Live data from Hacker News

ChatGPT for Teams

openai.com

81–90 of 453 posts

Re: ChatGPT for Teams

#81

100 messages / 3 hrs, with a 32k context window. That's really cost effective and efficient for my use case! Does anyone know if this applies to voice conversations? This is me while I'm driving: upload big PDF -> talk to GPT: "Ok, read to me the study/book/article word for word." Good job OpenAI.

> 100 messages / 3 hrs Sorry where do you see that? I only see "higher usage limits"?

https://help.openai.com/en/articles/8801707-what-is-the-mess...

That article doesn't say 100.

100 is what I read in the openai forums earlier today.

Re: ChatGPT for Teams

#82

I’ve got my stuff rigged to hit mixtral-8x7, and dolphin locally, and 3.5-turbo, and the 4-series preview all with easy comparison in emacs and stuff, and in fairness the 4.5-preview is starting to show some edge on 8x7 that had been a toss-up even two weeks ago. I’m still on the mistral-medium waiting list. Until I realized Perplexity will give you a decent amount of Mistral Medium for free through their partnership…

I have 20 years of software development experience, and I couldn’t understand anything you said. Is there a dictionary for this new lingo, or am I just too mid?

They are referring to LLM models. It‘s not about how much software dev experience you have

Re: ChatGPT for Teams

#83

Earlier quoted context omitted.

I have 20 years of software development experience, and I couldn’t understand anything you said. Is there a dictionary for this new lingo, or am I just too mid?

Oh thank you, I was reading and none of that made any sense to me. I thought it could be a presentation of some dumb AI output. Now I see I’m not alone.

That gave me an idea, here is what I got from Copilot:

You have set up your system to run different AI models and compare their performance using a text editor. You are using Mixtral-8x7, a high-quality open-source model developed by Mistral AI, Dolphin, an emulator for Nintendo video games, 3.5-Turbo, a customized version of GPT-3.5, a powerful natural language model, and 4-Series Preview, a new version of the BMW sports coupe. You have noticed that the 4.5-Preview, an upcoming update of GPT-3.5, is slightly better than Mixtral-8x7, which used to be a close match. You are still waiting to access Mistral-Medium, a prototype model that is even better than Mixtral-8x7, but only available to a limited number of users.

You have discovered that Perplexity, an AI company that provides information discovery and sharing services, offers free access to Mistral-Medium through their partnership with Mistral AI. You think that Perplexity is making a mistake by giving away such a valuable model, and that they are underestimating the superiority of Mistral-Medium over the 4.5-Preview. You also think that Mistral AI is the new leader in the AI industry, and that their techniques, such as DPO (Data Processing Optimization), Alibi (a library for algorithmic accountability), sliding window (a method for analyzing time series data), and modern mixtures (a way of combining different models), are well-known and effective. You believe that the advantage of Mistral AI lies in the gap between their innovation and the ability of other developers to replicate it on cheaper and more accessible hardware. You also think that the enterprise market is not fond of the complex structure of GPT-3.5 and its variants, and that they prefer to use Mistral AI's models, which are more affordable and operable on their own premises.

You end your text with a quote from the movie Armageddon, which implies that you are leaving a situation that you dislike, but also admire.

Re: ChatGPT for Teams

#84

I’ve got my stuff rigged to hit mixtral-8x7, and dolphin locally, and 3.5-turbo, and the 4-series preview all with easy comparison in emacs and stuff, and in fairness the 4.5-preview is starting to show some edge on 8x7 that had been a toss-up even two weeks ago. I’m still on the mistral-medium waiting list. Until I realized Perplexity will give you a decent amount of Mistral Medium for free through their partnership…

> Mistral Medium destroys the 4.5 preview. On what metrics? LMSys shows it does well but 4-Turbo is still leading the field by a wide margin. I am using 8x-7b internally for a lot of things and Mistral-7b fine-tunes for other specific applications. They're both excellent. But neither can touch GPT-4-turbo (preview) for wide-ranging needs or the strongest reasoning requirements. https://huggingface.co/spaces/lmsys/cha…

Keep in mind that modern quantitative approaches to LLM evaluation have been effectively co-designed with the rise of OpenAI, and folks like Ravenwolf routinely disagree with the leaderboards.

There's also very little if any credible literature on what constitutes statistically significant on MMLU or whatever. There's such a massive vested interest from so many parties (the YC ecosystem is invested in Sam, MSFT is invested in OpenAI, the US is invested in not-France, a bunch of academics are invested in GPT-is-borderline-AGI, Yud is either a Time Magazine cover author or a Harry Potter fanfic guy, etc.) in seeing GPT-4.5 at the top of those rankings and taking the bold one at I have my own biases as well and freely admit that I love to see OpenAI stumble (no I didn't apply to work there, yes I know knuckleheads who go on about the fact they do).

