MIT's MeMo keeps AI memory separate from reasoning, so teams can upgrade their LLM without retraining and see a 26% performance gain, researchers say.

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 ...

“Large language models (LLMs) have demonstrated remarkable performance and tremendous potential across a wide range of tasks. However, deploying these models has been challenging due to the ...

“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 ...

The popular discourse surrounding Artificial Intelligence companions frequently focuses on the psychological outcome—the ...

Google says its new TurboQuant method could improve how efficiently AI models run by compressing the key-value cache used in LLM inference and supporting more efficient vector search. In tests on ...

Use left and right arrow keys to seek audio. Dell has just unleashed its new PowerEdge XE9712 with NVIDIA GB200 NVL72 AI servers, with 30x faster real-time LLM performance over the H100 AI GPU. Dell ...

Very few organizations have enough iron to train a large language model in a reasonably short amount of time, and that is why most will be grabbing pre-trained models and then retraining the ...

My SBC cluster runs bigger models than a single Raspberry Pi, but the trade-offs are brutal ...