The wolf photo for the article was the most eerie example for me... if I am reading about the natural world, I want to see a real photo of the natural world.
What is the moat of the major ticketing companies? Is it deals with venues? It is hard to rationalize how one company can even get a stranglehold on an entire market like this.
I feel like I could ping any random HN user and build something better in a week, which means it has been done many times already... why don't alternatives gain traction?
Reagan halted antitrust enforcement and nobody fixed it, so they were allowed to own controlling stakes in several industries and freeze out competitors. They get exclusives with bands, agencies, venues, and promotions so at each point anyone who tries to do something else runs into a package they can’t compete with: a band which doesn’t play ball won’t get the big venues, a venue which acts independently won’t get the big acts, etc. It’s clearly abusive but they managed to spread enough money around to avoid action before Biden, and then Trump overturned that because he has the same mentality.
I have been thinking that these SWE benchmarks will continue to improve since these companies hire very intelligent software engineers, they can task a multitude of them to solve problems, and then train the model on those answers.
Data has always been the core of it all, onward to the next abstraction, I suppose.
I think computational thinking, or basically "how do I solve this problem efficiently" training data is more valuable then feeding in answers. I don't know what these AI models training data consist of, but it would be interesting to see a model trained purely on reasoning, methods, those foundational skills (basic programming? or maybe not) and then give it some benchmarks.
Even with search grounding, it scored a 2.5/5 on a basic botanical benchmark. It would take much longer for the average human to do a similar write-up, but they would likely do better than 50% hallucination if they had access to a search engine.
Training for tasks still works petty well, but “vision” is a super broad domain and most seem optimized for OCR and screen processing (which have verifiable outputs and relatively straightforward data generation)
I think a lot of Dwarkesh's mentality about AI being inevitable / ubiquitous comes from the same part of him that thinks that artificial things are "good enough", e.g. the way he allows his production team to use fake plastic plants on set. Is he correct? I'm not sure, but I know there are at least a few people who notice the difference.
I always listened to the podcast and forget they even have videos. Have a hard time imagining myself sitting and watching a 2 hour interview when I could listen while exercising or doing chores. Am I missing anything?
Hallucinations galore, the 'daily digest' provided me with this gem: "Apple's supposedly revolutionary $1,199 MacBook Neo is getting schooled by $500
Windows machines that do basically the same thing without the premium"
There is no way to build a Macbook Neo for $1,199 and this is obviously snarky, auto-generated slop.
That's what taking a stand looks like... if any of these employees lose their job, they are welcome to come crash at my place for as long as they would like; they will have a roof over their head and I will cook them 3 meals a day.
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