Explore the concept of "self-driving storage," where AI and AIOps autonomously manage data infrastructure. Learn how mobile storage partitions, predictive analytics, and agentic AI are used to automate capacity management, workload placement, and on-demand performance optimization without human intervention.
This summary explores Arpita Vats's insights on how Large Language Models (LLMs) are revolutionizing recommender systems. It contrasts the traditional feature-engineering-heavy approach with the contextual understanding of LLMs, which shifts the focus to prompt engineering. Key challenges like inference latency and cost are discussed, along with practical solutions such as lightweight models, knowledge distillation, and hybrid architectures. The conversation also touches on advanced applications like sequential recommendation and the future potential of agentic AI.
In this analysis, experts Bryan Casey, Mihai Criveti, and Chris Hay dissect the OpenAI GPT-5 release, comparing its capabilities against Anthropic's Claude Opus 4.1. While GPT-5 introduces significant improvements in accessibility, agentic capabilities, and reliability, the consensus is that it does not yet dethrone Claude as the daily driver for developers due to key differences in user experience and workflow management.
OpenAI researchers discuss the step-change in capabilities in ChatGPT-5, from coding and reasoning to creative writing. They detail the data-centric training processes, the shift toward asynchronous agentic workflows, and the future of AI development and its impact on the startup ecosystem.
OpenAI introduces GPT-5, a significant upgrade focused on expert-level reasoning, agentic capabilities, and real-world utility, particularly for developers and enterprises. The model introduces a new reasoning paradigm, "software on demand" capabilities, and state-of-the-art performance on coding, reasoning, and long-context benchmarks. The launch also includes major updates to the ChatGPT application and a powerful new API for developers.
In a presentation from Code w/ Claude, AWS advocates Du'An Lightfoot, Suman Debnath, and Banjo Obayami introduce Strands, a new open-source Python SDK for building AI agentic applications on AWS. They showcase how Strands simplifies development by focusing on three core components—models, tools, and prompts—and leverages the full reasoning power of foundation models like Claude 3.5 on Amazon Bedrock. The session includes live demos on creating a multi-tool weather agent, integrating with Modular Connected Protocol (MCP) servers for AWS documentation and diagram generation, and using Claude Code to auto-generate a complete Strands agent for AWS CDK.