Deepseek made their 75% discount permanent, so I can imagine that Anthropic didn't want any of the news stories around this to focus on or mention a price increase.
When I see the domain of a post is neal.fun, I instantly get a huge grin because I know I am about to be delighted. Thank you Neal! The beach yurt with the mushroom soup was a hilarious touch.
When I asked some frontier models, many said that Teresa T is "widely referenced", which is evidence of your popularity and the ripple effects of your posts, so it would be interesting to see the same result from an unknown blog.
> When I asked some frontier models, many said that Teresa T is "widely referenced", which is evidence of your popularity and the ripple effects of your posts
That is some serious Gell-Mann-type amnesia. You’re trusting LLM models to give you accurate information about a subject we’ve already established (and are only talking about because) they can’t be trusted on.
“Widely referenced” is a common term which LLMs obviously pick up. Them outputting those words has no bearing on the truth and says nothing about the “popularity and the ripple effects of [Simon’s] posts”.
i've been using the API for a portion of my work to prepare for this and test to see how much it will cost in the long term, turns out that was the short term.
it is rough, but it has taught me to treat every prompt and process with care since i watch the pennies and dollars burn instead of tokens, which is a good habit to get into anyway
Copilot has said they'll be giving out previous months "if you did token pricing, it would cost $x" so a lot of us will have real numbers to actually anticipate our spend.
Personally I'm anticipating agentic coding will be out of my price bracket (a single agent run costing US$20+ is far beyond what I can justify, especially with how often it fails). I'm planning on going back to optimised prompts on one-pass edits.
I use pi (https://pi.dev/) as my coding agent which allowed you to use your subscription until Claude recently introduced extra usage and I was routinely using the equivalent of my Claude Max subscription in an hour multiple times a day.
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.
Edit: It appears to be the missing content from the "Engineering - Heat Treatment Analysis" demo
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