The Changing Face of AI Research

From beating humans at poker games to predicting weather forecasts, AI technology is making great strides in present times

However, it is by no means clear yet whether this will project as a game-changer in the world ahead.

Computer programmers have been trying hard to find the right and relevant pattern in data just to be sure they become extremely good at beating multiplayer games. Perhaps they’re already on it.

A whitepaper published by researchers at Facebook and Carnegie Mellon University said their software is good at embracing randomness and that it is reliable to beat humans at games.

This project as a game-changing event for data science.

AI: the game-changer

Artificial intelligence is heralded as a solution to the complex problems faced by many industries and organizations. The prime concern for businesses today is to find out how to gain better insights into harnessing big data. For professionals, such as AI specialists and AI engineers working in this field, the motivation is to find the right and relevant potential of AI toward solving some of the world’s most challenging problems – social, economic, and environmental.

Without wasting time, let us see how AI is becoming the sole remedy for multiple domains and industries.

The gaming world

AI makes great strides in the gaming sector such as becoming the master of board games – chess and checkers. For instance, AlphaGo, a super AI and a prototype from Google Mind defeated Go, a complex and challenging Chinese strategy game.

AlphaGo likely conquered Lee Sedol at a widely-publicized match, Lee was one of the best Go players in the world. Most of the software developers made assumptions stating Go to be unassailable given the present condition of AI. But here we are.

At another event, AlphaGo made quite a hit and caught Sedol off-guard.

Since Sedol was developed by playing against itself a million times, the software became unpredictable. The reason why this software couldn’t determine why certain moves were made during the game.

Pluribus, another software collaborated by Facebook and CMU has been determined unpredictable since it involves six players to play the poker game. This was not at all the case with chess, checkers, and AlphaGo. These games involved merely two players. But traditionally with poker, it involves more than two hands, creating a major challenge for AI. Exploiting a single player’s hand is not at all feasible and Pluribus was designed just the opposite – it was designed to take on more than two opponents (five) concurrently.

Having six players play poker, the bets, the exchange of cards, and the chances of gaining possible outcomes will surprise even a supercomputer. This software required a reliable edge so that no mistakes were made.

Therefore, Pluribus started playing against itself. During this training period, AI took note of the outcomes for every possible variable. Further on, this software started playing one game at a time, making the required alterations for each variable.

The software did learn certain tips and crazy moves, and most of those moves were deemed winners.

As humans, we fidget and get nervous. This act of nervousness is predictable and can be easily spotted by the opponent. But with Pluribus, the software plays to its inherent strength, it is completely unpredictable and has no tell.

Tip: Software is consistent, has no emotions, and it is highly unpredictable.

The investment world

Most investment bankers have now realized that AI and machine learning is changing the enterprise world by storm.

Big giants such as Netflix, Amazon, and Alphabet are already building huge platforms in e-commerce, media distribution, and the internet search with the help of algorithms to understand the needs of the customer. It is surprising how to present companies are willing to do business, in the same manner, these companies conducted in the past years.

For instance, public cloud infrastructure has started democratizing data storage and computer processing. Besides this, it is now working as software-as-a-service companies to build applications that can convert a large amount of data into actionable insights.

Alteryx Inc., a leader in the self-service data analytics is one of the best platforms for data scientists. The ecosystem they’re working with allows them to fetch the data, build models, and use predictive analysis to predict possible and relevant insights.

With the hype around AI, tech professionals such as AI engineers will be in a hiring spree.

These companies are now realizing they’re sitting on a goldmine of information (data) which is stuck inside their manufacturing chain, supply chain, and retail chain. These data can be easily mined run businesses efficiently and to build new business models.

The banking sector now utilizes software to perform fraud modeling, retailers are using omnichannel analytics while the healthcare sector is now working on genome sequencing.

Tip: Collecting relevant data and understanding this data is the key.

About the Author

Michael Lyam is a writer, AI Enthusiast and Business Strategist at Alteryx. The 2018 Gartner Magic Quadrant named Alteryx to be the leader for machine learning and data science platforms. It now sits at the mid of digital transformation stack worth USD 15 trillion. The shares of Alteryx in the past 12 months were 209 percent, there’s a high possibility for these shares to increase in the upcoming days.

Featured image: ©VAlex

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