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
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
Therefore, the proposal goes that AGI necessitates
This line of thinking leads to many questions
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:
References
https://towardsdatascience.com/gpt-3-the-first-artificial-general-intelligence-b8d9b38557a1
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://medium.com/@ztalib/gpt-3-and-the-future-of-agi-8cef8dc1e0a1
https://www.theverge.com/21346343/gpt-3-explainer-openai-examples-errors-agi-potential
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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