Distributed training on M4 Mac Mini cluster We implemented... Google DeepMind DiLoCo on Apple Silicon to train large models with 100-1000x less bandwidth compared to DDP baseline. AI is entering a new era where a distributed network of consumer devices can train large models.show more

Running DeepSeek-V3 on M4 Mac Mini AI Cluster 671B... MoE model distributed across 8 M4 Pro 64GB Mac Minis. Apple Silicon with unified memory is a great fit for MoE.show more

A teaser of DeepCoreCloud! With 100+ GPUs in a... high-performance cluster, we’re bringing 24/7 AI computing to the world. Train models, deploy AI, and scale without limits! DeepCoreCloud is built for innovators. The future of AI infrastructure is almost here. Are you ready? #DeepCoreCloud #ItronixAI #GPUClustershow more

Cluster Protocol 🤝 StarLandAI We're forming a strategic alliance... with StarLand.AI StarLandAI is a generative AI network that supports running large models on decentralized computational power, offering MaaS (Model as a Service) API services for partners to easily build on-chain generative AI Dapps. 🤖🦾 Together, we are creating a more efficient and scalable environment for developing AI-driven applications. Stay tuned for groundbreaking AI innovations!show more

Canter 2B is a photography-oriented text-to-image model being trained... on just a single GPU by data-archetype 🐎 are we entering the indie ai models era? still training, the v0002 checkpoint is available, more to come ▶️ play on spacesshow more

As a supporter of the open weights ecosystem, we're... proud to be a post-training partner for NVIDIA Nemotron. We post-train Nemotron models for customer use cases, de-risk mainline RL runs on our AC2 platform and training stack, and contribute aggregate workload statistics for inference benchmarking. This is how open models get better, and we're excited to keep working closely with NVIDIA AI.show more

🚀 From smartphones to servers, each connected node fuels... the AI of tomorrow. 💡 In this new era, compute is the new oil and Hyra AI is building the pipeline with a decentralized network where your idle devices become powerful engines for AI. Explore more 👉show more

A 27-year-old guy from China bought 100 Mac minis... and turned his apartment into a server hub Instead of furniture, the space is filled with neat racks where a hundred Mac minis hum like a living organism, processing gigabytes of data in a continuous stream Many small AI startups in Asia cannot afford to train models on NVIDIA H100 servers: it is insanely expensive He provides his Mac minis for running and fine-tuning small, highly specialized models. He takes on the dirty work of data labeling and quality assurance by using his network of agents that check each other's work > His initial investment was $59,900 > He was able to recoup his costs in 3 months Right now, his average income is $25,000–$30,000 per month He is not a genius: he simply found a niche with high demand and created an offershow more

Announcing our $320M Series A at a $2.3B valuation,... led by Khosla Ventures, with General Catalyst, Eric Schmidt and Jeff Bezos. General Intuition is the frontier lab for acting in space and time. We build large action foundation models trained on billions of ground truth action-labeled gameplay clips from 17M monthly active users on Medal, and push the frontier of world models to generate infinite training environments.show more

☀️Very proud of the team for training 5.6! A... few of my highlights: - Great front-end aesthetics. E.g., I asked Sol to make a new blog for 5.6 with a celestial theme. - Much better CUA - Can work for much longer and is less lazy But it's not all great: - The writing quality has improved, but it's still bad in artifacts - Too many options with models/reasoning/fast mode/Cerebras/multi-agent We'll fix the above. What else should we improve? PS: belated post as there are so many other good models to train.show more

We found a new way to get language models... to reason. 🤯 No RL, no training, no verifiers, no prompting. ❌ With better sampling, base models can achieve single-shot reasoning on par with (or better than!) GRPO while avoiding its characteristic loss in generation diversity.show more

