Connecting UX and Workflow with AI Models #AI #huggingface #stablediffusion #mistral #llm #whisper youtu.be/wkaQZnSgBvk?feature…

This is a direct consequence of Anthropic's scaremongering as a PR strategy I assume this will be reverted soon enough, maybe after some supposed additional nerfing of the model, but still a terrible precedent, even if it might boost Anthropic's value pre-IPO once the model comes back (we're so good the government had to do this) The most surprising part is all foreign employees essentially not being able to do any work now. I can't imagine that even Anthropic expected that one, given how much foreign talent they hire in general (and even research superstars that don't have citizenship like Karpathy) Also a bit unclear how much of this isn't just payback for the previous Ant-US gov confrontation that gave Ant really good PR at the expense of the gov. We'll have to wait to see if OpenAI's next release faces similar restrictions

GLM-5.2 is Fully Open, Frontier Intelligence Belongs to Everyone Today, the sudden restriction of certain frontier models is deeply regrettable. At a time when access to frontier models is abruptly cut off for non-technical reasons, we are even more convinced of one thing: science should be global. The path to AGI (Artificial General Intelligence) must never be enclosed by high walls. We have always believed that AGI should be the cornerstone for all of humanity to collaboratively explore the boundaries of intelligence and solve complex challenges, rather than a privilege monopolized by a few rules and subject to revocation at any moment. In the face of external blockades and restrictions, our attitude is one of radical openness. Frontier intelligence must remain open-source, accessible, and buildable, serving every dedicated developer. GLM-5.2 is Zhipu's most capable open-source model to date. It not only supports a truly usable 1M context window but also maintains a continuous lead in the independent completion of long-horizon tasks, providing solid foundational support for building complex agent applications. It also continues to be our main engine for creating the strongest domestic coding model. Tonight at 5:21—at this special moment—GLM-5.2 will officially be available to all GLM Coding Plan users (including Lite / Pro / Max). The API will also go live next week. A step closer to frontier intelligence for everyone. The future of AI is open, and it is for the people. ModelKey: GLM-5.2

mythos will be bad ON PURPOSE on ai "frontier llm research" tasks, this is very very sad for the research community also the fact that this is un purpose not visible to the user is crazy

Brilliant idea! Next up: Apple randomly reboots your Mac if you're building competing tech, Gmail silently edits your email if you mention rival platforms, and Tesla Autopilot swerves if it detects you're working on self-driving cars. All in the name of safety, of course. Because malicious actors controlling the world’s operating systems, inboxes and cars would be extremely dangerous!

Scientific research is fundamental to advancing civilization and helping people globally to solve the most critical problems, from medicine to materials, from brain science to physics, and much beyond. This is only possible when scientists have access to the best tools of the time to conduct scientific research, including having access to AI-based tools.

BREAKING NEWS: Anthropic's latest model will NOT help you if it thinks your ML research/ML engineering is interesting, and/or will secretly degrade its IQ so that the average engineer won't notice. We are already seeing Anthropic's latest model's moderation filters our GPU inference research and programming 😭

Today we're shipping Nemotron 3 Ultra. A 550B MoE frontier-intelligence open model built for long-running agents. It delivers 5x faster inference and lowers the cost of complex agentic tasks by up to 30% versus other open frontier models.

San Diego built more apartments per person than any CA metro last year—and rents fell 2.2%, dropping the city from 5th to 12th priciest nationally.

