AI

Guided learning lets “untrainable” neural networks realize their potential

Even networks long considered “untrainable” can learn effectively with a bit of a helping hand. Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have shown that a brief period of alignment between neural networks, a method they call guidance, can dramatically improve the performance of architectures previously thought unsuitable for modern tasks. Their

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Build and deploy scalable AI agents with NVIDIA NeMo, Amazon Bedrock AgentCore, and Strands Agents

This post is co-written with Ranjit Rajan, Abdullahi Olaoye, and Abhishek Sawarkar from NVIDIA. AI’s next frontier isn’t merely smarter chat-based assistants, it’s autonomous agents that reason, plan, and execute across entire systems. But to accomplish this, enterprise developers need to move from prototypes to production-ready AI agents that scale securely. This challenge grows as

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Bi-directional streaming for real-time agent interactions now available in Amazon Bedrock AgentCore Runtime

Building natural voice conversations with AI agents requires complex infrastructure and lots of code from engineering teams. Text-based agent interactions follow a turn-based pattern: a user sends a complete request, waits for the agent to process it, and receives a full response before continuing. Bi-directional streaming removes this constraint by establishing a persistent connection that

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A “scientific sandbox” lets researchers explore the evolution of vision systems

Why did humans evolve the eyes we have today? While scientists can’t go back in time to study the environmental pressures that shaped the evolution of the diverse vision systems that exist in nature, a new computational framework developed by MIT researchers allows them to explore this evolution in artificial intelligence agents. The framework they

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