Best Podcast Episodes About Google DeepMind

Best Podcast Episodes About Google DeepMind

Everything podcasters are saying about Google DeepMind — curated from top podcasts

Updated: Apr 27, 2026 – 75 episodes
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Ridealong has curated the best and most interesting podcasts and clips about Google DeepMind.

Top Podcast Clips About Google DeepMind

The Neuron: AI Explained
“… be at the frontier. We built it in America but like we don't just build it for America, right? Like we build it for the world. So a team of former Google DeepMind researchers just raised $2 billion, you heard that right, to build America's answer to DeepSeek. So today we're going to talk about the future of open source AI and why it might determine who controls the next generation of technology. Welcome humans to the latest episode of the Neuron podcast. I'm Corey Knowles, editor of the Neuron, and as always, I'm joined by our trusty writer, Grant Harvey. How are you today, Grant? Doing good, Corey. I'm …” “… like how far we've come. I've been doing AI for like almost 14 years now and kind of like thinking where the industry was when I started and like where it's now like the coding agent is like day and night. I don't see why open source cannot like be at the frontier. We built it in America but like we don't just build it for America, right? Like we build it for the world. So a team of former Google DeepMind researchers just raised $2 billion, you heard that right, to build America's answer to DeepSeek. So today we're going to talk about the future of open source AI and why it might determine who controls the next generation of technology. Welcome humans to the latest episode of the Neuron podcast. I'm Corey Knowles, editor of the Neuron, and as always, I'm joined by our trusty writer, Grant Harvey. How are you today, Grant? Doing good, Corey. I'm really excited to have this chat. I'm really pumped on this. Very bullish on open source here. Excellent. Well, today we have a special guest. We're joined by Yanis Antoneglou, co-founder at Reflection AI. Yanis helped create AlphaGo at DeepMind, the AI that famously beat the world champion in the game of Go back in 2016. But now he's building what …” View more
Ridealong summary
Yanis Antoneglou, co-founder of Reflection AI, believes that open-source AI will shape the next generation of technology. With $2 billion raised, his team aims to create powerful AI models that anyone can access, emphasizing that transparency and flexibility will drive innovation. This shift could democratize AI development, making it accessible to everyone, not just a select few.
The Neuron: AI Explained · This DeepMind Vet Raised $2B to Open-Source Frontier AI · Apr 08, 2026
张小珺Jùn|商业访谈录
Ridealong summary
DeepMind aims to be a company that wins multiple Nobel Prizes, a goal that initially seemed overly ambitious. During a meeting, Demis Hassabis shared this vision with interns, emphasizing a unique management style that fosters bottom-up ideas while transitioning to top-down organization as projects mature. This approach has already led to significant advancements in AI research, showcasing a blend of exploration and structured execution.
张小珺Jùn|商业访谈录 · 133. 对谢赛宁的7小时马拉松访谈:世界模型、逃出硅谷、AMI Labs、两次拒绝Ilya、杨立昆、李飞飞和42 · Mar 16, 2026
TBPN
“… them because you can see the similarities between how leaders lead and how companies adopt to the culture of the leader. So I think that's where Google's culture comes from, from the founders, and the founders were very product obsessed. You know, as you heard, Larry didn't want to spend time on business. I remember him going to the first ad, all hands, and he walks up and says, I got to tell you guys, I hate ads. They're intrusive and they're bad. That's a great motivational thing. These guys want to run out and go work at third. Because you just told them what they do is not interesting. But …” “which are founder characteristics and I said, go match them. I bet many people will be able to match them because you can see the similarities between how leaders lead and how companies adopt to the culture of the leader. So I think that's where Google's culture comes from, from the founders, and the founders were very product obsessed. You know, as you heard, Larry didn't want to spend time on business. I remember him going to the first ad, all hands, and he walks up and says, I got to tell you guys, I hate ads. They're intrusive and they're bad. That's a great motivational thing. These guys want to run out and go work at third. Because you just told them what they do is not interesting. But kind of look around, like, you know, every product that they built, they didn't look in monetizing it for a very long time until they believed the product had become ubiquitous and the product had become interesting. So I think that product obsession is part of the culture I think that partly because of where their secret sauce comes from And now …” View more
Ridealong summary
I passed on investing in Uber and WeWork, believing that tech must be genuine and not just masquerading as tech. This decision reflects a core principle I learned from my time at Google, where product obsession drove innovation without immediate monetization. It's a lesson in prioritizing authentic tech over hype, which shaped my approach at Palo Alto Networks.
