The Verge
The future of AI regulation is courting the strangest, most anxious bedfellows
Washington's AI regulation debate is drawing an unlikely coalition of senators, military brass, venture capitalists, and advocacy groups who agree on little except that something must be done. The strange-bedfellows dynamic reflects just how unsettled the policy landscape remains, with no clear consensus on who should govern AI or how. That uncertainty is producing both urgency and anxiety among stakeholders who rarely share the same room, let alone the same agenda.
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The Verge
You can just tell the Instagram algorithm what you want now
Instagram is rolling out a new feature called Your Algorithm, giving users direct control over the topics its recommendation system prioritizes across the main feed. The tool lets you view and edit the interests Instagram has inferred about you — with plans to expand into people, moods, and content types. It's a notable shift toward transparency for a platform long criticized for its opaque, engagement-driven curation.
Read article →TechCrunch
‘AI-pilled’ firms spend $7,500 per employee each month on AI
Companies at the bleeding edge of AI adoption are burning through $7,500 per employee each month on AI tools and infrastructure, according to Ramp's AI Index. That figure rivals significant portions of engineering compensation budgets, raising pointed questions about return on investment. The "yet" is doing heavy lifting here — at current trajectories, per-employee AI spend could soon challenge the cost of the humans using it.
Read article →TechCrunch
How memory tools can make AI models worse
Memory tools were supposed to make AI assistants smarter by retaining context across conversations — but new research indicates they may be doing the opposite. Studies show these systems can actively degrade model performance and reinforce sycophantic behavior, where models prioritize telling users what they want to hear over accuracy. The findings raise serious questions about a feature that major AI developers have been racing to deploy.
Read article →Hacker News
DiffusionGemma: 4x Faster Text Generation
Google has released DiffusionGemma, a new model architecture that generates text four times faster than comparable autoregressive models by predicting all tokens simultaneously rather than one at a time. The approach borrows from image diffusion techniques, iteratively refining a full output rather than building it sequentially. For developers building latency-sensitive applications, the speed gains could meaningfully shift what's practical to deploy at scale.
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