I am new to this forum, I am a bioinformatician and heavy user of Deep learning…
To me, Numenta approach is much more interesting and profound than deep-learning and other ML methods, but the ML community is more interested in what works. Deep learning works in many cases ABOVE the average human performance, and hence, it is useful in many areas. But eventually it is just a powerful function-approximator.
Nevertheless, I have got the feeling that the ML field is moving toward Numenta direction faster than we think. Late research showed a significant improvement in unsupervised / self-supervised approaches which is the real "cake" of ML as Yan Lecun stated.
In 2018 we learned that unbelievable results can be achieved with system that just try to “model” the word, like: self-attention, language models and generative models. Thus, even in the deep-learning world, it is becoming clear that the future paradigm of ML is a not a data-angry classifier, but a strong model of the world, learned from sequential or forward predicting model (like GAN), which shockingly similar to Hawkins view of the brain: A “constantly changing multiple predictive models of the world” – In my opinion it is not far from what the recent “BERT” and “StyleGAN” models are, although the architecture is very different.
The amazing thing about the brain is how it can learn such a complex model of the world without much data and with a very low-powered and slow hardware. This is where Numenta should focus: The future AI technology is probably not a data-angry monster running on multiple GPUs, but a context-aware, self-supervised, ensemble of learners, that can learn numerous concepts and objects, and have a “common sense” about the world like human does. HTM has a much better chance to go there than DL.
I think that Deep learning is here to stay, but it is just a step toward a brain-like system of the future. We just need to go through GANs, Attention, Capsules, Language-models, etc. before hitting HTM again, probably with some clever take on current computation paradigm…
If the Numenta software will be as mature and elegant as keras or pytorch and will show some interesting unsupervised results on real problem, then it will fly. I don’t think that it has a chance to beat DL in big-data supervised tasks, where humans can’t.