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Generative AI hype distracts us from AI’s more important breakthroughs
Checkpointless training on Amazon SageMaker HyperPod: Production-scale training with faster fault recovery
AI might not be coming for lawyers’ jobs anytime soon
Nvidia Becomes a Major Model Maker With Nemotron 3

Checkpointless training on Amazon SageMaker HyperPod: Production-scale training with faster fault recovery

Foundation model training has reached an inflection point where traditional checkpoint-based recovery methods are becoming a bottleneck to efficiency and cost-effectiveness. As models grow to trillions of parameters and training clusters expand to thousands of AI accelerators, even minor disruptions can result in significant costs and delays. In this post, we introduce checkpointless training on…

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AI might not be coming for lawyers’ jobs anytime soon

But new benchmarks are aiming to better measure the models’ ability to do legal work in the real world. The Professional Reasoning Benchmark, published by ScaleAI in November, evaluated leading LLMs on legal and financial tasks designed by professionals in the field. The study found that the models have critical gaps in their reliability for…

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Nvidia Becomes a Major Model Maker With Nemotron 3

Nvidia has made a fortune supplying chips to companies working on artificial intelligence, but today the chipmaker took a step toward becoming a more serious model maker itself by releasing a series of cutting-edge open models, along with data and tools to help engineers use them. The move, which comes at a moment when AI…

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AI materials discovery now needs to move into the real world

The grand prize would be a room-temperature superconductor, a material that could transform computing and electricity but that has eluded scientists for decades. Periodic Labs, like Lila Sciences, has ambitions beyond designing and making new materials. It wants to “create an AI scientist”—specifically, one adept at the physical sciences. “LLMs have gotten quite good at…

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Google’s AI Playbook for Sustainability Reporting

We’re sharing a practical playbook to help organizations streamline and enhance sustainability reporting with AI. Corporate transparency is essential, but navigating fragmented data and labor-intensive processes often leaves little bandwidth for the strategic work that actually drives progress forward. After two years of integrating AI into our own environmental reporting process, we’re open-sourcing our learnings…

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Operationalize generative AI workloads and scale to hundreds of use cases with Amazon Bedrock – Part 1: GenAIOps

Enterprise organizations are rapidly moving beyond generative AI experiments to production deployments and complex agentic AI solutions, facing new challenges in scaling, security, governance, and operational efficiency. This blog post series introduces generative AI operations (GenAIOps), the application of DevOps principles to generative AI solutions, and demonstrates how to implement it for applications powered by…

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Adaptive infrastructure for foundation model training with elastic training on SageMaker HyperPod

Modern AI infrastructure serves multiple concurrent workloads on the same cluster, from foundation model (FM) pre-training and fine-tuning to production inference and evaluation. In this shared environment, the demands for AI accelerators fluctuates continuously as inference workloads scale with traffic patterns, and experiments complete and release resources. Despite this dynamic availability of AI accelerators, traditional…

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Customize agent workflows with advanced orchestration techniques using Strands Agents

Large Language Model (LLM) agents have revolutionized how we approach complex, multi-step tasks by combining the reasoning capabilities of foundation models with specialized tools and domain expertise. While single-agent systems using frameworks like ReAct work well for straightforward tasks, real-world challenges often require multiple specialized agents working in coordination. Think about planning a business trip:…

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