It is also the industry’s first benchmark to measure investigation performance in a lab environment mimicking an enterprise, with investigations autonomously retrieving data from live tools across the ...

“This is the first time someone’s doing this,” he says of making a large-scale error-corrected quantum computer. IBM’s road map involves first building smaller machines before Starling.

Discover the impact of large language model (LLM) agents on AI reasoning and test time scaling, highlighting their use in workflows and chatbots, according to NVIDIA.

LiteLLM allows developers to integrate a diverse range of LLM models as if they were calling OpenAI’s API, with support for fallbacks, budgets, rate limits, and real-time monitoring of API calls.

I’m trying to figure out the correct way to measure the actual execution time of each GPU during inference. I used the following script to run GPT-2 inference with 4 GPUs and 4-way tensor parallelism, ...

Whether we should trust AI - particularly generative AI - remains a worthy debate. But if you want a better LLM result, you need two things: better data, and better evaluation tools. Here's how a chip ...

Yale University, Dartmouth College, and the University of Cambridge researchers have developed MindLLM, a subject-agnostic model for decoding functional magnetic resonance imaging (fMRI) signals ...

Large language models evolved alongside deep-learning neural networks and are critical to generative AI. Here's a first look, including the top LLMs and what they're used for today.

Speculative sampling is revolutionizing AI with 3x faster text generation, balancing speed, accuracy, and energy efficiency.

In conclusion, FastDraft addresses the critical limitations of LLM inference by introducing a scalable, resource-efficient framework for training draft models. Its innovative methods of pre-training ...