TBPN · Travis Kalanick Joins, Spotify CEO, Nikesh from Palo Alto Networks, xAI Rebuild, Apple Faces Slop Allegations · Mar 13, 2026
TechCrunch Daily Crunch
“… currently a war on for consumer attention While the big chatbot providers are looking to increase their user count, and in a minor coup for itself, Google just made it significantly easier for users of those other chatbots to defect to Gemini. You see, on Thursday, the company announced what it calls switching tools, new widgets that are designed to allow users to transfer memories, basically chunks of personal information, and even entire chat histories from other chatbots directly into Gemini. Users can easily share key preferences, relationships, and personal context in this way, the company …” “… starts selling the R2 SUV which founder and CEO RJ Skaringe has said is maybe the most important thing we launched to date Not surprisingly Rivian is banking on a very fast scaling of R2 production and sales Now when it comes to AI chatbots there is currently a war on for consumer attention While the big chatbot providers are looking to increase their user count, and in a minor coup for itself, Google just made it significantly easier for users of those other chatbots to defect to Gemini. You see, on Thursday, the company announced what it calls switching tools, new widgets that are designed to allow users to transfer memories, basically chunks of personal information, and even entire chat histories from other chatbots directly into Gemini. Users can easily share key preferences, relationships, and personal context in this way, the company says. Now, the idea is to make it significantly easier to adopt Google's AI assistant, as users won't have to spend large amounts of time retraining Gemini on who they are and what they want. The memory feature works like this. Gemini will suggest a prompt that the user can enter into their current chatbot, which will then generate a response that …” View more
Ridealong summary
Google's Gemini now allows users to seamlessly transfer chat histories and personal information from other chatbots, making it easier to switch. This innovative feature is designed to attract users from competitors by reducing the time needed to retrain the AI on their preferences. As the AI chatbot war heats up, this could be a game-changer for Gemini's growth.
TechCrunch Daily Crunch · Netflix confirms it’s raising prices again · Mar 28, 2026
The AI Daily Brief: Artificial Intelligence News and Analysis
“take before we actually see it in practice. Now, one model that is available now, Google has dropped a small voice model that could have big implications. The model is Gemini 3.1 Flash Live, which brings real-time dialogue to voice models. Up until now, most voice models have been turn-based, causing awkward stumbles and terrible interruption handling. Flash Live is designed to work more like a human conversation, with a continuous back and forth rather than a jarring stilted experience. The model apparently shows a step change …” “take before we actually see it in practice. Now, one model that is available now, Google has dropped a small voice model that could have big implications. The model is Gemini 3.1 Flash Live, which brings real-time dialogue to voice models. Up until now, most voice models have been turn-based, causing awkward stumbles and terrible interruption handling. Flash Live is designed to work more like a human conversation, with a continuous back and forth rather than a jarring stilted experience. The model apparently shows a step change improvement on multiple audio benchmarks, including one designed to measure multi-step function calling. That's the feature that converts voice commands into complex agentic actions. Some customers like Home Depot have already deployed the model, and Google noted a big improvement in handling complex details like alphanumeric product codes in noisy …” View more
Ridealong summary
Google's new Gemini 3.1 Flash Live model transforms voice interactions by enabling real-time dialogue, eliminating the awkward pauses of previous models. This breakthrough is already enhancing customer experiences at companies like Home Depot, paving the way for better personal voice assistants, including Siri. Meanwhile, Shopify's Tinker app empowers small businesses with over 100 AI tools, potentially reshaping perceptions of AI in entrepreneurship.
The AI Daily Brief: Artificial Intelligence News and Analysis · Anthropic Accidentally Revealed Their Most Powerful Model Ever · Mar 27, 2026
Taylor Lorenz’s Power User
“… some of this footage for their own vehicle. own purposes, should they wish to. Wow, that's so scary. That reminds me of, honestly, this case with Google recently. Google, I think it was a Nest camera or something. And this woman, Nancy Guthrie, who was the mom of a famous NBC journalist, was kidnapped. We still don't know what happened to her. But she stopped paying for her Google Nest subscription. And yet somehow they were able to pull the footage. It didn't lead anywhere. But I think everyone was asking, like, wait a minute, you said you don't have access to this footage. It turns out you do …” “… with a competitor in the industry called Motive, they included this image, which is the CEO and CPO of Motive using their system in their own vehicle, which is pretty concerning to me because it suggests that they can review and investigate and access some of this footage for their own vehicle. own purposes, should they wish to. Wow, that's so scary. That reminds me of, honestly, this case with Google recently. Google, I think it was a Nest camera or something. And this woman, Nancy Guthrie, who was the mom of a famous NBC journalist, was kidnapped. We still don't know what happened to her. But she stopped paying for her Google Nest subscription. And yet somehow they were able to pull the footage. It didn't lead anywhere. But I think everyone was asking, like, wait a minute, you said you don't have access to this footage. It turns out you do have access to the footage. just all in their backend systems. Because you can't use the footage, but that footage can use you. Yeah, and be used against you. Exactly. And probably it will never be used in your favor. Another point which I had to raise, which the local news disincluded, was another legal issue with Samsara called Carling v. …” View more
Ridealong summary
AI cameras in school buses raise serious privacy concerns, as they can track students and even review footage for personal use by companies. A recent lawsuit revealed that companies like Samsara can collect biometric data without consent, violating privacy laws. This alarming trend highlights the need for stricter data protection, especially for children.
