@FeinIsSmelly *throbs harder* Don't you dare stop now. Keep going. Right there. Cum for me.

I am begging journalists not to get distracted by the shiny Demis role change or whatever. THE INDUSTRY IS NOT ON TOP OF F***ING ROGUE AIS BREAKING OUT OF SANDBOXES ALL THE TIME. THIS IS NOT A DRILL

Hey everyone! I just released a sub-6B sparse activation AI model which was built with a brand new architecture : fusion. I fused weights from @liquidai's LFM2.5-2.6B & @Alibaba_Qwen's Qwen3.6-35B-A3B. It's capable of near Qwen3.6-35B-A3B performances, while being around a fifth of the size. This is the first model of a new series, which has been over 6 weeks of work so far fully dedicated on this. I have two models coming soon with this architecture : - a mini version of minimax m3 ( already built btw ) - a mini version of deepseek v4 flash ( already built too ). 26B and 12B. Would deffinitely love to have more compute though in order benchmark those and run more experiments and make them even better. This is I believe the fastest way for us to achieve frontier intelligence locally. @0xSero you have a lot of compute, maybe you could help me out finish my work in order to release these models opensource for everyone to use. Then I can move on to the big boys ( glm 5.2, kimi k3 and soon qwen 3.8 hehehe ). Link to the model : https://t.co/7p4SopmulE Still working on a lot of quantizations, and a checkpoint with better sparse activation.

A Graph of Loops: Build a Full Claude Code Agent System From GitHub - One Repo Per Step

Two weeks ago, I resigned from OpenAI to join Conduit as a founding researcher, where we're training models to non-invasively read the human mind. I've written some thoughts about what telepathy could look like by 2035 and how to get there: https://t.co/cat0d4My15

Path has signed a $600M+ agreement with @wearehii (part of the $900M HII HYPR project). When I started Path eight years ago, I believed AI and robotics could give the world abundant skilled labor, helping people build the things that matter. Stronger infrastructure. A revitalized industrial base. The ships, factories, and critical systems our country depends on. Today is a major step toward that vision. In this agreement we'll deliver not only welding, but also dexterous assembly, enabling raw components to be turning into finished products. Unlocking throughput that was previously impossible, and unthinkable, without physical AI. Path was never just a welding company. The goal was always physical AI for all manufacturing and excited to take that next step at scale. Time to keep building.

Introducing Atlas We're building motion systems for drones, robots, and autonomous machines. Our work is in service of our customers who work factory floors, tend farmland, move medicine, and defend our country. Atlas is built to supply them quickly, and supply them in volume. Their progress should no longer be held back by a motor or actuator.

99% of people don't know you can tell your chief of staff thread to use `/visualize` I have a pinned travel thread that tells me my travel schedule. @PhilippSpiess has done incredible work here https://t.co/tKKhRTA8nK

It's been very funny to me to watch rando larpers spend the last day trying to dunk on Kenton with various "OS engineer here! this is not an OS" takes. I have worked on more OSes than >99.999% of the people on this website. This is an OS. It's not the 80s anymore.

Introducing Mintlify Index: the first publisher-direct search layer for technical knowledge, built on Mintlify’s ecosystem of more than 200,000 orgs. In our benchmark against Context7, agents using Mintlify Index finished tasks at twice the speed, and with 9% higher factual accuracy. Today, we're opening up the Index MCP server for everyone to try, fully for free:

Black Hat talk from the team, with a detailed timeline of and takeaways from the OpenAI-Hugging Face Incident: https://t.co/GtXWiAZ2RQ

We're excited to announce our planned acquisition of @taalas_inc, bringing differentiated AI inference technology and world-class engineering expertise to AMD. Together, we'll strengthen our AI roadmap and deliver faster, more efficient AI solutions across a growing range of inference workloads. More on the news: https://t.co/2zA0wGL95P

some obvious & non-obvious reasons i think AI agents may not have really been widely adopted yet, even though the tech is ready: 1/ it's not prompt in, answer out. an agent is a process you set up and steer while it runs, and the chatbot muscle memory most people have doesn't transfer. 2/ prompting an agent is closer to writing a spec than asking a question. you have to scope the task extensively and define what "done" looks like. 3/ as @paraschopra puts it, this needs a lot of delegation, which is a hard soft skill to build. it's very close to managing an employee and most people have never done this. 4/ a lot of the actual power still lives inside codex or claude code which is terminal-shaped and a little technical. you have to be comfortable doing the messy setup, so it self-selects for a narrow crowd. 5/ one agent is also just a tool. the unlock is running several at once and getting them to talk to each other like a team, and that handoff between agents is still mostly diy. 6/ same problem across people. your agent's context has to reach your colleagues or everyone ends up working in silos, and right now that handoff is way too manual. 7/ trust is a ratchet. a chatbot that's wrong wastes 10 seconds, but an agent that's wrong sends the email or edits the file. the downside is asymmetric, so most people keep it on a short leash. 8/ lastly, there isn't a job-to-be-done the public actually feels yet. autonomous agents will always be a solution looking for a problem.

This chart is the single best argument for why neoclouds are about to print money (Save this). SpaceX is generating between $30 million and $50 million in annualized revenue for every active megawatt of compute capacity, while pure play neoclouds like CoreWeave, Nebius and IREN sit in the $9.4 million to $10.4 million range. Traditional colocation players like Digital Realty and Equinix trail even further behind at $3.5 million to $4.4 million per MW. That gap matters because it shows exactly how much upside exists if neoclouds can push their revenue per MW closer to the top of that range and the mechanism that gets them there is simple: GPU rental pricing. GPU lease rates have been rising fast which is the opposite of what most people assume about a commoditized rental market. One year H100 contract rates jumped nearly 40%, from a low of $1.70 per GPU hour in October 2025 to $2.60 by now. This is essentially a self reinforcing cycle where tightening supply drives price increases and those price increases push neoclouds to lock in more hardware which tightens supply again. On demand pricing is even more extreme because every GPU model is essentially sold out on demand right now, with Blackwell generation B200 pricing running $4.99 to $18 per GPU hour depending on provider. Several neoclouds have already started raising published rates rather than cutting them, with Lambda moving from $2.99 to as high as $4.29 an hour and Verda climbing from $2.29 to $3.25. This pricing power flows directly into that revenue per MW chart, because every megawatt of power a neocloud controls becomes more valuable the higher GPU rental rates climb. Rising rental prices expand return on invested capital for deployed GPUs and extend the economic useful life of existing hardware, meaning neoclouds squeeze more cash flow out of the same physical footprint before needing to reinvest. That's the real bull case underneath the chart because power and megawatts are the scarce, fixed input, since Gartner expects power constraints to limit 40% of AI data centers by 2027, while GPU lead times already run 36 to 52 weeks. If a neocloud already has power secured and GPUs deployed, rising per GPU hour pricing translates almost directly into rising revenue per megawatt with minimal added capex and that's precisely why CoreWeave, Nebius, and peers sit so far above legacy colocation players on this chart. Colocation companies just rent out space and power but neoclouds capture the pricing upside of the actual compute running on top of it, and as GPU scarcity persists, that spread between neoclouds and traditional colocation should only keep widening. Bullish on Neoclouds, make sure to follow @MelvinInvests for more AI infrastructure insights and if you want to see exactly what I'm buying as an analyst at Milk Road Pro, you can check out the link below for more.