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AI is often sold as a utopian story. Unlimited abundance. Endless productivity. A better future for everyone. But behind that narrative is a very different reality, one driven by power, control, and a race that few people fully understand. We went deep on this topic in our first long-form, written by Nat Rubio-Licht. We believe this is one of the most important AI stories published this year. Read it here: thedeepview.com/articles/the…
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The Deep View retweeted
Anthropic revenue is concentrated among the top 1% of customers, who account for 46% of all spend, up from 25% last August.
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⚙️ New episode: Navrina Singh, CEO of @CredoAI Can AI move fast and still be safe? As the debate over AI safety and innovation grows more polarized, we explore the practical work of making powerful systems accountable. In this episode of The Deep View Conversations, we sit down with Navina to talk about what AI governance means for frontier labs, enterprises, and policymakers. They explore why governance is broader than regulation, how organizations can test and verify their AI systems, and what happens when capabilities advance faster than oversight. Topics covered: • Why Navrina sees AI safety and innovation as goals that can advance together • What the Hugging Face agent incident raises about frontier AI oversight • The “spectrum of trust,” from internal testing to independent audits and regulation • The risk of regulatory capture and the role of open models • How businesses weigh AI capability, cost, and control while managing "governance debt" • How Credo AI uses forward-deployed governance experts to help companies put oversight into practice • Why expertise, taste, and judgment remain valuable as AI takes on more work If you’re building, buying, or governing AI, this conversation offers a practical way to think about trust without losing sight of the technology’s promise. 📺 Watch on YouTube: piped.video/n1_aYOk7w7Q 🎧 Listen in your favorite podcast player: tdv.transistor.fm/episodes/a… Subscribe to Deep View Conversations for interviews with the leaders shaping the future of AI, business, and technology: tdv.transitor.fm And don't forget to sign up for The Deep View daily newsletter. We don’t just cover AI, we decode it. In a world flooded with hype, we deliver sharp, no-nonsense insights to keep you ahead of the curve and help you put AI to work every day: subscribe.thedeepview.com
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The Deep View retweeted
Humbled that @Apple chose to promote our episode on the iPhone Duo and the #AppleEvent in @ApplePodcasts.
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The Deep View retweeted
Here it is: @sabrinaa_ortiz and I broke down what makes the #iPhoneDuo different, Apple's surprising move to make the Apple Watch an AI wearable, and other leading #AI development from this week's #AppleEvent. 📺 piped.video/yc-t_getvQ8 🎙️ tdv.transistor.fm/episodes/6…
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We've got something interesting coming... @TheDeepView @sabrinaa_ortiz @Apple #AppleEvent #iPhoneDuo
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⚙️ New episode alert: Tara Seshan and Ty Geri of @OpenAI AI is transitioning from just answering questions to doing valuable work. The next challenge is making agents more accessible and simple enough that the technical details fade into the background. In this episode of The Deep View Conversations, @JasonHiner sits down with Tara and Ty from the ChatGPT Work team to explore what OpenAI is doing to make advanced agent capabilities useful to a lot more people. We also dig into some of the current challenges and how the team is approaching them. They explain how scheduled tasks and proactive assistance are changing the way people start their workdays, why AI lets teams move from debating ideas to testing prototypes, and how personalized software can turn one-off needs into purpose-built tools. They also discuss the challenge of token costs and model selection, why "super app" isn't the most useful framing for ChatGPT and Codex, and what it will take for agents to become more persistent, proactive, and connected. The conversation also covers: • How OpenAI is trying to bridge local and cloud workflows • Why Tara and Ty start their days with agents instead of Slack • Building personal apps and tools without traditional software overhead • The tradeoff between model capability, cost, and user control • More persistent agents and proactive personal assistance • Connecting agents to email, calendars, enterprise systems and third-party tools • Privacy, security and administrative controls for agentic work If you’re figuring out where agents fit into your work or what has to improve before you trust them with more of it, then this conversation offers a practical look at how OpenAI is preparing for that transition. 📺 Watch on YouTube: piped.video/watch?v=eoAMZUYQ… 🎧 Listen in your favorite podcast player: tdv.transistor.fm/episodes/6… Subscribe to Deep View Conversations for interviews with the leaders shaping the future of AI, business, and technology: tdv.transitor.fm And don't forget to sign up for The Deep View daily newsletter. We don’t just cover AI, we decode it. In a world flooded with hype, we deliver sharp, no-nonsense insights to keep you ahead of the curve and help you put AI to work every day: subscribe.thedeepview.com
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The Deep View retweeted
Home robots make the highlight reels. Factories make the case. Our CTO Pras Velagapudi on the "islands of automation" — the manual gaps between automated steps — and why humanoids earn their place there first. Thank you, @theDeepView @natrubio__ #AgilityRobotics #DigitRobot Read more: thedeepview.com/articles/ins…
