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BoltzGen on Amazon SageMaker AI accelerates protein binder design by managing GPU compute infrastructure end to end. BoltzGen is a diffusion-based generative model that designs proteins and peptides capable of binding to specific biomolecular targets. A typical design campaign involves multiple GPU-intensive steps: backbone generation, inverse folding, structural validation, and candidate ranking. Running these steps […]

Google, the New York Jobs CEO Council and Urban Assembly hosted an AI summit for 150 education and industry leaders. ​ 

It’s our goal for AWS to be the most secure place to run any workload, and in support of that we’ve been deeply investing in security across our services since AWS’s inception more than two decades ago.  Our AI services like Amazon Bedrock are built on this foundation and with the same focus. Bedrock provides customers with

Today, we’re excited to announce the availability of Anthropic’s most advanced Sonnet model, Claude Sonnet 5, on Amazon Bedrock and Claude Platform on AWS. Claude Sonnet 5 is the first Sonnet model of Anthropic’s latest generation and represents a meaningful step forward. It delivers top-tier intelligence at Sonnet pricing for coding, agents, and everyday professional

AI agents can do more than chat. With the right protocol, an agent can render an interactive chart inline in your conversation, update a shared canvas in real time, or pause mid-execution to ask for your approval before proceeding. These interactions (generative UI, shared state, and human-in-the-loop) need a standard way for agent backends to

Managing AI model access across dozens or hundreds of AWS accounts creates a dilemma. Either you grant AWS Marketplace permissions broadly, risking governance issues, or you manually enable subscriptions in each account. For organizations using third-party models like Anthropic Claude or Cohere, this operational overhead slows AI adoption. In this post, we show you how

Implementing resilience patterns for large language model (LLM) inference is critical as generative AI workloads move from experimentation to production at scale. With LLM powered apps now in production, organizations need ways to keep LLM inference highly available, responsive, and cost-effective at scale. Existing resilience best practices like static stability and implementing backoffs and retries

This post was co-written with Tim Chauncey and Dheeraj Bhadani of Outpost VFX. AI model training for visual effects (VFX) can take weeks, creating bottlenecks in production timelines. For Outpost VFX, which operates studios across the UK, Canada, and India delivering high-end film and episodic content, every day of delay impacts client deliverables and project

IBS Software’s Cargo system processes thousands of bilingual cargo logistics email messages daily. The system extracts critical information such as air waybill (AWB) numbers, flight details, weights, and delivery instructions in both English and Japanese. This added to the complexity of building a robust Named Entity Recognition (NER) solution. Challenges included manual intervention that slowed

The authors would also like to thank Karan Bhandarkar, Sue Cha, Yash Shah and Nieves Garcia for their contributions in making this initiative possible. If you process millions of email messages daily, fine-tuning Amazon Nova models can help you automate accurate data extraction while reducing costs and hallucinations. Parcel Perform, a leading AI Delivery Experience