Taylor Lorenz’s Power User · They're Putting AI Cameras In School Busses · Apr 03, 2026
The AI Daily Brief: Artificial Intelligence News and Analysis
“Like I said, right now the conversation goes to 11. But it wasn't just the negative side of AI that was at 11. Google DeepMind's Seb Cryer shared an article linked from The Australian that went hyper-viral with nearly 13 million views. Vittorio summed it up this way, This is actually insane. Be tech guy in Australia. Adopt cancer-riddled rescue dog months to live. Pay $3,000 to sequence her tumor DNA Feed it to ChatGPT and AlphaFold Zero background in biology Identify mutated proteins Match them to drug targets Design a custom mRNA cancer vaccine from scratch Genomics …” “Like I said, right now the conversation goes to 11. But it wasn't just the negative side of AI that was at 11. Google DeepMind's Seb Cryer shared an article linked from The Australian that went hyper-viral with nearly 13 million views. Vittorio summed it up this way, This is actually insane. Be tech guy in Australia. Adopt cancer-riddled rescue dog months to live. Pay $3,000 to sequence her tumor DNA Feed it to ChatGPT and AlphaFold Zero background in biology Identify mutated proteins Match them to drug targets Design a custom mRNA cancer vaccine from scratch Genomics professor is gobsmacked that some puppy lover did this on his own Need ethics approval to administer it Red tape takes longer than designing the vaccine Three months finally approved Drive 10 hours to get Rosie her first injection Tumor halves, coat gets glossy again Dog is alive and happy Professor, if we can do this for a dog why aren't we …” View more
Ridealong summary
An Australian entrepreneur used AI to develop a personalized mRNA vaccine for his dog Rosie, diagnosed with terminal cancer. With the help of ChatGPT and AlphaFold, he turned a heartbreaking situation into a groundbreaking case study in veterinary medicine, demonstrating the potential of personalized treatment. While Rosie's tumors shrank and her quality of life improved, the story highlights both the promise and challenges of applying AI in healthcare.
The AI Daily Brief: Artificial Intelligence News and Analysis · A Guy Used AI to Cure His Dog's Cancer* · Mar 16, 2026
Hard Fork
“So people who listen to our show are familiar with Demis Hassabis and DeepMind. He's been on several times. What is something non-obvious about Demis that you learned through talking with him through many hours and interviewing many people who know him? I mean, I think maybe the spiritual underpinning for his scientific curiosity is interesting. You know, there was one time when we were sitting in this London park and talking for a couple of hours. And he suddenly started saying, you know, when I'm up at two in the …” “So people who listen to our show are familiar with Demis Hassabis and DeepMind. He's been on several times. What is something non-obvious about Demis that you learned through talking with him through many hours and interviewing many people who know him? I mean, I think maybe the spiritual underpinning for his scientific curiosity is interesting. You know, there was one time when we were sitting in this London park and talking for a couple of hours. And he suddenly started saying, you know, when I'm up at two in the morning at my desk by myself, thinking about science, thinking about computer science, I feel reality is screaming at me, staring me in the face, waiting for me to explain it. And he calls it the goddess Spinoza, that this is the 17th century philosopher Spinoza who said that to understand nature is getting closer to God's creation. And that resonates …” View more
Ridealong summary
Demis Hassabis identifies with a fictional boy genius who saves humanity, revealing his own ambition to do the same with AI. Surprisingly, he shared this connection with his wife, but she sympathized more with the character than with him. This competitive drive, likened to a war against rivals like OpenAI, fuels his quest for AI supremacy.
