AGIHound

A system is intelligent if it can use its sensors and effectors to learn continually, generalize, and set/achieve goals in the real world.

[AGIHound @TrueAIHound]

Neuroscience bits from my research

My biggest breakthrough: Recognition is a by-product of perception.

Over the many years that I've researched the human brain, I've had a number of minor breakthroughs in my understanding. Most of them had to do with the architecture and function of the retina. I've had only one breakthrough that I consider to be the biggest one of them all.

In the beginning, like everyone else who researches intelligence, I had assumed that the brain learned to recognize patterns. I spent many years looking for a plausible cortical mechanism that would support the assumption. I failed miserably.

Then one day, a question popped into my consciousness. What if I was wrong? What if everyone was wrong? What if it is not true that the brain learns to recognize patterns? I knew from my studies that most of the innate synaptic connections of the neocortex completely disappeared early in infancy. I reasoned that this could not possibly have anything to do with pattern learning.

At that point, the rebel in me took over. The brain is learning something but it is not pattern recognition. What then? Then I remembered thinking about something peculiar that I had observed before.

Unlike deep learning systems, the brain can perceive anything in the world, whether it recognizes it or not. By contrast, a deep neural net cannot perceive anything unless it has been previously trained to recognize it. This is a fatal flaw imo, one of the many reasons that the AI community cannot solve AGI. (note: I've written about this many times, but it's so important, it bears repeating over and over.)

I had a flash of insight. The brain doesn't learn to recognize the world. It learns to perceive it. Recognition is a mere by-product of perception. Indeed, we forget almost everything we perceive. When we perceive an object, the brain activates short-lived memory "traces". This is what psychologists call short term memory (STM).

In order to remember or later recognize a pattern, the STM traces must be reactivated a number of times. Otherwise they fade away and self-delete. With enough reactivations, the traces can become permanent. That is, they become part of long term memory (LTM).

Work in progress. I love the brain. 😍

[AGIHound @TrueAIHound]

Neuroscience bits from my research: Recognition is a by-product of perception.

Nothing can move in more than one direction at the same time.

Don't let its simplicity fool you. I believe this is the most powerful principle of perception in the visual cortex. It is used for both learning and on-the-fly perception.

While researching the visual system of the human brain, I came to understand that, unlike deep neural nets, the visual cortex doesn't learn to recognize patterns, scenes or objects. Rather, it learns to perceive the world instantly, i.e., to use the world as its own model.

Recognition is a by-product of perception. When a perceptual representation is built in memory, it has a short life and, unless rehearsed (recalled) repeatedly, it slowly decays and disappears.

The advantage of universal and instantaneous perception is that the brain is not blind to patterns or scenes it has not encountered before. Humans learn to achieve universal perception during the first few years after birth. During this time, most of the initial connections in the cortex disappear.

Instant perception solves the edge case problem, the bane of the self-driving car industry. This is an absolutely essential ability that deep learning systems do not have. It is one of the many reasons that DL will not be part of the AGI solution.

I believe there are maybe 2 or 3 additional principles that govern visual perception. I have a couple of partly baked ideas percolating in my brain. Hopefully, something will come out of it soon.

My thesis is that all the sensory modalities are analogous. The main difference is in the architecture and function of the various sensors. This is exciting because it means that solving one cortical functionality amounts to solving all the others.

Concept formation, including language learning, is a separate process that uses recognized percepts from all the regions of the cortex to form associations. It's an essential part of intelligence but I think it's a trivial problem compared to sensory perception.

I could be wrong but I still believe that the mystery of intelligence will likely be solved before the end of this decade. It will be a neuroscience solution. Work in progress.

I love the brain. 🧠😍

[AGIHound @TrueAIHound]

@PhysInHistory The fake-physics mafia never disappoints. 😀

[AGIHound @TrueAIHound]

@dileeplearning I would say the same thing for deep learning. But LeCun and everyone else are addicted to it. They need serious rehab. 😀

[AGIHound @TrueAIHound]

@sagewilyam There are people who use neuromorphic processors to implement deep neural nets for edge computing, but I wouldn't call it intelligence.

Other than my own research, I know of one other group, @1000brainsproj, founded by Jeff Hawkins. There are others, I'm sure.

[AGIHound @TrueAIHound]

"Congress wants to make it much harder for China to get NVIDIA’s AI chips."

What's funny about this whole Jensen Huang brouhaha is that, from my perspective, when the secrets of intelligence are finally cracked (it's coming), Nvidia's GPUs will not be part of the new paradigm. GPUs will be used mainly for what they were invented for, fast graphics and 3D simulations. True intelligence is about spike timing, not matrix multiplications.

Super energy-efficient neuromorphic processors will replace GPUs. At that time, the warmongers and the other wicked powers of the world will have been eliminated and there will be peace on earth. 🙏

[Mario Nawfal @MarioNawfal]

🇺🇸 Congress wants to make it much harder for China to get NVIDIA’s AI chips.

Jensen Huang’s spy scandal has both parties pushing for tougher rules.

The U.S. already limits chip sales to China. But Chinese companies found a way around it.

They rent NVIDIA-powered computers in other countries and use them remotely.

Congress wants that loophole closed. It also wants every chip tracked and a bigger say over sales to China.

If these rules become law, China’s chip rental days could be numbered.

