"Go build memories" - Jeff Hawkins

The more they innovate, more they are challenged. Chip designers received an interesting challenge this month from Jeff Hawkins, the famous founder of Palm and Handspring and an expert on the human brain: If they really want to design something intelligent, they shouldn't be doing processors. They should be making memories.

At the International Solid State Circuits Conference in San Francisco, Hawkins addressed the question of "Why can't a computer be more like a brain?" He has been preoccupied with that question for decades and recently has been working on the answers for his new start-up, Numenta. Broader story here.

Hawkins said computers today are fast at solving calculations but terrible at doing things that children can do, like understanding simple stories or recognizing the difference between a cat and a dog. That's because computers are designed with Von Neumann architecture, with a processor connected to memory. The brain, by contrast, has a very different design. It is a "hierarchical memory system." At the lowest level, the brain's neural connections store memories such as the shape of an object. At the next level up, the pattern associated with a human form is stored. And at the highest level, the brain recognizes the person as Bill Clinton.

The brain operates on the same formula, or algorithm, in every region, according to Hawkins. It doesn't have one algorithm for processing vision or a different one for processing sound. Each part of the brain is also self-training. You are born with nothing and learn. Each part of the brain learns based on what information is passing through it.

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Naturally Stupid

I am just another naturally stupid guy that had nothing to do with Artificial Intelligence (AI).

But I became a great fan of David Gelernter after reading a few of his lucid descriptions of complex AI concepts that I stumbled upon, mistaking it for philosophy initially. He talks of AI in such a plain language, just as Stephen Hawking glides along deep science concepts in A Brief History of Time. Gelernter believes it’s highly unlikely that a conscious mind will ever be built out of software, and belongs to what he calls as “anti-cognitivists” camp. Here's to sample his style -

"So what is it like to be a computer running a complex AI program? "Exactly like being a computer running any other kind of program".

Of course, we can't know literally what it's like to be a computer executing a long sequence of instructions. But we know what it's like to be a human doing the same. Imagine holding a deck of cards. You sort the deck; then you shuffle it and sort it again. Repeat the procedure, ad infinitum. You are doing comparisons (which card comes first?), data movement (slip one card in front of another), and so on. To know what it's like to be a computer running a sophisticated AI application, sit down and sort cards all afternoon. That's what it's like.

The computer's routine never varies: grab an instruction from memory and execute it; repeat until something makes you stop.

If you sort cards long enough and fast enough will a brand-new conscious mind (somehow) be created? This is, in effect, what *cognitivists* believe."

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He amazes me with his lucidity. Aren't you too...?

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More things change....

The obvious is not necessarily unambiguous.

Awestruck…? I realized it when I was trying to improve my odds at playing Chess against computer. When it beat me game after game (Level : pro), I was raging within. More games, more surrenders later, I sensed there’s more to winning than just strategy and outthinking the machine. That’s when I chanced upon this insightful piece by William Saletan. Worth a read.

Excerpts –

“We certainly needed the challenge. Chess computers, in particular, have exposed our complacency. Grandmasters used to dismiss computers as calculators, unfit for elite competition. Our vanity was so blinding that in 1997, when world champion Garry Kasparov lost to a machine called Deep Blue, he implied that the computer had received human coaching during the match.

Computers kept winning, and we kept whining. In post-game press conferences, players swore that they'd been winning right up until the moment when, for unclear reasons, they lost. Five months ago, the current champ, Vladimir Kramnik, overlooked an instant checkmate by his artificial opponent, Deep Fritz. "I rechecked this variation many times and analyzed quite far ahead," Kramnik protested. "It seemed to me I was winning."

“Kramnik's blunder was no accident. It happened because of flaws in the human brain. We thought we were smarter than computers for two reasons. First, we could choose a goal and figure out how to get there, whereas computers had to start with the available moves and see where they led. Second, computers had to think through every possible move, whereas we could recognize crucial patterns and focus on the moves that mattered. But that's why Kramnik missed the checkmate: It looked different from the usual threat pattern, and he was thinking too far ahead. Even the best brain sometimes needs computer assistance.”

“When the cosmic game between humans and computers is complete, here's how the sequence of moves will read. In the opening, we evolved through engagement with nature. In the middle game, we projected our intelligence onto computers and co-evolved through engagement with them. In the endgame, we merged computers with our minds and bodies, bringing that projected intelligence back into ourselves. The distinction between human and artificial intelligence will turn out to have been artificial.”

Pretty balanced article from Artificial Intelligence (AI) genre, surprisingly. Normally it leans way too much towards AI or argues in favor of human ascendancy. Truth however is - the more things change, more they remain the same. It’s just a round-tripping exercise in the *human–computer–human* grid. So be it. Certainly I am not the one to relax until I beat it at least 10 games in a row. And when it wins against me, it’s after a lot of sweat for its neural network.

That…means a tough fight. I like that anyday.

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