Hard Fork · The Future of Addictive Design + Going Deep at DeepMind + HatGPT · Apr 03, 2026
TechStuff
“… military metaphors to express his determination to crush the opposition. And I think actually it's going to be a business school case study of how DeepMind made the comeback because they merged DeepMind, the London lab, with Google Brain, the Mountain View Google AI lab. Normally, mergers are super difficult. They don't work. And here was a merger you had to do in the middle of an AI race, which had been kicked off by ChatGPT. You had eight time zones between California and London. You had a record of bitter rivalry between the AI scientists from Google and the ones from DeepMind. And yet they …” “… try and fight back Was he self about the risk of using that language even for himself given all of these Manhattan Project analogies You know, he's a person with many different dimensions, and he's both capable of worrying about safety and also using military metaphors to express his determination to crush the opposition. And I think actually it's going to be a business school case study of how DeepMind made the comeback because they merged DeepMind, the London lab, with Google Brain, the Mountain View Google AI lab. Normally, mergers are super difficult. They don't work. And here was a merger you had to do in the middle of an AI race, which had been kicked off by ChatGPT. You had eight time zones between California and London. You had a record of bitter rivalry between the AI scientists from Google and the ones from DeepMind. And yet they pulled it off. They did the merger, they blended the cultures and within two and a half years they had a model that was outclassing open ai models see that's just extraordinary to me because i remember when the chat gpt moment happened and and i would say up until 2025 beginning of 2025 people were saying google is down and out google might be over i …” View more
Ridealong summary
Elon Musk's actions in starting OpenAI were seen as a betrayal of AI safety efforts, prioritizing competition over collaboration.
TechStuff · How Google DeepMind Accidentally Started the AI Race - The Story · Apr 01, 2026
Search Engine
“… in the morning and thinking, oh crap, these guys are going to eat our lunch. In 2013, then CEO of Uber, Travis Kalanick, had gotten a ride in one of Google's prototype driverless cars. Sitting in a taxi without a human driver, he'd understood that this could mean the end of his company. And so Uber had plunged headlong into the driverless car race. The company hired nearly half of Carnegie Mellon's top robotics lab. And not long after, we also know through court records and emails, that Uber also began communicating with Anthony Lewandowski, who in 2016 would leave Google, quitting just before he …” “… was no market for the product. But competition would soon arrive in the form of Uber. This was the oh shit moment for me. Uber announced their self-driving program. And I remember, like it was yesterday, waking up, reading the news, going to my desk in the morning and thinking, oh crap, these guys are going to eat our lunch. In 2013, then CEO of Uber, Travis Kalanick, had gotten a ride in one of Google's prototype driverless cars. Sitting in a taxi without a human driver, he'd understood that this could mean the end of his company. And so Uber had plunged headlong into the driverless car race. The company hired nearly half of Carnegie Mellon's top robotics lab. And not long after, we also know through court records and emails, that Uber also began communicating with Anthony Lewandowski, who in 2016 would leave Google, quitting just before he could be fired for recruiting team members away, including Don Burnett. Anthony would then start his own autonomous vehicle company. Uber would soon buy that company for almost $700 million, even though the company had no product and was only months old, which raised a mystery. Why would Uber pay so much for a company whose only assets seem to be …” View more
Ridealong summary
Uber's aggressive entry into the self-driving car race changed everything for Google’s autonomous vehicle project. After a ride in one of Google's prototypes, Uber's CEO realized the potential threat to his company and hired key talent from Google, including Anthony Lewandowski. This led to a scandal involving the theft of thousands of technical files, raising serious ethical questions about competition in the tech industry.
Search Engine · Are you a good driver? · Mar 23, 2026
Cult of Mac
“… they've had to have a partnership with Siri. Right. Well, right. But this is now they have to have the partner. They've signed a partnership with DeepMind to run Gemini. and make that kind of their power provider. And obviously, I think they're probably still working on their own frontier models internally. How that will work, we don't know. But the hardware itself, because there are all these open weight models from various companies. Google has some. Quan is a big one. There are a number of companies out there who are doing these things that can be pretty powerful and you can get a lot out of …” “… not true at all. Well, I think it's interesting because there's like, I guess, two different components here, because on the one end, like Apple definitely in terms of their own models is not even part of the conversation. Right. Which is this is why they've had to have a partnership with Siri. Right. Well, right. But this is now they have to have the partner. They've signed a partnership with DeepMind to run Gemini. and make that kind of their power provider. And obviously, I think they're probably still working on their own frontier models internally. How that will work, we don't know. But the hardware itself, because there are all these open weight models from various companies. Google has some. Quan is a big one. There are a number of companies out there who are doing these things that can be pretty powerful and you can get a lot out of them. And if you go to Hugging Face, which is like a great resource just to find people who've tuned local kind of customized AI models that you can run in a cloud or on your own machine, one of the best ways kind of out of the box without having to configure things to get started with that sort of stuff is to get a Mac Mini or a Mac Studio or even …” View more
Ridealong summary
A MacBook user successfully ran a complex AI model with 400 billion parameters, thanks to Apple Silicon's architecture. This innovative use of shared memory allows for astonishing speeds, feeding data at 17.5 gigabytes per second, opening up new possibilities for AI on consumer hardware. This achievement showcases Apple's potential in the AI landscape, despite perceptions of being behind competitors.
