Knowledge catalogue
Johny Sroji, the GOAT who made Apple silicon program what it is, is now in charge of all hardware at Apple as Chief Hardware Officer Media Johny Srouji Taking Over as Apple's Chief Hardware Officer as
NEW on Hugging Face: Hardware filters 🖥️ A new Hardware filter on the Models page results to models that fit a specific GPU, CPU, or Apple Silicon chip, so you only see what will actually run on your
Cool new paper from NVIDIA. Looks like agentic coding is moving into hardware design. HORIZON treats hardware design as repository-level code evolution. A Markdown harness becomes a project pack with
It's wild how quickly Etched designed and got the chips out, all within 2 years. They went deep, hardcoding attention into silicon and getting very high MFU. This kind of hardware tailored made for LL
This appears to be a discussion or interview featuring Mina Fahmi sharing insights and advice about hardware development processes related to streaming, likely covering technical considerations, tools
Confidential Computing keeps your data from being tracked or used in three ways: - End-to-end encrypted inference - Hardware-enforced isolation that extends to the GPU with @nvidia Confidential Comput
Comparing hardware on InferenceX just got a massive upgrade. Our new changelog update lets you compare every change for any gpu all on the same chart. Just select any model and GPU config, then select
proud of this launch from a strong team. dedicated hardware for high throughput, low cost search building for the new era of recommenders and agents Dedicated Read Nodes are now generally available. P
Decoupling embedding from ingestion means whatever hardware is on hand can do the work. One script, runtime device check: MPS on Apple Silicon, CUDA on NVIDIA, CPU fallback otherwise. 10K-20K records
This approach will mean that American robotics companies can't access the hardware they need for R&D. Unitree was recently designated as a Chinese military company and its products are a threat to our
What hardware actually powers open-source AI? Not benchmarks. Not vendor marketing. Real-world community usage. We’re launching @huggingface Hardware: → trending GPUs & CPUs → VRAM distribution → infe
Cohere announced Command A+, their most advanced large language model to date, designed with optimization for efficient hardware requirements to enable broader deployment and accessibility. The model
(1/5) FP4 hardware is here, but 4-bit attention still kills model quality, blocking true end-to-end FP4 serving. To fix that, we propose Attn-QAT, the first systematic study of quantization-aware trai
Today, we're kicking off the first phase of the research preview for Model Hardware Standard (MHS): a new standard for AI agents to safely operate physical equipment in scientific research and advance
300,000 AI builders have already added their hardware to HF to instantly see what model they can run locally. To do so, go to https://huggingface.co/settings/local-apps and add your hardware specs. Yo
Qwen 3.8 27B now runs locally inside RunAnywhere! Your app can use the same local AI setup across different hardware. On Mac it runs Swift + mlx. On Windows, Electron + llama.cpp. Different architectu
Open weights = freedom. You can run them on your own hardware. No vendor can pull the plug. No API can deprecate you. No company logs your private data. That's sovereignty. Closed models hand one comp
Open models matter. Ollama works hard with the model creators, hardware partners, and most importantly developers building software leveraging various open models for their own use cases. For my first
Yann LeCun shared details about an early AI prototype project developed over 9 months by a small team in Paris at UMA_Rob, covering artificial intelligence, software, and hardware components. The proj
At UMA, we build and own the full stack, from hardware to software. This allows us to bake safety in at all levels, rather than bolt it on as an afterthought. Because trust is everything when robots s
Hugging Face Jobs integration with LeRobot enables users to run robotics tasks and training jobs on Hugging Face's infrastructure, streamlining the deployment and execution of robot learning models. T
This post highlights four recent improvements to the ecosystem of open-weight large language models designed to run efficiently on consumer hardware, covering developments that make local LLM deployme
OpenAI Robotics is hiring, looking for exceptional full-stack hardware, ops, systems, and ML engineers to help us program and manufacture robots that are useful for society. AI should be able to help
I'm excited about the new @amd Ryzen AI Halo because we need more local hardware for AI builders! There's something fun and exciting about building on your own machines rather than sending to the clou
To run GLM-5.1 locally (744B params, 40B active MoE), full precision needs ~1.65TB disk + enterprise hardware like 8x H200/B200 GPUs. Minimum practical setup: Unsloth 2-bit GGUF quant (~220-236GB). Fi
It is very cool to see llama.cpp on the big stage in todays Windows event! The software and hardware stacks are finally coming together. Our community has put a lot of hard work in the past years and
Project Suncatcher is our moonshot exploring whether we can one day host machine learning infrastructure in space 🚀 To do so, we need to know whether our AI hardware can operate in orbit. Can our TPUs
Day-0 OpenVINO support from @inteldevs! 🥳 Qwen-Image-2.1 is ready to run optimized on Intel hardware. One open-weight checkpoint for both generation and editing. 👇 We're excited to offer Day0 OpenVINO
C/C++ provide direct hardware and memory control with near-zero overhead, delivering the raw speed needed for extreme performance work like AI training stacks. Higher-level languages add layers that c
Open hardware from @huggingface (https://huggingface.co/docs/lerobot/en/so101) + frontier AI = 🔥🔥🔥 i gave astra a robot, a paint brush, and a camera then asked it to paint the golden gate bridge in re
