The Deep View

Intelligence for the age of intelligence.

[The Deep View @theDeepView]

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:
https://t.co/CRTAJUFh9t

[Jason Hiner @jasonhiner]

One of AI's biggest surprises of 2026 is the Mac mini becoming the icon of the AI agent explosion.

What's been less surprising, even if it's under the radar, is how Apple silicon keeps stacking up win after win with the people and teams powering the AI boom.

I talked to Apple about it, and wrote a story on @TheDeepView.

🔗 Read the exclusive:
https://t.co/W5VRx0O9Ak

[The Deep View @theDeepView]

The Deep just published its 3rd exclusive of the week.

Learn how #AppleSilicon keeps quietly stacking up wins across the AI ecosystem and how it has positioned itself for the next stage of the AI boom where on-device AI will play a bigger role.

🔗 https://t.co/Wuw16j0rVf

[The Deep View @theDeepView]

Behind the current AI boom is a developer community that both uses and builds powerful tools. Google recently released a wave of new developer-focused AI tools at Google I/O, but one person has gone further: fostering an entire online community.

Google's Logan Kilpatrick joined The Deep View Conversations podcast straight from Google I/O, not only to share more insights on the new products but also to draw on his rich quilt of experiences to address the broader AI space, the future of software engineering, the developer community and more.

While Logan's official role is as a member of technical staff at Google DeepMind, he has become a well-respected voice in the developer community, accumulating over 320K followers on X and constantly engaging with users. Prior to joining Google, Logan worked for NASA, OpenAI, Apple, and other AI startups, making him a builder at his core.

Topics covered in this episode:
+ 'Vibe coding' compared to agentic engineering
+ The capabilities of Google's new Gemini 3.5 Flash
+ The internal "flywheel" at Google, where teams use AI to accelerate the development of products
+ The differences between AI Studio and Project Antigravity
+ The need for developers to regularly "reset their level of ambition”

If you want to understand the distinction between rapid prototyping and managing million-line production codebases with AI, this conversation will leave you much more knowledgeable about the principles of agentic engineering.

📺 Watch on YouTube: https://t.co/urPnbHwBfU
🎧 Listen in your favorite podcast player: https://t.co/UqeA6kZUhy

Subscribe to Deep View Conversations for interviews with the leaders shaping the future of AI, business, and technology: https://t.co/nLQWo5Aq8M

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: https://t.co/EqClu8hTsa

[Jason Hiner @jasonhiner]

It's official. @Nvidia is not a GPU company.

At @ComputexTaipei, the company talked more about CPUs than GPUs. And then there were world models, robotaxis, and the OS for the datacenter.

Nvidia wants the whole AI stack.

My latest for @TheDeepView:
https://t.co/8zkng45Ge1

[The Deep View @theDeepView]

See how @Twelve_Labs just unveiled new tools to help fight AI slop by making it easier and faster for creators to produce and edit real video.

This is an exclusive from The Deep View's Nat Rubio-Licht (@natrubio__).

🔗 https://t.co/HW14XDafGr

[The Deep View @theDeepView]

⚙️ New episode: @IanSilber of @OpenAI

In the latest episode of The Deep View Conversations podcast, senior reporter Nat Rubio-Licht (@natrubio__) sits down with Ian, who leads product design at OpenAI, to explore how ChatGPT is evolving for the future.

Silber explains why designing for AI requires a different mindset than designing traditional apps. Instead of treating the model as something behind the interface, he says designers now have to think of the model itself as part of the material they work with. That shift changes everything from product decisions and user experience to ethics, safety, and human judgment.

The conversation also covers Silber’s experience at @Instagram, how that shaped his approach to building fast-growing consumer products, and how OpenAI’s design team is thinking about the next phase of @ChatGPTapp, including more proactive and agentic experiences. Silber also shares how he personally uses AI in his work, from brainstorming design principles to prototyping ideas with #Codex.

Topics covered:
+ How OpenAI approaches product design for ChatGPT
+ Why AI changes the traditional design process
+ What designers can learn from fast-growing consumer products like Instagram
+ How ethics, safety, and responsibility show up in AI design
+ Why human judgment will become more important as AI tools improve
+ How Codex and image generation are changing prototyping workflows
+ What young designers should know as they enter the AI era
+ Why curiosity and adaptability matter in a fast-changing industry

If you’re a designer, product leader, builder, technologist, or anyone trying to understand how AI is changing creative work, product development, and human decision-making, you don’t want to miss this episode.

📺 Watch on YouTube: https://t.co/nm4Ynd0Bet
🎧 Listen in your favorite podcast player: https://t.co/ISGbAwfF8E

Subscribe to The Deep View Conversations for interviews with the leaders shaping the future of AI, business, and technology: https://t.co/nLQWo5Aq8M

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: https://t.co/EqClu8hTsa

[Jason Hiner @jasonhiner]

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: https://t.co/mdNOJKwtX5

[The Deep View @theDeepView]

⚙️ 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: https://t.co/Pb1EJVcbKc
🎧 Listen in your favorite podcast player: https://t.co/TsXcje7V9R

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: https://t.co/EqClu8hTsa

[The Deep View @theDeepView]

⚙️ 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: https://t.co/tqLyPlz9nm
🎧 Listen in your favorite podcast player: https://t.co/UQrftLXuoG

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: https://t.co/EqClu8hTsa

[Jason Hiner @jasonhiner]

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

[Jason Hiner @jasonhiner]

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!

[Jason Hiner @jasonhiner]

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:
https://t.co/eE2lspy5aF

[Nat Rubio @natrubio__]

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: https://t.co/83He3bdP6W

[The Deep View @theDeepView]

⚙️ 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: https://t.co/JLlzhux8Vh
🎧 Listen in your favorite podcast player: https://t.co/R8asbMIwNc

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

[The Deep View @theDeepView]

⚙️ 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: https://t.co/JLlzhux8Vh
🎧 Listen in your favorite podcast player: https://t.co/R8asbMIwNc

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

[The Deep View @theDeepView]

⚙️ 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: https://t.co/yZe4gOrQim
🎧 Listen in your favorite podcast player: https://t.co/MXrEodb5PN

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: https://t.co/EqClu8hTsa

[The Deep View @theDeepView]

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__)
https://t.co/DdluhTsQLT

[Jack Clark @jackclarkSF]

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.

[Nat Rubio @natrubio__]

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 https://t.co/CiQpVFPjkX

[The Deep View @theDeepView]

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:
https://t.co/Xwqu5n0Z5q