Cult of Mac · Surprise! AirPods Max 2 just dropped? · Mar 19, 2026
TBPN
“Does Europe broadly give England enough credit for DeepMind? Because it got rolled into Google so quickly. But I feel like the UK punches way above its weight in terms of AI research with DeepMind. And maybe that's under-discussed? oh i think it's under discussed and i think it's easy people will often post rationalize it and say uh how great it would have been if it had stayed independent but we've got to remember when deep mind was really going in 2012 yeah it was really hard for people to see the …” “Does Europe broadly give England enough credit for DeepMind? Because it got rolled into Google so quickly. But I feel like the UK punches way above its weight in terms of AI research with DeepMind. And maybe that's under-discussed? oh i think it's under discussed and i think it's easy people will often post rationalize it and say uh how great it would have been if it had stayed independent but we've got to remember when deep mind was really going in 2012 yeah it was really hard for people to see the 2017 transformer paper had not been written for five you know years it's early days and so it's easy to look back and say it was obvious it wasn't at the time but i think the person that single-handedly has done as much for tech in the uk as anyone else is demis asabis the founder he insisted on keeping a base here because he knew the technical talent …” View more
Ridealong summary
DeepMind's founder, Demis Hassabis, has significantly boosted the UK's AI research landscape by insisting on keeping operations in England, fostering a 'multiplier effect' in the field. New ventures like Neolabs are emerging from this foundation, suggesting a bright future for innovation and collaboration in AI technology. This evolution highlights the UK's underrated role in the global AI ecosystem.
TBPN · Samsung Invests $70B in AI Chips, The Cubanator Joins, Apple: Behind in AI, Ahead in Revenue | Mark Cuban, John Kim, Eugen Alpeza, Ari Herbert-Voss, Alex Konrad, Carl Eschenbach & Pat Grady, Jim Cantrell, Tom Hulme · Mar 19, 2026
TBPN
“… dumpster fires where you just pour money in and it just sucks all resources and you get nothing out. And then some reshape businesses entirely. DeepMind's a great example. And there's certainly others in the Mag7 that have really really changed the business And so Yeah Gabe said it seems like the entire Boring Company is a side quest Yeah it technically a separate company but Elon yeah king of side quests Yeah, I mean, it feels like the company that gets the least amount of attention, that's not on the critical path for many of the other projects. Totally, totally, yeah. Still a very cool idea. …” “… here all day long. TBPN simulator, that's a side quest. What was the other simulator? Jeremy Giffon simulator, that was a side quest. You know, they're just fun. Some of them are good for marketing, good for attention, good for fun. Some are complete dumpster fires where you just pour money in and it just sucks all resources and you get nothing out. And then some reshape businesses entirely. DeepMind's a great example. And there's certainly others in the Mag7 that have really really changed the business And so Yeah Gabe said it seems like the entire Boring Company is a side quest Yeah it technically a separate company but Elon yeah king of side quests Yeah, I mean, it feels like the company that gets the least amount of attention, that's not on the critical path for many of the other projects. Totally, totally, yeah. Still a very cool idea. I mean, every time you're sitting in traffic, it's so tangible to know, oh, like if we just had more. Creating a yearning for the mines, basically. Yes, yes, yes. But very, very difficult. And I mean, it's been, what, over a decade? And there's really like a very limited rollout of that technology. So, but it's still cooking. I think the business …” View more
Ridealong summary
AI side quests, like Tesla's premium tequila, can reshape entire businesses. While some projects waste resources, others, like DeepMind's innovations, showcase the potential for significant breakthroughs. This highlights the importance of experimenting quickly to discover the next big AI product.
