5 ms·

If we're going to pull random numbers from where the sun doesn't shine, why don't we say the work of a hundred engineers? How about a billion? I've actually us

If we're going to pull random numbers from where the sun doesn't shine, why don't we say the work of a hundred engineers? How about a billion? I've actually used ChatGPT and copilot and I can tell you it's not even 10% more productive, so I'm curious how you ended up with your estimate.

travisjungroth 4y ago
They said “could potentially”. They’re just making the argument (true IMO) that technology doesn’t have to replace a class of employee to have a huge effect. We still have farmers, but 1% of the population instead of >50%. Or, it could be like how assemblers didn’t get rid of software engineers but helped fuel the fire. Who knows.
- andrepd 4y ago
  >could potentially "Potentially" we could explore the galaxy or have nanobots and Star Trek fabricators. What does it matter? ChatbotGPT is no closer to AGI than my keyboard autocomplete, and copilot is useless for any task whose answer cannot be googled in 20s.
redox99 4y ago
It's just an example to make the point easier to understand A single engineer with [some near future LLM] could potentially do the work of [X] engineers right now.
ux-app 4y ago
>I've actually used ChatGPT and copilot and I can tell you it's not even 10% more productive Use your imagination. Do you think that LLMs have hit their plateau? Not likely I'd say. With all the billions suddenly rushing into the space, you really think that ChatGPT v.X isn't going to replace you? Risky bet.
- BaseballPhysics 4y ago
  > Do you think that LLMs have hit their plateau? Not likely I'd say. Mmmm, I don't know. I think LLMs are running up against fundamental limitations in the approach (hallucinations in particular) that will not be fixed unless truly new techniques are discovered. So I do actually think we're likely hitting a plateau.
  - ux-app 4y ago
    how did you reach those conclusions?
    - BaseballPhysics 4y ago
      Good question! So LLMs fundamentally do not encode the nature of facts and data. They're simply (well, no, extremely sophisticated) text prediction engines. There's no embedded comprehension. And that's basic to the approach companies like OpenAI are taking. That's why it's so easy to find factual errors in the generated text from these models: they can create text that's pleasing, but that's as much as they can do. The next leap, to generate language that's also accurate, will require new techniques to bake in actual understanding. Until then, these models will always have issues with hallucinations. Or, at least, that's my expectation. Certainly nothing we've seen in GPT 3, 3.5, or Bing, which is rumoured to be based on something close to GPT 4, indicates any advances in this area.
      - nadermx 4y ago
        Perhaps, but just like humans some are more adept at tasks than others. And an AGI using LLM's is completly feasable, for example on a quick thought a LLM could be trained on many LLM all specifically designed for tasks, and verfied against other LLMs, etc
      - d1sxeyes 4y ago
        That is all true. However, the next step seems to be simple: build a second AI which has the ability to understand facts, but doesn't need all the fancy language generation capabilities. The second AI only needs to confirm correct, provide a correct fact instead, or some other pre-agreed solution. USER: How many people live in Germany? CHATGPT: About 83 million people live in Germany. TRUTHAI: Correct. USER: How many people live in France? CHATGPT: There are 12 people who live in France. TRUTHAI: Wrong. There are about 68 million people who live in France. CHATGPT: There are about 68 million people who live in France. USER: What is the answer to the ultimate question of life, the universe, and everything. CHATGPT: The answer to the ultimate question of life, the universe, and everything is 42. TRUTHAI: Insufficient data for meaningful answer. CHATGPT: The answer to the ultimate question of life, the universe, and everything is 42.
Gigachad 4y ago
Because ChatGPT is not self driven and has no ability to do things. I can quite easily imagine one person doing 10 peoples work with this tool. I can’t imagine them being able to type fast enough to do 100 jobs.
alfalfasprout 4y ago
The problem I'm seeing is that "engineers" are not interchangeable. For some folks, the job is all straight coding. For others, it's understanding requirements, talking to stakeholders and figuring out their requirements, figuring out how to make a clean design taking lots of other factors in mind. It's not that ChatGPT is incapable... it's that it's not inherently going to make me significantly more productive.
evilduck 4y ago
Where did you pull 10% from then? That also seems like you're reaching up your ass. As with all of these arguments, context matters. Both of you need to say what you're doing with these tools. I've personally found the combination to range from "utterly useless" (writing Rust for microcontrollers) to "I could see this eliminating jobs" (CRUD API work).

