Got it. You think if you tuned again after calibrating tool calling it would be beneficial?

Bummer. Do you think it was the training data or just nature of fine tuning? Something else? What were you tuning it for if you don’t mind my asking?

Did you notice a big improvement in the tasks you were tuning for? What is your hardware setup and how long did it take?

Thanks!

I’ve heard a lot about Lora like Unsloth. Have you used anything like it?

Yeah that’s what I’m thinking. Similar to the interconnectedness people experience with psilocybin.

Yeah I read that but it could still be something that has been spread across Asian regions. I agree though, there’s likely something specific to the shroom.

What’s the secret sauce? How it writes the skills? When it decides to do it within a conversation? Sounds like it creates skill files (markdown?) and saves them to a library, then an agent pulls in relevant skills during future prompts?

I can see this being obsolete very soon. Couldn’t you make Codex or Code do this for you. Build your own agent/s even. Maybe it’ll be included in future releases of major commercial LLMs.

I want some.

Also, why haven’t any of the researches tried it? I’m curious if seeing little people is a cultural thing or an unique effect of the drug. I’m less surprised that there’s a psychedelic chemical out there that modern science has not studied yet.

Clean it up a little around the edges and it’s actually pretty cool looking new footwear

Public service announcement: induction takes days, especially if it’s early like 39 weeks.

Ah yeah context and token limits are gonna hold you back. Opus output is more than output large chapters, but you’ll probably get the best results by prompting via API (command line/CLI). You can set max output limits and provide files for RAG. You also might need to upgrade to a plan that can handle marathon sessions better like Claude Max. Claude is also better for creative writing apparently. Good luck!

Have you tried providing some reference stories for context via RAG? That should help ground some of the writing. If you wanna go all out you can fine-tune a model to adapt to the style of writing you’re looking for. There should be some “novel writing assistant” models out there because people are definitely writing and publishing books with AI. Good luck!

Do leases count? Could be leasing, or maybe got some 84 month loan.

I can’t help but think this is an attack on black parenting, but maybe that’s reading into it too much. I can’t imagine the White House caring so much about a gorilla. Way more than Melissa Hortman, and she was human. There’s a political reason for this post.

What about quantum computing? That’s seems to be the next step. Much more efficient. Again, I’m totally out of my depth there as well. I only understand qubits at a very basic level. I don’t even really understand wave functions.

Wow most of this goes way over my head. I kind of understand the limiting to 8 bit method. I’ve heard about that being done elsewhere.

When you say negative numbers you’re talking about the embedding?

I still don’t understand gradient descent fully, but can you explain why you think it should be replaced and with what?

Thanks!

Can you give me a use case?

Doxxing?

Thanks for the explanation. Maybe I don’t understand, but I thought by nature LLMs were not deterministic. Is it because you’re breaking the output up into pieces?

Haha that AI generated summary is even less appealing than the video. I’m not a coder so what I’m saying is the value of Grace doesn’t translate to me. Is it that using Grace code you’re able to output prompts that LLMs are better at processing? I’m asking for examples of how you are using it. Thanks!

Thanks for sharing! Yeah interesting community. Some people don’t like sharing ideas.

I skimmed through the video but not sure what the use of Grace would be. I can already ask an LLM to generate markdown for me. How do you use it?