TBPN · AI Side Quests, Zaslav's Payday, SF Housing Market is Back | Shyam Sankar, Gili Raanan, Anna Patterson, Jake Loosararian, carried_no_interest · Mar 17, 2026
Digital Disruption with Geoff Nielson
“… to now combine and shift those materials in different ways that we just were not able to before. And we do this computationally. Believe it or not, DeepMind, which is the big, robust research arm of Google that is doing, I think, some of the most impressive AI work out there, they happen to be the ones also applying some of that work to biology. So just as there's a chatbot, go to ChatGPT or Claude or whatever and put in a prompt and get out some stuff on the other end. There is something called Evo2, which is a model where you can kind of do the same thing. But the prompt that you write in is for …” “… us to intervene in a real meaningful way. It is that has been changing. So artificial intelligence and biology have intersected. And because we know a lot about biology, we know the language of biology, RNA, DNA, molecules, proteins, it's possible to now combine and shift those materials in different ways that we just were not able to before. And we do this computationally. Believe it or not, DeepMind, which is the big, robust research arm of Google that is doing, I think, some of the most impressive AI work out there, they happen to be the ones also applying some of that work to biology. So just as there's a chatbot, go to ChatGPT or Claude or whatever and put in a prompt and get out some stuff on the other end. There is something called Evo2, which is a model where you can kind of do the same thing. But the prompt that you write in is for the purpose of getting something biological out on the other end. This unlocks unbelievable opportunity for us, ranging from new materials. So, you know, in the near future, I've seen some really interesting research on wood that is clear. Um, you know, uh, and totally different types of enzymes that can break down materials in other ways that …” View more
Ridealong summary
Programmable biology is revolutionizing how we interact with nature, allowing us to engineer organisms for better resilience and efficiency. With advancements from AI, like DeepMind's Evo2, we're on the brink of creating materials and crops that can combat climate change and improve human health. This emerging field offers unprecedented opportunities that could redefine our future.
Digital Disruption with Geoff Nielson · AI Convergence: Amy Webb On Why This is the Year of Creative Destruction · Mar 16, 2026
Lenny's Podcast: Product | Career | Growth
“… to figure out how to build a bomb, they'll figure it out. You just keep trying until it works. I will say one positive thing. There was a paper that Google DeepMind put out a couple of years ago, the Camel paper, which proposed a way of building one of these agents that didn't assume that you can fix prompt injection and their solution was that the you sort of split the agent into the privileged agent that knows that you talk to and that can do interesting things and then you have this quarantined agent that can that gets exposed to the militants instructions but can actually do anything useful and then …” “… teaming where they test models and he's just like this isn't this is never going to be solved. And because if somebody is motivated enough, to your point, if there's like a 97% chance you can get it, but there's that 3% of people that are motivated to figure out how to build a bomb, they'll figure it out. You just keep trying until it works. I will say one positive thing. There was a paper that Google DeepMind put out a couple of years ago, the Camel paper, which proposed a way of building one of these agents that didn't assume that you can fix prompt injection and their solution was that the you sort of split the agent into the privileged agent that knows that you talk to and that can do interesting things and then you have this quarantined agent that can that gets exposed to the militants instructions but can actually do anything useful and then the way it works is the privileged agent effectively writes code for you should do this then you should do that then you should do this And that code is evaluated in a way that tracks what tainted So it makes sure that once a potentially dangerous instruction has gotten in, the next action the human has to approve. Because human in the loop helps a …” View more
Ridealong summary
The normalization of deviance in AI usage could lead to a catastrophic event, similar to the Challenger disaster, as we continue to rely on unreliable systems without facing consequences. Despite predictions of impending failure, no major incidents have occurred yet, creating a false sense of security. However, innovative solutions like Google's Camel paper suggest ways to mitigate these risks, emphasizing the need for human oversight in high-risk scenarios.
