Recent comments in /f/MachineLearning

michaelthwan_ai OP t1_jcws6h8 wrote

Reply to comment by Secret-Fox-5238 in [P] searchGPT - a bing-like LLM-based Grounded Search Engine (with Demo, github) by michaelthwan_ai

ChatGPT said what I want to say.

>I apologize for any confusion or misinformation in my previous response. You are correct that SQL databases do support various text search and similarity matching features, including the use of keywords like LIKE and CTE (Common Table Expressions) to enable more flexible and efficient querying.
>
>While it's true that specialized tools like Elasticsearch, Solr, or Algolia may offer additional features and performance benefits for certain natural language processing tasks, SQL databases can still be a powerful and effective tool for storing and querying structured and unstructured data, including text data.
>
>Thank you for bringing this to my attention and allowing me to clarify my previous response.

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suineg t1_jcwhvs3 wrote

Reply to [D] Simple Questions Thread by AutoModerator

I'm curious on the feasibility of a concept before I start going down the road. I am also unsure if maybe there is already a project that I should look into.

There is a fantasy book series that I enjoy and it's 10 books and 3.3M words (I don't have a character count). The world and characters are complicated and their interactions with other characters is sometimes pretty obscure. I want to make a dynamic wiki and search tool for two things.

Phase 1 - Ingest all of the text and start building out character profiles, book profiles, etc. The front end would tag information based on what book so if you've only ready up to book 7 you don't get 8-10 spoiled. You could give it a parameter like "list all the battles character a and character b are in together".

Phase 2 - This would be the difficult portion much later on and I'm not focused on it yet. You could get ask it something like "give me a view of character b after event_32" and based on the descriptions it would generate art. You could also give it things like "give me a scene of character b, d, and h at the battle of event_40" and it would generate one based on that stored event.

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sanxiyn t1_jcw2yoz wrote

Reply to comment by clueless1245 in [R] ChatGLM-6B - an open source 6.2 billion parameter Eng/Chinese bilingual LLM trained on 1T tokens, supplemented by supervised fine-tuning, feedback bootstrap, and RLHF. Runs on consumer grade GPUs by MysteryInc152

On the other hand, commercial use restriction is not compatible with generally accepted definition of open source, for example The Open Source Definition.

> 6) No Discrimination Against Fields of Endeavor. The license must not restrict anyone from making use of the program in a specific field of endeavor. For example, it may not restrict the program from being used in a business, or from being used for genetic research.

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thedabking123 t1_jcvmwoq wrote

Reply to [D] For those who have worked 5+ years in the field, what are you up to now? by NoSeaweed8543

It happens in every career in every field; I'm 37 and have been a PM of an ai-driven product for a while now.

I am starting to care more about corporate leadership and using money earned to enjoy life than the technical bits I've been cycling around for a while on

Some ideas that may apply to you

  1. you could focus on people management and direct teams on larger projects
  2. you could try and find companies with new interesting problems to solve (MLOps for LLM models in firms like Jasper, or OpenAI, or Cohere, or perhaps HCI loops between humans and UI-embedded LLMs like at adept.ai ?)
  3. you could find a truly deep R&D job on a crazy new area and go at something novel. (i personally would love to spend 2-3 yrs exploring neurosymbolic computing or quantum computing once i get tired of corporate politics; haven't decided yet)
  4. etc.

No one job is a constant set of discovery and joy and focus. Everything gets old after a while so be prepared to refresh your career again in 3-5 yrs.

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Expensive-Type2132 t1_jcvddj4 wrote

Reply to comment by alfredr in [R] What are the current must-read papers representing the state of the art in machine learning research? by alfredr

If you’re outside of the community, it might be more beneficial to look at applicative papers to get an understanding of tasks, objective functions, datasets, training strategies, etc. Especially during this period where there isn’t that much architectural diversity. But, nevertheless, read whatever you’re noticed to read!

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egoistpizza t1_jcvcl5h wrote

Reply to [P] searchGPT - a bing-like LLM-based Grounded Search Engine (with Demo, github) by michaelthwan_ai

Hi! Your project and other projects based on this topic constitute a valid response to active curiosity on this subject. It will be in the interest of society for AI-powered search engines to enter the active development process and gather their unique user base. The only doubt is that as OpenAI and other AI "for-profit" companies close their projects to external analysis and development over time (see GPT-4), AI-powered applications will become closed boxes and the development potential of these projects will be limited. The active protest reactions that we can show on this issue can lose its effect over time, the masses can close their eyes in the face of hype and demand products that are harmful to us in the long run. For this reason, I think that the protest in this area should be made as a mass as soon as possible.

I may have stretched the subject a bit too much, I liked your project and other similar projects quite a lot. Not only did it answer the test question I just asked, it also corrected my grammatical errors in the question, causing me to be a little surprised swh. My request is that we, as a society, do not forget about the potential that we are losing by getting immersed in leading projects. AI-powered applications are great, but we must not forget our rights that these companies take away from us day by day.

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