The Deep View

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-r…

The most coherent AI governance framework we've seen didn't come from Silicon Valley, Washington, or the EU. It came from the Vatican, surprisingly. Pope Leo XIV's manifesto on AI is 44,000 words. The short version: ban AI from making lethal force decisions, avoid power concentration, protect kids, put dignity over efficiency, and recognize that the course of AI is a choice, not an inevitability. Anthropic co-founder Christopher Olah (an atheist) showed up and said: "We need moral voices that the incentives cannot bend." He's right. And right now, those voices are scarce. My full take at @TheDeepView: thedeepview.com/articles/pope-…

⚙️ Special episode alert: Juston Payne, head of @Google AI glasses AI smart glasses have quietly built momentum over the past several years, promising to put artificial intelligence directly in your line of sight. Now, Google has shown us the final product of its first AI glasses, which appear to have a clear competitive edge. Juston, Google's director of product management for XR, joins The Deep View Conversations straight from Google I/O, where the company pulled back the curtain and gave the world a first look at two of the pairs of glasses that will lead the collection when they launch in the fall: a pair from Gentle Monster and one from Warby Parker. Talking with The Deep View's Sabrina Ortiz, Juston discusses how the AI smartglasses came to be, including the collaboration between Samsung, Google, Warby Parker, and Gentle Monster. In addition to discussing details of the new launch, including design, product choices, functionality, the roadmap, and more, Juston also sheds light on the broader AI glasses market and why people should give them a shot. Topics covered: + The thought put into the aesthetics and comfort of smart glasses + What products will be available for users to purchase at launch + How the glasses act as an equivalent of a touchscreen on a phone for interacting with Gemini + The computation offloading strategy that leverages the user’s smartphone + The choice to first launch with an audio-only product rather than in-lens displays + How Google is approaching privacy concerns with the cameras on the glasses + Real-world use cases for AI smart glasses If you want to understand how AI glasses are reshaping the way people connect, this conversation will leave you much more knowledgeable about Google's strategy. 📺 Watch on YouTube: youtube.com/watch?v=SY1CVl… 🎧 Listen in your favorite podcast player: tdv.transistor.fm/episodes/45-go… Subscribe to Deep View Conversations for interviews with the leaders shaping the future of AI, business, and technology. 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

⚙️ New podcast episode: Robert Brooks IV of Lambda In this episode of The Deep View Conversations, we talked with Brooks, Lambda's chief commercial officer, about the massive AI infrastructure buildout now underway. Lambda’s mission is to build supercomputers for superintelligence. But Brooks argues that the story is bigger than GPUs, data centers, and rising demand. It is about why compute is becoming one of the most strategically important resources in the AI economy, and why Lambda believes compute is not a commodity. The conversation goes deep on Lambda’s vision for democratizing AI, why the company invests in research, and how its experience building physical infrastructure shapes what it can offer AI labs, hyperscalers, enterprises, and researchers. Topics covered include: + Why Lambda thinks “one GPU per person” is achievable + The hidden complexity behind modern AI data centers + Why compute demand keeps surprising the industry + His $40,000 robot experiment and what it taught him about the future of work + How AI is changing the way leaders spend their time If you want to better understand the physical and economic foundations powering the AI boom, this conversation is worth your time. 📺 Watch on YouTube: youtube.com/watch?v=BvnQb0… 🎧 Listen in your favorite podcast player: tdv.transistor.fm/episodes/44-ho… Subscribe to Deep View Conversations for interviews with the leaders shaping the future of AI, business, and technology. 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

It's that time of year. @Apple #WWDC2026

On the ground at #google with @sabrinaa_ortiz. So proud of this wonderful soul and grateful to work with her for the past four years!

