CJ Dulberger

Building Kitchen Cloud | Futurist | Technologist | Alum @UF 🐊 | #AI #VR #AR #EmergingTech #Science #Sustainability #History

[Sakana AI @SakanaAILabs]

Introducing Sakana Fugu: A full multi-agent orchestration system accessible via a single model API.

Our ‘Fugu Ultra’ model matches the performance of Fable and Mythos, delivering frontier capability without the risk of export controls.

Try it: https://t.co/hhO6qTawgb 🐡

[Cursor @cursor_ai]

We're excited to join forces with @SpaceX to advance the frontier of useful AI. Expect significant improvements to Cursor soon.

[Anthropic @AnthropicAI]

The US government, citing national security authorities, has issued an export control directive to suspend all access to Fable 5 and Mythos 5 by any foreign national, whether inside or outside the United States, including foreign national Anthropic employees.

The net effect of this order is that we must abruptly disable Fable 5 and Mythos 5 for all our customers to ensure compliance.

Access to all other Claude models is not affected.

We apologize for this disruption to our customers. We believe this is a misunderstanding and are working to restore access as soon as possible.

Read our full statement: https://t.co/bwn0sximKZ

[ElevenLabs @ElevenLabs]

Introducing Avatars in @ElevenCreative.

The best AI voices, now with a face. Create studio-grade talking videos from a script, a voice, and an avatar - all in one place.

[Josh Woodward @joshwoodward]

The new killer NotebookLM feature: easily being able to expand your search beyond your own source files

Then, with today's update, you can also make new output formats: PDFs, DOCX, XLSX, PPTX, charts, etc.

We want NotebookLM to keep helping you do better research

[Anthropic @AnthropicAI]

Our internal data shows Claude is accelerating AI development—a possible path to recursive self-improvement, or AI autonomously building a more capable successor.

It’s happening faster than we thought, and the implications deserve greater attention. https://t.co/OVVPJO7VQx

[SciTech Era @SciTechera]

Wow. This is crazy.

A developer trained an AI agent in simulation and deployed it onto a real robotic air hockey table using reinforcement learning.

This robot can track the puck with millimeter-level accuracy and react in roughly 20 milliseconds, fast enough to challenge even skilled human players.

We’re moving from robots that follow programmed rules to machines that learn strategies in simulation and execute them in the physical world.

[Kitchen Cloud @TheKitchenCloud]

Recipe apps have solved the wrong problem. 🧵

[Andrej Karpathy @karpathy]

Personal update: I've joined Anthropic. I think the next few years at the frontier of LLMs will be especially formative. I am very excited to join the team here and get back to R&D. I remain deeply passionate about education and plan to resume my work on it in time.

[Nathie @NathieVR]

This guy created a VR experience that literally lets you tear down reality.

[Google for Health @GoogleForHealth]

New from @GoogleDeepMind: Announcing AI co-clinician, a research initiative exploring the potential for real-time multimodal AI as an assistive component of the care team. https://t.co/qQzc5fu7O3

[Google DeepMind @GoogleDeepMind]

Algorithms are part of nearly every aspect of life, from the physics of the natural world to planning shipping routes.

Our Gemini-powered coding agent AlphaEvolve has been accelerating progress over the last year - from quantum and biotechnology to logistics and @Google’s AI infrastructure. ↓ https://t.co/CAjvAqJiod

[CJ Dulberger @cjdulberger]

👀

[Claude @claudeai]

We’ve agreed to a partnership with @SpaceX that will substantially increase our compute capacity.

This, along with our other recent compute deals, means that we’ve been able to increase our usage limits for Claude Code and the Claude API.

[Matthew Bromberg @MBromberg]

Today we’re opening Unity AI Beta to the world.

Unity AI is a suite of Unity native tools that are trained in Unity and grounded in your project context. It’s the only AI agent that knows Unity from the inside - because we built it.

Try the beta today: https://t.co/XD1G1B91P8. We can’t wait to see what you build.

