Sunday, July 24, 2016

Quantifying Probabilities for Gambling System Strategies

That brings us back to this notion that chance is both something that can’t be explained away any further, and yet there’s something deeply human about the desire to create a story to explain why things happen. Computers are now showing us strategies and explanations we never could have arrived at on our own; as you say, they’re outpacing their creators. What are some of the ramifications of that process?

One of the things that really surprised me in writing the book is how quickly these developments are happening. Even the Go victories this year: I think lots of people didn’t expect it to happen that suddenly. And likewise with poker: last year some researchers found the optimal solution for a two-player limit game. Now you got a lot of bots taking on these no-limits stakes games—where you can go all-in, which you often see in tournaments—and they’re faring incredibly well.

In many cases, these poker bots are turning up with strategies that humans would never have thought to attempt.

The developments are happening a lot faster than we expected and they’re going beyond what their creators are capable of. I think it is a really exciting but also potentially problematic line, because it’s much harder to unpack what’s going on when you’ve got a creation which is thinking much further beyond what you can do.

I think another aspect which is also quite interesting is some of the more simple algorithms that are being developed. Along with the poker bots which spend a huge amount of time learning, you have these very high-speed algorithms in gambling and finance, which are really stripped down to a few lines of code. In that sense, they’re not very intelligent at all. But if you put a lot of these things together at very short time scales—again, that’s something that humans can’t compete with. They’re acting so much faster than we can process information; you’ve got this hidden ecosystem being developed where things are just operating much faster than we can handle.

This goes beyond simply teaching bots to play poker or Watson winning at Jeopardy! There are wider ramifications.

Yes. And I think the increasing availability of data and our ability to process it and create machines that could learn on their own, in many ways, it’s challenging some of those early notions about learning machines. Even some of the criticisms and limitations that Alan Turing put forward when they were first coming up with these ideas, they’re now being potentially surpassed by new approaches to how machines could learn.

You have these poker bots, instead of learning to play repeatedly, they’re developing incredibly human traits. Some of these bots, people just treat them like humans: they refer to them in human terms because they bluff and they deceive and they feign aggression. Historically, we think of these behaviors as innate to our species, but we’re seeing now that potentially these are traits you could have with artificial intelligence. To some extent it’s blurring the boundaries between what we think is human and what’s actually something that can be learned by machine.


- Interview with Adam Kucharski author of The Perfect Bet: How Science and Math Are Taking the Luck Out of Gambling

What is Artificial Intelligence?


International Data Corp. predicts the worldwide market for cognitive software platforms and applications, which roughly defines the market for AI, to grow to $16.5 billion in 2019 from $1.6 billion in 2015 with a CAGR of 65.2%. The market includes offerings from both established tech giants and AI startups.

But many technology leaders don’t have clear ideas about the role of AI in their business, or how to maximize its value. “The number one issue for CIOs is how can I invest anything in artificial intelligence without having clear visibility into real business results,” Gartner Inc. fellow and research vice president Tom Austin said.

- More Here


Quote of the Day

The human brain is a complex organ with the wonderful power of enabling man to find reasons for continuing to believe whatever it is that he wants to believe.

- Voltaire

Saturday, July 23, 2016

Wisdom Of The Week


Why explore extraterrestrial caves? Partly for the same reasons scientists venture into caves on Earth. They’re protected from weather and (on other worlds) from meteoric bombardment, so their geological formations serve as frozen records of the planet’s past. Then there’s the life question. Liquid water on Mars is likely to exist underground, at depths where ice is melted by warmth from the planet’s interior. In caves, the temperature stays relatively stable, so they would also offer refuge from the 200-degree Fahrenheit day-night swings on the surface. Most important, they offer protection from radiation. Since Mars’ protective magnetic field flickered out eons ago, the constant barrage of cosmic rays on the surface likely would have destroyed any exposed critters. If life moved underground to escape, caves are a good place to look for fossil evidence of their tenancy. It’s even possible that in some Martian caves, life still exists.

