Shows
Zero to OneFrom Dropout to a16z-Backed - How Daniel Reid Cahn Is Reinventing Mental Health with AIThis might be the most insane AI founder story you’ll hear all year.Dropped out of high school.Met the Queen of England. 👑Helped pivot Instabase by building a transformer before it was cool.Now? He’s building a foundation model for the human mind — and raised from a16z, Menlo, and Benchmark.🎙️ We sat down with Daniel Reid Cahn, cofounder & CEO of Slingshot AI, to unpack how he’s using AI to reinvent mental health — without replacing human therapists.🔍 What we cover:Why the future of therapy isn...2025-05-271h 16
Thinking Machines: AI & PhilosophyAI Therapy with Slingshot's Derrick Hull“Everyone should go to therapy.” It’s a common statement, but much harder to achieve than it looks. There’s only one therapist for every 10K would-be clients, and the gap is only growing every year.That gap is what my latest guest - Dr. Derrick Hull - has spent his career trying to fix. Now serving as the founding Clinical Lead at Slingshot AI, Derrick previously led Clinical R&D at Talkspace, where he was instrumental in popularizing text-message therapy, a previously controversial modality now recognized as critical to increasing accessibility to mental health care. Derrick has had...2025-03-1736 minThinking Machines: AI & PhilosophyWhat if we could cure loneliness? Philosophy, dopamine, and more with Mark UnglessArtificial neural networks were designed to emulate the human brain - and their insane performance on a wide range of tasks is pretty good evidence to support the comparison.Well, it's a bit more complicated than that, at least according to my guest Mark Ungless, former neuroscience lecturer at Imperial and Oxford and current Director of AI at the UK's Mental Health Innovations. Mark and I have collaborated on research for 5+ years, and I've long enjoyed his thoughts on the biology of the brain, the philosophy of the mind, and how AI is changing...2025-02-261h 11Thinking Machines: AI & PhilosophyDoes Philosophy Make Progress? Chatting with Every's Dan ShipperIs the AI revolution we're experiencing going to push us into a future we can't imagine? Or will the pace of progress enable us to adjust along the way?Dan Shipper spends his time thinking and writing on these topics (and many others) as the founder and CEO of Every Media, a technology-focused publication trying to understand the future. Dan is also a lifelong coder and entrepreneur with a background in philosophy and its intersection with tech. Dan and I share a ton in common (beyond just our first names!), so I think you all will enjoy...2025-01-2350 minThinking Machines: AI & PhilosophyOpenAI o1: Another GPT-3 moment?GPT-3 didn't have much of a splash outside of the AI community, but it foreshadowed the AI explosion to come. Is o1 OpenAI's second GPT-3 moment?Machine Learning Researchers Guilherme Freire and Luka Smyth discuss OpenAI o1, it's impact, and it's potential. We discuss early impressions of o1, why inference-time compute and reinforcement learning matter in the LLM story, and the path from o1 to AI beginning to fulfill its potential.00:00 Introduction and Welcome00:22 Exploring O1: Initial Impressions03:44 O1's Reception06:42 Reasoning and Model Scaling18:36 The Role of Agents27:28 Impact...2024-10-1851 minThinking Machines: AI & PhilosophyThe Future is Fine Tuned (with Dev Rishi, Predibase)Dev Rishi is the founder and CEO of Predibase, the company behind Ludwig and LoRAX. Predibase just released LoRA Land, a technical report showing 310 models that can outcompete GPT-4 on specific tasks through fine-tuning. In this episode, Dev tries (pretty successfully) to convince me that fine-tuning is the future, while answering a bunch of interesting questions, like:Is fine-tuning hard?If LoRAX is a competitive advantage for you, why open-source it?Is model hosting becoming commoditized? If so, how can anyone compete?What are people actually fine-tuning language models for?How worried are you about OpenAI eating your...2024-05-2452 minThinking Machines: AI & PhilosophyPre-training LLMs: One Model To Rule Them All? with Talfan Evans, DeepMindTalfan Evans is a research engineer at DeepMind, where he focuses on data curation and foundational research for pre-training LLMs and multimodal models like Gemini. I ask Talfan: Will one model rule them all?What does "high quality data" actually mean in the context of LLM training?Is language model pre-training becoming