/'Cloud Realities' is an original podcast from Capgemini
ABOUT DHRUV PARTHASARATHYDhruv Parthasarathy has spent the last 8 years focused on applying modern software and machine learning techniques in healthcare. Dhruv currently serves as the CTO of Commure, HATCO, and Augmedix. In the role of CTO, he leads product, engineering, and design teams. Prior to this, Dhruv helped found Athelas which eventually merged with Commure.In these roles, Dhruv has designed and developed end-to-end solutions for revenue cycle automation, ambient documentation, patient engagement, and at-home diagnostics for oncology.Before this, Dhruv was the Director of Machine Learning Programs at Udacity, where he led the development of the AI, Self-Driving Car, Deep Learning, and Machine Learning Nanodegree programs.Dhruv also worked as a Product Engineer at Udacity, where he rebuilt the main signed-in experience and was responsible for the backend development. Dhruv obtained a Bachelor's degree in Computer Science from Massachusetts Institute of Technology in 2013. Following this, they pursued a Master's degree in Computer Science with a concentration in Artificial Intelligence at MIT from 2013 to 2014. This episode is brought to you by Side – delivering award-winning QA, localization, player support, and tech services for the world's leading games and technology brands.For over 30 years, Side has helped create unforgettable user experiences—from indies to AAA blockbusters like Silent Hill 2 and Baldur's Gate 3.Learn more about Side's global solutions at side.inc. SHOW NOTES:How the Commure team moves with speed & momentum (3:26)Commure's operational strategy / key leadership principles (4:57)Hiring & cultivating multi-talented individuals (7:16)How to optimize decision-making, push decisions down & minimize risk (8:40)Why speed is a core principle for building successful eng orgs (11:36)Getting unstuck in your decision-making as an eng team (13:07)Challenges faced while building a high-performing eng team in healthcare (15:47)Tactics for hiring less experienced engineers & bringing them up to speed (18:22)Customization as a product principle and how it manifests in EPD (20:55)Why the polymath style approach to engineering is more vital now than ever (23:47)Lessons learned around scope & using it to create leverage (26:06)Frameworks for assessing areas most likely to create a compound win (28:22)Rapid fire questions (30:35)LINKS AND RESOURCESCinema Speculation - The long-awaited first work of nonfiction from the author of the #1 New York Times bestselling Once Upon a Time in Hollywood: a deliriously entertaining, wickedly intelligent cinema book as unique and creative as anything by Quentin Tarantino.This episode wouldn't have been possible without the help of our incredible production team:Patrick Gallagher - Producer & Co-HostJerry Li - Co-HostNoah Olberding - Associate Producer, Audio & Video Editor https://www.linkedin.com/in/noah-olberding/Dan Overheim - Audio Engineer, Dan's also an avid 3D printer - https://www.bnd3d.com/Ellie Coggins Angus - Copywriter, Check out her other work at https://elliecoggins.com/about/
Au programme :Le premier téléphone « américain » coute 1999$Netflix et TF1 signent un accord majeurLe reste de l'actualité : temps des ados sur Tiktok, évolution des shorts, le journal de l'IA…Infos :Animé par Patrick Beja (Bluesky, Instagram, Twitter, TikTok)Co-animé par Guillaume Vendé (Bluesky).Co-animé par Siegfried Thouvenot alias Captain Web (Twitter).Produit par Patrick Beja (LinkedIn) et Fanny Cohen Moreau (LinkedIn).Musique libre de droit par Daniel BejaLe Rendez-vous Tech épisode 624 – En tech, rien n'est simple – Purism Liberty Phone, Netflix
digital kompakt | Business & Digitalisierung von Startup bis Corporate
Tauche ein in die faszinierende Welt der Singularity! Im Gespräch mit Joel Kaczmarek enthüllt Lars Jankowfsky, Gründer von Gradion, die Geheimnisse hinter dem exponentiellen Technologiewachstum. Gemeinsam erkunden sie die Chancen und Herausforderungen, die uns in den kommenden Jahrzehnten erwarten. Von der medizinischen Revolution bis hin zu interplanetaren Reisen – welche Rolle spielt künstliche Intelligenz und wie verändert sie unser Leben? Lass dich inspirieren und erfahre, warum die Zukunft aufregender ist, als du denkst! Du erfährst... …wie Lars Jankowfsky die Chancen und Risiken der Singularity einschätzt …welche Rolle künstliche Intelligenz in der medizinischen Forschung spielt …wie die Entwicklung von Robotik Arbeitsplätze und Gesellschaft verändert …welche Energiefragen bei exponentiellem Technologiewachstum aufkommen …warum die Zukunft von Kapitalismus und Gesellschaft neu gedacht werden muss __________________________ ||||| PERSONEN |||||
