11–20 of 63 posts
There are some advantages to not having to make an LLM that impresses every human being on the planet. Imagine training the AI to be good in only one specific thing. I think it will become much more precise and deterministic.
This is just my hypothesis. I'm excited to see where this goes.
Earlier quoted context omitted.
Looking at what they're doing here probably not as much as you think. As you note, with the plethora of open/open-ish LLMs today and LoRA + PEFT you can fine tune with low VRAM and pretty quickly so even a single A100 or whatever cloud GPUs are just fine. I've even seen people pull it off in reasonable time on super cheap T4s, A10s, etc. I doubt anyone reading a blog post is attempting to train a "true" multi-billion…
[flagged]
Ok, I'll try again because I read the article and watched the demo video from Mosaic:
- MosaicML claims to have some magic that efficiently autoscales with awareness of specific instance per hour pricing.
- MosaicML claims to have auto-optimize magic that makes training 3-7x faster.
- The incentives seem to be aligned because their value prop is likely "we'll markup 10% but save you 50%" (or whatever).
It's too bad Replit didn't provide the costs for this post in the same way Stanford, etc have done with Alpaca, Vicuna, etc. They probably didn't for from-scratch training because the answer to your question is almost certainly "it depends" or "if you have to ask you can't afford it" (for now).
Did we ever get any resolution about what happened after this company threatened to sue their intern for making a side project that supposedly stole all their great ideas? I would like to know before I ever consider anything from them again.
Story for those who didn't see it: https://intuitiveexplanations.com/tech/replit/
This is interesting. I think the future of AI will not be re-creating something like ChatGPT, but using variations of these methodologies to train AI models for specific tasks. There are some advantages to not having to make an LLM that impresses every human being on the planet. Imagine training the AI to be good in only one specific thing. I think it will become much more precise and deterministic. This is just my h…
That reminds me - I saw a somewhat-clever acronym variant for LLM that communicated this the other day but it escapes me ATM...
[0] - https://www.mosaicml.com/blog/introducing-pubmed-gpt
[1] - https://cloud.google.com/blog/topics/healthcare-life-science...
[2] - https://dev.to/reaminated/thoughts-on-bloomberggpt-and-domai...
Earlier quoted context omitted.
[flagged]
Ouch. Ok, I'll try again because I read the article and watched the demo video from Mosaic: - MosaicML claims to have some magic that efficiently autoscales with awareness of specific instance per hour pricing. - MosaicML claims to have auto-optimize magic that makes training 3-7x faster. - The incentives seem to be aligned because their value prop is likely "we'll markup 10% but save you 50%" (or whatever). It's too…
This is interesting. I think the future of AI will not be re-creating something like ChatGPT, but using variations of these methodologies to train AI models for specific tasks. There are some advantages to not having to make an LLM that impresses every human being on the planet. Imagine training the AI to be good in only one specific thing. I think it will become much more precise and deterministic. This is just my h…
There is plenty of less attention-grabbing work being done on "domain specific LLMs" like BioMedLM[0], Med-PaLM[1], BloombergGPT[2], etc. That reminds me - I saw a somewhat-clever acronym variant for LLM that communicated this the other day but it escapes me ATM... [0] - https://www.mosaicml.com/blog/introducing-pubmed-gpt [1] - https://cloud.google.com/blog/topics/healthcare-life-science... [2] - https://dev.to/ream…
Also I'm not talking about just 'prompt' output model. These ones are great and I'm sure they will be extremely impressive. However I'm talking more about being able to 'operate' something.
Imagine this, an AI able to operate some specific API in a deterministic / reliable way. I'm talking about complex operations.
SO the output is not so much a text prompt but an SOP and then actually Operating the SOP.
Imagine going into an app and say "can you boot up a cluster on AWS and run a wordpress site, point domain example.com to the site".
Imagine this "you know my database for app X, what was the latest snapshot", it replies with the date / time of the snapshot, and you reply with "can you move that snapshot from google cloud and create a new database from that snapshot on AWS cloud?", and it does it for you.
That's what I look forward to.
Earlier quoted context omitted.
The founder admitted his mistake and the ex-intern's site is back up and running https://riju.codes/ . I'm personally a fan of both Amjad's (CEO) and Radon's (intern) and realize that everyone makes mistakes. It's not a reason to discount the hard work of the people at replit.
A badly behaved CEO is absolutely a reason to avoid using a whole company. Reading through the entire story leaves me with a bad taste in my mouth, especially this bit: "still refused to list any specific part of Replit he thought I had copied, even when I asked him for such details multiple times during the phone call, despite his continuing to claim both privately and publicly that I copied Replit unethically". I h…
Did we ever get any resolution about what happened after this company threatened to sue their intern for making a side project that supposedly stole all their great ideas? I would like to know before I ever consider anything from them again.
The founder admitted his mistake and the ex-intern's site is back up and running https://riju.codes/ . I'm personally a fan of both Amjad's (CEO) and Radon's (intern) and realize that everyone makes mistakes. It's not a reason to discount the hard work of the people at replit.
I’m curious what he’s said or done to make you a fan?
Earlier quoted context omitted.
There is plenty of less attention-grabbing work being done on "domain specific LLMs" like BioMedLM[0], Med-PaLM[1], BloombergGPT[2], etc. That reminds me - I saw a somewhat-clever acronym variant for LLM that communicated this the other day but it escapes me ATM... [0] - https://www.mosaicml.com/blog/introducing-pubmed-gpt [1] - https://cloud.google.com/blog/topics/healthcare-life-science... [2] - https://dev.to/ream…
Yeah that's awesome. I honestly think the next 'leap' in AI will come from these 'domain specific' models. Also I'm not talking about just 'prompt' output model. These ones are great and I'm sure they will be extremely impressive. However I'm talking more about being able to 'operate' something. Imagine this, an AI able to operate some specific API in a deterministic / reliable way. I'm talking about complex operatio…
It actually seems like more of a task for good 'ol fashioned NLP (intent recognition) with some wiring for all of the connectors...
Did we ever get any resolution about what happened after this company threatened to sue their intern for making a side project that supposedly stole all their great ideas? I would like to know before I ever consider anything from them again.
The founder admitted his mistake and the ex-intern's site is back up and running https://riju.codes/ . I'm personally a fan of both Amjad's (CEO) and Radon's (intern) and realize that everyone makes mistakes. It's not a reason to discount the hard work of the people at replit.