Re: Forbes on next generation of AI

aka
Welcome to the Machine
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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
>
>
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> 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
>>
>>
>>
>>
>>