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⚙️ New episode: Sameer Samat (@ssamat) of @Google @Android The smartphone has been built around apps and taps for nearly two decades. Google believes AI will fundamentally change that. In this episode of The Deep View Conversations, @JasonHiner talked with Samat, president of Android ecosystem at Google, about what the company means when it says it's transforming Android from an operating system into an intelligence system. Samat explains why the next generation of computing could shift us from micromanaging our devices to simply telling them what we want to accomplish. We dig into how AI agents could navigate apps and complete multistep tasks and why those agents need to follow us across phones, computers, cars, watches and glasses. And what happens to the app-centric model that has defined smartphones for the past 15 years? We also get into some of the practical ways this is already taking shape. Samat discusses Google’s app automations and Rambler, the new Google Keyboard experience that can turn your voice brain-dumps into polished text. He also explains how Google is thinking about permissions, sandboxing and human oversight as AI agents gain the ability to take action on our behalf. The conversation goes well beyond the phone. We talk about why smart glasses and cars could be especially powerful interfaces for AI agents, what Google learned from the original Google Glass, and why the best AI features may be the ones consumers barely think of as AI. Other topics covered include: • How AI is already changing work inside Google • Why product managers can now build functional prototypes themselves • Samat's favorite overlooked AI tool • His "calendar cleanse" strategy for getting time back If you’re trying to understand where mobile computing goes next, what AI agents will actually look like on phones, and how Google plans to weave intelligence across devices, this conversation offers insights into what the company is building and why. 📺 Watch on YouTube: piped.video/hlbuo_KbDPs 🎧 Listen in your favorite podcast player: tdv.transistor.fm/episodes/5… Subscribe to Deep View Conversations for interviews with the leaders shaping the future of AI, business, and technology: tdv.transitor.fm And don't forget to sign up for The Deep View daily newsletter. We don’t just cover AI, we decode it. In a world flooded with hype, we deliver sharp, no-nonsense insights to keep you ahead of the curve and help you put AI to work every day: subscribe.thedeepview.com
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⚙️ New episode: Zuzanna Stamirowska of Pathway What comes after large language models? In this episode of The Deep View Conversations, we talked with Stamirowska, CEO and co-founder of Pathway, to explore why her team believes today’s dominant AI architecture has fundamental limits, and what it could take to move beyond them. Pathway is developing Dragon Hatchling, a new architecture designed to give AI native memory, continual learning, and a different approach to reasoning. Stamirowska explains why today’s LLMs can appear to remember without actually internalizing what they learn, why reasoning through language creates its own constraints and costs, and how Pathway is trying to build models that can think in a more abstract way. The conversation looks at how those architectural changes could affect hallucinations, interpretability, safety, and the enormous compute demands of modern AI. Stamirowska shares how her background in complex systems and game theory shaped Pathway’s approach, why the company made an early bet on challenging the transformer, and how the AI coding revolution has already radically changed the way her own team works. Topics covered: • Why transformers struggle with memory and continual learning • How Pathway’s Dragon Hatchling architecture works • How a different architecture could reduce compute costs • How interpretability could make advanced AI more predictable • Why Pathway’s engineers have largely stopped writing code themselves • How Stamirowska uses Codex, Claude Code, and other AI tools • Why leaders should be ruthless about identifying the critical path If you’re interested in what could come after today’s LLMs, and whether the next big leap in AI will require more than simply scaling transformers, this conversation offers a fascinating look at one of the teams betting on a fundamentally different path. 📺 Watch on YouTube: piped.video/fjB6sEPC4CE 🎧 Listen in your favorite podcast player: tdv.transistor.fm/episodes/5… Subscribe to Deep View Conversations for interviews with the leaders shaping the future of AI, business, and technology: tdv.transitor.fm And don't forget to sign up for The Deep View daily newsletter. We don’t just cover AI, we decode it. In a world flooded with hype, we deliver sharp, no-nonsense insights to keep you ahead of the curve and help you put AI to work every day: subscribe.thedeepview.com
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The Deep View retweeted
The energy at the #Ai4 conference this week matched the intensity of the AI movement in 2026, and I walked away with several clear takeaways. Nat Rubio-Licht (@natrubio__) and I represented @TheDeepView, moderated panels, met with AI companies, partnered with @hiddenlayersec to host a dinner for AI leaders, wrote articles, and recorded a podcast episode in a quiet corner of The Venetian. Here are some of the insights I learned from talking with so many interesting folks at Ai4: + A number of companies are quietly working on what's next after LLMs to solve for their shortcomings + There's still quiet tokenmaxxing happening at companies that are seeing massive productivity gains by untethering the right engineers from token caps + What software engineers spend their time on has completely flipped from this time last year; the best ones are now orchestrators and prioritizers + The ROI pain is still real for AI projects but it's not slowing down investment in AI; companies are still seeing enough to convince them that AI transformation will yield big results + If you learn the latest best practices for prompting AI, you can basically get an idea of what will be in the next models + One example of the above that works right now, is when you have an important topic (or if you're ever unsure about a response you get from a chatbot), simply ask a follow-up question: "Review this as a skeptical expert in [field]" or "Recheck your answer step by step and identify any mistakes." If you were at @Ai4Conferences this week, what were your top takeaways?
