A research article by Horace He and the Thinking Machines Lab (X-OpenAI CTO Mira Murati founded) addresses a long-standing issue in large language models (LLMs). Even with greedy decoding bu setting ...
Forged in collaboration with founding contributors CoreWeave, Google Cloud, IBM Research and NVIDIA and joined by industry leaders AMD, Cisco, Hugging Face, Intel, Lambda and Mistral AI and university ...
The company tackled inferencing the Llama-3.1 405B foundation model and just crushed it. And for the crowds at SC24 this week in Atlanta, the company also announced it is 700 times faster than ...
“Large Language Model (LLM) inference is hard. The autoregressive Decode phase of the underlying Transformer model makes LLM inference fundamentally different from training. Exacerbated by recent AI ...
Users running a quantized 7B model on a laptop expect 40+ tokens per second. A 30B MoE model on a high-end mobile device ...
A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
Researchers from the University of Maryland, Lawrence Livermore, Columbia and TogetherAI have developed a training technique that triples LLM inference speed without auxiliary models or infrastructure ...
FuriosaAI Inc., a semiconductor startup that’s laser-focused on artificial intelligence, has unveiled a new accelerator chip it says is geared for large language models and multimodal AI. Its new chip ...
This mini PC is small and ridiculously powerful.
MOUNTAIN VIEW, Calif.--(BUSINESS WIRE)--Enfabrica Corporation, an industry leader in high-performance networking silicon for artificial intelligence (AI) and accelerated computing, today announced the ...
A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...