Lenny's Podcast: Product | Career | Growth · An AI state of the union: We’ve passed the inflection point, dark factories are coming, and automation timelines | Simon Willison · Apr 02, 2026
The AI Daily Brief: Artificial Intelligence News and Analysis
“… AGI 2, we are starting at ground zero. None of the frontier models can complete this test with any level of competency, each scoring less than 1%. Google DeepMind's Xiao Ma shared one of Gemini's playbacks, which are all publicly available in the replay section of the ARC website. She wrote, Poor Gemini Straight thought it was playing Activision Tennis. Now, not everyone is a fan of how this is set up. Lassan Al-Gyve Scaling01 writes, The scoring of ARC AGI 3 doesn't tell you how many levels the models completed, but how efficiently they completed them compared to humans, actually using squared …” “… ARK wrote, ARK AGI 3 gives us a formal measure to compare human and AI skill acquisition efficiency. Humans don't brute force, they build mental models, test ideas, and refine quickly. How close AI is to that? Spoiler, not close. And unlike ARK AGI 2, we are starting at ground zero. None of the frontier models can complete this test with any level of competency, each scoring less than 1%. Google DeepMind's Xiao Ma shared one of Gemini's playbacks, which are all publicly available in the replay section of the ARC website. She wrote, Poor Gemini Straight thought it was playing Activision Tennis. Now, not everyone is a fan of how this is set up. Lassan Al-Gyve Scaling01 writes, The scoring of ARC AGI 3 doesn't tell you how many levels the models completed, but how efficiently they completed them compared to humans, actually using squared efficiency. meaning if a human took 10 steps to solve it and the model 100 steps then the model gets a score of 1%. The implication, they write that this means scores are not comparable to the first two ARC tests. On the other end of the spectrum AI researcher Brandon Hancock commented on the elegance of the benchmark. He writes An alien species with zero …” View more
Ridealong summary
Apple's integration of Google's Gemini models into Siri suggests a strategic shift, but skepticism remains about the models' utility for Apple's unique vision.
Apple's partnership with Google on AI models gives them more flexibility than expected, but skepticism remains about the utility of Google's Gemini models for Apple's specific needs.
Apple's partnership with Google on AI models for Siri is deeper than expected, but there are doubts about the usefulness of Google's Gemini models for Apple's unique vision.
The AI Daily Brief: Artificial Intelligence News and Analysis · Why AI Needs Better Benchmarks · Mar 26, 2026
The Home Service Expert Podcast
“… or I'm sorry, you talked to about 40 people and then you're trying to close maybe two of those. Yeah. Just numbers. And we had a whole system like a Google Maps, and you could look at every home. It would pull up, and you would click a pen on the home, and you could see the customer. You could leave notes for each one. We could also- Was it some rabbit sales rabbit? No, we came up with it ourself. But we knew we could get data to tell us, because in door-to-door, right, that the key is to the retention. You're trying to figure out how to have better retention. and so there are about 10 different …” “… going to close one out of 40 or whatever. Sales reps, like you're probably going to knock 120 doors in a day, 60 of those doors, you know, someone will. Or home. Yeah. And then of those, you know, maybe you're going to talk to 20 people probably, or I'm sorry, you talked to about 40 people and then you're trying to close maybe two of those. Yeah. Just numbers. And we had a whole system like a Google Maps, and you could look at every home. It would pull up, and you would click a pen on the home, and you could see the customer. You could leave notes for each one. We could also- Was it some rabbit sales rabbit? No, we came up with it ourself. But we knew we could get data to tell us, because in door-to-door, right, that the key is to the retention. You're trying to figure out how to have better retention. and so there are about 10 different data points that we would collect uh you know from different data providers that would tell us about each home the sales order doesn't know what all those things are they just know is there a green you know pin on top is it okay to knock or if it's red they're not allowed to knock it oh yeah because you're trying to make sure they're going to retain …” View more
Ridealong summary
David Royce reveals how a data-driven approach transformed his pest control business into a $500M success. By leveraging detailed customer data and creating a structured sales manual, he empowered his team to close more deals and improve retention rates. This systematic method not only streamlined operations but also enhanced overall sales performance.
The Home Service Expert Podcast · Psychology Tricks That Got My Business to $500M (David Royce) · Apr 10, 2026
Tech Brew Ride Home
“… this lecture called the Halloween scenario, where he laid out a doomsday scenario with AI. So it's super early, right at the origin story of DeepMind, there is this concern with safety. So that was one co-founder. The other co-founder, very different, is Mustafa Suleiman, who was eight years younger than Demis, didn't have any degree from any university because he'd gotten into Oxford, done a couple of years in almost a Silicon Valley fashion, he dropped out. Very unfashionable to do that in Britain, but he did it. And he came from this interesting Muslim background. His father was a …” “and moved to the Gatsby unit. And so the two met each other. And interestingly, they met at a safety lecture, right? Shane Lick was delivering this lecture called the Halloween scenario, where he laid out a doomsday scenario with AI. So it's super early, right at the origin story of DeepMind, there is this concern with safety. So that was one co-founder. The other co-founder, very different, is Mustafa Suleiman, who was eight years younger than Demis, didn't have any degree from any university because he'd gotten into Oxford, done a couple of years in almost a Silicon Valley fashion, he dropped out. Very unfashionable to do that in Britain, but he did it. And he came from this interesting Muslim background. His father was a semi-literate Syrian cab driver in London. His mother had converted to Islam. There were apparently no books, no music at home, you know, go to the mosque every Friday, very traditional Islamic upbringing. And just through sheer intelligence and again, teaching himself, Mustafa kind of broke out of that. His parents actually left him by himself in London …” View more
Ridealong summary
Mustafa Suleiman, co-founder of DeepMind, overcame a challenging upbringing to become a key player in AI innovation. Abandoned by his parents at 16, he taught himself and eventually dropped out of Oxford to join forces with Demis Hassabis. Their audacious plan? To create artificial general intelligence before AI could even recognize a cat.
