Data and AI releases

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1,990 this month · 171 companies

Amazon Bedrock AgentCore Memory now supports configurable time-to-live for long-term memory

Update11 days agoUnverifiedAdded Oct 21, 2026

Amazon Bedrock AgentCore Memory now lets you set a time-to-live (TTL) on long-term memory records, so they are automatically deleted after a retention period you define. By default, long-term memory records do not expire.

Topics: AI agents, Security, Developer tools, Regions

AWS's release notes

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Updateunverified

Amazon Bedrock now supports reasoning summaries for OpenAI models

Amazon Bedrock now supports the reasoning.summary parameter for OpenAI models through the Responses API. This capability lets you request a human-readable summary of a model’s reasoning alongside its response, helping you understand its approach to complex tasks such as coding, analysis, and multi-step problem solving.

Updateunverified

OpenAI GPT-6.1 Sol now supports Ultrafast mode on Amazon Bedrock

Today, AWS announces the availability of Ultrafast mode for GPT-6.1 Sol from OpenAI on Amazon Bedrock. Ultrafast mode provides faster inference for workloads where speed matters most. The Amazon Bedrock inference engine delivers the performance, security, and reliability required for production workloads.

Updateunverified

Grok 4.7 is now available on Amazon Bedrock in AWS GovCloud (US)

Amazon Bedrock now supports SpaceXAI Grok 4.7, a frontier model built for coding, agentic tasks, and knowledge work in AWS GovCloud (US). Grok 4.7 builds on Grok 4.6 with better mixed-document handling, more dependable repo-scale coding with planning and error recovery, and enhanced browser-use agents for form fills and portal navigation.

Updateunverified

Claude Haiku 5.5 is now available on AWS

AWS now offers Claude Haiku 5.5, the fastest and most efficient model in the Claude 5.5 family, built for subagents and high-volume, cost-sensitive work. According to Anthropic, it costs around 75% less than Claude Haiku 4.5 for most tasks.

Also shipped on Oct 13, 2026

AWS in October 2026
Betaunverified

What's included:

- Three training methods: Supervised fine-tuning (SFT) , direct preference optimization (DPO) , and reinforcement learning with group relative policy optimization (GRPO) . Each method trains a low-rank adapter (LoRA) or the full model weights. Custom loss functions : Train with any objective you compute in PyTorch from the model's log-probabilities.