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Build multi-agent systems with LangGraph and Amazon Bedrock

Large language models (LLMs) have raised the bar for human-computer interaction where the expectation from users is that they can communicate with their applications through natural language. Beyond simple language understanding, real-world applications require managing complex workflows, connecting to external data, and coordinating multiple AI capabilities. Imagine scheduling a doctor’s appointment where an AI agent …

Over-training large language models may make them harder to fine-tune

A small team of AI researchers from Carnegie Mellon University, Stanford University, Harvard University and Princeton University, all in the U.S., has found that if large language models are over-trained, it might make them harder to fine-tune. In their paper posted on the arXiv preprint server, the group compared the impact of different amounts of …

Beyond ARC-AGI: GAIA and the search for a real intelligence benchmark

GUEST: Intelligence is pervasive, yet its measurement seems subjective. At best, we approximate its measure through tests and benchmarks. Think of college entrance exams: Every year, countless students sign up, memorize test-prep tricks and sometimes walk away with perfect scores. Does a single number, say a 100%, mean those who got it share the sa…Read …

Dynamic model can generate realistic human motions and edit existing ones

When exploring their surroundings, communicating with others and expressing themselves, humans can perform a wide range of body motions. The ability to realistically replicate these motions, applying them to human and humanoid characters, could be highly valuable for the development of video games and the creation of animations, content that can be viewed using virtual …