3 ms·

Consider that this is just the beginning for LLMs, and GPT-4 is already somewhat magical. There’s no reason to believe that this already magical program can’t g

Consider that this is just the beginning for LLMs, and GPT-4 is already somewhat magical. There’s no reason to believe that this already magical program can’t get exponentially better. Magic ^ X It’s going to be a wild ride. Also consider that LLMs don’t have the “last 5%” problem that self-driving software has, where widespread use is currently untenable because humans still need to intervene and that poses safety problems. LLMs are very complimentary to a large breadth of human work, until they stop being complimentary and instead become a substitute. Another thing I’ll say is, the investment in the already mind-blowing LLMs like GPT-4 is relatively puny, a fraction of the cost of building 1 skyscraper. What’s happening is that the market has been validated and much larger sums of $$$ are going to flood in, including into the research pipeline which can solve problems such as data “scarcity” for future AI. Imagine a much smarter version of GPT-4, except constantly thinking like a human does (as opposed to prompt-response-wait-prompt-response…), constantly working towards some specified goal, and…placed in a robot body like those made by Boston Dynamics. That’s not even in the far future. It’s technically possible in 6-12 months. Finally, looping back to self-driving - I think you’ve reached your conclusion too early there. Once the last 5% problem is solved for self-driving, it will be solved for everyone and forever and getting from point A to B on the road will forever be available to you by a robot chauffeur 24/7, forever deliver things to you autonomously, and improve supply chain/logistics by a lot, with downstream reduction in the price of delivered goods.

datadrivenangel 3y ago
LLMs also have the last 5% problem for sure.
- keenmaster 3y ago
  True, but there is a wide range of use-cases where “failure” of an LLM is tolerated, and it’s almost never safety-critical like driving is.
  - notmypenguin 3y ago
    That’s going to depend upon deployment context. The hype around LLMs and the word AÍ has certainly been received by the general public as license for further penetration of markets. I doubt most humans are comfortable with autonomous vehicles yet we have a relentless push for the same from the worlds richest man, who insists upon foisting it upon us all. I see LLMs being deployed in wildly inappropriate scenarios at the moment, and safety critical can consist of an interruption while driving, for example. Media systems in vehicles are borderline actively dangerous IMO
    - keenmaster 3y ago
      I actually agree when it comes to vehicles. I personally would not use self-driving until it is further refined. On the other hand, I haven’t seen LLMs used in safety critical applications or otherwise dangerous integration of LLMs into a product or service. There is mostly upside with little downside.

datadrivenangel 3y ago

LLMs also have the last 5% problem for sure.

keenmaster 3y ago
True, but there is a wide range of use-cases where “failure” of an LLM is tolerated, and it’s almost never safety-critical like driving is.
- notmypenguin 3y ago
  That’s going to depend upon deployment context. The hype around LLMs and the word AÍ has certainly been received by the general public as license for further penetration of markets. I doubt most humans are comfortable with autonomous vehicles yet we have a relentless push for the same from the worlds richest man, who insists upon foisting it upon us all. I see LLMs being deployed in wildly inappropriate scenarios at the moment, and safety critical can consist of an interruption while driving, for example. Media systems in vehicles are borderline actively dangerous IMO
  - keenmaster 3y ago
    I actually agree when it comes to vehicles. I personally would not use self-driving until it is further refined. On the other hand, I haven’t seen LLMs used in safety critical applications or otherwise dangerous integration of LLMs into a product or service. There is mostly upside with little downside.