[Andrej Karpathy @karpathy]

Fireside chat at Sequoia Ascent 2026 from a ~week ago. Some highlights:

The first theme I tried to push on is that LLMs are about a lot more than just speeding up what existed before (e.g. coding). Three examples of new horizons:

1. menugen: an app that can be fully engulfed by LLMs, with no classical code needed: input an image, output an image and an LLM can natively do the thing.
2. install .md skills instead of install .sh scripts. Why create a complex Software 1.0 bash script for e.g. installing a piece of software if you can write the installation out in words and say "just show this to your LLM". The LLM is an advanced interpreter of English and can intelligently target installation to your setup, debug everything inline, etc.
3. LLM knowledge bases as an example of something that was *impossible* with classical code because it's computation over unstructured data (knowledge) from arbitrary sources and in arbitrary formats, including simply text articles etc.

I pushed on these because in every new paradigm change, the obvious things are always in the realm of speeding up or somehow improving what existed, but here we have examples of functionality that either suddenly perhaps shouldn't even exist (1,2), or was fundamentally not possible before (3).

The second (ongoing) theme is trying to explain the pattern of jaggedness in LLMs. How it can be true that a single artifact will simultaneously 1) coherently refactor a 100,000-line code base *and* 2) tell you to walk to the car wash to wash your car. I previously wrote about the source of this as having to do with verifiability of a domain, here I expand on this as having to also do with economics because revenue/TAM dictates what the frontier labs choose to package into training data distributions during RL. You're either in the data distribution (on the rails of the RL circuits) and flying or you're off-roading in the jungle with a machete, in relative terms. Still not 100% satisfied with this, but it's an ongoing struggle to build an accurate model of LLM capabilities if you wish to practically take advantage of their power while avoiding their pitfalls, which brings me to...

Last theme is the agent-native economy. The decomposition of products and services into sensors, actuators and logic (split up across all of 1.0/2.0/3.0 computing paradigms), how we can make information maximally legible to LLMs, some words on the quickly emerging agentic engineering and its skill set, related hiring practices, etc., possibly even hints/dreams of fully neural computing handling the vast majority of computation with some help from (classical) CPU coprocessors.

[Robert Scoble @Scobleizer]

The future of video games in this paper.

I asked Grok to explain why it is important but in language my stupid brain can understand:

++++++

Grok answered:

Hey kiddo!

Imagine you’re playing a video game and your character can suddenly run, jump, climb walls, grab toys, dance, and fight dragons—all super smooth and real-looking, like a real person or animal. Right now, grown-ups who make games have to draw every single move by hand, and it takes forever and sometimes looks a little stiff or glitchy.

MotionBricks is like a magic super-brain for the computer. It knows 350,000 different moves all by itself and can make them happen crazy fast—like 15,000 times every second! That means the game characters (and even real robots) can move naturally, without weird pauses or sliding feet.

Why is that a big deal?

•Games will feel way more fun and real, like you’re really inside the adventure.

•Robots in the real world will get smarter faster—they’ll be able to walk around your house, pick up stuff, and help people without getting stuck or breaking things.

So it’s like giving video games and robots a giant box of magic Lego moves that build themselves. Pretty cool, right? That’s why everyone is excited! 🚀

[Kitchen Cloud @TheKitchenCloud]

One year of Kitchen Cloud. We started with a simple belief: food waste is a systems problem, and better intelligence can help solve it. We have been building toward something meaningful. Thank you to everyone who has been part of this journey. We are just getting started.

[Google Gemma @googlegemma]

A completely local agent that lives right inside your browser.

Powered by Gemma 4 E2B and WebGPU, it uses native tool calling to:

🔍 Search browsing history
📄 Read and summarize pages
🔗 Manage tabs

100% local. No servers needed!

[Zain Shah @zan2434]

Imagine every pixel on your screen, streamed live directly from a model. No HTML, no layout engine, no code. Just exactly what you want to see.

@eddiejiao_obj, @drewocarr and I built a prototype to see how this could actually work, and set out to make it real. We're calling it Flipbook. (1/5)

[Stitch by Google @stitchbygoogle]

Today, we’re open-sourcing the draft specification for DESIGN.md, so it can be used across any tool or platform. We’re also adding new capabilities.

DESIGN.md lets you easily export and import your design rules from project to project. Instead of guessing intent, agents know exactly what a color is for and can even validate their choices against WCAG accessibility rules.

Watch David East break down this shared visual language in action👇. New capabilities and links in 🧵