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I love that Phind cites what it scrapes. This should be the obligation of all LLM. I always suggest people use it over ChatGPT.
As a user, i perfer getting the right response compared to the thing spitting out a link. (not saying phind is bad). Lets focus on getting llm right before nerfing it in its baby stages.
> You can now get high quality answers for technical questions in 10 seconds instead of 50. ChatGPT 4 does not take 50 seconds to answer, so I don't understand this comparison.
Recently I've used gpt 4 and yes it does take up to a minute even for easy questions. I've asked it how to scp a file on Windows 11 and it'll take a minute to tell me all the options possible. If this takes 1/5th the time for equivalent questions, I'd consider switching
If so, consider adding one of the “just get to the point” prompts. GPT4’s defaults have been geared towards public acceptance through long-windedness which is imo entirely unnecessary when using it to do functional things like scp a file.
Earlier quoted context omitted.
As a user, i perfer getting the right response compared to the thing spitting out a link. (not saying phind is bad). Lets focus on getting llm right before nerfing it in its baby stages.
Who said anything about nerfing? Citation is just additive, no?
I tried this, but I still have yet to get any LLM to answer me a programming question (that actually works) that I actually want to solve. Basically: "How can I send network control commands to an AppleTV in C#" They always make up some nonexistent library or gives an example using some nonexistent API.
“Make me a billionaire… I’m still poor! Bad AI!”
You need to collaborate with the AI, use it to help with each small step of the problem, with input references provided.
To a degree Phind can do the reference chasing for you, but it’s not magic.
> We can achieve up to 100 tokens per second single-stream while GPT-4 runs around 20 tokens per second at best. Is that with batching? If so, thats quite impressive. > certain challenging questions where it is capable of getting the right answer, the Phind Model might take more generations to get to the right answer than GPT-4. Some of this is sampler tuning. Y'all should look at grammar based sampling ( https://git…
The results are impressive and things have been really progressing quickly, so kudos.
But even by your own description in this post, something like “rivals GPT-4 at coding” seems a more accurate appraisal.
https://www.phind.com/search?cache=ay8rx37gq8oy3z7uixftlqkt
https://chat.openai.com/share/a3a91dcc-a91a-4b04-8afd-40bd1a...
from my last week test of opensource model , it keep repeating and gives out broken outputs, using q4
This V7 model is much better than the V2 model that we previously open-sourced. And Q4 quantization would also likely have a large detrimental impact.
Earlier quoted context omitted.
Recently I've used gpt 4 and yes it does take up to a minute even for easy questions. I've asked it how to scp a file on Windows 11 and it'll take a minute to tell me all the options possible. If this takes 1/5th the time for equivalent questions, I'd consider switching
Not my experience at all. Are you counting the entire answer in your time? If so, consider adding one of the “just get to the point” prompts. GPT4’s defaults have been geared towards public acceptance through long-windedness which is imo entirely unnecessary when using it to do functional things like scp a file.
Also, use case thing. It is very likely the case that for certain coding use cases, Phind will always be faster because it's not designed to be general purpose.