Читать книгу Machine and human intelligence. Updated research - - Страница 2

Research of machine and human intelligence based on own knowledge and experiments, analysis of various sources: publications of scientific articles, posts, interviews, news updates, etc. Information for a wide audience, from the very entry level, to experts. The material is more about questions than about answers. Intelligence is an unsolved mystery of nature.

«Intelligence is a human construct to represent the ability to achieve goals.» (Michael E. Hochberg, «A Theory of Intelligences»). Simple and straightforward, but intelligence is not only humans have, and what intelligence is?

«A core function of intelligence is grounding, which is the process of connecting the natural language and abstract knowledge to the internal representation of the real world in an intelligent being, e.g., a human.» (Bing Liu,«Grounding for Artificial Intelligence»). Good point, but intelligence has many more core functions.

«Consider the space of all possible forms of intelligence, what can be called the intelligence

space.» (Paul S. Rosenbloom, «Defining and Exploring the Intelligence Space»). Interesting concept, but even to imagine such «space of all possible forms of intelligence» is close to impossible task.

«In the lone banana problem, the statistics suggested that bananas only appear in twos (or more) and so the AI could not imagine a single banana, because the data and parametric tuning that had gone on didn’t allow it to consider that approach, on average» (Daniel Hook,«The Lone Banana Problem»). No surprise, machine models can only use patterns from their training data and can’t come up with something totally new. «AGI» – did you say, give me two.

«AlphaGeometry is a neuro-symbolic system made up of a neural language model and a symbolic deduction engine, which work together to find proofs for complex geometry theorems. Akin to the idea of „thinking, fast and slow“, one system provides fast, „intuitive“ ideas, and the other, more deliberate, rational decision-making.» (Trieu Trinh and Thang Luong, «An Olympiad-level AI system for geometry»). An interesting idea, a combined approach, in addition, code generation and execution can be used.

«The artificial intelligence may share different principles from the natural intelligence, but both can inspire each other, which may call for establishing new mathematical physics foundation.» (Haiping Huang,«Eight challenges in developing theory of intelligence») – there’s a joke that goes: «if you want to figure out how it works, program it.»

«Machines will be capable, within 20 years, of doing any work that a man can do.» – wrote Herbert Simon in 1960, who won the Nobel Prize in economics and the Turing Prize in computer science.

«Every intelligence is specialized, including human intelligence. Intelligence is a collection of skills and an ability to acquire new ones quickly. It cannot be measured with a scalar quantity. No intelligence can be even close to general, which is why the phrase „Artificial General Intelligence“ makes no sense. There is no question that machines will eventually equal and surpass human intelligence in all domains. But even those systems will not have „general“ intelligence, for any reasonable definition of the word general.» (Yann LeCun). AI, AGI, etc. – is just marketing, nothing more. There are many questions in what areas and what machines can do. Computers are just tools, they have no will of their own. A model of will is possible, but it’ll be just a model. Truly autonomous systems and self-aware systems are projects of the very distant future.

«People don’t change their minds.» (Daniel Kahneman) – partially true, there are other words – «People think one thing, say the second and do the third.»

The limits of my language mean the limits of my world (Ludwig Wittgenstein). It shows that language plays a key role in everything, intelligence and language are tightly connected. To hack an intelligence, hack a language.

«My machine learning professor taught me something I’ll never forget: Always focus on the analysis, and don’t worry about the code. Copy the code. Steal it. Ask somebody to write it for you. It doesn’t matter. Coding is easy. Knowing what to code is what truly matters.» (Santiago Valdarrama). That’s what distinguishes intelligence, to understand what’s important, what you should focus on, and what you shouldn’t waste resources on.

«AI can be considered something that mimics human cognitive functions.» (Igor Ashmanov). It is not a bad definition, considering that AI has different definitions: strong, weak, general AI, etc. You can give another definition yourself, and it will have the right to exist.

«Education is what remains after one has forgotten what one learned in school.» – Albert Einstein. Yes, that’s right, knowledge and intelligence develop only in work. Unused knowledge dies and is forgotten.

«The Truth About Emotional Intelligence. For those who have it, it predicts success in many ways.» (Marc Brackett). EI is an essential part of an intelligence, perhaps even more significant then everything else.

«The capacity to understand the world, understand the physical world, the ability to remember and retrieve things, persistent memory, the ability to reason, and the ability to plan are four essential characteristics of intelligent systems» (Yann Lecun). It is not a good definition, what it means to understand the world, to reason, to plan. It is not easy to give a good definition of intelligent systems, but it is easy to replace some abstractions with another abstractions.

«How does next-token prediction in large language models (LLMs) yield remarkably intelligent behavior? … These models have demonstrated extraordinary capabilities beyond just mastering language.» (Ibrahim Alabdulmohsin, Vinh Q. Tran, Mostafa Dehghani, «Fractal Patterns May Unravel the Intelligence in Next-Token Prediction»). There is nothing remarkable, not intelligent because all answers are manually prepared. Next-Token prediction is just a way to probablistically store and retrive data, there is no intelligence at all. LLM can be thought of as an interactive dictionary or encyclopedia with an advanced query language.

In his paper «Computing Machinery and Intelligence» Alan Turing asked the

question «Can machines think?» and introduced the Turing Test to verify whether machines could achieve human-level intelligence. The problem is that it is possible to create an emulation of thinking. Modern computing systems can process all the information collected by mankind, moreover, a huge number of human editors (AI-trainers) can be used to correct such systems. The old Turing test does not make sense, but it is possible to develop a test in which there should be no previously known typical patterns of reasoning. The new test should be based on the ability to generate and test hypotheses, build probabilistic chains of reasoning, without the ability to solve the problem by brute force.

«If you are the smartest person in the room, you need to find a smarter room.» (Ranal Currie) – definitely, environment is extremely critical, communications with smarter persons than you will make you smarter.

«These 4 phrases you have higher emotional intelligence (paraphrase, ask questions): „What I hear you saying is..“, „Let me get this right..“, „How did that make you feel?“, „What might have led you to that?“» (Aditi Shrikant, «If you use any of these 4 phrases you have higher emotional intelligence than most») – summarizing, paraphrasing and asking questions indicate that you are actively involved in conversations what gives you a basis for emotional intelligence usage.

«Intelligence is multidimensional, and therefore there’s no one point at which AI will exceed human intelligence.» (Pedro Domingos). Sounds good, especially since current AI is just bits of human work wrapped in technology.

«The Measure of Intelligence is The Ability to Change.» – Albert Einstein. An obligatory property of intelligence, without the ability to change intelligence is impossible.

«Intelligence is the ability to adapt to change.» (Stephen Hawking) – echoes Einstein’s previous quote.