The fallacy of this is that more creates more. More hours, more hiring, more something. And it is true in a sense. If you put in more work, more work will happen. But I think for most startups, the leverage is really in how differently you approach the problem, how well you cultivate your team, and the strategy. Any large company can outspend you on hours. They have thousands or tens of thousands more people, spending more hours. If hours worked were the metric, every large company and government organization would always win and do the best work. More hours, better output. This thinking is often representative of younger founders, where the startup becomes their identity and life. They have a hard time doing anything else, and cannot understand that your work is not the person that is you. But activities outside of work can grow you as a person too and make you do better work. I’ve never worked this way. As a designer, I always saw the need to take a step back, to take a break. At times, I might work 12 hours or 16 hours, or whatever amount was needed, but it wasn’t the norm. You just can't grind design, you need inspiration. But taking that step away from the work, would give me more perspective, inspiration and I could approach the problem differently or I could just see the solution. Grinding is never good for any creative problem, and startups or creating new products are often mostly about creative problem solving. Grinding works ok for email jobs, or where you just executing on very clear playbook. With Linear, we’ve never worked this way. We work reasonable hours, 5 days a week. All of us founders have families. Many of our employees have families. I personally stop every evening, spend time with the family, cook dinner for the family, eat dinner together, and focus on things outside of work. Sometimes I work in the late evenings or weekends, but to me the pride is that I don’t need to. Company should be succesful without it. My goal is to build a company that is sustainable in the long term, and doesn’t require heroics or personal sacrifices every single day. There are times when our team is heroic. Launches, incidents, some other work that just needs to be done. They will work late into the night because they know it is the right thing. But we don’t require that every day or every week, and the more this happens, the more I think it is a failure of our company and leadership. The team and the leaders should always keep a reserve to use when something is needed. Our thinking was also that quality, which we value, doesn’t emerge from working more or stressing people more. It emerges when you create the conditions for it to emerge. Often it is the appreciation, space, time, and how the person feels. A person who is rested will do better work. I wouldn’t attribute much of our success to working a lot. The success came from having clear thinking, ideas, and focus to do the right things. I sometimes wish we could move the culture more toward a Zen master. Real mastery is not exerting the most effort. It is achieving the outcome with the least necessary effort.

A very cool model for the GPU poor bros Trained on an ungodly amount of tokens for a 8b a1b model Gonna be super fast excited to try this out huggingface.co/LiquidAI/LFM2…

The road to Hell is paved with closed-source citadels disguised as good intentions. The Pope is right: AI takes on the characteristics of those who build it, finance it, and regulate it. So the question is: who gets to hold the great and wonderful power of AI? If the answer is a handful of closed source companies, murkily censored, quietly surveilling every step of our lives, every private conversation, enshrined in law as 'safe' and 'open' when they're nothing but the surveillance economy squared, then all we've done is build a few modern East India Companies, digital oligarchies of the few, cloaked in the language of safety. Open Source and Open Weights are how you spread the fantastic enabling power of AI to everyone, everywhere. Permissionless innovation. Everyone gets the hammer and nails to build houses and churches and factories. The more hammers, the more widely spread, the more the decentralized genius of humankind can flourish. Everyone gets the Printing Press. The printing press singlehandedly uplifted and spread of intelligence and knowledge around the world. The more we could record all kinds of knowledge, the more we spread the ability to read, the more equal and advanced society became. Before the press, knowledge was learned by one person and passed into dust with them when they died or passed only to only a small group of students. When we only had monks in a cave copying religious texts, a closed system, it limited the spread of intelligence and limited the growth of civilization. The printing press was the single greatest invention in the history of the world because it let anyone print anything and spread knowledge throughout the whole world. AI can do the same, but only if we build the bazaar, and never let the citadel people convince the world that they're the special people who should control who gets access to intelligence while pretending they're building the bazaar. What the world needs now is more intelligence, more widely spread and more widely available. Open is the way. And it always has been. And the road to Hell was always built with walls, towers, spiked gates and moats so that only the few could enter.

🦙 llama.cpp now has a BUILT-IN model router ♠ and it completely replaces Ollama Open WebUI for model switching 🔹 One server, one config file, any model on disk 🔹 Switch models instantly without restarting anything 🔹 Zero duplicate model storage across backends 🔹 Full per-model control via a simple INI file 🔹 Native llama.cpp performance, no abstraction layer 🔥 Watch the full video below 👇 youtu.be/V2t_YRsyqeI

I’m so glad AI killed LeetCode interviews. For 10 years, tech companies made every engineer grind the same puzzles and prove they could invert a binary tree from memory. Today, the dumbest AI model can walk in and one-shot the entire interview. Thank you, AI.