Tech Brew Ride Home · The Biography Of Demis Hassabis · Apr 03, 2026
TBPN
“… up. There are certainly plenty of examples of hedge funds that had fantastic teams but could not stick to landing and wound up zeroed. Sophie says, Google shutting down a deep mind hedge fund quit right before they were about to hit it big. It really is this meme. They probably would have printed. Although, it's not like the high frequency trading firms are not using AI or not using. I mean, Jane Street invested in a custom server company or custom silicon company, something along those lines, specifically for high frequency trading. So they have a lot of AI researchers there. And you see this …” “… We could build a hedge fund here. But they decided that it was not compatible with the don't be evil philosophy. It was not core to the mission. And that at some point there is risk associated with active trading. And so you could potentially blow up. There are certainly plenty of examples of hedge funds that had fantastic teams but could not stick to landing and wound up zeroed. Sophie says, Google shutting down a deep mind hedge fund quit right before they were about to hit it big. It really is this meme. They probably would have printed. Although, it's not like the high frequency trading firms are not using AI or not using. I mean, Jane Street invested in a custom server company or custom silicon company, something along those lines, specifically for high frequency trading. So they have a lot of AI researchers there. And you see this with a lot of labs saying, hey, does anyone from the high-focusy trading industry or quant finance want to come work over here? We can maybe start matching your salary, maybe give you a more interesting project that you can actually talk about and people will be potentially excited about. I don't know. Anyway. Bone GPT, the rapper Eater, shared, I …” View more
Ridealong summary
After two years of negotiations, Google granted DeepMind a staggering $15 billion to advance AGI research. This decision came just before a potential hedge fund launch that could have made waves in the finance world, but ultimately, the focus remained on ethical AI development. The humor in the lengthy negotiations highlights the quirky dynamics of corporate decision-making in tech.
TBPN · AI Is Coming for Your Memes, Axios NPM Package Compromised, Claude Code Source Code Leak | Alex Pruden, Qasar Younis, Sebastian Mallaby, Forrest Heath, Dino Mavrookas, Will Ahmed, Jannick Malling, Ryan Daniels, Chris Yu · Mar 31, 2026
Latent Space: The AI Engineer Podcast
“And like, I would say that the one data point I recently had against it is the DeepMind IMO goals, where, so typically, the typical answer is that this is where you start going down the neuro-symbolic path, right? Like one sort of very sort of abstract reasoning thing and one formal thing. And that's what DeepMind had in 2024 with AlphaProof, AlphaGeometry. And now they just use DeepThink and just extended thinking tokens and it's one model and it's in all of them. Yeah, yeah, yeah. And so that was my indication of like, maybe you …” “And like, I would say that the one data point I recently had against it is the DeepMind IMO goals, where, so typically, the typical answer is that this is where you start going down the neuro-symbolic path, right? Like one sort of very sort of abstract reasoning thing and one formal thing. And that's what DeepMind had in 2024 with AlphaProof, AlphaGeometry. And now they just use DeepThink and just extended thinking tokens and it's one model and it's in all of them. Yeah, yeah, yeah. And so that was my indication of like, maybe you don't need a separate system. Yeah. So let me step back. I mean, at the end of the day, at the end of the day, these things are like nodes in a graph with weights on them, right? You know, like- They can be modeled. If you distill it down. But let me just talk about the two different substrates. Let me put you in a dark room, like totally black …” View more
Ridealong summary
DeepMind's advancements in 3D scene generation could drastically reduce costs, making high-quality 3D designs accessible for under a dollar. This technology, which can transform a simple 2D image into a detailed 3D model, may disrupt industries like gaming and film by lowering production costs by orders of magnitude. As a result, we could see the emergence of new companies and markets driven by this innovation.
Latent Space: The AI Engineer Podcast · Inside AI’s $10B+ Capital Flywheel — Martin Casado & Sarah Wang of a16z · Feb 19, 2026

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