Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025) ...
MemRL separates stable reasoning from dynamic memory, giving AI agents continual learning abilities without model fine-tuning ...
The Anthropic philosopher explains how and why her company updated its guide for shaping the conduct and character of its ...
Rebecca Qian is the Co-Founder and CTO of Patronus AI, with nearly a decade of experience building production machine ...
Reinforcement learning frames trading as a sequential decision-making problem, where an agent observes market conditions, ...
The Rho-alpha model incorporates sensor modalities such as tactile feedback and is trained with human guidance, says ...
Humans&, a startup that believes AI should empower people, not replace them, has reportedly raised a $480 million seed round ...
Humans& Inc., a three-month-old artificial intelligence startup, today announced that it has closed a $480 million seed round ...
By Akash Sriram Jan 20 (Reuters) - AI startup Humans&, founded by former OpenAI, Alphabet and xAI researchers, has raised ...
New “AI GYM for Science” dramatically boosts the biological and chemical intelligence of any causal or frontier LLM, delivering up to 10x performance gains on key drug discovery benchmarks and ...
Transformer on MSN
Teaching AI to learn
AI"s inability to continually learn remains one of the biggest problems standing in the way to truly general purpose models.
AI hallucinations produce confident but false outputs, undermining AI accuracy. Learn how generative AI risks arise and ways to improve reliability.
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