This is going to be a little bit long, but I want to give hope to my fellow anxious ML engineers. We see a lot of propaganda on how this or that AI one shotted something, about how incredibly strong the models are getting and how we don't even need to review PRs and we can just ship to production. Although this can be true for some cases, its also far from being representative of all the challenges we have to face. I started using claude code 4 month ago, and quickly realized how it really does change the way we work. I can experiment 10x faster, fix small issues without coding and refactor code without sweating. BUT, these tasks were "just" tedious and not hard. The challenge in my day to day work is to take a research code and integrate it into transformers using our standards. Its challenging because code beauty is abstract and subjective just like a philosophy. By relying too much on claude, and on how seemingly good the code it produces look, I pushed the deepseekv4 integration without realizing that claude really did not understand the model. I gave it access to `transformers`, the original paper, the original code, the different blog posts and my past chats and skills created to add a model, a b200 node node and a LOT of tokens, but it did NOT nail it. It did not understand the eager attention path, it did not understand the basics of causal attention. It was even wrong implementing the manifold constrained hyper connections. It helped to reduce the burden of exploring implementation and debugging but it did not help reason around the model. I am not a doomer, I think our job as Software Engineers has never been this great, I am just saying that we still have a job, and we should still be a bit careful when it looks to good to be true 😉

Like the fact that they are doing something different and saving valuable time when interacting with AI

Thinky's secret plan: 1: Increase Human<->AI bandwidth 2: Raise ceiling of human AI intelligence 3: Help humans continue as main-characters in the new world We are at Step 1. Interaction Models are great real-time collaborative tools for humans. Here's a preview:

Looks interesting. Good to research in non turn based models. It gets tiring to wait for the model to finish it's turn to prompt it or steer it with more information.

Pi was built when there were already agent harnesses around. Here’s why Mario Zechner(@badlogicgames), found them suboptimal and built Pi, a minimalist self-modifying agent: #1 - Mario initially was a believer in Claude Code: "I was a believer in Claude code because they were the first that packaged agentic search up in a really compelling package. And at the time that fit my workflow really well. Everything around the LLM was kind of nice and tidy and easy to understand. I was super happy. I was proselytising Claude code." #2 - Reverse engineering Claude Code highlighted the degradation that Mario felt as a user: "I personally like simple tools that are stable and that I can rely on. Even if they have non-deterministic parts, all the deterministic parts should be as stable as possible. That was just not the experience with Claude Code around summer 2025. They would take away your control of the context. They would inject stuff behind your back, which is bad. Then, your workflows stopped working because there's now a system reminder that you don't even see in the UI that would modify the behaviour of the model. They would also do this to the system prompt. I built a little service where I can track the progression or evolution of the system, prompt and tool definitions and, with every release, it was messing with stuff. That just messed with my workflows and I don't appreciate that." #3 - PI was built with an appreciation for simple and reliable tools: "If I commit to a development tool, I want it to be a stable, reliable thing like a hammer. I don't want my hammer to break a different spot every day. That's terrible. We need somebody who goes the full velocity kind of way. But I don't want to work with a tool like that."

Jensen is one the smartest and most far seeing folks the world. "If an AI scientist warns people that AI is going to permeate across radiology and radiologists are going to get wiped out, it might seem helpful but it's hurtful. If we convince everybody not to be radiologists and we now need radiologists, that actually is hurtful to society. "It is hurtful to convince all the young college graduates not to study software engineering because we are going to need more software engineers than ever. That's hurtful." "Scaring people with nonsensical things, which are not going to happen, that this is an existential threat, there's a 20% chance that is is existential, that's ridiculous. "That it's going to wipe out 50% of college level jobs. "That is it going to completely destroy democracy. "These kinds of comments are not helpful. They are made by...CEOS. And you become a CEO, maybe you adopt a God complex and somehow you know everything." Brutal. And right.

This is a great thing