3 ms·

Dominance is such a charged word. We have been corrupted by words like that. Why should we care about dominance? We should care about collaboration and peopl

by nico 4y ago

Dominance is such a charged word. We have been corrupted by words like that. Why should we care about dominance? We should care about collaboration and people’s well being. Barring a catastrophe, AI is not going to stop. At the current rate, by next month we will have some previously-never-seen model/algorithm/chip/tech that will run locally on our phones and computers. At that point is game over for the big server-model companies. After that… well, pretty much all companies will be at stake. There’s a much bigger revolution happening right now than just the tech industry. We will be forced to ask ourselves what it means to be human. No company is going to dominate AI, AI is going to dominate AI.

atleastoptimal 4y ago
AI will dominate but only on huge distributed compute clusters. Local will be able to run models at reasonable speeds only when they're 4 years old.
- thatjoeoverthr 4y ago
  Four years will come and go.
- yreg 4y ago
  Doesn't the recent development (Stable Diffusion, LLaMA) tell us that these things actually run surprisingly well locally and that the models can be compressed much further? And aren't we finding out that the amount of parameters seems to matter less than we used to believe?
- xyzzy123 4y ago
  All indications are that you can scale LLMs up & down pretty smoothly, I bet there will be lots of workflows in future using AI on pc-or mobile scale hardware which can call out to cloud AI for "deep thinking" or to double check stuff. It seems likely there will be AIs specialised in taxes or medicine, people/systems will consult multiple AIs to smooth out errors and look for consensus etc. In short, I agree with OP that we will probably end up with something that looks more like an ecosystem than a hegemony.
- nico 4y ago
  For the other replies: I think @atleastoptimal was making a joke about families/parenting.
Aperocky 4y ago
> by next month we will have some previously-never-seen model/algorithm/chip/tech that will run locally on our phones and computers. At that point is game over This comment is so wildly inaccurate and hype, and yet so common in the GPT craze on HN It is not happening on your phone and computers in the near term for 2 reasons: 1. Entropy, the models are LARGER, NOT SMALLER. The amazing performance come from the fact that they are BIG. This is opposite of Moore's law, which itself is ending. 2. Companies want to make money on their models, vending a client is clearly not the direction that companies are going. In fact greedy companies wanted everything to happen on the server end even without any real customer need, e.g. Jira.
- nico 4y ago
  1. You might not be up to date. This was posted on HN 4 days ago: https://news.ycombinator.com/item?id=35281026 https://news.ycombinator.com/item?id=35281026 Check it out. They are claiming 100x faster training and inference with smaller models, performing almost with the same accuracy as GPT. People are already running models on their phones. Some people have been posting here and on Twitter how they can run Alpaca (Llama + GPT fine tuning), on their Pixel phones. 2. The cat is out of the bag. People are creating and releasing stuff faster than companies can keep up with. Have you seen what ChatGPT is already able to do with plug-ins? You can give it control of a Linux machine and tell it “create a basic CRUD app and run it on a docker container”, and it will do it. That means soon AI is going to be training itself, or at least with minimum input/direction from humans.
  - aleksiy123 4y ago
    Do you have any links to chatgpt with Linux. I want to try
    - nico 4y ago
      They used ChatGPT’s code interpreter plug-in. Here’s a good write up about that plug-in and an overview of a lot of the things you can do: https://andrewmayneblog.wordpress.com/2023/03/23/chatgpt-code-interpreter-magic/ https://andrewmayneblog.wordpress.com/2023/03/23/chatgpt-cod... If you don’t have access to plug-ins yet, you could do it yourself by using the GPT api, writing a prompt that tells GPT they are interacting with a terminal and to only output terminal commands, then pass the output to a terminal, and passing back the output to GPT in a loop. I can’t find the exact link to the docker app video/article. Lately it’s really hard to keep up. The search feature here on HN kinda sucks on mobile and Google is hopelessly behind with how fast things are coming out.

by nico 4y ago

atleastoptimal 4y ago

AI will dominate but only on huge distributed compute clusters. Local will be able to run models at reasonable speeds only when they're 4 years old.

thatjoeoverthr 4y ago
Four years will come and go.
yreg 4y ago
Doesn't the recent development (Stable Diffusion, LLaMA) tell us that these things actually run surprisingly well locally and that the models can be compressed much further? And aren't we finding out that the amount of parameters seems to matter less than we used to believe?
xyzzy123 4y ago
All indications are that you can scale LLMs up & down pretty smoothly, I bet there will be lots of workflows in future using AI on pc-or mobile scale hardware which can call out to cloud AI for "deep thinking" or to double check stuff. It seems likely there will be AIs specialised in taxes or medicine, people/systems will consult multiple AIs to smooth out errors and look for consensus etc. In short, I agree with OP that we will probably end up with something that looks more like an ecosystem than a hegemony.
nico 4y ago
For the other replies: I think @atleastoptimal was making a joke about families/parenting.

Aperocky 4y ago

> by next month we will have some previously-never-seen model/algorithm/chip/tech that will run locally on our phones and computers. At that point is game over This comment is so wildly inaccurate and hype, and yet so common in the GPT craze on HN It is not happening on your phone and computers in the near term for 2 reasons: 1. Entropy, the models are LARGER, NOT SMALLER. The amazing performance come from the fact that they are BIG. This is opposite of Moore's law, which itself is ending. 2. Companies want to make money on their models, vending a client is clearly not the direction that companies are going. In fact greedy companies wanted everything to happen on the server end even without any real customer need, e.g. Jira.

nico 4y ago
1. You might not be up to date. This was posted on HN 4 days ago: https://news.ycombinator.com/item?id=35281026 https://news.ycombinator.com/item?id=35281026 Check it out. They are claiming 100x faster training and inference with smaller models, performing almost with the same accuracy as GPT. People are already running models on their phones. Some people have been posting here and on Twitter how they can run Alpaca (Llama + GPT fine tuning), on their Pixel phones. 2. The cat is out of the bag. People are creating and releasing stuff faster than companies can keep up with. Have you seen what ChatGPT is already able to do with plug-ins? You can give it control of a Linux machine and tell it “create a basic CRUD app and run it on a docker container”, and it will do it. That means soon AI is going to be training itself, or at least with minimum input/direction from humans.
- aleksiy123 4y ago
  Do you have any links to chatgpt with Linux. I want to try
  - nico 4y ago
    They used ChatGPT’s code interpreter plug-in. Here’s a good write up about that plug-in and an overview of a lot of the things you can do: https://andrewmayneblog.wordpress.com/2023/03/23/chatgpt-code-interpreter-magic/ https://andrewmayneblog.wordpress.com/2023/03/23/chatgpt-cod... If you don’t have access to plug-ins yet, you could do it yourself by using the GPT api, writing a prompt that tells GPT they are interacting with a terminal and to only output terminal commands, then pass the output to a terminal, and passing back the output to GPT in a loop. I can’t find the exact link to the docker app video/article. Lately it’s really hard to keep up. The search feature here on HN kinda sucks on mobile and Google is hopelessly behind with how fast things are coming out.