GPT3 and AGI: Beyond the dichotomy – part two


This blog continues from
GPT3 and AGI: Beyond the dichotomy – part one

GPT3 and AGI

Let’s first clarify what AGI should look like

Consider the movie ‘Terminator’

When the Arnold Schwarzenegger character comes to earth – he
is fully functional. To do so, he must be aware of the context. In
other words, AGI should be able to operate in any
context

Such an entity does not exist

And nor is GPT3 such an entity

But GPT3 however has the capacity to respond ‘AGI-like’ to
an expanded set of contexts much more than traditional AI
systems.

GPT 3 has got many things going for it

  • Unsupervised learning is the future
  • Linguistic capabilities distinguish humans
  • But Language is much more than encoding information. At a
    social level, language involvesjoint attention to environment,
    expectations and patterns.
  • Attention serves as a foundation for social trust
  • Hence, AGI needs a linguistic basis – but that needs
    attention and attention needs context. So, GPT-3 – linguistic –
    attention – context could lead to AGI-like behaviour

Does AGI need to be conscious as we know it or would
access consciousness suffice?

In this context, a recent paper

A Roadmap for Artificial General Intelligence: Intelligence,
Knowledge, and Consciousness: Garrett Mindt and Carlos
Montemayor


https://www.academia.edu/43620181/A_Roadmap_for_Artificial_General_Intelligence_Intelligence_Knowledge_and_Consciousness

makes an argument is that

  • integrated information in the form of attention suffices for
    AGI
  • AGI must be understood in terms of epistemic agency, (epistemic
    = relating to knowledge or the study of knowledge) and
  • Eepistemic agency necessitates access consciousness.
  • access consciousness: acquiring knowledge for action,
    decision-making,  and  thought,  without  necessarily  being 
    conscious

 

Therefore, the proposal goes that AGI necessitates 

  • selective attention for accessing information relevant to
    action,  decision-making,  memory  and    
  • But not necessarily consciousness as we know it

 

This line of thinking leads to many questions

  • Is consciousness necessary for AGI?
  • If so, should that consciousness be the same as human
    consciousness
  • Intelligence is typically understood in terms of
    problem-solving. Problem solving by definition leads to specialized
    mode of evaluation. Such tests are easy to formulate but check for
    compartmentalized competency (which cannot be called intelligence).
    They also do not allow intelligence to ‘spill over’ from one
    domain to another – as it does in human intelligence. 
  • Intelligence needs information to be processed in a
    contextually relevant way.
  • Can we use epistemic  agency  through  attention as the
    distinctive mark of general intelligence even without
    consciousness? (as per Garrett Mindt and Carlos Montemayor)
  • In this model, AGI is based on joint attention to preferences
    in a context sensitive way.
  • Would AI be a peer or subservient in the joint attention
    model?

Finally, let us consider the question of spillover of
intelligence. In my view, that is another characteristic of AGI.
Its not easy to quantify because tests are specific to problem
types currently. A recent example of spillover of intelligence is
from facebook AI supposedly inventing it’s own secret
language.
The media would have you believe that groups of
AGI are secretly plotting to take over humanity. But the reality is
a bit mundane as explained.
The truth behind facebook AI inventing a new language

In a nutshell, the system was using Reinforcement learning.
Facebook was trying to create a robot that could negotiate. To do
this, facebook let two instances of the robot negotiate with each
other – and learn from each other. The only measure of their
success was how well they transacted objects. The only rule to
follow was to put words on the screen. As long as they were
optimizing the goal(negotiating) and understood each other it did
not matter that the language was accurate (or indeed was English).
Hence, the news about ‘inventing a new language’. But
to me, the real question is: does it represent intelligence
spillover?

Much of future AI could be in that direction.

To Conclude

We are left with some key questions:  

  • Does AGI need consciousness or access consciousness?
  • What is role of language in intelligence?
  • GPT3 has reopened the discussion but still hype and dichotomy
    (both don’t help because hype misdirects discussion and dichotomy
    shuts down discussion)
  • Does the ‘Bitter lesson’ apply? If so, what are its
    implications?
  • Will AGI see a take-off point like Google translate did?
  • What is the future of bias reduction other than what we see
    today?
  • Can bias reduction improve human insight and hence improve
    Joint attention?
  • GPT-3 – linguistic – attention – context
  • If context is the key, what other ways can be to include
    context?
  • Does problem solving compartmentalize intelligence?
  • Are we comfortable with the ‘spillover’ of intelligence in
    AI? – like in the facebook experiment

 

References


https://towardsdatascience.com/gpt-3-the-first-artificial-general-intelligence-b8d9b38557a1

https://www.gwern.net/GPT-3


http://haggstrom.blogspot.com/2020/06/is-gpt-3-one-more-step-towards.html

https://nordicapis.com/on-gpt-3-openai-and-apis/


https://www.datasciencecentral.com/profiles/blogs/what-is-s-driving-the-innovation-in-nlp-and-gpt-3

https://bdtechtalks.com/2020/08/17/openai-gpt-3-commercial-ai/


https://aidevelopmenthub.com/joscha-bach-on-gpt-3-achieving-agi-machine-understanding-and-lots-more-artificial/


https://medium.com/@ztalib/gpt-3-and-the-future-of-agi-8cef8dc1e0a1


https://www.everestgrp.com/2020-08-gpt-3-accelerates-ai-progress-but-the-path-to-agi-is-going-to-be-bumpy-blog-.html


https://www.theverge.com/21346343/gpt-3-explainer-openai-examples-errors-agi-potential


https://www.theguardian.com/commentisfree/2020/aug/01/gpt-3-an-ai-game-changer-or-an-environmental-disaster

http://dailynous.com/2020/07/30/philosophers-gpt-3/


https://marginalrevolution.com/marginalrevolution/2020/07/gpt-3-etc.html


https://artificialintelligence-news.com/2020/09/10/experts-misleading-claim-openai-gpt3-article/


https://analyticsindiamag.com/gpt-3-is-great-but-not-without-shortcomings/


https://www.3mhisinsideangle.com/blog-post/ai-talk-gpt-3-mega-language-model/


https://venturebeat.com/2020/06/01/ai-machine-learning-openai-gpt-3-size-isnt-everything/

https://discourse.numenta.org/t/gpt3-or-agi/7805

https://futureofintelligence.com/2020/06/30/is-this-agi/

https://www.quora.com/Can-we-achieve-AGI-by-improving-GPT-3

https://bmk.sh/2020/08/17/Building-AGI-Using-Language-Models/

https://news.ycombinator.com/item?id=23891226

 

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DICHOTOMY