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Wed, Jun 10 05:58 PM

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TechnologyHacker News2h ago

We put the Bun Rust rewrite in production

At Prisma we've been working on a Compute offering to complement our hosted Postgres. We settled on Bun early in the process as we liked the experience we'd be able to provide thanks to Buns batteries-included approach. But then we started using Bun in anger, and we found many memory leaks in t...

TechnologyHacker News4h ago

Coding Agent Memory Benchmarks

Something I’m finding while testing SWE-context-bench for the agent memory layer I’m building: evaluating memory is harder than checking whether the agent solved the next task with fewer tokens. The setup: An agent solves a coding task. Later, it gets a related task that should benefit from the...

TechnologyDev.to11h ago

Cache Deep Dive IV — TLB, Huge Pages, and Memory-Level Parallelism

Earlier parts examined the performance characteristics of sequential and random access under single-threaded execution, and noted in passing the destructive effect of random access on the TLB. This part devotes full attention to the TLB: what it is, why a TLB miss is more severe than a cache mis...

TechnologyDev.to15h ago

How I Gave My AI Agent a Real Memory Without Touching Its Internals

As someone who runs multiple AI agents for day-to-day tasks, I kept hitting the same wall: every new conversation was a total memory wipe. I'd ask my agent about a project we discussed yesterday, and it had no idea what I was talking about. Frustrating.

TechnologyNature17h ago

Efficient and accurate neural-field reconstruction using resistive memory

Nature, Published online: 10 June 2026; doi:10. 1038/s41586-026-10646-w A co-optimized AI hardware–software system using resistive-memory computing improves energy efficiency and parallelism for sparse signal reconstruction in imaging and three-dimensional vision applications.

TechnologyHackerNoon23h ago

Your GPU Is Probably Idle

A GPU holding memory isn't the same as a GPU doing work (an H100 can sit at 0% utilization with 20 GiB allocated), and most idle time comes from everything around the card, not the card itself. So feed it from the input pipeline, hand it big tensor-friendly shapes, fuse small kernels with torch....