- From: Timothy Holborn <timothy.holborn@gmail.com>
- Date: Fri, 3 Sep 2021 14:05:26 +1000
- To: paoladimaio10@googlemail.com
- Cc: Dave Raggett <dsr@w3.org>, public-cogai <public-cogai@w3.org>
- Message-ID: <CAM1Sok2PkB_p67tHJ8PX2poupg1dn2R4C3F-ipY2Tt0-_21MDg@mail.gmail.com>
On Fri, 3 Sept 2021 at 13:58, Paola Di Maio <paola.dimaio@gmail.com> wrote: > aka > Welcome to the Machine > https://www.youtube.com/watch?v=fn1R-5p_j5c > https://www.youtube.com/watch?v=KjGXnSdVwCY&list=PLCbmz0VSZ_voecSIK9nZ3lZgtb4F0-GAS&index=37 <https://www.youtube.com/watch?v=KjGXnSdVwCY&list=PLCbmz0VSZ_voecSIK9nZ3lZgtb4F0-GAS&index=37> > > > > <https://www.avast.com/sig-email?utm_medium=email&utm_source=link&utm_campaign=sig-email&utm_content=webmail&utm_term=icon> Virus-free. > www.avast.com > <https://www.avast.com/sig-email?utm_medium=email&utm_source=link&utm_campaign=sig-email&utm_content=webmail&utm_term=link> > <#m_3281678328223586068_DAB4FAD8-2DD7-40BB-A1B8-4E2AA1F9FDF2> > > On Fri, Sep 3, 2021 at 11:32 AM Paola Di Maio <paola.dimaio@gmail.com> > wrote: > >> Hay Dave and all >> I think that what is being proposed as the future of AI is promoting >> certain technical advances which are interesting but far from being >> intelligence, for a number of reasons which I expound elsewhere >> It is not AI, in the sense of autonomous intelligence, This intelligence >> is just the result of some clevel algorithm and execution of >> sophisticated maths. It is not intelligent at all, >> as you point out, it fails basic intelligence tests :-) It cannot produce >> anything that has not been encoded. It has no such ability. >> We should not confuse advanced computation with intelligence >> Can these methods deliver useful computational results and be applied >> usefully? >> Yes. Are they intelligent? They Only encode some of the cognitive >> functions of their developers >> as well its limitations (Ie, if the programmer had designed a system >> capable of answering out of the box questions, the AI would be able to >> answer it) >> >> Intelligence by contrast is innate reasoning. Nobody programs the innate >> intelligence of sentient being other than perhaps the brain washing that >> comes with education/learning and its constraints >> The question then is, can such natural intelligence be engineered? >> It s not needed, and it is not desirable because innate intelligence in >> human >> is often suppressed and even punished. When individuals use their >> intelligence they >> start questioning the purpose of the machine/s (including society, >> imposed norms) >> >> It s a long discussion >> I reject that what is being purported as AI is intelligence at all >> Sitting naked in the forest, ergo sum >> >> >> <https://www.avast.com/sig-email?utm_medium=email&utm_source=link&utm_campaign=sig-email&utm_content=webmail&utm_term=icon> Virus-free. >> www.avast.com >> <https://www.avast.com/sig-email?utm_medium=email&utm_source=link&utm_campaign=sig-email&utm_content=webmail&utm_term=link> >> <#m_3281678328223586068_m_-2439605095502055446_DAB4FAD8-2DD7-40BB-A1B8-4E2AA1F9FDF2> >> >> On Thu, Sep 2, 2021 at 10:24 PM Dave Raggett <dsr@w3.org> wrote: >> >>> What do you think about the ideas in Forbes article on the next >>> generation of AI? >>> >>> See: >>> https://www.forbes.com/sites/robtoews/2020/10/12/the-next-generation-of-artificial-intelligence/ >>> >>> Forbes believe in unsupervised learning, federated learning, and >>> transformers for neural networks. >>> >>> Unsupervised learning (aka self-supervised learning) is based on >>> “predicting everything from everything else”, e.g. language models from >>> billions of documents. This avoids the bottleneck of having to label data >>> for supervised learning, and is more flexible in allowing the learning >>> system to figure out its own labels and "being able to explore and absorb >>> all the latent information, relationships and implications in a given >>> dataset.” >>> >>> Federated learning is about services that support privacy friendly >>> machine learning by a third party across training data without having to >>> transfer the data to that party. Instead, the learning process is applied >>> locally to the data, and the results transmitted to the third party for >>> aggregation with the overall model. >>> >>> Transformers are a technique for learning across sequences of things, >>> e.g. words in text or frames of video, that is readily executed in parallel >>> and computationally more efficient that previous techniques. This was first >>> applied to language models to predict text following a previous text >>> extract (e.g. BERT and GPT-3), but is now being applied more widely. e.g. >>> to video. >>> >>> Whilst GPT-3 is pretty amazing in the quality of the text it can >>> generate, it is limited in the kinds of reasoning it can apply. It knows >>> simple generalisations, but is very limited in respect to reasoning about >>> time, and is unaware as to what it doesn’t know. As an example, asking for >>> the sum of two large numbers returns a large number, but not the actual >>> sum, asking for the US president in 1610 returns a historical figure rather >>> than stating that the question doesn’t make sense as the USA wasn’t in >>> existence then. >>> >>> This is unsurprising as language models are not the same as higher level >>> reasoning that children are taught at school and through interaction with >>> their parents and peers. >>> >>> What do you think? >>> >>> Dave Raggett <dsr@w3.org> http://www.w3.org/People/Raggett >>> W3C Data Activity Lead & W3C champion for the Web of things >>> >>> >>> >>> >>>
Received on Friday, 3 September 2021 04:07:17 UTC