With reported 3x speed gains and limited degradation in output quality, the method targets one of the biggest pain points in production AI systems: latency at scale.

Researchers from the University of Maryland, Lawrence Livermore, Columbia and TogetherAI have developed a training technique that triples LLM inference speed without auxiliary models or infrastructure ...

AI agents now provision infrastructure and approve actions, but many inherit over-scoped privileges without proper governance ...

AT&T's chief data officer shares how rearchitecting around small language models and multi-agent stacks cut AI costs by 90% at 8 billion tokens a day.

The vulnerability in the Batch amendment's signature validation was found during the voting phase and never reached mainnet, ...

AI API calls are expensive. After our always-on bot burned through tokens, we found seven optimization levers that cut costs by 45-50% without sacrificing output quality.

After a testnet with 700,000 accounts and $50 million in pre-deposits, Decibel begins mainnet trading with an onchain order ...

NYSE’s move toward onchain systems aims to enable faster settlement and more efficient collateral use. Here’s what it could change for trading, risk management and market structure.

Autonomous AI agents with wallet access can trigger irreversible and costly on-chain transactions without human oversight.

When an app needs data, it doesn't "open" a database. It sends a request to an API and waits for a clear answer. That's where FlaskAPI work fits in: building ...