Archive for February, 2016

Artificial Intelligence Post Number 30

February 26, 2016

In past updates I suggested that the first applications of artificial intelligence would occur in the stock market, because mutual funds and hedge funds would fund the development of the required AI to beat the market. Of course these investment companies would not make their applications of AI public because that would either discount their value or make the government take action to remove these obvious advantages over the average investor.

But I believe that their trail is obvious if you look at a chart of the S&P 500 for the last five years. You will see that the character of changes in the S&P 500 have changed dramatically in recent years. Both the percent of change and the velocity of change have increased versus earlier periods. You can look at this on either a linear or log chart and you will see the same thing. Note Oct 19, 2014; Aug 16, 2015; Oct 4, 2015; and Jan 4, 2016.

This is not enough data to conclude that this is statistically significant to a 95% confidence level, but it is getting close. And it certainly is worth watching.

As I have said before, I would not try to play the general market with what is going on. Buying a specific stock for its growth potential may be valid. But in my opinion, the overall market is now being largely influenced by AI programs.

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Artificial Intelligence Post Number 29

February 6, 2016

A 2/4/2016 article by Cade Metz of Cade Metz Business describes how Artificial Intelligence (AI) is transforming Google Search. Here are some relevant quotes from this article that supports how AI is proceeding on its ability to discover “deep neural networks, networks of hardware and software that approximate the web of neurons in the human brain. By analyzing vast amounts of digital data, these neural nets can learn all sorts of useful tasks, like identifying photos, recognizing commands spoken into a smartphone, and, as it turns out, responding to Internet search queries. In some cases, they can learn a task so well that they outperform humans. They can do it better. They can do it faster. And they can do it at a much larger scale.”

“The truth is that even the experts don’t completely understand how neural nets work. But they do work. If you feed enough photos of a platypus into a neural net, it can learn to identify a platypus. If you show it enough computer malware code, it can learn to recognize a virus. If you give it enough raw language—words or phrases that people might type into a search engine—it can learn to understand search queries and help respond to them. In some cases, it can handle queries better than algorithmic rules hand-coded by human engineers.”

“At one point, Google ran a test that pitted its search engineers against Rank Brain,” a deep learning system. “Both were asked to look at various web pages and predict which would rank highest on a Google search results page. RankBrain was right 80 percent of the time. The engineers were right 70 percent of the time.”

“Increasingly, we’re discovering that if we can learn things rather than writing code, we can scale these things much better.”

Those of you who have read my book Artificial Intelligence Newborn – It is 2025 , and I am Here! will see that AI seems to be progressing even faster than in my fiction novel. Perhaps the title should have been “It is 2020, and I am Here!

Update on Elliot Wave’s prediction that the S&P 500 will drop 41.6% this year from 1880 to 1100. I said that don’t believe it! The current S&P is 1880, flat since EW’s prediction early this year.