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Phind Model beats GPT-4 at coding, with GPT-3.5 speed and 16k context

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Re: Phind Model beats GPT-4 at coding, with GPT-3.5 speed and 16k context

#81
post #71
post #57

I know it isn't popular, but I wish there was a way to use this inside Emacs. Or, vim. I just don't want to use VS Code anymore.

Pretty sure GitHub Copilot has emacs/vim integration.

It does, although not the most recent features. I use the compatible features in Vim and I really like it. Not enough to switch editors though.

Re: Phind Model beats GPT-4 at coding, with GPT-3.5 speed and 16k context

#82

Well, neither GPT4 or this Phind model where able to answer my torture test: "Write amaranth code that can be used to control the readout of a frame from a kodak CCD with 4096 columns and 2048 rows." Which yes, is missing a lot of detail (you could/I have feed/fed in a datasheet). But Phind goes off on using pyserial (?!), and GPT4 assumes amaranth is a hypothetical CCD control library and makes a useless class contr…

That’s torture for humans as well. The key to LLMs is communicating clearly to the information cloud.

Re: Phind Model beats GPT-4 at coding, with GPT-3.5 speed and 16k context

#83

> 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

This isn't a fair comparison because I have custom instructions that mention being brief but complete, but I did "how to scp a file on Windows 11"

ChatGPT4: 14 seconds

phind with "pair programmer" checked: 65 seconds

phind default: 16 seconds

Re: Phind Model beats GPT-4 at coding, with GPT-3.5 speed and 16k context

#85
post #56

> it supports up to 16k tokens > Llama 1 supports up to 2048 (2K) tokens, Llama 2 up to 4096 (4K), CodeLlama up to 16384 (16K). [0] This is wild to me. The token window is one of the limiting factors for having an AI that can actually remember you and past conversations. Having a large window is key for future AI applications that involve long running conversations (weeks, months, years). The tech is already very imp…

Still waiting for the day that medium term memory (token average pooling like in sentence transformers) becomes used for this. It's staring all of these companies in the face and apparently no one thinks to implement it.

I've been thinking along the same lines. The token window IMO should be a conceptual inverted pyramid, where there most recent tokens are retained verbatim but previous iterations are compressed/pooled more and more as the context grows. I'm sure there's some effort/research in this direction. It seems pretty obvious.

Re: Phind Model beats GPT-4 at coding, with GPT-3.5 speed and 16k context

#86

Earlier quoted context omitted.

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.

LOL, it’s not just for “public acceptance”. Look up Chain of Thought. Asking it to get to the point typically reduces the accuracy.

> LOL, it’s not just for “public acceptance”. Look up Chain of Thought. Asking it to get to the point typically reduces the accuracy.

Just trying to provide helpful feedback for you, this would have been a great comment, except for the "LOL" at the beginning that was unnecesary and demeaning.

Re: Phind Model beats GPT-4 at coding, with GPT-3.5 speed and 16k context

#87

I'm glad there's growing competition, but GPT4 still outperforms. Here's a recent question I asked: Could you please provide me with a query for my PostgreSQL table? It consists of three columns: 'id,' 'teaser,' and 'full_text,' all of which are of type 'text.' Most 'full_text' entries are articles around 1000 words in length. I'd like to update the 'teaser' column for each row with the first approximately 200 words…

One example is not enough for performance conclusions

Re: Phind Model beats GPT-4 at coding, with GPT-3.5 speed and 16k context

#88
Asked it to write a program that I've written before, to compare with gpt4. Didn't really get what I was asking for, gpt4 understood it perfectly, and is ready to continue prompting toward completion.

https://www.phind.com/agent?cache=cloeowfla000dl1084ermly3c vs https://chat.openai.com/share/4147da33-3669-4657-88fa-3a9dfc...

Might not be representative of the whole thing, but it went on about random things I didn't ask about, and just basic information I already knew

Re: Phind Model beats GPT-4 at coding, with GPT-3.5 speed and 16k context

#90

I'm glad there's growing competition, but GPT4 still outperforms. Here's a recent question I asked: Could you please provide me with a query for my PostgreSQL table? It consists of three columns: 'id,' 'teaser,' and 'full_text,' all of which are of type 'text.' Most 'full_text' entries are articles around 1000 words in length. I'd like to update the 'teaser' column for each row with the first approximately 200 words…

One example is not enough for performance conclusions

There is a performance conclusion in the title though.
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