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The Deep View retweeted
A look at OpenAI's open-source agent harness that now powers Codex and ChatGPT Work, as the company works to optimize the harness to cut runaway token usage (@jasonhiner / The Deep View) (Visit Techmeme dot com for the link and full context!)
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Ahead of Samsung Unpacked, I went hands-on with Samsung's new AI glasses, and they look promising. TLDR; To the touch, they felt pretty light and they look good. I wasn't able to try them on or test any of the features, so that will have to wait until they launch in the fall. Functionally, they seem to operate similar to the Meta Ray-Bans, since they also lack in-lens displays and sport a camera, open-ear speakers and microphones. Candidly, I am hoping that between now and the actual launch, Samsung will try harder to differentiate itself from Meta. Samsung has deep expertise in hardware, and it'd be great to see them use that to drive the category forward rather than simply making their own version of something that's already been done.
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LIVE: "What we're seeing is that the rate and pace of agentic AI adoption is much, much faster than any of us thought... And every customer conversation is telling us that this buildout is just beginning." @LisaSu at @AMD Advancing AI event
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"Today I'm excited to announce that #Helios is in full production." — @LisaSu @AIatAMD Helios is @AMD's competitor to @Nvidia's flagship #VeraRubin AI system for training (and running) the next AI models. "Customer demand for Helios is extremely strong," said Su.
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The Deep View retweeted
Here at the opening keynote of @AMD Advancing AI event where @LisaSu is about to talk about where AI goes next.
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The Deep View retweeted
This is the bigger picture. Filing "Most nations risk becoming AI dependents" under #mustread AI and #technews via @natrubio__ @thedeepview. thedeepview.com/articles/mos…
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The Deep View retweeted
We have information that Moonshot AI distilled Anthropic’s Fable for the development of its K3 model. To do this they developed a sophisticated internal platform to conduct large scale distillation against U.S. models, allowing them to quickly switch between multiple methods of access to avoid detection. Moonshot AI has also acquired GB300-equipped servers and has accessed GB300s in Thailand, likely to train its AI models.   The United States strongly supports the free and fair development of AI, including a thriving competitive ecosystem that spans frontier models, specialized systems, open-source frameworks, and open-weight models. Legitimate AI distillation used to create smaller, more efficient models plays a vital role in this open innovation ecosystem. However, large-scale, covert industrial distillation aimed at stealing proprietary U.S. technology and undermining American research is unacceptable.
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The Deep View retweeted
I'm glad @DemisHassabis put forward such specific recommendations on how to police frontier AI models going forward. I break down his proposals on @TheDeepView. There's been too much fear mongering about AI in 2026 and not enough people putting forward actual proposals and being willing to have them put under the microscope. The world needs creative thinking and bold ideas to start more public dialogue around the future of AI. If we want to see AI take a different trajectory, then it's up to all of us to engage in the dialogue. thedeepview.com/articles/dem…
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In the legal complaint filed today, Apple eviscerates OpenAI with a trove of evidence showing an illegal campaign of stealing its trade secrets. It's hard to look at this lawsuit in any other light until OpenAI comes forward to defend itself. thedeepview.com/articles/app…
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