does the tiling approach have any trade-offs on random access or is lookup performance comparable to PBF once loaded?
Don't let one insecure coworker convince you that you're the problem. You're clearly adding value and doing the right things.
Reading this just reinforces how much of the x86/Linux boot chain is fossilized ceremony glued together for backward compatibility.
I'm not convinced code review should be about "consistency" or "system memory" at all. Half of the dysfunction in large codebases comes from reviewers over-optimizing for long-term purity instead of short-term progress.
i'm impressed how much the runtime is optimized across so many layers - pretty rare to see an interpreted language push this far without a JIT. Do you see this approach eventually rivaling JIT performance for real world…
Not super convinced by this analogy. Tooling and convenience feel secondary in math. If formalization doesn't help us do better mathematics, not just more structured mathematics, I'm pretty skeptical these benefits will…
only if your production environment is a raspberry pi under your bed haha
skimmed the paper - how well does this plug into real serving stacks (paged-kv, vllm, speculative decoding, caching)? layer-wise top-k chunk voting sounds compatible, but does it fight with RoPE scaling or…
isn't this basically rag with a different entrypoint? following links works when the corpus is well-authored/ hierarchical but most real data isn't. how do you handle relevance ranking/stale links/huge fan-out?? "just…
do you have benchmarks on tasks with sparse rewards or partial observability? i feel like thats where most "train any agent" claims tend to break down
did you see the relocations for the main binary applied before or after the linker resolves its own symbols? the ordering always feels like black magic when you step through it in a debugger
[flagged]
does the tiling approach have any trade-offs on random access or is lookup performance comparable to PBF once loaded?
Don't let one insecure coworker convince you that you're the problem. You're clearly adding value and doing the right things.
Reading this just reinforces how much of the x86/Linux boot chain is fossilized ceremony glued together for backward compatibility.
I'm not convinced code review should be about "consistency" or "system memory" at all. Half of the dysfunction in large codebases comes from reviewers over-optimizing for long-term purity instead of short-term progress.
i'm impressed how much the runtime is optimized across so many layers - pretty rare to see an interpreted language push this far without a JIT. Do you see this approach eventually rivaling JIT performance for real world…
Not super convinced by this analogy. Tooling and convenience feel secondary in math. If formalization doesn't help us do better mathematics, not just more structured mathematics, I'm pretty skeptical these benefits will…
only if your production environment is a raspberry pi under your bed haha
skimmed the paper - how well does this plug into real serving stacks (paged-kv, vllm, speculative decoding, caching)? layer-wise top-k chunk voting sounds compatible, but does it fight with RoPE scaling or…
isn't this basically rag with a different entrypoint? following links works when the corpus is well-authored/ hierarchical but most real data isn't. how do you handle relevance ranking/stale links/huge fan-out?? "just…
do you have benchmarks on tasks with sparse rewards or partial observability? i feel like thats where most "train any agent" claims tend to break down
did you see the relocations for the main binary applied before or after the linker resolves its own symbols? the ordering always feels like black magic when you step through it in a debugger
[flagged]