BC ARTIFICIAL INTELLIGENCE

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Carlos E. Perez
@IntuitMachine 5 years, 11 months ago 1013 views

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**My attempt to map the research doctrines of various groups working on Artificial General Intelligence.**

Although one might see names of individuals here as well as organizations, take it just as identification of the organization behind the person and a very narrow slice of their overall research portfolio.

Here is a @swardley map that captures the relationship of doctrine with other individual and organizational processes.

We can capture a party's doctrine by either an explicitly stated agenda or an aggregation of the kind of approach that is pursued. A doctrine is an invariant property of the overall behavior of a party.

In this map one can see the conflict between different parties (compare @garymarcus with the deep learning folks).

Also you can compare groups like @DeepMind and @OpenAI which although are both working on Deep RL. Deepmind has a neuroscience flavor that is reflected in its classification as being more organic.

Because it is unnatural to capture a high dimensional concept such as doctrine in just two dimensions. The dimensions have been selected to be purposefully ambiguous so as to allow the reader some leeway in interpretation.

The vertical axis reflects a difference in inspiration for the hypothesis generated by the doctrine. One can be biologically inspired like @numenta or one can be less so, but informed by a mathematical idea (i.e. free energy).

The horizontal axis reflect the known tension between representationalists and non-representationlists. In one side are functionalists that identify specific mechanisms. On the other extreme are enactivists that try to capture the complexities of the ecosystem.

Every scientific discipline as well as each individual researcher follows a research agenda that is explicitly or implicitly driven by a doctrine. The debates we see between various groups are the manifestations of the conflicts in doctrine.

There is an argument to be made (see: @blamlab ) that the complexity of intelligence requires a pluralistic approach, yet people and organizations seek a dogmatic stance instead. This is of course unavoidable, it is the nature of the human condition.

I've captured this in a blog post that hopefully will expand the details: https://t.co/Qek1Z1WH7S

More from Carlos E. Perez

Carlos E. Perez
@IntuitMachine

We wake up each day with the same attention budget as everyone else. This is the one thing all humans equally share.

Spending that attention budget by doing this is what gives meaning to our lives.

It's is only through doing that we learn. It is only through learning that we find meaning.

Yet many of us waste attention budget exclusively on consumption. Seeking the random dopamine hits that tickle our curiosity. Yet we seek only the convenient things to do.

Activities that are convenient, that takes little effort don't consume a lot of attention. But enough of these small distractions will. But unfortunately, there's little learning taking place.

Carlos E. Perez
@IntuitMachine

In physics, energy is that which is causally invariant or symmetric with respect to time. Said differently, energy is never created or destroyed, it is conserved in the universe.

Now there is a question about information. Is information causally invariant? Does information remain the same with respect to time? To understand this, let's first understand what energy is, then attempt to understand what information is.

The strange thing about energy is that it is this universal currency that seems to be interchangeable between the different forces in nature (i.e. electromagnetic, strong, weak and gravity). It is that thing that makes change possible.

Now let's assume that the universe is computational in nature. That is, anything we see in nature is a consequence of computation. That is, there is computation underneath the physics that is driving the universe to change.

What does it mean then that information is conserved in this computational universe? Also, how is energy conservation related to information conservation?

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Carlos E. Perez
@IntuitMachine

Nice to discover Judea Pearl ask a fundamental question. What's an 'inductive bias'?

Help! What precisely is "inductive bias"? Some ML researchers are in the opinion that the machine learning category of \u2018inductive biases\u2019 can allow us to build a causal understanding of the world. My Ladder of Causation says: "This is mathematically impossible". Who is right? 1/
— Judea Pearl (@yudapearl) February 14, 2021

I crucial step on the road towards AGI is a richer vocabulary for reasoning about inductive biases.

explores the apparent impedance mismatch between inductive biases and causal reasoning. But isn't the logical thinking required for good causal reasoning also not an inductive bias?

An inductive bias is what C.S. Peirce would call a habit. It is a habit of reasoning. Logical thinking is like a Platonic solid of the many kinds of heuristics that are discovered.

The kind of black and white logic that is found in digital computers is critical to the emergence of today's information economy. This of course is not the same logic that drives the general intelligence that lives in the same economy.

Carlos E. Perez
@IntuitMachine

AGI Significance Paradox: As progress accelerates towards AGI, the number of people who realize the significance of each new breakthrough decreases.

Why is it that you can boil a frog in water without it jumping out if you gradually increase the temperature?

The problem for the frog is that it does not have the internal models to realize that there is a change in the water temperature. A cold-blooded creature like the frog has its temperature regulated by the external environment.

To recognize change, an agent must have an internal model of reality that is able to recognize this change. Unfortunately, a majority of the population do not have good models of human general intelligence.

In fact, even the simplistic dual-process model of system 1 and system 2 is not very well known.

Carlos E. Perez
@IntuitMachine

A children's book written in 1954 inspired by Wiener's Cybernetics that explains some common day analog systems:

Analog computation originally meant the construction of a simulation of another system by means of a mechanical or electrical system that represented the same dynamics as the physical system. That is an analog of what's being simulated.

Nobert Wiener generalized this idea in Cybernetics to describe control systems that through negative feedback promoted stability.

W.Ross Ashby argued that negative feedback was insufficient for maintaining the stability (homeostasis) of complex system. Ashby proposed the Law of Requisite Variety.

These machines that 'seem to think' are examples of what was known as analog computation. Cybernetics, control theory, biology are examples of analog computation. But what does this mean other than being the opposite of discrete/digital computation?

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एकबार महाराज पाण्डु शिकार खेलने वन गए।झाडियों के पीछे कुछ हिल रहा था। मृग है सोचकर राजा ने बाण चलाया जो जाकर ऋषि किन्दम और उनकी पत्नी को लगा।वे दोनो रति-क्रीड़ा में लिप्त थे।

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ANTARVEDI LAKSHMI NARASIMHA SWAMY, EAST GODAVARI DIST.(AP)

Located where Vasistha Godavari joins Bay of Bengal.

Present structure was built by Kapanati Krishnamma of Agnikula Kshatriya clan in 1823.

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@LostTemple7

Legend says that here Maharishi Vasishta prayed to Narasimha to end the demon Rakta Vilochana.

Narasimha created Maha Maya, also called Ashwaroodambika or Gurralakka to suck his blood as he got a boon from Brahma that blood falling from his body would produce another demon.

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Narasimha,then,washed Sudarshan Chakra at a place called Chakra Tirtha.

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Later Sri Rama prayed here and Arjun also visited here.

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One can have Nijarupa Darshanam (main murti without any decorative shield) between 6.00 a.m. and 8.00 a.m.

Anna Prasadam is very famous and distributed daily from 10:30 to 2 pm.