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Escapade5160

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Most large orgs do not need to train end users. They just need to add glm-5.2 to their router and their in house harness will pick it up. Then slowly limit usage on anthropic models and people will swap willingly. It's a simple /model command in every harness.

Claude Sonnet 5 22 days ago

At that price you should just use glm-5.2. You get an Opus class model for 1/3 the cost.

It's in YouTube's best interest to only show users content they're interested in. Replace the word algorithm with users and you'll have a more accurate representation of how YouTube actually works. The reason those videos didn't get the love they deserved is because they're niche content, the 10 minute review videos appeal to a wider audience and therefore gain more traction.

Claude Fable 5 1 month ago

It's crazy to release a model that just swaps you to another model when you ask it hard questions. Fable changes to Opus 4.8 when you talk about cybersecurity, biology, and a couple other categories. You still pay Fable input token cost though. Frontier models are stalling, this is anthropic trying to hype the market up. Now they're talking about stopping frontier model research. It's kind of strange how the moment they become the highest valued AI company, all of a sudden they're talking about everyone stopping frontier model development for "safety". They're just as corrupt as the rest.

This is the same gripe I have over any LLM vulnerability tooling. 95% of what gets flagged is something that if taken by itself could be a vulnerability. However, the path to execute that specific vuln, in that specific function, is impossible in that particular code base and it just makes noise.

Am I correct in my understanding that they are not actually able to 100% know what Claude is thinking? They have trained a new model to make a guess about what Claude is thinking, but we cannot validate that the guess is 100% valid, right? They are basically saying "we have trained a model to reaffirm what we believe Claude is thinking" ? Hoping I'm wrong in my understanding of this because this does not appear to be good research to me.

I am in the same boat. Reading is a transaction and lately everyone wants to put 60 seconds of effort into writing an article and expect me to put 10 minutes into reading it, and I just can't. The writing feels dead, soulless even. Every sentence or phrase is structured like a mongering, click baity headline and it's insufferable.

At this point markdown is going to be the foundation of the entire AI web. Someone the other day showed off Markdown as a responsive frontend protocol. Now we've got email. How long until we're writing classes in markdown? We can only abstract this so far before we confuse AI more than help it.

Theoretically it only requires it for birth. One can argue that once we achieve the singularity, it could immediately scale on its own as it decides.

I recently tried to learn it and found it frustrating. A lot of docs are for 0.15 but the latest is (or was) 0.16 which changed a lot of std so none of the existing write ups were valid anymore. I plan to revisit once it gets more stable because I do like it when I get it to work.

Almost no one knows the shortcut to open the emoji menu on their computer. AI is why there is an increase. Even if someone does know the shortcut, the menu is annoying to use and it slows down your workflow too much for most people to go through the effort.