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

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?

Chess may be a good analogy for explaining the difference between a descriptive model of reality and a generative model of reality.

A descriptive model of chess will describe the rules (i.e. initial setup, allowed moves, points per piece, objectives). This tells you how a chessboard might evolve and also narrows the combinations of realistic chess positions.

In contrast, a generative model involves the actual gameplay between competing players that follow the rules. It generates new styles and patterns. It establishes new strategies and tactics. It generates new openings, middle gameplay, and end game tactics.

A generative model is an evolutionary model that leads to emergent behavior. As a consequence, a master of chess is able to recall the layout of chess positions in a real game in an instant, yet is unable to remember pieces placed in random positions.

That is because causality is present in the movements of pieces in a chessboard. An intuitive system like the human mind is able to capture that causality as a means to understanding and recall.

Does artificial anthropocentric intelligence lead to superintelligence?

When I use the term Artificial General Intelligence, my meaning of 'General' comes from the psychology definition of the G-factor that is tested in general intelligence tests.

It is an anthropocentric measure. The question that hasn't been explored in depth is whether a "human-complete" synthetic intelligence leads to a superintelligence. The prevailing assumption is that this expected.

I am going to argue that this assumption may not be true.

The assumption that goes into AGI automatically exploding into a superintelligence is driven by the bias that human intelligence is perceived at the pinnacle of all intelligence.

Abduction is that thought process where we renew our past, question our present, and reimagine our future.

It was C.S. Peirce, a century ago, that coined the use of this term to describe a thought process that would convey hypothesis making.

A little over 50 years ago, proponents of Artificial Intelligence, proposed that deduction would be the core feature of human intelligence. This idea was driven by the bias towards formal logical systems and the emergence of computers.

This approach was in stark contrast to cybernetics (introduced a decade early) that proposed that dynamical systems were a model for intelligence. The descendant of this approach was coined as artificial neural networks.

This dynamical systems approach was later understood as being similar to an induction based thought process. Deep Learning leads to what can be characterized as Artificial Intuition.

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?

@ImPranav_M @GunduHuDuGa That's a good qsn, if not a bit nuanced. Avataras are of many varieties and frankly, most of the classification is only for our understanding and not really binding on Paramatma Himself. We can take several approaches to understanding this. If you go by a Vedantic approach,+

@GunduHuDuGa Avatara means that which descends from an exalted state (Taara). Going by Upanishadic observaton of Purnam adham purnam idham, every manifestation of Bhagavan is indeed wholesome. In fact, Avataras usually happen when Iswara is propitiated with certain qualities already+

@GunduHuDuGa described in the Vedas by other Devatas. So, in order to please them, He assumes the form that best envisages the said Vaidika tatvam. For example, Varaha and Nrusimha avatars, though they have sthoola prayojanas, also exemplify the Tejovanna tatvam propounded by Upanishads.+

@GunduHuDuGa All these tatvams ultimately emanate from Him so whatever form He takes is indeed Purna. Now, one may ask then if that's the case, why such a distinction had to be made in the first place. That is because of upasana vidhis and understanding of how Bhagavad tatvam shines+

@GunduHuDuGa with each Leela being performed. Let's take Nrusimha avatar. The purpose of the avatar is neither to save Hiranyakasipu nor rescue Prahlada. For that He need not descend down as H's boons are applicable only for Brahman's creation and not Paramatma Himself.+

stacks are eating the world

business used to be easiest to comprehend via a) market-based logic of horizontal vs. vertical STRUCTURE, b) professionalization/specialization based FUNCTION c) core competencies based BEHAVIORS

this has pretty much collapsed in the last decade

Structure = sclerosis
Functional specialization = bureaucracy
competencies = inertial habits

"Stack" thinking instead lets technology structure (rather than market structure) drive business org logic

Companies seem to do well when they identify an entire stack of technologies they are good at (not just point bits) and organize to conform to its logic. There is a "full-stack" dimension of technical specialization that is the spine of the org

It feels buzzwordy, but it really is getting to be that way. AI stack, decarbonization stack, mobility stack, electrification stack... some end-to-end pathway of turning physics into economics via layers of tech artistically baked together like a cake

Ok...just spent a few looking at The Weekend’s page and it is weird AF!!! First off is this banner pic he has...take a look at it...a CLOSE LOOK AT IT....see all the ‘strange’ images he has within it? Notice the dice...all the 6’s...serpent tongue....
NOTHING TO SEE HERE.👇thread