MIT's MeMo framework trains a compact memory model that boosts LLM performance by up to 26.73% without retraining, with major implications for crypto AI agents.

Researchers used large language models to efficiently detect anomalies in time-series data, without the need for costly and cumbersome training steps. This method could someday help alert technicians ...

Researchers at the Massachusetts Institute of Technology (MIT) are gaining renewed attention for developing and open sourcing a technique that allows large language models (LLMs) — like those ...

Large language models already read, write, and answer questions with striking skill. They do this by training on vast libraries of text. Once that training ends, though, the model’s knowledge largely ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Dany Lepage discusses the architectural ...

Researchers at MIT have developed a framework called Self-Adapting Language Models (SEAL) that enables large language models (LLMs) to continuously learn and adapt by updating their own internal ...

DeepSeek today released an improved version of its DeepSeek-V3 large language model under a new open-source license. Software developer and blogger Simon Willison was first to report the update.

Bulls**t Automation: Generative AI services are tickling the imagination of every single CEO in the tech industry right now. They are expected to replace millions of workers and automate almost ...

The original version of this story appeared in Quanta Magazine. Two years ago, in a project called the Beyond the Imitation Game benchmark, or BIG-bench, 450 researchers compiled a list of 204 tasks ...

CAMBRIDGE, MA - Identifying one faulty turbine in a wind farm, which can involve looking at hundreds of signals and millions of data points, is akin to finding a needle in a haystack. Engineers often ...