All the evidence looks like S-curves. Slow start, rapid growth that is often interpreted as exponential growth then comes the inevitable slow down and plateau.
As we have seen on a different type of AI, in face recognition and image classification, it was quite easy to get to 50% or 70% accuracy, but then it gets ever more difficult and e…
All the evidence looks like S-curves. Slow start, rapid growth that is often interpreted as exponential growth then comes the inevitable slow down and plateau.
As we have seen on a different type of AI, in face recognition and image classification, it was quite easy to get to 50% or 70% accuracy, but then it gets ever more difficult and expensive to improve accuracy, especially in situations that need 99.99% accuracy or better.
Mind you, both LLMs and image categorisation are pattern finding algorithms, so are in many ways very similar.
All the evidence looks like S-curves. Slow start, rapid growth that is often interpreted as exponential growth then comes the inevitable slow down and plateau.
As we have seen on a different type of AI, in face recognition and image classification, it was quite easy to get to 50% or 70% accuracy, but then it gets ever more difficult and expensive to improve accuracy, especially in situations that need 99.99% accuracy or better.
Mind you, both LLMs and image categorisation are pattern finding algorithms, so are in many ways very similar.