The Black Box Farce: Cracking the Code to AI Investing

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AI Investing
The Black Box Farce: Cracking the Code to AI Investing

‘If humanity collectively decides that creating digital superintelligence is the right move, then we should do so very, very carefully.’

So said US entrepreneur, Elon Musk.

Here’s why I’m thinking about this.

4,000 years ago China created a game so unorthodox that it captivated Asia.

It’s an abstract game where two players pitch against each other to secure their stake of the board.

It’s considered one of the most complex games ever, even though the game only has two main rules.

Players feel out of touch with reality because the experience is so unique.

This game is called Go.

It’s been said that Go players don’t play to understand Go, they play to understand what understanding is…

Well, that was until Google’s artificial intelligence called DeepMind got involved…

Why am I telling you this?

There’s a valuable lesson for stock market traders here.

DeepMind changes the course of history

Google’s DeepMind has a long history.

It began playing the old arcade game called Breakout.

You might remember this one.

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It was a game where you had to break all the blocks by bouncing a ball off the walls.

See the image below…

Source: Confectionerynews.com

DeepMind successfully beat the game.

It learnt to win all on its own.

But it wasn’t an instant result. Deep Mind took 100 games just to understand what it actually needed to do.

By 300 games, the AI was now as good as a human. And by 500 games, the AI implemented the most optimal system to beat the game.

Pretty cool if you ask me. But what does this have to do with trading? Hang in there, I’ll get to that soon!

DeepMind continued to progress and eventually began trailing its new system to play Go.

That’s the game I told you about before…and many assume an AI player was far off winning this due to its complexity.

Google called this program Alpha Go.

Yep, looks like DeepMind felt it was time to move up from old-time arcade games.

It annihilated the professionals

Google needed brains in order to perfect their program, and not any brain, but that of Fan Hui.

Fan is a Chinese-born French Go player. He became a professional in 1996 and became the coach of the French national Go team in 2005.

In the game of Go, he’s ranked as a 2 ‘dan’ professional. That’s on a scale of 1–10, with 10 being the best.

Despite the seemingly low ‘dan’ level, Fan Hui was the European champion in 2013, 2014 and 2015.

That’s just to give you an idea of the skill DeepMind was searching for.

Anyway…DeepMind invited Fan to London to play against their computer program.

Can you guess the outcome?

It was a massive victory for DeepMind. It proved their program was capable of beating even a world champion at this game.

There is something which I want to leave you with.

Fan played against the computer day in and day out after failing.

It was weeks until eventually, he found a weakness in the program…and was able to beat it.

Don’t hold your breath, there’s no black box

And that’s the point I want to make here.

The team behind AlphaGo said…‘Everything AlphaGo does is because human created it’.

Which means the system is only as good as its engineer, coding and software make up.

Today, AlphaGo has been replaced by AlphaGo Zero, a much more sophisticated program.

Though, when it comes to investing alongside AI…as will surely happen in the near future.

The thing to remember is that nobody has cracked the code to AI investing.

And if anyone has, they surely haven’t tested it successfully against human emotion and psychology. Which is a major factor in today’s markets…

But not only that…

At what point does the AI learn to distinguish between a move in the market that signals a buy, or even a sell.

Especially as we enter periods of euphoric buying, or desperate selling.

I’ll follow this up with part two next week. This is a massive trend that we should be watching. It could dictate how we build wealth in the future.

Have a great weekend,

Jonathan Evans Signature

Jonathan Evans,
Analyst, Profit Watch

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