“This is where the action is in terms of exploration,” says Penny Boston, a veteran cave scientist who just left the New Mexico Institute of Mining and Technology to become director of the NASA Astrobiology Institute, the agency’s focal point in the search for extraterrestrial life. Recently she’s been a leading advocate for what may strike many as a novel idea: that the ideal place to search for alien biology is not on the Martian surface, where NASA’s rovers have been looking, but beneath it.


- Mars, Underground: Looking for life on other planets? Go deep

Quote of the Day




Friday, July 22, 2016

Nation's first Vegetarian Drive-Through Opens In California

The crowds have been non-stop during the first week of business at a California fast food restaurant, with a twist. It's a drive-through that is actually good for you.

It is the nation's first organic drive-through restaurant. It has only been open five days and already it is struggling to keep up with demand.

Hungry customers at the new Amy's drive thru were patient and determined to order lunch. The wait is really long. Some said they heard the wait was 20 minutes long.

The line inside the restaurant was almost out the door, all for a chance to try organic, vegetarian fast food.

Kelsea Baraga is trying a veggie Amy burger and brought her mom along to try it too.

"Processed foods definitely are big on my mind. My daughter keeps bugging me about going vegetarian," customer Amy Braga said.

[---]

Schiefer says the local company, which has been making frozen organic foods for years, never dreamed the restaurant would be such a hit.

"So many people have shown up and it's giving us a lot of hope that this is a concept that works," Schiefer said.


- More Here

Quote of the Day






Thursday, July 21, 2016

Peter Webster, The Meteorologist Who Saves Lives

How does Big Data enable you to do that?
To do a one- to two-day forecast for a country like India, you just need to develop a forecasting model that covers India and its immediate neighbors. But as the forecast horizon increases, the influence of weather events thousands of miles away also become important. So for a 10-to 15-day forecast, we have to use a global model. We use the rainfall forecasts from the European Center for Medium Range Weather Forecast model in the United Kingdom. The model has grid points every 25 km over the globe and 130 levels in the vertical. Each day, the model is run twice and integrated out to 15 and 30 days. At these two points, the model is run 51 times with slightly different initial data to simulate the uncertainty in what we know about the state of the atmosphere and the physics of how the atmosphere works. Terabytes of data are generated each day and streamed to Georgia Tech where we stream it to obtain a regional forecast over Bangladesh, where we eventually stream the data via cellphone.

Do you have trouble convincing people who might not understand these complex models?

These people are living on the edge. They realize how vulnerable they are, so they’re accepting these forecasts.

It also helps that you’ve been correct?

In our first year there, 2007-08, we forecast all three major floods. There were no false positives. More importantly, there were no false negatives—a flood never came when we didn’t predict one.

[---]

You can’t talk about Big Data without talking about privacy, can you?

There are issues with privacy when it comes to meteorological data. Some nations sell their data. Some nations believe that data belongs to them. We wanted to give India a flood forecasting scheme for the entire Ganges, and all we needed was their river data at a few points, and they wouldn’t give it to us. They wouldn’t give us sea-level data. That makes it very difficult.

Yet you’ve been able to help India, right? 

Ahmedebad, a city of 4 million people, is impacted adversely by extreme heat waves that occur in the months before the monsoon rains. They wanted to be able to forecast these waves in advance so that they could allocate their scant resources optimally and develop a heat action plan.

- More Here


Quote of the Day

Never respond to an angry person with a fiery comeback, even if he/she deserves it, don't allow their anger to become your anger.

- via Reddit

Wednesday, July 20, 2016

Quote of the Day

It was Darwin’s chief contribution, not only to Biology but to the whole of natural science, to have brought to light a process by which contingencies a priori improbable are given, in the process of time, an increasing probability, until it is their non-occurrence, rather than their occurrence, which becomes highly improbable.

- Sir Ronald Aylmer Fisher