Enterprise AI roadblocks and roadmaps, security and physical AI: Day two at TechEx

The rise of enterprise AI has exposed a glaring weakness in traditional data governance strategies: how to measure the success of data governance. Most organizations struggle in this space. But […] The post AI Success Depends on These Data Governance Metrics appeared first on AIwire.

Anthropic's rapid revenue growth and profitability highlight the transformative potential and competitive dynamics in the enterprise AI sector. The post Anthropic expects 130% revenue surge to $10.9B in June quarter appeared first on Crypto Briefing.

Pi Network completes V23 mainnet upgrade with protocol, Ubuntu, and PostgreSQL updates to improve speed, security, and stability. Pi Network said its mainnet has completed a major V23 upgrade, covering protocol, server, and database changes. The update also included subsystem restructuring and large-scale historical data processing, while users await further official updates on future network […] The post Pi Network V23 Upgrade Strengthens Mainnet Speed Security And Ecosystem Growth appeared first on Live Bitcoin News.

Faced with the growing volume of submission to its bug bounty program, GitHub is replacing cash bounties with swag rewards for reports with low security impact — and asking researchers to stop submitting reports that are low quality or about things that aren’t its fault. The cloud-based code repository platform has seen a sharp increase in submissions that don’t demonstrate real security impact over the past year due to newer tools such as generative AI. “Not every valid submission represents a meaningful security risk. Some reports identify hardening opportunities or documentation gaps,” Jarom Brown, a senior security researcher at GitHub, wrote in a blog post. On top of that, he said, many of the reports GitHub receives describe out-of-scope scenarios in which someone experiences an “undesirable” outcome after interacting with malicious content in GitHub. “These reports are often well-written and technically accurate in their observations, but they misunderstand where the security bo

Insider Brief PRESS RELEASE — Hyundai Mobis (KRX 012330) hosted an event in Silicon Valley to identify global partners and expand collaboration in robotics and physical AI. The company plans to broaden open innovation it has pursued in the mobility sector toward new business areas to proactively strengthen its competitiveness. Hyundai Mobis announced that it held […]

A December 2025 paper from Silicon Valley venture capital firm Foundation Capital, titled “AI’s trillion-dollar opportunity,” has generated significant excitement in the enterprise AI industry. The reason? It introduces the new concept of a “context graph,” a knowledge graph designed to capture a new AI paradigm known as “decision traces.” The context graph is emerging as a potentially powerful idea. The context graph approach could capture the full context, reasoning, and causal relationships behind critical business decisions, making it a highly practical concept. As the paper notes, “Agents don’t simply need rules; they need access to the decision traces that show how rules were applied in the past, where exceptions were granted, how conflicts were resolved, who approved what, and which precedents actually govern reality.” This point is echoed by some of the commentary on the prediction, which points out that the most important knowledge comes from the data about the decisions that

A December 2025 paper from Silicon Valley venture capital firm Foundation Capital, titled “AI’s trillion-dollar opportunity,” has generated significant excitement in the enterprise AI industry. The reason? It introduces the new concept of a “context graph,” a knowledge graph designed to capture a new AI paradigm known as “decision traces.” The context graph is emerging as a potentially powerful idea. The context graph approach could capture the full context, reasoning, and causal relationships behind critical business decisions, making it a highly practical concept. As the paper notes, “Agents don’t simply need rules; they need access to the decision traces that show how rules were applied in the past, where exceptions were granted, how conflicts were resolved, who approved what, and which precedents actually govern reality.” This point is echoed by some of the commentary on the prediction, which points out that the most important knowledge comes from the data about the decisions that

Redis' Iris could accelerate enterprise AI adoption by bridging data retrieval gaps, enhancing efficiency, and reducing infrastructure costs. The post Redis launches Iris, a context and memory platform for AI agents appeared first on Crypto Briefing.