When you think of @OpenAI, "open models" probably isn't the first thing that comes to mind. But the company has quietly built a credible open-weight lineup that deserves more attention than it's getting. Two days before GPT-5 launched last August, OpenAI released GPT-OSS-120B and GPT-OSS-20B under an Apache 2.0 license. Both are Mixture-of-Experts (MoE) reasoning models. The 20B version runs locally in 16GB of memory on most laptops. The 120B version rivals o4-mini and fits on a single 80GB GPU. When I asked the OpenAI team why these models haven't broken through, they pointed to something interesting: the open-model community gravitates toward models that are easy to fine-tune with supervised learning. GPT-OSS behaves more like a reasoning model with web search, which makes it more capable but harder to customize. It rewards reinforcement learning instead. The OpenAI team said that one of the main reasons for releasing these open models was because some enterprises have workloads that have to be run locally on their own hardware for regulatory and security reasons. My read: As agents consume more tokens and compute gets harder to come by, the economics of running workloads locally is about to get a lot more attractive for a lot more people, especially developers. That means GPT-OSS (and other open models) are likely to get more attention. Full piece in @TheDeepView: thedeepview.com/articles/why-o…

Today for @theDeepView: OpenAI announced it's support of two safety bills, the grand opening of a DC workshop, and outlined it's support for "intelligence as a utility" in a blog post. But with so much power in it's hands, it's important to question the incentives. Read my latest: thedeepview.com/articles/opena…

⚙️ Special episode alert! Senior reporter Sabrina Ortiz (@sabrinaa_ortiz) sits down with Mindy Brooks, VP of Product for @Google @Android, in an exclusive interview on The Deep View Conversations. 📺 Watch on YouTube: youtube.com/watch?v=0JcTQX… 🎧 Listen in your favorite podcast player: tdv.transistor.fm/episodes/43-an… Brooks explains why Google is focusing its AI strategy on Android around saving users small amounts of time across dozens of daily tasks. The conversation explores how Android is evolving from an operating system into a more personalized, context-aware "intelligence system" powered by Gemini. Topics covered include: + Rambler for Gboard, Google’s new AI-powered voice dictation system to rival Wispr Flow + The expansion of Task Automation across more apps + How Create My Widget uses AI to generate custom widgets on demand + How Intelligent Autofill is powered by Gemini's Personal Intelligence + The Android AI feature Brooks personally uses the most

⚙️ New episode of The Deep View Conversations: Dr. Olena Zhu of @Intel. What happens when AI moves from cloud-only to running everywhere, including on your laptop, your phone, and other devices around you? In this episode, senior reporter Sabrina Ortiz sits down with Olena Zhu, who leads AI for the client computing group at Intel, to explore one of the biggest shifts underway in AI: the move toward accessible, affordable, and privacy-first AI systems. Zhu explains why the economics and infrastructure demands of cloud-only AI may not scale indefinitely, and why on-device AI could become a critical part of the industry's future. She also reflects on the evolution from traditional AI systems to LLMs and now to agentic AI, and why this wave feels fundamentally different from the hype cycles that came before it. The conversation also dives into how AI is changing the way people work, learn, and experiment, including the surprising mindset Zhu believes helps people get the most value from AI tools today. Topics covered include: + Why cloud-only AI has limits + The future of on-device and edge AI + AI affordability, energy use, and data sovereignty + How agentic AI changed Zhu’s workflow + Why experimentation matters more than expertise + Intel’s vision for privacy-first AI systems + The hidden infrastructure challenge behind AI growth + Why AI adoption may depend on trust and accessibility If you're concerned about the affordability, accessibility, and privacy of AI, you don't want to miss this episode. 📺 Watch on YouTube: youtube.com/watch?v=VwE7qO… 🎧 Listen in your favorite podcast player: tdv.transistor.fm/episodes/42-wh… Subscribe to Deep View Conversations for interviews with the leaders shaping the future of AI, business, and technology. 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

Exclusive: OpenAI and a coalition of researchers from Nvidia, Microsoft, AMD, Broadcom and Intel, unveiled a new open source networking protocol called MRC, designed to make GPU clusters more reliable and efficient. Already in production at both OpenAI and Microsoft data centers, one OpenAI researcher told @TheDeepView that this protocol is a “critical component” to the company’s compute strategy. 🔗 Read more in our story from Nat Rubio-Licht (@natrubio__) thedeepview.com/articles/exclu…

I've spent the past few weeks reading 100s of public data sources about AI development. I now believe that recursive self-improvement has a 60% chance of happening by the end of 2028. In other words, AI systems might soon be capable of building themselves.

