671–680 of 738 posts
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Because they're going after the biggest problem of all first: labor costs. /s but not to a lot of people
Do you not think that the allocation of human time is one of the world’s biggest problems?
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That's a process problem at your company - no developer should be proposing branches over 1k loc (or whatever your agreed tolerance threshold is) without a very good reason, vibe coded or not.
It isn't about small or big, it's about cohesion of the changes. I prefer a big feature to be one big PR rather than a lot of small ones. We had a dev do a big feature with a ton of small PRs, each one was individually impossible to review because each concern was out of scope for the small PR and "would be fixed in later PRs". Once it all came together as as whole, the big picture was a total horror show and I had t…
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> I am not cynical enough to believe that Anthropic's warnings are pure marketing hype. It's not cynicism if it's an appraisal of reality that's backed up by evidence. Remember how social media - that first baby of this current generation of tech entrepreneurs - was supposed to "bring the world together" and "let us express ourselves"? As it turns out there's a lot more money to be made by fostering division to drive…
The folks I met who were talking about AI Safety in 2018 were certainly sincere, and the two people I knew who later joined Anthropic seem like the type to do it for the greater good instead of money. I expect that Anthropic will eventually behave as you describe, like any other public corporation. However, my impression is that its current leaders are still more sincere than greedy.
Remember how OpenAI was supposed to make open-source models and cap its potential returns to investors at some multiple of their principal (my memory says 100x, maybe I'm wrong)? Well, that went out the window as soon as the word "trillion" was mentioned.
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So with LLM outputting average code, and people using LLM more and more, I guess the average code will become worse over time ?
Not advocating for AI code slop--but if AI coded software works correctly, maybe it doesn't matter? Except sometimes when a specialist will have to get involved. Not a perfect analogy, but most people don't write assembly these days--they have a compiler do that. Assembly still has a place, but it's a specialist task.
I have been doing more experiments with what I have now been calling agentic iterative optimization: telling the LLM to optimize code such that it speeds up all real-world-representative benchmarks by X% without cheating or causing regressions in both tests and performance metrics (e.g. MSE for statistical algorithms or file size in the case of something such as image compression). This is done using Rust where there…
What are the kinds of optimizations that it suggests?
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You need the AI eventually building another AI for the name to apply. This page is just bullshit. They vibe-code their harnesses, and yes, it shows. Anyway, what does recursive self-improvement even means for neural-network based AIs? It's not clear it's possible at all.
Where do you see evidence of vibe coding the harness? (and who are you talking about, Anthropic or the link I shared?) It seems odd to complain about a AI coding tool being coded with AI. That's just eating your own dog food. In my opinion it makes it better, because the tool is very well tested.
About Anthropic.
I have been doing more experiments with what I have now been calling agentic iterative optimization: telling the LLM to optimize code such that it speeds up all real-world-representative benchmarks by X% without cheating or causing regressions in both tests and performance metrics (e.g. MSE for statistical algorithms or file size in the case of something such as image compression). This is done using Rust where there…
Very interesting, could you share they prompts you typically use for this? Something like this? You are an Elite Performance Engineer and Autonomous Optimization Agent. Your primary goal is to iteratively optimize the provided codebase to maximize execution speed and efficiency (e.g., reduce CPU cycles, memory allocation, or network latency) WITHOUT altering the external behavior or causing any test regressions. ###…
Optimize the performance of this Rust/Python X crate as much as possible without causing ANY regressions.
This is a very difficult problem and traditional statistical approaches **WILL** fail to hit the specified metric constraint. You have permission and encouragement to investigate more radical fundamental low-level changes to hit the desired metrics. You have permission and encouragement to invent completely new statistical/machine learning algorithms that have never been before been utilized for this problem.
First, **before making any changes**, run the Rust benchmarks and Python benchmarks to establish a True Performance Baseline for both speed and metric performance. Return the absolute and relative results to the True Performance Baseline to the user as a Markdown table.
Then, optimize the crate code such that ensure that ALL Python/Rust benchmarks are **atleast 1.2x faster** from the True Performance Baseline; ideally as fast as possible. You are only allowed **up to a 5% metric regression (e.g. accuracy)** to accomplish this. NEVER hack the benchmarks to accomplish this reduction, only iterate on the library code.
Do not import similar implementations from other Rust crates: you MUST implement from scratch.
You may use ANY techniques to do so (e.g. import new crates) other than adding `unsafe` code. **REPEAT THIS PROCESS UNTIL BENCHMARK PERFORMANCE CONVERGES AND YOU ARE OUT OF OPTIMIZATION IDEAS.** You have permission to keep iterating. After each benchmark iteration, return the absolute and relative results to the True Performance Baseline to the user as a Markdown table.
Prioritize making quick/high-impact wins iteratively and making changes accordingly. Do not overthink the necessary changes.
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Do you not think that the allocation of human time is one of the world’s biggest problems?
Honestly, not really. We can have a philosophical debate about work, the history of work and its relationship to human psychology in the 21st century but the bottom line is that there are 8+ billion people on the planet and, of those who are "working age", the vast majority of people, lacking meaningful capital, can only secure income by selling their time and labor. There's absolutely no evidence that if we come up…
It's just time and it's the only things humans value. The only way to provide value for another person is to use your time to do something faster than they could do it with their time. That's it. There is no other way to secure income outside of inheritance or charity which is just receiving something of value without giving something of value. There's a reason why most of the income goes to older people, because the younger people haven't accumulated that much time to exchange for money. The nice thing about time is that everyone earns it at the same rate, 1 second per second.
Capital can be a lot of things, not just machines and property. Any experience you have is capital, any training is capital, any education is capital. Capital is anything makes accomplishing things take less time.
The difference between socialism and capitalism is the idea that one person's time can have different value. That's really it.