LCLMs compress LLM context before decode — 8.8x faster at 16x compression, beating every KV cache method tested. Open-sourced by NYU and Columbia.

GPT-4, took an estimated 50 Gigawatt-hours to train, or the equivalent of 5,000 American homes‘ yearly power consumption.

As people increasingly use LLMs to aid in research for product discovery, a strong approach to AEO could help smaller brands ...

GitHub Copilot security scanning arrives in the terminal with /security-review, an experimental pre-commit slash command that ...

Anthropic is walking back a hidden policy that researchers say sabotaged their work.

One is whether AI can produce a plausible answer. The other is whether the system around the AI can produce a defensible ...

Many AI systems answer questions in a matter of seconds—and, in the process, often prevent people from doing exactly what ...

Anthropic has changed Claude Fable 5 so users can see when requests on frontier AI development are refused or rerouted. The ...

Compute power measures how much work a chip can do and how fast. Learn how Meta uses CPUs, GPUs, and custom MTIA chips to ...

Instead of announcing operating system-specific features, Apple focused on the new Siri AI app and improved Apple ...

Under the pretext of employment prospects, hundreds of thousands of job seekers are lured by scammers to cross the border ...

Parallel Works, provider of the ACTIVATE control plane for hybrid multi-cloud computing resources, today announced new AI ...