commoditized?Are companies like Google and OpenAI keeping their AI secrets to themselves?Does the startup or open source community stand a chance next to the giants?Also check out Talfan's latest paper at DeepMind, Bad Students Make Good Teachers.2024-05-1837 minThinking Machines: AI & PhilosophyOn Adversarial Training & Robustness with Bhavna Gopal"Understanding what's going on in a model is important to fine-tune it for specific tasks and to build trust."Bhavna Gopal is a PhD candidate at Duke, research intern at Slingshot with experience at Apple, Amazon and Vellum.We discussHow adversarial robustness research impacts the field of AI explainability.How do you evaluate a model's ability to generalize?What adversarial attacks should we be concerned about with LLMs?2024-05-0944 minThinking Machines: AI & PhilosophyOn Emotionally Intelligent AI (with Chris Gagne, Hume AI)Chris Gagne manages AI research at Hume, which just released an expressive text-to-speech model in a super impressive demo. Chris and Daniel discuss AI and emotional understanding:How does “prosody” add a dimension to human communication? What is Hume hoping to gain by adding it to Human-AI communication?Do we want to interact with AI like we interact with humans? Or should the interaction models be different?Are we entering the Uncanny Valley phase of emotionally intelligent AI?Do LLMs actually have the ability to reason about emotions? Does it matter?What do we risk, by empowering AI with...2024-04-1939 minThinking Machines: AI & PhilosophyClip: Why Greatness Cannot Be Planned with Joel Lehman2024-03-2202 minThinking Machines: AI & PhilosophyWhy Greatness Cannot Be Planned (with Joel Lehman)Former OpenAI Research Scientist Joel Lehman joins to discuss the non-linear nature of technological progress and the present day implications of his book, Why Greatness Cannot Be Planned.Joel co-authored the book with Kenneth Stanley back in 2015. The two did ML research at OpenAI, Uber, and the University of Central Florida and wrote the book based on insights from their work.We discuss:AI time horizons, and the Implications for investors, researchers, and entrepreneursExploration vs exploitation for AI startups and researchers, and where to fit in differential bets to avoid direct competitionThe...2024-03-2247 minThinking Machines: AI & PhilosophyWhere are the good AI products? (with Varun Shenoy)“Where are the good AI products?” asks Varun Shenoy, ML engineer in his latest blog post. Varun and I talk through:What are the cool applications that exist? Why aren't there more of them?What do (the few) good AI application companies have in common?What technological or societal leaps are blocking the existence of more AI apps that matter?The optimist case and the pessimist case for the near future of AI. As Varun puts it, what if the emperor has no clothes?We'd love to hear what you think. Feel free to reach out on Link...2024-03-1246 minThinking Machines: AI & PhilosophyThe End of RAG (with Donato Riccio)ML Engineer and tech writer Donato Riccio wrote an article entitled "The End of RAG?" discussing what might replace Retrieval Augmented Generation in the near future. The article was received as highly controversial within the AI echo chamber, so I brought Donato on the podcast to discuss RAG, why people are so obsessed with vector databases, and the upcoming research in AI that might replace it.Takeaways:RAG is necessary due to LLMs' limited context window and scalability issues, and the need to avoid hallucinations and outdated information.Larger/infinite context window models and linear-scaling models...2024-02-0940 minThinking Machines: AI & PhilosophyGPUs and how the cloud is changing (with Cedana Founder, Neel Master)What’s going on with GPUs? We talk through the GPU bottleneck/supply gut, Meta’s apparent 600,000 H100-equivalents and the future of the GPU cloud.Neel Master is the CEO and founder of Cedana, enabling pause/migrate/resume for compute jobs. Neel is a serial entrepreneur, former founder of Engooden and angel investor. He started his career in ML research at MIT's CSAIL.Topics from this podcast include:Cedana's real-time save, migrate and resume for compute technology, enabling the migration of compute jobs across instances without interruptionWhen will there be enough GPUs?What does...2024-02-0242 minThinking Machines: AI & PhilosophyLive Video Translation with AIFounders of Lingopal, Deven Orie and Casey Schneider, join to talk about their startup