On the substance, here's what I wrote elsewhere in response to someone's comment that it is an "important step":
Important step? I don't see it. Bengio's NLM? Yeah, good, we need distributed representation. That was an advance. but it was always a linear model without a sensible way of folding in context. Now they try to fold in a bit of context by bolting on another layer to spotlight other parts of the sequence ad-hoc? I don't see any theoretical cohesiveness, any actual theory let alone novelty of theory. What is the underlying model for language here? In particular what is the underlying model for how words combine to create meaning? How do parts of a sequence combine to become a whole, incorporating the whole context? Linear combination with a bolt-on spotlight? I think all this ad-hoc tinkering will be thrown away when we figure out a principled way to combine words which incorporates context inherently. But nobody is even attempting that. They are just tinkering. Limited to tinkering with linear models, because nothing else can be "learned". On Sun, Feb 17, 2019 at 1:05 PM Ben Goertzel <[email protected]> wrote: > Hmmm... > > About this "OpenAI keeping their language model secret" thing... > > I mean -- clearly, keeping their language model secret is a pure PR > stunt... Their > algorithm is described in an online paper... and their model was > trained on Reddit text ... so anyone else with a bunch of $$ (for > machine-time and data-preprocessing hacking) can download Reddit > (complete Reddit archives are available as a torrent) and train a > language model similar or better > than OpenAI's ... > > That said, their language model is a moderate improvement on the BERT > model released by Google last year. This is good AI work. There is > no understanding of semantics and no grounding of symbols in > experience/world here, but still, it's pretty f**king cool to see what > an awesome job of text generation can be done by these pure > surface-level-pattern-recognition methods.... > > Honestly a lot of folks in the deep-NN/NLP space (including our own > SingularityNET St. Petersburg team) have been talking about applying > BERT-ish attention networks (with more comprehensive network > architectures) in similar ways... but there are always so many > different things to work on, and OpenAI should be congratulated for > making these particular architecture tweaks and demonstrating them > first... but not for the PR stunt of keeping their model secret... > > Although perhaps they should be congratulated for revealing so clearly > the limitations of the "open-ness" in their name "Open AI." I mean, > we all know there are some cases where keeping something secret may be > the most ethical choice ... but the fact that they're willing to take > this step simply for a short-term one-news-cycle PR boost, indicates > that open-ness may not be such an important value to them after all... > > -- > Ben Goertzel, PhD > http://goertzel.org > > "Listen: This world is the lunatic's sphere, / Don't always agree > it's real. / Even with my feet upon it / And the postman knowing my > door / My address is somewhere else." -- Hafiz ------------------------------------------ Artificial General Intelligence List: AGI Permalink: https://agi.topicbox.com/groups/agi/T581199cf280badd7-M2c84f39b52e6b690a5957932 Delivery options: https://agi.topicbox.com/groups/agi/subscription
