I find myself wanting to block Reddit°hard word, etc°hard word. on the router°hard word level. There is nothing worth°hard word reading there.
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the real way to get an "a-ha°hard word" moment from the machine, is with time-travel°hard word. 🔥 with time travel, the machine can return a better answer instantly°hard word!
the "head" of the response°hard word has to be noticeably°hard word ahead of where "committed°hard word" responses°hard word are. so, there is a possibility°hard word to jump backwards°hard word.
🔥 isn't°hard word this beam-search°hard word?
💡 ... maybe.
but, the idea is: you can assert°hard word a token°hard word ERROR PATH: RETREAT°hard word 32.
then°hard word, the "reason" for the message can be added as°hard word input°hard word.
it is the a-ha°hard word moment. but, implemented°hard word better than DeepSeek°hard word.
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the reaction to DeepSeek°hard word has been, in my estimation°hard word, ridiculous°hard word.
I tried the 7b and 8b distilled°hard word models. And what I saw was a cheap parody°hard word of thought. Thought-processes°hard word that didn't°hard word make sense, and didn't°hard word actually reflect°hard word how the machine generated°hard word thoughts.
but, apparently, people like it.
Maybe the 400b model gives better answers? Or, maybe, people just see the shape of the answer and trust it more.
💡 if the goal°hard word of the machine is to solve°hard word industrial°hard word tasks, this is mostly already baked°hard word in to my estimations°hard word. but, for the goal°hard word of making°hard word consumers°hard word happier°hard word, there is clearly a factor°hard word I am not°hard word considering.
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theory 1: people don't°hard word want to think the machine is smart°hard word; they want the machine to make them feel smart°hard word. both the appearance°hard word of struggling°hard word and the visible°hard word chain-of-thought°hard word (even if obviously flawed°hard word) contribute°hard word to this feeling.
theory 2: people don't°hard word know that the machine could already do 90% of this 12 months ago. they see a demo°hard word (or, more likely, hear about a demo°hard word) and, miraculously°hard word, now they know what will happen.
theory 3: we know that a light human touch guiding°hard word the machine's°hard word responses°hard word can improve accuracy°hard word substantially. and, that human touch can also be automated°hard word.
⚔️ well, actually, apparently very few other people knew°hard word that.
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i'm°hard word going to stick with Theory 1 for today. that people like Deepseek°hard word (and feel it is better) because it makes them feel smart°hard word.
which ... is depressing°hard word. but, also, easily solvable°hard word.
the question is: what question could you pose°hard word that would lead somebody°hard word to come up with this answer on their own?
💡 it seems unlikely°hard word that 8B models can do this. but I assume°hard word the 600B models can.
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people want the machine to make them feel smarter°hard word. 🔥 because people are self-centered°hard word, gullible°hard word, and insecure°hard word.
💡 they want it to behave°hard word in a way that I instinctively°hard word hate. they want the PT°hard word Barnum°hard word version°hard word of AI°hard word.
💬 give the people what they want!
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this is probably one of the reasons why the default°hard word tone for every chatbot°hard word is obsequious°hard word. so much that's°hard word a great question! / you're°hard word absolutely right / let me know what else i can do to help.
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💡 one can apply a politeness°hard word filter°hard word to the output°hard word of the machine. but the latency°hard word of such a system is already high.
⚔️ well, actually, it probably is just another layer°hard word or two.
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Seen°hard word on social°hard word media°hard word: Anthropic°hard word is losing°hard word because they have rate limits! 💡 of course they have rate limits. the machine is not°hard word too cheap to meter, at least at the quality people expect.
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a game of chess.
the idea of the attack worked in theory. and the attack worked in practice. but the actual°hard word attack did not°hard word work, in theory.
✨ chess can be a ritual°hard word. like the i-Ching°hard word.
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can the machine participate°hard word in rituals°hard word?
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there are two kinds of answers people want from the machine.
- Answers where people are willing to wait 10 minutes to definitely°hard word have the "right" answer.
- Entertainments°hard word. The various°hard word "instant°hard word chat-bots°hard word" are party tricks. A very good party trick. But, ultimately°hard word, a party trick.
🔥 perhaps testing is a third category°hard word.
Whereas°hard word: for many valuable°hard word use-cases°hard word, having a 5-minute latency°hard word to do it right, is not°hard word objectionable°hard word. 💡 the evocative questions, the "what do you mean by LONDON" and "can you talk more about LONDON", will be interactive°hard word. ⚙️ we do not°hard word have LONDON implemented°hard word here yet°hard word.