story, developing real-time translation software for enterprises.Topics include:Why is translation so hard?How are enterprise and consumer AI products different (e.g. Google Translate vs Lingopal)?Should AI product companies be doing AI research?Is it safe to rely on open source?Share your thoughts with us at hello@slingshot.xyz or tweet us @slingshot_ai.2024-01-2228 minThinking Machines: AI & PhilosophyIs open-source AI safe? (with SafeLlama founder, Enoch Kan)Founder of the SafeLlama community, Enoch Kan joins us today, to talk about safety in open source and medical AI. Enoch previously worked in AI for radiology, focused on mammography at Kheiron Medical. Enoch is an open source contributor, and his substack is called Cross Validated.Key topics they discuss include:New jailbreaks for LLMs appear every day. Does it matter?How do internet firewalls compare to AI “firewalls”?Why do human radiologists still exist? Would it be safe to replace them all today?Does safety matter more or less as models become more...2024-01-1236 minThinking Machines: AI & PhilosophyWhat is the future of AI-assisted or AI-driven software?Join Daniel Cahn on another SlingTalk episode with Kristian Freed (ex-CTO at Pariti and Elder), discussing the past, present and future of AI-assisted or AI-driven software.They talked about:The Evolution of Coding Tools: From basic text editors to advanced IDEs and the integration of AI tools like Co-Pilot.The Impact of AI on Software Development Practices: How AI is reshaping the way code is written and the process of software development.AI-Generated Code and Its Potential: Exploring the current capabilities of AI in generating code and its future implications.AI as a Mentor and Learning...2024-01-0532 minThinking Machines: AI & PhilosophyIs the Turing Test Outdated?In 1950, Alan Turing asked, “Can machines think?” He suggested the Imitation Game as a test to evaluate whether a machine can think, more commonly called the “Turing Test.” Today we ask, is the Turing Test outdated? Joining Slingtalks this week are Kristian Freed & Guilherme Freire, founding engineers at Slingshot. Guilherme argues against the Turing Test, Kristian argues in favor.Key topics they discuss include:A recent paper claims that GPT-4 comes close to passing the Turing Test. Is the paper’s result valid? How close are we to passing the Turing Test?Defining the Turing Test and unders...2023-12-1645 minThinking Machines: AI & PhilosophyPrompt EngineeringJoin Daniel Cahn on SlingTalks as he welcomes Jonathan Pedoeem (Founder of PromptLayer) to talk through Prompt Engineering. This episode offers an in-depth look into the past, present, and future of prompt engineering and the intricacies of crafting effective AI prompts.Key topics they discuss include:Is prompt engineering more art or more science?The role of “prompt engineer” and whether prompt engineering is a highly specialized skill or a skill as common as GooglingApproaches to evaluating prompts - in theory and in practiceTechniques for AI-driven prompt engineeringOpenAI’s new “GPTs” feature, and how it will change the...2023-12-0838 minThinking Machines: AI & PhilosophyAI for Investment DiligenceAdam Kirsh (Head of Product & Engineering, Stealth Startup) joins Slingshot to talk about how AI is transforming investment due diligence.Beyond AI in diligence, we discuss:“Horizontal” and “vertical” business models, that start from a point solutionBuilding products vs. building relationships, and on being an AI partner for the enterpriseAI-native startups and the reinvention of business models for the AI ageMaking incremental progress as a startup vs. visionary top-down redesigns of entire processes or even industriesConsumer vs. enterprise applications of LLMs (analogy: iPhones vs Blackberrys)We wrap up with some thought-provoking reflections and an open invitati...2023-11-2433 minThinking Machines: AI & PhilosophyThe Myth of Human-in-the-LoopEx-Datadog Founding PM, Ayush Kapur, joins Daniel Cahn on SlingTalks to talk through the overloaded term, "Human in the Loop". They hone in on the impact of both, emotional and philosophical aspects of human interactions, for instance, your interaction with a doctor, and how those services can be considered irreplaceable by AI.Key topics include:Human-in-the-loop as human review vs. partially automated processesUse cases where human-in-the-loop makes automation useless because humans have to repeat the exact same steps as the AI.Liability and “human-washing,” where