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How to build custom reasoning agents with a fraction of the compute
Training AI reasoning models demands resources that most enterprise teams do not have. Engineering teams are often forced to choose between distilling knowledge from large, expensive models or relying [...]
Microsoft's new AI training method eliminates bloated system prompts without sacrificing model performance
In building LLM applications, enterprises often have to create very long system prompts to adjust the model’s behavior for their applications. These prompts contain company knowledge, preferences, a [...]
How an Oregon court became the stage for a $115,000 showdown between Meta and Facebook creators
Some of the most successful creators on Facebook aren't names you'd ever recognize. In fact, many of their pages don't have a face or recognizable persona attached. Instead, they run pa [...]
The best streaming deals: Get 50 percent off MasterClass subscriptions, plus save on Starz, Audible, Crunchyroll and others
Whether you’re a true cord-cutter or you just want to watch the next season of Stranger Things when it drops, everyone’s on the lookout for streaming deals nowadays. Plenty have chosen VOD and liv [...]
Researchers baked 3x inference speedups directly into LLM weights — without speculative decoding
As agentic AI workflows multiply the cost and latency of long reasoning chains, a team from the University of Maryland, Lawrence Livermore National Labs, Columbia University and TogetherAI has found a [...]
Why LinkedIn says prompting was a non-starter — and small models was the breakthrough
LinkedIn is a leader in AI recommender systems, having developed them over the last 15-plus years. But getting to a next-gen recommendation stack for the job-seekers of tomorrow required a whole new [...]
MIT's new fine-tuning method lets LLMs learn new skills without losing old ones
When enterprises fine-tune LLMs for new tasks, they risk breaking everything the models already know. This forces companies to maintain separate models for every skill.Researchers at MIT, the Improbab [...]