Small language models fail at rare tasks because frequent ones constantly overwrite what they've learned. A new study with models ranging from 4 million to 4 billion parameters shows this mechanism in detail and offers a practical fix: instead of scaling up models, it may be enough to increase how often the target task appears in the training data.<br /> The article Researchers pinpoint why larger language models pick up skills that small ones miss appeared first on The Decoder. [...]
Anthropic launched a new capability on Thursday that allows its Claude AI assistant to tap into specialized expertise on demand, marking the company's latest effort to make artificial intelligenc [...]
Anthropic said on Wednesday it would release its Agent Skills technology as an open standard, a strategic bet that sharing its approach to making AI assistants more capable will cement the company [...]
One major challenge in deploying autonomous agents is building systems that can adapt to changes in their environments without the need to retrain the underlying large language models (LLMs).Memento-S [...]
Picture this scenario: An Anthropic Skill scanner runs a full analysis of a Skill pulled from ClawHub or skills.sh. Its markdown instructions are clean, and no prompt injection is detected. No shell c [...]
Market researchers have embraced artificial intelligence at a staggering pace, with 98% of professionals now incorporating AI tools into their work and 72% using them daily or more frequently, accordi [...]
The trend of AI researchers developing new, small open source generative models that outperform far larger, proprietary peers continued this week with yet another staggering advancement.Alexia Jolicoe [...]
Earlier this week, the AI startup Liquid, formed in 2023 by former MIT computer scientists, debuted LFM2.5-2.6B, a new open-weight language model designed specifically for agentic workloads. In releas [...]
Agent skills have become an important part of real-world AI applications, providing a mechanism — a set of instructions saved in a folder of text-based markdown (.md) files, usually — for models t [...]