Q&A: Nvidia exec on how ‘confidential computing’ can secure AI agents

NVIDIA’s AI chip cycle pulls risk capital from ETH as users stall on fragmented L2s. Fees fell post-Dencun, but the app story still fights for oxygen.

With AI agents increasingly expected to remember conversations, preferences, and decisions over extended periods, Microsoft Research has developed Memora, a memory system designed to provide more scalable and reliable long-term recall than existing approaches. AI agents are increasingly expected to retain context across weeks or months rather than individual chat sessions. Memory can become fragmented, leading to duplicate information and slower retrieval as knowledge grows. According to Microsoft, Memora can solve this problem by decoupling what the AI remembers from how it looks up that information, ultimately reducing context token usage by up to 98% while matching or exceeding full-context accuracy, Microsoft Research claimed in a blog post. Limitations of today’s memory architectures As AI assistants and autonomous agents move into long-horizon deployments, the absence of a principled memory system has become a critical bottleneck. While modern LLMs are powerful reasoners, they st

With AI agents increasingly expected to remember conversations, preferences, and decisions over extended periods, Microsoft Research has developed Memora, a memory system designed to provide more scalable and reliable long-term recall than existing approaches. AI agents are increasingly expected to retain context across weeks or months rather than individual chat sessions. Memory can become fragmented, leading to duplicate information and slower retrieval as knowledge grows. According to Microsoft, Memora can solve this problem by decoupling what the AI remembers from how it looks up that information, ultimately reducing context token usage by up to 98% while matching or exceeding full-context accuracy, Microsoft Research claimed in a blog post. Limitations of today’s memory architectures As AI assistants and autonomous agents move into long-horizon deployments, the absence of a principled memory system has become a critical bottleneck. While modern LLMs are powerful reasoners, they s

Whether you are using an AI code generator, vibe coding, or applying spec-driven development methodologies, your job doesn’t end with AI writing the code. Whether you’re using AI to develop applications, APIs, data pipelines, AI agents, or other automations, writing the code is just one part of the job. Developers must still perform code validation, test applications, automate deployment, and configure infrastructure. According to one survey, only 16% of a developer’s time is spent writing code. The remaining 84% is spent on other activities including defining requirements, triaging bugs, and addressing vulnerabilities. Additionally, while AI code generation speeds up development, it can come at the cost of quality and collaboration. In Atlassian’s State of Teams 2026 survey, nearly 50% of respondents say their AI outputs aren’t reliably high quality and admit that using AI is a compromise between speed and quality. Knowledge workers say the pressure to execute is also problematic, wit

OKX is bringing together payments, identity and reputation into a marketplace for AI agents.

The investigation highlights the geopolitical tensions in tech supply chains, impacting investor confidence and emphasizing regulatory scrutiny. The post Taiwan escalates probe into Super Micro Computer’s AI servers amid Nvidia chip smuggling allegations appeared first on Crypto Briefing.

A market analysis by Deloitte Legal suggests that in the next three to five years AI agents could handle 30% of the work within corporate ...

The probe highlights potential enforcement gaps in semiconductor export controls, prompting increased cross-border regulatory scrutiny. The post Super Micro Computer’s Taiwan offices raided in Nvidia chip smuggling probe appeared first on Crypto Briefing.