16 Feb 2020

How to lead a large AGI company

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How would you lead an AGI company with 100,000 employees?

I would separate the employees into multiple smaller companies, as large companies are difficult to wield. Furthermore, I think that it is useful for different companies to work on the same problem using different approaches, which is something I would promote. I see the need for a variety of positions:

  • (30%) Tooling and core technologies: Building tools that are used by other employees to make progress (visualization, compilation, hardware, database, network). (Bachelor/Master/PhD)
  • (25%) Applied research: Put the results of fundamental research into application in a variety of products. (Master/PhD)
  • (15%) Fundamental research: Work on scientific theories in order to improve our understanding of intelligence, learning, doing science, solving problems, programming, etc. (Master/PhD)
  • (15%) IT: Deal with infrastructure management and scaling. (Bachelor/Master/PhD)
  • (5%) Management: Ensuring that work is going in a specific direction and is not a random walk. (Bachelor/Master/PhD)
  • (5%) Data collector: Acquire data necessary for experiments done by fundamental researchers and applied research scientists. (Bachelor)
  • (5%) Administrative/HR/Facility management: Deal with business related tasks such as people management, facility management/maintenance, etc. (Bachelor)

15 Jan 2020

Biology and genetics for AGI researchers

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Why are biology and genetics interesting to AGI researchers?

Because it may provide interesting ideas and clues that can help with the development of AGI.

We currently know of a single instance of a system that is able to produce human-level intelligence: a human being. AGI researchers often try to understand how specific components such as the brain works. A lot of valuable work on the neuron has led to the creation of the deep learning field. Deep learning has definitely proven its value, but I am more interested in something else.

Genetics is seen as the programming of life. What I find interesting is that we can see the current human DNA as our latest implementation of this code. Since this code did not come out of existence from out of nowhere, studying DNA's history can give us ideas as to how a seed AI might come to be. It is also useful to understand how the environment has shaped DNA's existence.

Initially, there were only atoms and molecules. Through different physical and chemical processes, these molecules aggregated and formed more and more complicated assemblies. Through a multitude of steps, we reached the point where there were cells that contained DNA inside of them. This process might have been entirely random although the formation of complex structures happening randomly does not seem highly likely. Understanding the mechanisms or processes that helped create this order may be the equivalent of a pre-evolution natural selection.

My hope is that by studying such fields it is possible to discover how DNA increased in length, what were the different steps and challenges that were encountered that forced it to increase in size, as well as the potential causes of parts of DNA changing over time.

Just like a git repository, I'd like to be able to look at DNA's history and understand what happened to its code since its "Initial commit". It might also be interesting to figure out what kind of programmer nature is.

14 Jan 2020

Differences between brain and CPU

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What are the differences between a brain and a CPU?

  • The brain is extremely parallel (each neuron processing many signals), while CPUs are currently limited to a few cores.
  • The brain appears to be able to only do a single thing at once (single process, single thread).
  • CPUs can explicitly control their memory access while the brain memory organization and access is unclear.
  • The brain is a lot slower in terms of sequential operations, processing at a maximum of 250-1000 Hz while current generation (2020) desktop CPUs are in the 3-5 GHz range.
  • The brain does not have a clear instruction set.
  • The brain consumes glucose for energy, while a CPU consumes electricity.
  • The human brain is much larger (average 1273 cm3 for men, 1131 cm3 for women) than a CPU chip (Intel Core i7-10710U is 46mm by 24mm (height unknown but definitely less than 10 mm) which is less than 11 cm3).
  • Heat dissipation is done through cerebral circulation in the brain and through a heatsink attached to a CPU.
  • The brain is biodegradable, the CPU is not.
  • Signal is transmitted between neurons using neurotransmitters (chemically) while CPUs transmit signals between transistors electrically.
  • The organization of the brain evolves over time (in a single person), while a CPU chip will remain the same its whole life.
  • We currently cannot transplant a brain from one person to another, but we can transfer a CPU from one computer to another (as long as the motherboard is compatible).
  • The brain contains a large amount of memory, while the CPU has a small amount of memory and relies on larger memory stores (RAM, disks).
  • It is possible to reverse engineer a CPU by trying a different combination of inputs and recording the output (immutable). Doing the same with a part of the brain may result in different results as the brain is mutable.

  • The brain may not have different levels of memory cache (we do however talk about short and long term memory).

13 Jan 2020

Humans modeled as computers

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What do humans modeled as computers look like?

  • Numerous processes all running in parallel in different regions of the body and the brain (heartbeat, breathing, sight, smell, taste).
  • The brain runs multiple processes at once, each processing a different modal input (sight, taste, touch, hearing, smell).
  • Those processes are buffered and a process takes care of synchronizing the different input streams to create a coherent flow of information.
  • The spinal cord and nerves are network cables, transferring information from the limbs and other regions of the body to the main processing unit, the brain.
  • The eyes are digital cameras that can see into the world, converting photons into bits of data.
  • The ears are microphones that can listen to a limited range of frequencies (20-20000 Hz).
  • The mouth act as a speaker to emit sound for others to perceive
  • Touch is complex as it deals with textures, temperatures, moisture and pressures, however it can likely be modeled as a surface with discrete elements that measure a few things such as the force currently applied on it, the temperature, moisture.
  • Taste and smell are also complex as they are specialized receptors that will perceive different fragrances based on the distribution of particles that are perceived and that can be recognized.
  • The arms, legs, hands, feet are actuators used to interact with the environment.
  • The stomach and intestine are the power supply.
  • Neurons throughout the body act as distributed memory and storage, as well as processing units.
  • Blood is used as a mechanism to transfer energy between components. It also acts as a heatsink for the brain.

Will an AGI be superior to a large group of individuals (e.g., society or a company)?

Most likely.

An AGI may be a strong single-minded entity. Unlike societies and companies that are composed of numerous individuals with different values/beliefs/opinions (VBO), an AGI is expected to have a single set of clear, concise and non-contradicting VBO. An AGI should be able to explore all potential alternatives and reason about all the potential sets of VBO in order to determine the most coherent and appropriate set to hold.

Meanwhile, we as individuals hold VBO that are often inconsistent. As a group, we are heterogenous in our VBO which means that conflict will arise since some sets of VBO cannot coexist. Our biggest issue is that we are competitive by nature. People fight over resources if they are limited. Fighting leads to winners and losers. The winners may not be necessarily the individuals with the "best" set of VBO. The fact that the "fittest" VBO may end up as the winner instead of the "best" set of VBO sounds unlikely to lead us to produce the optimal solution to a desired goal.

(This assumes that there is a single "best" VBO set and not various VBOs sets in the heterarchy of VBOs.)