No new law was enacted. The ISPs are enforcing a court order.

If it happens gradually enough, they will just find other jobs. After the transition, society will be producing more with the same labor force, and thus the aggregate utility will increase.

I don't understand how this is the top comment. LLMs have unlocked a lot of value for me personally, and arguably for the society as a whole. They are also one of the coolest technologies I've tried in years. As a technologist, I'm really glad that money is pouring in and allowing us to find its limits.

Comments URL: https://news.ycombinator.com/item?id=46672143

Points: 4

# Comments: 2

But I don't want to spoil the fun. The agents are really good at searching the web now, so posting the tricks here is basically breaking the challenge.

For example, chatGPT was able to find Matt's blog post regarding Task 1, and that's what gave me the largest jump: https://blog.mattstuchlik.com/2024/07/12/summing-integers-fa...

Interestingly, it seems that Matt's post is not on the training data of any of the major LLMs.

I've also built a bitorrent implementation from the specs in rust where I'm keeping the binary under 1MB. It supports all active and accepted BEPs: https://www.bittorrent.org/beps/bep_0000.html

Again, I literally don't know how to write a hello world in rust.

I also vibe coded a trading system that is connected to 6 trading venues. This was a fun weekend project but it ended up making +20k of pure arbitrage with just 10k of working capital. I'm not sure this proves my point, because while I don't consider myself a programmer, I did use Python, a language that I'm somewhat familiar with.

So yeah, I get what you are saying, but I don't agree. I used highload as an example, because it is an objective way of showing that a combination of LLM/agents with some guidance (from someone with no prior experience in this type of high performing architecture) was able to beat all human software developers that have taken these challenges.

Creating a parser for this challenge that is 10x more efficient than a simple approach does require deep understanding of what you are doing. It requires optimizing the hot loop (among other things) that 90-95% of software developers wouldn't know how to do. It requires deep understanding of the AVX2 architecture.

Here you can read more about these challenges: https://blog.mattstuchlik.com/2024/07/12/summing-integers-fa...

I used highload as an example because it seems like an objective rebuttal to the claim that "but it can't tackle those complex problems by itself."

And regarding this:

"Claude is very useful but it's not yet anywhere near as good as a human software developer. Like an excitable puppy it needs to be kept on a short leash"

Again, a combination of LLM/agents with some guidance (from someone with no prior experience in this type of high performing architecture) was able to beat all human software developers that have taken these challenges.

If you think you can beat an LLM, the leaderboard is right there.

I don't think you've seen the full potential. I'm currently #1 on 5 different very complex computer engineering problems, and I can't even write a "hello world" in rust or cpp. You no longer need to know how to write code, you just need to understand the task at a high level and nudge the agents in the right direction. The game has changed.

- https://highload.fun/tasks/3/leaderboard

- https://highload.fun/tasks/12/leaderboard

- https://highload.fun/tasks/15/leaderboard

- https://highload.fun/tasks/18/leaderboard

- https://highload.fun/tasks/24/leaderboard

- https://highload.fun/tasks/15/leaderboard

- https://highload.fun/tasks/24/leaderboard

In both cases my score showed other players that there were better solutions and pushed them to improve their scores as well.

Who is this useful for? What is the strategy behind this?