Join us for a powerful conversation with Larry Ward, President of Political Media Incorporated (PMI), as we explore the intersection of politics, marketing, and digital freedom. With decades of experience across the political, corporate, and non-profit worlds, Larry shares how PMI has helped shape the modern political landscape — all while staying ahead of the curve in a rapidly changing media environment. From pioneering digital outreach in the early 2000s to tackling the challenges of online censorship and algorithmic suppression, PMI has consistently led with innovation and conviction. In this episode, we break down the tools, strategies, and principles that continue to drive their mission forward. In this episode, you'll hear about: How digital platforms transformed political engagement. The subtle yet powerful ways censorship creeps into online advertising. How targeted messaging thrives even in suppressed environments. What AI means for the future of political speech and media strategy. If you're curious about the future of free speech, or how real change is driven through media strategy, this episode is a must-watch. Explore Larry's work and case studies at Politicalmedia.com/case-studies
[AAA] In 'Access All Areas' shows we go behind the scenes with the crew and their friends as they dive into complex challenges that organizations face—sometimes getting a little messy along the way.This week, we address the ‘big rocks' that can obstruct or delay successful outcomes in organizational transformations. Dave, Esmee, and Rob are joined by Jasmin Booth, Head of Product Delivery to discuss the transformation to being a (digital) product based organization.TLDR05:22 Access All Areas: This third episode focuses on the products we build that drive outcomes.06:52 Conversation with Jasmin about our digital products37:06 What makes it better to be in a product centric organization? 54:00 Conclusion of the seven Big Rocks and how to smash them59:00 Going on the Blue Bell railway HostsDave Chapman: https://www.linkedin.com/in/chapmandr/Esmee van de Giessen: https://www.linkedin.com/in/esmeevandegiessen/Rob Kernahan: https://www.linkedin.com/in/rob-kernahan/with Jasmin Booth: https://www.linkedin.com/in/jasminbooth15/ProductionMarcel van der Burg: https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman: https://www.linkedin.com/in/chapmandr/SoundBen Corbett: https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett: https://www.linkedin.com/in/louis-corbett-087250264/'Cloud Realities' is an original podcast from Capgemini
digital kompakt | Business & Digitalisierung von Startup bis Corporate
Tauche ein in die Welt des Prompt Engineerings mit Joel Kaczmarek und Ruppert Bodmeier! In dieser Episode von digital kompakt geht es um die Kunst, KI-Modelle so zu steuern, dass sie genau das liefern, was du brauchst. Ruppert, ein Experte für Innovationsentwicklung bei Disrooptive, teilt seine Erfahrungen und Herausforderungen auf dem Weg zur perfekten KI-Nutzung. Erfahre, wie du durch gezieltes Prompt Engineering Wettbewerbsvorteile schaffen kannst und warum der Kontext dabei entscheidend ist. Lass dich inspirieren und entdecke, wie du die Zukunft der KI für dich nutzen kannst! Du erfährst... …wie Ruppert Bodmeier die Kunst des Prompt Engineering meistert und einzigartige Lösungen schafft …warum Beharrlichkeit und Resilienz im Umgang mit KI entscheidend sind …wie du durch präzise Kontextdefinitionen bessere KI-Ergebnisse erzielst …welche Rolle APIs spielen, um Wettbewerbsvorteile mit KI zu sichern …wie du mit modularen Befehlen und Ketten einzigartige Projekte realisierst __________________________ ||||| PERSONEN |||||
It seems like we are bombarded by news about millions of dollars pouring into AI startups, which have crazy valuations. In this episode, Chris and Dan dive deep into the highs, lows, and hard choices behind funding an AI startup. They explore early bootstrapping, the transition to venture capital, and what it's like to trade in code commits for investor decks. Featuring:Chris Benson – Website, GitHub, LinkedIn, XDaniel Whitenack – Website, GitHub, XLinks:Builder.ai Collapses: $1.5bn 'AI' Startup Exposed as 'Actually Indians' Pretending to Be BotsSponsors:Miro: Feeling overwhelmed by AI? Miro brings clarity by combining human creativity with intelligent tools to help teams get great work done. Learn more at miro.com.
