Comparing market cap of Nvidia, Tesla and Amazon in the last 5 years

The echoes of Y2K resonate in today’s AI landscape as executives flock to embrace the promise of cost reduction through outsourcing to language models.

However, history is poised to repeat itself with a similar outcome of chaos and disillusionment. The misguided belief that language models can replace the human workforce will yield hilarious yet unfortunate results.

  • huf [he/him]@hexbear.netEnglish
    4·
    6 months ago

    these LLMs seem an excellent fit for expert systems as long as you train them on relevant data instead of all the garbage of the collective internet

    • ☆ Yσɠƚԋσʂ ☆@lemmygrad.mlOP
      6·
      6 months ago

      For sure, there are a lot of legitimate use cases for this stuff. We’re actually starting to see them being put to good use in China. One story I saw a little while back was about monitoring rail infrastructure and identifying potential faults so they can be repaired proactively. This is an excellent use case because it leverages the ability of the model to correlate a whole bunch of data which is something that humans find challenging to do, but also keeps it out of proactive decision making. This kind of approach of having LLMs work along side humans seems like the most promising approach in the near future.