"It's on my todo to build my own stack... of apple minis and run Llama on my own little cluster on my desk." - Garry Tan Quick AI homelab tutorial: - Install EXO Labs on each mini (open source, steps in README) - Make sure all the minis are on the same WiFi network or for faster/more reliable results, connected over Thunderbolt/Ethernet. Devices will auto-discover each other and auto-shard the LLMs. - Now you can chat to your cluster with your preferred LLM GUI (the tiny corp tinychat ships with exo)show more

today's sota coding models train on hundreds of thousands... of coding simulation sandboxes all you need to do so is a sandbox where the agent solves problems (vLLM + openenv + opencode), a trainer (TRL) and a verifier to check solutions we just teach you how to do it for free (no need to thank it's ok)show more

Success! 🍎🤖 I can now control Unitree robots on... a Mac Mini M4 running macOS with a simple tweak! The unitree_sdk2_python ( thread implementation isn’t essential—getting the DDS subscriber and publisher to work is enough. I replaced Unitree’s Linux thread logic with a simple Python while loop for sensor reading and robot control. Here’s a video of me controlling a Go2 robot on macOS (M4 Mac Mini) using a Python script for low-level control and sensor reading.show more

1/ Gemini 2.5 is here, and it’s our most... intelligent AI model ever. Our first 2.5 model, Gemini 2.5 Pro Experimental is a state-of-the-art thinking model, leading in a wide range of benchmarks – with impressive improvements in enhanced reasoning and coding and now #1 on Arena by a significant margin. With a model this intelligent, we wanted to get it to people as quickly as possible. Find it on Google AI Studio and in the Google Gemini for Gemini Advanced users now – and in Vertex in the coming weeks. This is the start of a new era of thinking models – and we can’t wait to see where things go from here.show more

✨ Every time the video models get better, the... try on model on Photo AI also becomes a lot more useful, as a large % of my customers now are e-commerce store And showing clothes in a video is nice for sales! With AI this means stores don't need to do expensive shoots flying a model and entire camera and light crew around the world They can just upload a few photos of their models, then upload the clothes, and describe the setting (like a beach in Thailand) and in less than 10 seconds it's generated, for a video in less than a minute! Below is the input: a dress laid flat, and output: a full video shootshow more

World Models are the path for some AI Models... in the future. But how can we efficiently train these models to not only see the world the way humans do but to see the world in a new and unique way. By visualizing, what is normally sequenced audio patterns, we can derive much more insights. Here we see Paganini in a visual form that can than be described and transcribed into a World Model. We can observe connections in a manner that may not have been clear prior to the digitalization of music and sound in this way. The company with the most valuable potential in building a World Model is Tesla. Not that this type of visualization is being used, but that the mechanisms are in place, and the technology is in place for the company to thrive in this new form of AI.show more

With the introduction of AI-powered features on Taobao and... Tmall, this year's 11.11 is all about ensuring a smarter and more seamless shopping experience! 🛍 From personalized shopping lists to virtual try-ons, we're entering a new era of e-commerce that makes consumer shopping easier and more personal!show more

Traditional physics-based models struggle with extreme rainfall, often overestimating... light events while underestimating extreme precipitation. Our new hybrid climate model, NeuralGCM, more accurately simulates extreme rainfall, mean precipitation (with a 40% bias reduction compared to CMIP6 models), and the diurnal cycle of precipitation. These improvements are a direct result of training the model on NASA satellite observations, not just reanalysis data.show more

We are entering an extremely exciting era for open-weight... models. Kimi K2.6 now feels like a top agentic model. I took it for a spin via Fireworks AI fast inference APIs. Kimi K2.6 has impressive agentic capabilities, design skills, and the ability to synthesize large amounts of information. I built a little Skill that produces survey papers on any AI research topic you want. (see example in the clip) You can use the skill to tell your agent to generate a survey on whatever topic and watch it go to work. The artifact was fully generated by Kimi.ai's Kimi K2.6. It's cheap and fast. Next step for me is to explore ways to continue integrating the capabilities of these models on use cases like automating my LLM knowledge bases and augmenting my agent memory capabilities. Stay tuned for more.show more