Au programme :Copyright vs IA: les choses sérieuses commencentWWDC à tête reposée: Liquid Glass et damage controlMistral au centre de VivatechLe reste de l'actuInfos :Animé par Patrick Beja (Bluesky, Instagram, Twitter, TikTok)Co-animé par Marion Doumeingts (Instagram, Bluesky, Twitter).Produit par Patrick Beja (LinkedIn) et Fanny Cohen Moreau (LinkedIn).Musique libre de droit par Daniel BejaLe Rendez-vous Tech épisode 623 – IA vs Copyright: le vrai combat débute---Liens :
Prof. James Evans, a University of Chicago sociologist and data scientist, believes we're training AI to think too much like humans—and it's holding science back.In this episode, Evans shares how our current models risk narrowing scientific exploration rather than expanding it, and explains why he's pushing for AIs that think differently from us—what he calls “cognitive aliens.” Could these “alien minds” help us unlock hidden breakthroughs? And what would it take to build them?
An recent article in Variety was titled: "Sylvester Stallone-Backed Largo.ai Teams With Brilliant Pictures for ‘World's First Fully AI-Automated Film Company'". Obviously this caught our attention! We sit down with Sami Arpa, CEO of Largo.ai, to unpack how films are developed, funded, and brought to life using AI. We discover how tools like script analysis, financial forecasting, and digital twins are helping creators and studios make smarter decisions. Featuring:Sami Arpa – LinkedInDaniel Whitenack – Website, GitHub, XLinks:Largo AISylvester Stallone-Backed Largo.ai Teams With Brilliant Pictures for ‘World's First Fully AI-Automated Film Company' Sponsors:Outshift by Cisco: AGNTCY is an open source collective building the Internet of Agents. It's a collaboration layer where AI agents can communicate, discover each other, and work across frameworks. For developers, this means standardized agent discovery tools, seamless protocols for inter-agent communication, and modular components to compose and scale multi-agent workflows.
Mark Ericksen, creator of the Elixir LangChain framework, joins the Elixir Wizards to talk about LLM integration in Elixir apps. He explains how LangChain abstracts away the quirks of different AI providers (OpenAI, Anthropic's Claude, Google's Gemini) so you can work with any LLM in one more consistent API. We dig into core features like conversation chaining, tool execution, automatic retries, and production-grade fallback strategies. Mark shares his experiences maintaining LangChain in a fast-moving AI world: how it shields developers from API drift, manages token budgets, and handles rate limits and outages. He also reveals testing tactics for non-deterministic AI outputs, configuration tips for custom authentication, and the highlights of the new v0.4 release, including “content parts” support for thinking-style models. Key topics discussed in this episode: • Abstracting LLM APIs behind a unified Elixir interface • Building and managing conversation chains across multiple models • Exposing application functionality to LLMs through tool integrations • Automatic retries and fallback chains for production resilience • Supporting a variety of LLM providers • Tracking and optimizing token usage for cost control • Configuring API keys, authentication, and provider-specific settings • Handling rate limits and service outages with degradation • Processing multimodal inputs (text, images) in Langchain workflows • Extracting structured data from unstructured LLM responses • Leveraging “content parts” in v0.4 for advanced thinking-model support • Debugging LLM interactions using verbose logging and telemetry • Kickstarting experiments in LiveBook notebooks and demos • Comparing Elixir LangChain to the original Python implementation • Crafting human-in-the-loop workflows for interactive AI features • Integrating Langchain with the Ash framework for chat-driven interfaces • Contributing to open-source LLM adapters and staying ahead of API changes • Building fallback chains (e.g., OpenAI → Azure) for seamless continuity • Embedding business logic decisions directly into AI-powered tools • Summarization techniques for token efficiency in ongoing conversations • Batch processing tactics to leverage lower-cost API rate tiers • Real-world lessons on maintaining uptime amid LLM service disruptions Links mentioned: https://rubyonrails.org/ https://fly.io/ https://zionnationalpark.com/ https://podcast.thinkingelixir.com/ https://github.com/brainlid/langchain https://openai.com/ https://claude.ai/ https://gemini.google.com/ https://www.anthropic.com/ Vertex AI Studio https://cloud.google.com/generative-ai-studio https://www.perplexity.ai/ https://azure.microsoft.com/ https://hexdocs.pm/ecto/Ecto.html https://oban.pro/ Chris McCord's ElixirConf EU 2025 Talk https://www.youtube.com/watch?v=ojL_VHc4gLk Getting started: https://hexdocs.pm/langchain/gettingstarted.html https://ash-hq.org/ https://hex.pm/packages/langchain https://hexdocs.pm/igniter/readme.html https://www.youtube.com/watch?v=WM9iQlQSFg @brainlid on Twitter and BlueSky Special Guest: Mark Ericksen.