a human-in-the-loop is used for masking decisions effectively made by AI.The...2023-11-1536 minThinking Machines: AI & PhilosophyAI-Generated Content and the Boring ApocalypseAI is increasingly doing the heavy lifting in our communications and content generation. On this episode, Guilherme Freire, Founding ML Engineer at Slingshot, joins the podcast to discuss the impact of AI-generated content.Some of the topics discussed:“Proof of Work” for humans, when AI makes personalization and connection too easyPotential for subpar AI-generated to put high-quality content creation out of businessHyper-personalized AI leading to greater divisiveness and bias; or on the flip side, for AI to serve as a "benevolent dictator" nudging us towards better habits and more diverse thinkingThe changing meaning of “free speech” in the a...2023-11-0839 minThinking Machines: AI & PhilosophyProgramming for Machine Learning (Tech Talk)Daniel hosts our machine learning research intern and Cambridge Masters student, Andy Lo, to talk about the present and future of ML programming. Topics include:PyTorch vs. TensorFlow vs. Jax vs MoJoNo-code, low-code and pro-code for ML engineersThe (frustrating) world of debugging ML codeHave thoughts? We'd love to hear them! Drop an email at hello@slingshot.xyz or reach out on Twitter: @slingshot_ai.2023-10-3033 minThinking Machines: AI & PhilosophyAI's End of History IllusionIn this episode, Daniel shares his perspective on the opportunities for the next wave of AI-native startups.Machine Learning isn’t just about sentiment classification, churn prediction, and revenue forecasting anymore. Generative models can simulate real intelligence. But hard problems continue to require hard solutions, and prompt engineering with retrieval augmented generation won’t be nearly enough.Have thoughts? We'd love to hear them! Drop an email at hello@slingshot.xyz or reach out on Twitter: @slingshot_ai.2023-10-2508 minThinking Machines: AI & PhilosophyDesign Driven Development at SlingshotDaniel hosts our Founding Engineer, Edwin Zhang to unravel the balance in Design Driven Developments. Key things they cover:The conundrums faced when balancing user wants with real, valuable needs - showcasing our stance on "Doing what people need, not just what they want."A peek into the futuristic vision of browsers like Arc and how we regard the Browser Company.The harmonious dance between engineering-driven, customer-driven, data-driven, and design-driven developments.The delicate art of prioritising features based on feasibility, utility, and the tech's cool factor.The transformative power of machine learning in reshaping user interactions and breaking...2023-10-1624 minThinking Machines: AI & PhilosophyLLM Inference Speed (Tech Deep Dive)In this tech talk, we dive deep into the technical specifics around LLM inference.The big question is: Why are LLMs slow? How can they be faster? And might slow inference affect UX in the next generation of AI-powered software?We jump into:Is fast model inference the real moat for LLM companies?What are the implications of slow model inference on the future of decentralized and edge model inference?As demand rises, what will the latency/throughput tradeoff look like?What innovations on the horizon might massively speed up model inference?2023-10-0639 minThinking Machines: AI & PhilosophyWhy is Llama 2 Open Source? What is Meta up to?This episode delves into the ongoing debate of the competitiveness between open-source and closed-source models and the reasons behind Meta's decision to publish Llama2 with a permissive open-source licenseWe cover:How much bigger can closed-sourced models be, compared to open-source?Are new competitor foundation models doomed, if Meta enters the game?What does “second place” look like, in open source?Can open-source datasets compete?Will very large open-source models soon become illegal?2023-09-2228 minThinking Machines: AI & PhilosophyCan AI be Creative?Ever seen a piece of work and thought, "Wow, a machine did that?" In our very first Slingtalk episode, we unravel the broad world of AI and where creativity plays a part in the process. We cover:- AI models and consciousness- Poetry in language models- Algorithms, novelty, and where inspiration comes from - Creativity and the part randomness plays in the processJourney through this fusion of code, model agents, and creativity!Have thoughts? We'd love to hear them! Drop an email at hello@slingshot...2023-09-1213 min