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Google I/O 2026 revealed a far more aggressive AI strategy than many expected. Rob Enderle explains what this could mean for the future of apps, work, and computing.
Gartner predicts AI-powered search tools will push brands to spend more on PR and earned media as companies compete for visibility inside chatbot-generated answers.
LinkedIn is expected to unveil new efforts targeting AI slop and engagement bait, raising broader questions about authenticity, platform trust, and AI-assisted writing online.
Advances in AI, robotics, and emotional design are pushing pet robots beyond novelty status and closer to becoming interactive household companions.
AI-generated legal hallucinations are increasingly leading to sanctions, delayed cases, and governance concerns as courts and law firms struggle to control unauthorized AI use and fabricated legal reasoning.
A newly disclosed Linux privilege escalation flaw dubbed "Dirty Frag" is raising concerns among security researchers who warn it could give attackers reliable root access across a wide range of enterprise environments.
A recently patched GitHub RCE flaw is raising broader questions about implicit trust in software supply chains. CodeHunter CEO Ken Ammon explains why trusted users and platforms no longer guarantee safe code.
Meta says it is expanding AI-based age enforcement tools across Facebook and Instagram to identify potentially underage users.
As AI systems take on more autonomous roles, concerns about alignment, oversight, and hardware-level safeguards are becoming more urgent across both enterprise and defense environments.
Apple is reportedly exploring U.S.-based chip production partnerships with Intel and Samsung as geopolitical tensions and supply chain concerns push tech companies to diversify manufacturing beyond Taiwan.
As AI agents move into production, traditional container security is failing at scale. Edera is addressing this gap with hypervisor-based isolation designed for GPU-heavy, multi-tenant environments.
Super Productivity stands out with flexible workflows, offline-first design, and free syncing. It adapts to how you work instead of forcing structure, making it one of the most practical tools I've used.
The economics of AI don’t always match expectations. High compute, infrastructure, and reliability costs mean human labor remains the more cost-effective option across many real-world tasks.
As AI demand accelerates, infrastructure limits are emerging as the real bottleneck. Power, cooling, and supply chains now shape deployment timelines and ROI.
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