New from @sabrinaa_ortiz: OpenAI just released an upgrade to it's instant model that promises to make ChatGPT more accurate - an important improvement given how many people use the chatbot every day. Read more about it in @theDeepView thedeepview.com/articles/chatg…

In the latest episode of The Deep View Conversations, we sit down with Alex Rinke, co-founder and co-CEO of @Celonis, to unpack one of the most overlooked truths in enterprise AI. Don't miss it: tdv.transistor.fm/episodes/41-wh…

Last month, @TheDeepView published a longform story that raised the red flag about AI power centralizing into too few hands. Yesterday, Sam Altman published a manifesto calling for AI to be decentralized. thedeepview.com/articles/altma…

AWS CEO Matt Garman says we're rapidly moving toward a world of 1 billion agents. And he says Amazon is hiring more developers than it ever has and only sees that accelerating. Amazon is hiring 11,000 roles more broadly in 2026. And "the jobs will be a little different." It will be more valuable to solve customer problems and understand how all the tech pieces fit together. People will spend more time on the highest value things.

NEW: To commemorate Google Translate’s 20-year anniversary, the company launched pronunciation practice, which uses AI to analyze your speech and give you instant feedback. The feature is now available in the US and Infia in English, Spanish and Hindi. Google says it is one of its most-requested features.

⚙️ New episode alert! Analysts, marketers, and business owners face the same question: How do you reach audiences in an era when AI is reshaping how people search and find information they need? That’s a top-of-mind issue for Pat Brown, SVP of global marketing, growth, analytics, and platform at @Adobe. Brown joins The Deep View Conversations to share his unique perspective on the issue, with the expertise of someone who was doing marketing science before it was even called that, and who, in his current role, is responsible for global marketing execution across various forms of media and has to put these skills into practice every day. Pat breaks down how AI is moving beyond content generation to reshape media workflows end-to-end, from audience measurement to agents that automate entire processes. Topics covered: + The role of AI agents in automating marketing workflows + How AI in marketing can augment rather than replace creativity + AI-powered marketing tools that help analyze patterns and signals + Whether AI has “killed” SEO and what that means for marketers’ jobs + The rise of new terms like AEO and GEO in a “zero-click” search world + Why it’s still worth investing in marketing and brand strategy despite AI changes + Why today’s AI-driven SEO landscape feels like the early days of SEO If you want to understand how AI is reshaping and helping individuals connect more effectively with audiences, this conversation will leave you feeling more knowledgeable about those topics. 📺 Watch on YouTube: youtube.com/watch?v=j_vo4W… 🎧 Listen in your favorite podcast player: tdv.transistor.fm/episodes/40-ho… Subscribe to the podcast for weekly conversations with the leaders shaping the future of AI. 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

Another insight on GPT-5.5 from my article on The Deep View: The OpenAI team said the model itself and the company's agentic coding tool Codex were used to build GPT-5.5. This process of the models helping to build themselves is called recursive self-improvement (RSI) and it has long been anticipated as a moment when AI would take a dramatic leap forward. If you're not familiar with RSI yet, it's time to start learning. Full story: thedeepview.com/articles/opena…

For GPT-5.5, let's talk about safety. Because the model is lot more powerful and a lot more agentic, safety had to scale up to match. And the press talked about this with the OpenAI team. In a briefing earlier this morning, OpenAI VP of Research @Mia_Glaese said the company increased its safety protocols to match the new model by undergoing third‑party safeguard testing and red‑teaming for both cybersecurity and bioweapons risks. As a result, the model ships with a stronger set of safeguards and users will see more refusals from the model for cyber‑related misuse attempts. Glaese also said GPT‑5.5 is not cyber‑permissive (unlike Claude Mythos) but has cyber mitigations and is being launched with those protections in place. Basically, the guardrails are stricter and more visible to users, according to OpenAI. I'm confident people on Twitter are going to be kicking the tires on that to see how easily they can hit guardrails.