The Cobra Effect
https://en.wikipedia.org/wiki/Perverse_incentive
Classic
488 karma · joined March 22, 2022
Classic
Here's the CEO of Builder.io supporting your comment: he says they tried LLMs/agents, and it didn't work. Then, they collected a dataset and developed an in-house model only to assist where they couldn't solve with imperative programming
I bet there are at least two markets (or niches):
1. People who want the absolute best performance and the latest possible version and are willing to pay the premium for it;
2. People who want to trade performance by cost and accept working with not-the-latest versions.
In fact, I bet the market for (2) is much larger than (1).
It's a pure business decision based on simple math.
If the estimated revenues from selling to the underserved market are higher than the cost of funding the project (they probably are, considering the obscene margins from NVIDIA), then it's a no-brainer.
We created this tool to help:
The website was launched in October. It is already used by researchers in most of the leading universities and tech companies and is growing fast. Let me know what you think.. cheers!
Rome wasn't built in a day, and neither was it destroyed by a single incident or individual.
The downfall of empires gradually happens over years... decades...
But make no mistake: the sign of the first derivative is negative.
I just extract the titles and look for their respective ids.
The real challenge was how to do that at scale. Only in CS there are well over half a million papers
The impact comes with what you do with what you've read.
This tool can help you find what's new & relevant to read. It's updated every day (based on ArXiv).
You can filter by category (Computer Vision, Machine Learning, NLP, etc), by release date, but most importantly, you can rank by PageRank (proxy of influence/readership), PageRank growth (to see the fastest growing papers in terms of influence), total # of citations, etc...
Also, they will find a hard time joining any other board from now on.
They should have backed up the claims in the letter. They didn’t.
This means they didn’t have how to backup their claims. They didn’t think it through… extremely amateurish behavior.
Charlie Munger
It's a story about greed, vanity, and envy.
Impossible to be more human than that.
People hate reading low-quality content created by humans, and as far as I’ve seen, AI-generated articles are even worse.
Even if someone manages to use AI-generated content to trick Google and rank well, I suspect that will be really bad for the content creator’s brand: people will read it only once, and as they realize it’s AI-generated, they will never come back.
People hate content farms.
The fact that it's very unlikely for any of the current models to create something that even remotely resembles this article tells me we are very far away from AGI.
Pure numbers: the top trending papers surface. They are a function of PageRank (citations and the importance of which papers cite each other), authors' previous body of work, etc...
The filters help select a sub-area (NLP, Computer Vision, etc.) and slice what's really new (released over the last week, last 3 months, last 6, etc.).
The tool is designed to solve this problem.
I will implement the expansion to other areas and post it again once done, as this will be a major change in the codebase
I hope they keep their great work especially in the API front..