AI/LLM: Difference between revisions
< AI
Jump to navigation
Jump to search
No edit summary |
|||
Line 9: | Line 9: | ||
* [https://www.perplexity.ai/ Perplexity] | * [https://www.perplexity.ai/ Perplexity] | ||
** [https://www.perplexity.ai/search/what-software-is-needed-for-tr-XT_VpmS4RRiFBZF0bvuNOQ What software is needed for training a large language model (LLM)?] | ** [https://www.perplexity.ai/search/what-software-is-needed-for-tr-XT_VpmS4RRiFBZF0bvuNOQ What software is needed for training a large language model (LLM)?] | ||
==ideas== | |||
* LLMs could make federated search (of which I think {{l/htyp|YaCy}} is currently the only exemplar) actually workable/useful: | |||
** You type in your search -- either as keywords or as a natural-language query. | |||
** A search is done (however LLMs do it currently -- I don't know if they fine-tune the search parameters or just pass them on to a search engine). | |||
** The LLM then processes/glosses the top results to look for pages that seem to be most applicable to the request. If nothing passes a threshold test, it looks at the next bunch of results. If it can't find anything likely, it summarizes what it did find and notes that it may not be what you're looking for. | |||
* I'd like to see an LLM browser plugin that can find tabs based on natural-language queries -- "where's the one with that medical form?" "Have I stashed any tabs about...[subject]?". Similarly, an app or library which can take a URL, load the corresponding web page, and produce a summary and keywords would also be hella useful. | |||
==Notes== | ==Notes== | ||
* '''2024-10-07''' [https://arxiv.org/pdf/2410.05229 GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models] (paper by Apple researchers; [https://sfba.social/@drahardja/113310311247575811 via]) | * '''2024-10-07''' [https://arxiv.org/pdf/2410.05229 GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models] (paper by Apple researchers; [https://sfba.social/@drahardja/113310311247575811 via]) |
Revision as of 15:40, 15 November 2024
Large Language Model AI (LLMs)
|
I often use these for answering questions (usually technical, occasionally political).
commercial services
- ChatGPT (by OpenAI, which is neither open nor AI[1])
- Copilot (Microsoft)
- FastGPT: seems to be Kagi's own model, not just a front-end to some other LLM
- Perplexity
ideas
- LLMs could make federated search (of which I think YaCy is currently the only exemplar) actually workable/useful:
- You type in your search -- either as keywords or as a natural-language query.
- A search is done (however LLMs do it currently -- I don't know if they fine-tune the search parameters or just pass them on to a search engine).
- The LLM then processes/glosses the top results to look for pages that seem to be most applicable to the request. If nothing passes a threshold test, it looks at the next bunch of results. If it can't find anything likely, it summarizes what it did find and notes that it may not be what you're looking for.
- I'd like to see an LLM browser plugin that can find tabs based on natural-language queries -- "where's the one with that medical form?" "Have I stashed any tabs about...[subject]?". Similarly, an app or library which can take a URL, load the corresponding web page, and produce a summary and keywords would also be hella useful.
Notes
- 2024-10-07 GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models (paper by Apple researchers; via)
- 2023-05-24 Worried About Sending Your Data to a Chatbot? 'PrivateGPT' Is Here
Code Sources
- Auto-GPT «chains together LLM "thoughts", to autonomously achieve whatever goal you set.»
- Downside: not fully autonomous; still depends on OpenAI
- privateGPT
Footnote
- ↑ ...in the sense that LLMs in general are not really what the term "AI" means to me.