Introducing Z1T: Our first family of transformer-like models made for sparse probabilistic hardware like Z1 Achieving up to 140x energy efficiency gains over GPUs and revealing a new scaling law for s
Our new new one-click local model setup is perfect for use with NVIDIA hardware Local AI agents should be easy to set up. That’s why @NousResearch is bringing one-click local model setup to Hermes Age
Speaking of fine-tuning, we’ve got support on @axolotl_ai. Start training North Micro Vision right away, no hardware required. Find their docs here: https://docs.axolotl.ai/docs/models/cohere-north-mi
My conversation with @ericvishria of Benchmark. Eric has spent a decade investing across software and hardware, backing companies like Fireworks, Sierra, Sunday Robotics, and Cerebras. This one is abo
The administration is very consistent: All aspects of foreign involvement in AI are banned: people (students and employees), hardware and models. And funding is down to a drip and capital allocation i
Grok 4.5 is not yet using our internally developed C/C++ inference software that exact maps to the GB300 hardware. Doubling or more of the current speed is probably achievable. I think AI has just hit
Tesla FSD v14 Lite is rolling out to customers with our AI3 hardware FSD v14 Lite is now rolling out to AI3 early-access customers. Based on the feedback, will rollout to more customers over the next
we're starting to send out invites for the our first Midjourney hardware launch and i feel like im missing some important mutuals. poke me if you haven't gotten an invite and think you should. we have
“.. So now Google and Anthropic pay rent on the hardware Grok couldn't use, and that rent is the AI revenue story SpaceX takes public on Thursday.” 🦔Google signed a deal to pay SpaceX 920 million a mo
Reimagining technology as a catalyst for human connection, @tigrisli designs installations, electronic hardware, and experiences that evoke curiosity and play. See her perfume installation, transformi
A TLDR on LangSmith Sandboxes: ✅ Hardware-virtualized microVM ✅ Kernel-isolated from your services + other sandboxes. ✅ Same SDK and API key as the rest of LangSmith ✅ Any framework or custom code ✅ N
Elon Musk posted on X to recruit engineers and technical talent interested in optimizing hardware performance to join SpaceX. The post encourages those with expertise in achieving exceptional performa
Gary Marcus discusses declining prices for NVIDIA's H100 and H200 AI chips, suggesting that inflated valuations and returns on investment for AI hardware customers are becoming unsustainable as the ma
“The future of AI is going to be local models running on extraordinary desktop hardware.” - @Jason This line from the recent @theallinpod hit hard. For years AI meant sending everything to the cloud,
300,000 AI builders filled their hardware profile on @huggingface and we're sharing the results: http://hf.co/hardware. Excited to see how it evolves in the coming months especially with the explosion
Hugging Face just released @LeRobotHF a humanoid robot you can build for roughly $2,500! A full open stack with hardware, simulation, training environments, runtime tools, datasets and robot learning
Computer is secure by default. Every task runs in its own hardware-isolated sandbox with VPC-level storage and compute separation. Agents are authenticated with short-lived proxy tokens instead of raw
The internet gave language models their data for free. Robots don’t have that. Every trajectory has to be earned through hardware, time, teleoperators, and real consequences. Shrey’s piece on simulati
Claude Opus 4.7 just implemented an AlphaZero-style self-play pipeline from scratch. It did this on consumer hardware in three hours, then beat the Pascal Pons solver 7 of 8 as first-mover on Connect
LM Studio is the most popular way to run open-source LLMs on your own hardware. Your Hermes Agent now runs natively on @lmstudio: auto-discovering your models, loading them on demand with the right co
If you want to build proactive agents on real hardware, come build with us today. We’re co-hosting the Proactive Agent Build Day at @agihouse_org Ambient agents. persistent memory. accessibility. @Eve
Here's how anyone can find models that work for your hardware easily. 1. Go to http://huggingface.co and make an account 2. Models tab to find weights and all compressions 3. Click on your profile on
releasing qwen3.6 35b a3b carnice edition (inspired by @kaiostephens) to enjoy an hermes agent tailored finetuned on unified memory hardware! safetensors and gguf versions (q8, 6,5 and 4) available! f
We push Prefill/Decode disaggregation beyond a single cluster: cross-datacenter + heterogeneous hardware, unlocking the potential for significantly lower cost per token. This was previously blocked by
On July 31, 2026 at 01:40 AM, Twitter user Murtaza Khomusi posted a “throwback” tweet reminiscing about opening his first iPhone in 2007 (“2k7 vibez”) and questioned whether this marked the start of t
Great report from Google and MIT. Co-designing ML models and the accelerators is an exciting research direction. This report introduces Coco, an agent platform TPU architects use for hardware and mode
Introducing Fleet: GPU benchmarking entirely in your browser. Run WebGPU compute kernels drawn from real AI workloads directly on your hardware and earn a personalized card built for your device. Rate
Devin Outposts are now available on NVIDIA Brev. Write and profile kernels, run experiments, serve and fine-tune OSS models, and test against real hardware. Try it out: https://brev.nvidia.com/launcha
Run Devin Outposts on @nvidia Brev to give Devin access to GPU infrastructure for debugging training runs, inspecting GPU state, reproducing failures, and validating fixes on the hardware where the wo
Nvidia's stock rose 2.6% following news that xAI is selling 220,000 used GPUs on the secondhand market, potentially indicating a shift in AI hardware demand or xAI's operational priorities. The report