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.

Content creators and IP holders are getting creative in order to fight back against the LLMs that are trawling their data ...

Researchers from Meta and Google built AutoTTS to automatically discover optimal LLM reasoning strategies, cutting token ...

Security professionals have spent two decades defending against human attackers who use automation as a force multiplier. That model is obsolete. The adversary now fielding against every ...

The expansion of large language models (LLMs) is creating a new problem for power grids: electricity demand from AI data ...

The engineering team at Meta recently outlined how the company migrated a data ingestion platform that transfers several petabytes of MySQL social graph data daily to improve reliability and ...

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.

OpenAI saw off ⁠Elon Musk’s ​legal challenge to ​its pivot from non-profit to private company. Yet ​its original ​open-source ...

Sometime in early 2026, an autonomous AI agent connected to a public-facing WebSocket endpoint, received a full interactive shell without entering a single credential, and used that access to extract ...

Chinese aerospace researchers have introduced a new system that leverages Large Language Models (LLMs), ...

AutoTTS, a framework from Meta, Google, and university researchers, cuts LLM token usage by 69.5% while maintaining accuracy, with implications for AI-driven crypto tools.

Organizations need to internalize a simple principle: Calling an LLM API is a data transfer. You're trusting the provider with every piece of information included in that context window. The data ...