And once you factor in "mixtral is aligned to the demands of the user and GPT balks at using profanity while happily taking sides on things Ilya has double-spoken on", even e.g. MMLU is nowhere near the whole picture.

It's easy and cheap to just try both these days, don't take my word for which one is better.

Re: ChatGPT for Teams

#85

Earlier quoted context omitted.

I have 20 years of software development experience, and I couldn’t understand anything you said. Is there a dictionary for this new lingo, or am I just too mid?

Yeah that was completely incoherent to me as well.

Same bro

Re: ChatGPT for Teams

#86

I’ve got my stuff rigged to hit mixtral-8x7, and dolphin locally, and 3.5-turbo, and the 4-series preview all with easy comparison in emacs and stuff, and in fairness the 4.5-preview is starting to show some edge on 8x7 that had been a toss-up even two weeks ago. I’m still on the mistral-medium waiting list. Until I realized Perplexity will give you a decent amount of Mistral Medium for free through their partnership…

I have 20 years of software development experience, and I couldn’t understand anything you said. Is there a dictionary for this new lingo, or am I just too mid?

On reflection this thread is pretty clearly of general interest and my comment was more jargon that language, I hang out in ML zones too much.

For a broad introduction to the field Karpathy's YouTube series is about as good as it gets.

If you've got a pretty solid grasp of attention architectures and want a lively overview of stuff that's gone from secret to a huge deal recently I like this treatment as a light but pretty detailed podcast-type format: https://arize.com/blog/mistral-ai

Re: ChatGPT for Teams

#87

I’ve got my stuff rigged to hit mixtral-8x7, and dolphin locally, and 3.5-turbo, and the 4-series preview all with easy comparison in emacs and stuff, and in fairness the 4.5-preview is starting to show some edge on 8x7 that had been a toss-up even two weeks ago. I’m still on the mistral-medium waiting list. Until I realized Perplexity will give you a decent amount of Mistral Medium for free through their partnership…

I have 20 years of software development experience, and I couldn’t understand anything you said. Is there a dictionary for this new lingo, or am I just too mid?

Half LLM, half boomer

Re: ChatGPT for Teams

#88

Earlier quoted context omitted.

I have 20 years of software development experience, and I couldn’t understand anything you said. Is there a dictionary for this new lingo, or am I just too mid?

They are referring to LLM models. It‘s not about how much software dev experience you have

I have heard of LLMs, and understand most everything posted on HN, except quantum computing stuff.

Re: ChatGPT for Teams

#89

Earlier quoted context omitted.

> Mistral Medium destroys the 4.5 preview. On what metrics? LMSys shows it does well but 4-Turbo is still leading the field by a wide margin. I am using 8x-7b internally for a lot of things and Mistral-7b fine-tunes for other specific applications. They're both excellent. But neither can touch GPT-4-turbo (preview) for wide-ranging needs or the strongest reasoning requirements. https://huggingface.co/spaces/lmsys/cha…

Keep in mind that modern quantitative approaches to LLM evaluation have been effectively co-designed with the rise of OpenAI, and folks like Ravenwolf routinely disagree with the leaderboards. There's also very little if any credible literature on what constitutes statistically significant on MMLU or whatever. There's such a massive vested interest from so many parties (the YC ecosystem is invested in Sam, MSFT is in…

> It's easy and cheap to just try both these days, don't take my word for which one is better.

I literally use 8x-7b on my on-prem GPU cluster and have several fine tunes of 7b (which I said in the previous post). I've used mistral-medium.

GPT-4-turbo is better than them all on all benchmarks, human preference, and anything that isn't biased vibes. My opinion - such that it is - is that GPT-4-turbo is by far the best.

I have no vested interest in it being the best. I'd actually prefer if it wasn't. But all objective data points to it being the best and most lived experiences that are unbiased agree (assuming broad model use and not hyperfocused fine-tunes; I have Mistral-7b fine-tunes beating 4-turbo in very limited domains, but that hardly counts).

The rest of your post I really have no idea what's going on, so good luck with all that I guess.

Re: ChatGPT for Teams

#90

Earlier quoted context omitted.

I have 20 years of software development experience, and I couldn’t understand anything you said. Is there a dictionary for this new lingo, or am I just too mid?

On reflection this thread is pretty clearly of general interest and my comment was more jargon that language, I hang out in ML zones too much. For a broad introduction to the field Karpathy's YouTube series is about as good as it gets. If you've got a pretty solid grasp of attention architectures and want a lively overview of stuff that's gone from secret to a huge deal recently I like this treatment as a light but p…

I appreciate it, will check it out :)
Post reply on HN