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Leverage NVIDIA NeMo, Amazon Bedrock AgentCore, and Strands Agents to build, optimize, evaluate, and deploy scalable, secure AI agents with seamless observability and production-grade infrastructure on AWS.

Dropbox Dash’s custom-built hybrid feature store integrates Feast, Spark, and Dynovault to deliver low-latency, real-time machine learning features at scale for fast, relevant search ranking.

Databricks Clean Rooms enable secure, privacy-first multi-party data collaboration across clouds using Unity Catalog and Delta Sharing for controlled, governed analysis without exposing raw data.

Databricks Spatial SQL now delivers up to 17x faster spatial join performance out-of-the-box using optimized R-tree indexing and Photon enhancements, eliminating the need for external libraries or tuning.

A concise technical overview of the current state, challenges, and opportunities of deploying AI in enterprise environments.

Developers can now submit and publish apps in ChatGPT to enhance conversations with new capabilities, discoverable via the app directory and supported by an Apps SDK and comprehensive guidelines.

OpenAI Academy for News Organizations offers AI-driven training, resources, and practical guidance to empower journalists and publishers in enhancing newsroom efficiency, investigative reporting, and business sustainability while addressing ethical and operational challenges.

Technical overview of Stripe's next-day settlement, detailing eligibility, payout scheduling (automatic and manual), US dashboard availability, the 0.6% fee, and its relation to Instant Payouts.

Next-day settlement enables Stripe users in the US to access domestic transaction funds within one business day, offering a faster and flexible payout option with a 0.6% fee.

Technical post examining how Stripe Capital financing causally accelerates SMB revenue growth, validated by two randomized trials across COVID-era and post-COVID economic conditions.

MIT researchers developed a computational framework using embodied AI agents to simulate and study the evolution of diverse vision systems influenced by environmental tasks and constraints.

PaTH Attention introduces an adaptive, context-aware positional encoding technique that enhances large language models' ability to track state changes and sequential reasoning while maintaining transformer efficiency.