111–120 of 141 posts
You pay $200/month to Anthropic, $200/month to OpenAI, $200/month to Cursor, $200/month to $200/month to Google, and seeing that it didn't come to a nice round $1024/month, you pay $200/month to Sakana to coordinate it all, because why not. While you're at it, feel free to send me $200 as well, I'll generate a crypto address ending with "AI".
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Of course, premium headphones existed before. I have a WH-1000XM4 sitting right next to me. But your aunt Josie didn't have one. Now Apple is selling 80 million units / year and the ~$300 price tag has become normal. Before that, most people had headphones that were 10 times cheaper.
$300 isn’t what AirPods cost though. You can get a pair of AirPods 4 for $129 on Apple.com, and I presume that is still the most popular model. If you’re paying ~$300, you are buying premium headphones.
I just averaged it out.
https://xkcd.com/927/
You pay $200/month to Anthropic, $200/month to OpenAI, $200/month to Cursor, $200/month to $200/month to Google, and seeing that it didn't come to a nice round $1024/month, you pay $200/month to Sakana to coordinate it all, because why not. While you're at it, feel free to send me $200 as well, I'll generate a crypto address ending with "AI".
Happy user here, pairing it with Composer 2.5, with Fugu Ultra as advisor and Fugur as planner. For scope/architecture it’s on par with useful Fable-style orchestration than one chat thread. I've been shipping production on archive.tw with Fugu Ultra in /advisor on oh-my-pi. Advisor doesn’t slow the loop if the driver stays fast. Worth it if your harness can split advisor from worker.
Edit: nevermind, but which plugin or so?
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Kind of shocking - a model comes out that beats mythos and offers a reasonable price and it ... gets downvoted? Probably taking hate from both sides - OpenAI / Claude fans who are undercutting its moat. Chinese open-model fans that want it to be cheaper. But it's a genuine accomplishment to hit those benchmarks and offer a reasonable plan? Bizarre reaction TBH.
Which model is that? What is it named?
[0] https://dev.classmethod.jp/en/articles/sakana-fugu-ga-first-...
Imho there are two dimensions here: Firstly different LLMs and secondly the strategy in which you break down the problem in an agentic fashion (e.g. break up to separate agents with own persona and then judge evaluates across all agents). You can of course mix-up the dimensions as well and that's what I have been tinkering* with for a good few months with some success. This was all done using home-brew setup running…
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We found that an all open source fusion was 1/3 the price and better than Fable https://trustedrouter.com/blog/open-fusion-beats-fable-5
Brilliant. What this actually is, is a swarm, albeit a very small one. I'm wondering if for research specifically, swarm size (on higher temp?) would outweigh model size. At least, for the initial data gathering phase. You'd probably want a sequence of progressively larger models to filter it. Have you guys tested it on anything other than research?