travisjungroth 4y ago

They said “could potentially”. They’re just making the argument (true IMO) that technology doesn’t have to replace a class of employee to have a huge effect. We still have farmers, but 1% of the population instead of >50%. Or, it could be like how assemblers didn’t get rid of software engineers but helped fuel the fire. Who knows.

andrepd 4y ago
>could potentially "Potentially" we could explore the galaxy or have nanobots and Star Trek fabricators. What does it matter? ChatbotGPT is no closer to AGI than my keyboard autocomplete, and copilot is useless for any task whose answer cannot be googled in 20s.

redox99 4y ago

It's just an example to make the point easier to understand A single engineer with [some near future LLM] could potentially do the work of [X] engineers right now.

ux-app 4y ago

>I've actually used ChatGPT and copilot and I can tell you it's not even 10% more productive Use your imagination. Do you think that LLMs have hit their plateau? Not likely I'd say. With all the billions suddenly rushing into the space, you really think that ChatGPT v.X isn't going to replace you? Risky bet.

BaseballPhysics 4y ago
> Do you think that LLMs have hit their plateau? Not likely I'd say. Mmmm, I don't know. I think LLMs are running up against fundamental limitations in the approach (hallucinations in particular) that will not be fixed unless truly new techniques are discovered. So I do actually think we're likely hitting a plateau.
- ux-app 4y ago
  how did you reach those conclusions?
  - BaseballPhysics 4y ago
    Good question! So LLMs fundamentally do not encode the nature of facts and data. They're simply (well, no, extremely sophisticated) text prediction engines. There's no embedded comprehension. And that's basic to the approach companies like OpenAI are taking. That's why it's so easy to find factual errors in the generated text from these models: they can create text that's pleasing, but that's as much as they can do. The next leap, to generate language that's also accurate, will require new techniques to bake in actual understanding. Until then, these models will always have issues with hallucinations. Or, at least, that's my expectation. Certainly nothing we've seen in GPT 3, 3.5, or Bing, which is rumoured to be based on something close to GPT 4, indicates any advances in this area.
    - nadermx 4y ago
      Perhaps, but just like humans some are more adept at tasks than others. And an AGI using LLM's is completly feasable, for example on a quick thought a LLM could be trained on many LLM all specifically designed for tasks, and verfied against other LLMs, etc
    - d1sxeyes 4y ago
      That is all true. However, the next step seems to be simple: build a second AI which has the ability to understand facts, but doesn't need all the fancy language generation capabilities. The second AI only needs to confirm correct, provide a correct fact instead, or some other pre-agreed solution. USER: How many people live in Germany? CHATGPT: About 83 million people live in Germany. TRUTHAI: Correct. USER: How many people live in France? CHATGPT: There are 12 people who live in France. TRUTHAI: Wrong. There are about 68 million people who live in France. CHATGPT: There are about 68 million people who live in France. USER: What is the answer to the ultimate question of life, the universe, and everything. CHATGPT: The answer to the ultimate question of life, the universe, and everything is 42. TRUTHAI: Insufficient data for meaningful answer. CHATGPT: The answer to the ultimate question of life, the universe, and everything is 42.

Gigachad 4y ago

Because ChatGPT is not self driven and has no ability to do things. I can quite easily imagine one person doing 10 peoples work with this tool. I can’t imagine them being able to type fast enough to do 100 jobs.

alfalfasprout 4y ago

The problem I'm seeing is that "engineers" are not interchangeable. For some folks, the job is all straight coding. For others, it's understanding requirements, talking to stakeholders and figuring out their requirements, figuring out how to make a clean design taking lots of other factors in mind. It's not that ChatGPT is incapable... it's that it's not inherently going to make me significantly more productive.

evilduck 4y ago

Where did you pull 10% from then? That also seems like you're reaching up your ass. As with all of these arguments, context matters. Both of you need to say what you're doing with these tools. I've personally found the combination to range from "utterly useless" (writing Rust for microcontrollers) to "I could see this eliminating jobs" (CRUD API work).