Every organization is built on people, structures, and culture. But culture isn't static—it evolves with every interaction, ambition, and shift in circumstance. As IT drives business transformation, new technologies reshape how people connect and collaborate. In this ever-changing landscape, a strong, adaptive culture is the key to lasting success. This week, Dave, Esmee and Rob talk to Jitske Kramer, Corporate Anthropologist about what technology is doing to cultures and human systems and how AI can mess with the narrative. TLDR00:50 Introduction of Jitske Kramer and her book Navigating Tricky Times02:05 Rob shares his confusion about saying “thank you” to AI07:25 In-depth conversation with Jitske Kramer11:30 Visual communication via tattoos even at AWS re:Invent25:00 Corporate framing and what's going on within organizations today46:22 Exploring the contrast between the natural pace of human transformation and the rapid acceleration of technology54:14 Editing the documentary Patterns of Life55:56 Esmee's 2x Outro speed surprises everyone!Guest:Jitske Kramer: https://www.linkedin.com/in/jitskekramer/https://jitskekramer.substack.com/Tricky Times event: https://tricky-times.com/events/navigating-tricky-times-leading-through-the-messy-middle-of-change/HostsDave Chapman: https://www.linkedin.com/in/chapmandr/Esmee van de Giessen: https://www.linkedin.com/in/esmeevandegiessen/Rob Kernahan: https://www.linkedin.com/in/rob-kernahan/ ProductionMarcel van der Burg: https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman: https://www.linkedin.com/in/chapmandr/ SoundBen Corbett: https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett: https://www.linkedin.com/in/louis-corbett-087250264/ 'Cloud Realities' is an original podcast from Capgemini
Au programme :WWDC: Les grands enseignements, Liquid Glass et iOS 26WWDC: l'iPad devient un « Mac Lite » (et les autres OS)Les actions planifiées, la prochaine étape de l'IA?Le reste de l'actualitéInfos :Animé par Patrick Beja (Bluesky, Instagram, Twitter, TikTok)Co-animé par Christophe Camicas (Bluesky).Co-animé par Olivier Frigara (Bluesky).Produit par Patrick Beja (LinkedIn) et Fanny Cohen Moreau (LinkedIn).Musique par Daniel BejaLe Rendez-vous Tech épisode 622 – WWDC 2025: L'iPad devient « Mac Lite » et Liquid Glass est partout – iOS 26, MacOS 26, iPadOS 26, VisionOS 26, WatchOS 26---Liens :
In episode 1860, Jack and guest co-host Andrew Ti are joined by host of Worse Than You, Mo Fry Pasic, to discuss…REAL ID Isn’t Real, Cyber Trucks Just Totally Stop Selling, This AI Expert Thinks The AI Bubble’s About to Pop and more! What you need to know about the REAL ID requirements for air travel The Racist Origins of the Real ID Act Top Trump agency reveals key reason why REAL ID will be enforced 'Mass surveillance': Conservatives sound alarm over Trump admin's REAL ID rollout Trump’s Insistence on Real ID Has Become a Flashpoint for His Tinfoil Hat Fans You can get a free Krispy Kreme doughnut on May 7 for Real ID deadline: Here's how Homeland Security chief says travelers with no REAL ID can fly for now, but with likely extra steps Flying out of Indianapolis without REAL ID? Don't fret — the airport isn't turning people away Tesla’s Inventory of Unsold Cybertrucks Skyrockets, Despite Offering $10K Discounts and Concealing Listings The Silicon Valley sceptic warning tech’s new bubble is about to burst Deep Learning Is Hitting a Wall Microsoft’s £2.5bn investment in Britain at risk from creaking power grid Chess helped me win the Nobel Prize, says Google’s AI genius OpenAI overrode concerns of expert testers to release sycophantic GPT-4o The next British boom could be in the offing – if Starmer abandons net zero Finance worker pays out $25 million after video call with deepfake ‘chief financial officer’ LISTEN: Indeed by CruzaSee omnystudio.com/listener for privacy information.
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