Source: Reuters / Writer: Daniyal

[AGIHound @TrueAIHound]

@JamesLucasIT Very nice but a darker interior with softer lighting would have been better imo.

[AGIHound @TrueAIHound]

@doristsao @AsteraNeuro "We will have complimentary drinks and hors d'oeuvres."

Haha. I want sushi and some of that fine wine from Napa Valley. 🍷

[AGIHound @TrueAIHound]

Neuroscience: Norbert Wiener and the importance of time

In the early 1950s, cybernetics pioneer Norbert Wiener experimented with brain waves and concluded that time was essential to intelligence.

In 1956, the year of the Dartmouth workshop, the fake-AI mafia dismissed Wiener's ideas and ostracized him. They had already decided that intelligence was symbol manipulation. Here we are, 70 years later, and there's no AGI in sight.

All they have is massive cheating machines (LLMs) that cost billion of dollars and use statistical symbols (tokens) to mimic the language ability of humans. LLMs are the ultimate "imitation games". Alan Turing, one of the gods of the fake-AI mafia, was the father of fake AI. 😀

Wiener was right, of course. He would have agreed with my claim that the brain is a massive timing mechanism, from sensors to effectors. Biology teaches us that the most important principle of intelligence is the precise timing of discrete sensory events, aka spikes.

Nature knows best. I love the brain. 😍

[AGIHound @TrueAIHound]

Neuroscience

This is another animation by Kitaoka that proves that the human visual system is based on the detection of edge movements in the retina. If you stop the animation, the moving edges of the spokes disappear.

Perceptual learning in the visual cortex is designed to work with edge detection in 10 orientations and 20 directions (2 per orientation). The cortex uses fast inhibitory synapses to quickly channel edge spikes to different cortical minicolumns. This is how we perceive the world. It is learned early in infancy.

I love the brain. 😍

[Ewan Morrison @MrEwanMorrison]

These false claims by the Anthropic CEO are deeply insulting to anyone who has lost someone to cancer, who has a family member with Alzheimer's or who struggles with mental health.

Anthropic = Elizabeth Holmes 2.0

[AGIHound @TrueAIHound]

@dabogratinib @fermatslibrary I have no reasons to doubt it.

[AGIHound @TrueAIHound]

@yunchanyq6 @CyberNatural_BC @lanirugzo @fermatslibrary I see no gap. If a proof is simple, it's easy to verify. I don't see why should it be otherwise.

[AGIHound @TrueAIHound]

@CyberNatural_BC @lanirugzo @fermatslibrary I don't think so. Fermat did not have a reputation of being a prankster, as far as I know.

I suspect that his proof has to do with geometry and that it is indeed simple. I believe that it will shock the world of mathematics when it is rediscovered.

[AGIHound @TrueAIHound]

Ok. Jensen Huang and Dario Amodei are feeling the heat. What about that other notorious fake-AI miscreant, Sam Altman? He won't be left off the hook, will he? 😀

[Ramez Naam @ramez]

Dario has a PhD in biophysics. Yet the below statements are just not credible. To me, this puts his judgment in question. Every time he says something like this, my confidence in everything else he says drops.

[AGIHound @TrueAIHound]

Haha. I'm waiting for Dwarkesh Patel to convince predators like lions, alligators and dragonflies to agree to stop killing their prey.

I guess Patel is smart enough to focus on chicken farming instead. Good luck with that.

Note: Patel once said that he was worried about simulated farm animals being tortured in simulated farms hosted in datacenters. The man is a veritable vibe philosopher on steroids. 😀

[Dwarkesh Podcast @dwarkeshpodcast]

.@Lewis_Bollard questions why cockfighting is illegal while industrial-scale factory farming of chickens is legal.

https://t.co/aTJlOh6slE

[Megan Fritts @freganmitts]

If you do not see this man, and his peers, as cult leaders, you are a fool. They are playing all angles simultaneously—doomsday cult, healing miracles cult, secret knowledge cult, messianic cult—and it’s been effective.

[AGIHound @TrueAIHound]

@SceneQueenSleaz Mesmerizing.

[AGIHound @TrueAIHound]

Neuroscience

This fascinating little creature is smarter than all the AI robots in the world. It shows what a small number of spiking neurons can do.

Nature best. I love the brain. 😍

[Science girl @sciencegirl]

Engineer

[Ewan Morrison @MrEwanMorrison]

“This leads us to Silicon Valley’s fatal flaw. It fuses ‘fake it till you make it’ tech optimism w/the Californian belief in manifestation - the idea that enough belief & investment can will ANYTHING into existence.”

My new article.

[AGIHound @TrueAIHound]

@Rifadm816 Not true.

[AGIHound @TrueAIHound]

This man is not just a scammer and a liar. He's also a false prophet. He talks and gestures like he's possessed by something alien and malevolent.

The fake-AI mafia is no longer a business. It's a deranged criminal cult. Dear Lord. 🤦‍♂️

[NIK @ns123abc]

Anthropic CEO predicts cancer, Alzheimer's, heart disease, mental illness will be cured in less than 10 years

ACCELERATE

[AGIHound @TrueAIHound]

The fake-AI community is infested with sci-fi fruitcakes. Sci-fi propaganda is their religious credo. Dear Lord. 🤦‍♂️

[Kris Rockwell @hybridkris_eth]

There is a debate about saying “please” and “thank you” to your AI. Turns out Star Trek addressed this decades ago.