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Being good at video games is a measure of intelligence, study finds

The Independent

If you're good at games, you might also be good at everything else. That's according to a new study that found two of the world's most popular video games act like IQ tests. Those who are the best at them also get the highest scores on traditional intelligence tests, suggesting that video games might actually make you smarter. Both games – League of Legends and Defence of the Ancients 2 (DOTA 2) – combine strategic thinking with quick reactions, and so could both reward and train up particular kinds of thinking. That seemed to be confirmed by the study, which compared people's levels of skill in the games with their IQ.


Artificial Intelligence's Winners and Losers

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The board game Go is older and more complex than chess. While it's been 20 years since IBM's Deep Blue beat world chess champion Garry Kasparov, computers only started beating Go experts a few years ago. An Oct. 18 report in the science journal Nature tells us that this particular man/machine contest is done. A system built by the DeepMind unit of Alphabet (ticker: GOOGL) beat Go's reigning world champ 100 games to none. The deposed champ, you should know, is a prior version of the same artificial intelligence system, which beat one of humankind's international champions in 2016.


Exclusive: Infosys "re-imagining" tennis using AI Access AI

@machinelearnbot

Infosys, a global leader in technology services and consulting, is aiming to reinvent the way people consume sport using extensive player data. The Indian firm, which had revenues of $9.5 billion in its last financial year, demonstrated its'Infosys Information Platform (IIP)' during the recent ATP Tennis tournament in London, of which it was a headline sponsor. Speaking to Access AI, the firm's head of energy and services for Europe Mohamed Anis, who joined in 2000, said Infosys uses machine learning to analyse historical data on player performance, which in turn is able to predict behaviour, shot selection, and even a probabilistic outcome of the match itself. Anis (pictured) said the data is delivered in real time and can be used to help spectators view the game/match on an entirely different level – comparable to that of the coach. "Tennis has been around for a very long time," explained Anis.


Hyperparameter Tuning of Deep Learning Algorithm

#artificialintelligence

Random Sampling Method: In random method, we have high probability of finding good set of params quickly. Random sampling allows efficient search in hyperparameter space. In this range, it is quite reasonable to pick random values. This way we will spend equal resource to explor each interval of hyperparameter range.


Post-Hire Employee Engagement and Workforce Management: Leveraging AI in the Workplace

#artificialintelligence

It's about employee engagement, performance management, skills development, and a host of related time- and resource-intensive functions. If the history of enterprise systems, applicant tracking systems, recruitment marketing, and related technologies are any indication, the pace of change may vary, but the strategic value will continue to grow as AI applications begin to span the multiple functions of HR, from recruiting to compensation and performance management. Along with its powerful promise, AI also poses ethical questions as pointed out by an active player in the AI space, Shon Burton, CEO and founder of HiringSolved. That is, HR depends on humans to do the most important parts of its function, interacting with candidates and employees, finding talent, determining strategy, and evolving with the business.


How to Use Automation to Boost PPC Performance

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Smart bidding uses advanced machine learning to amend bids based on a wide range of real-time signals including device, location, time of day, remarketing list, language, and operating system. My agency has even created a script that modifies bids for every product group on Google Shopping based on a target ROI figure, saving our account managers huge amounts of time manually amending bids. A great example of how to utilize the power of automation to help monitor account performance is an AdWords Script like Google's Account Anomaly Detector. At Hallam, we use the Google Analytics API to populate our PPC reports in Google sheets, ensuring that our account managers automatically get the data they need to send their clients, and that their monthly "reporting time" is dedicated to analyzing the information and planning necessary actions for the next period.


What You Need to Know About Machine Learning – Part One - Phrasee

#artificialintelligence

A computer program is said to learn from experience "E" with respect to some class of tasks "T" and performance measure "P" if its performance in tasks "T", as measured by "P" improves with experience "E" This, of course, is just a fancy way of saying that if a machine is able to perform a task more effectively over time based on measuring its own performance and changing how it performs its tasks accordingly, it can be considered a learning machine. Mining and compiling enough data and exhaustively analyzing all the variables involved may not produce perfect predictions of future events, but it can get you pretty darn close. Today, with machine learning involved, the process happens in real time, with little or no interruption to the business day. The machines involved learn as they go.


5 Ways Machine Learning Increases Marketing Performance

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Machine learning recognizes patterns in customers' past engagement and actions. Machine learning customer segmentation models can be used very effectively to increase relevancy. Machine learning's ability to provide predictive analytics increases the likelihood a customer will convert by supporting real-time interactions across multiple channels. By finding patterns in past customer behavior and optimizing our analytics machine learning helps us predict a customer's journey and thus their lifetime value.


Monitoring APIs @DevOpsSummit @Catchpoint #API #DevOps #AI #WebPerf

#artificialintelligence

DevOps at Cloud Expo taking place October 31 - November 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA, will feature technical sessions from a rock star conference faculty and the leading industry players in the world. With major technology companies and startups seriously embracing Cloud strategies, now is the perfect time to attend 21st Cloud Expo, October 31 - November 2, 2017, at the Santa Clara Convention Center, CA, and June 12-14, 2018, at the Javits Center in New York City, NY, and learn what is going on, contribute to the discussions, and ensure that your enterprise is on the right path to Digital Transformation. The upcoming 21st International @CloudExpo @ThingsExpo, October 31 - November 2, 2017, Santa Clara Convention Center, CA, and June 12-14, 2018, at the Javits Center in New York City, NY announces that its Call For Papers for speaking opportunities is open. With major technology companies and startups seriously embracing Cloud strategies, now is the perfect time to attend @CloudExpo @ThingsExpo, October 31 - November 2, 2017, at the Santa Clara Convention Center, CA, and June 12-4, 2018, at the Javits Center in New York City, NY, and learn what is going on, contribute to the discussions, and ensure that your enterprise is on the right path to Digital Transformation.


A Business Leader's Guide to Machine Learning Centric Digital

#artificialintelligence

While AI and machine learning are normally used for number crunching applications, more complex analytical projects such as hiring were assumed to be a task requiring human reasoning. This requires a commitment to evaluating the full extent of what machine learning can do in their organization, finding agreement on a machine learning strategy among all top executives and bringing in external experts to advise the company on executing that strategy. The second type has a breadth of knowledge on how to communicate the potential of machine learning, converting results into insights and visualizations that make sense to managers on the front lines. In the end, as the WEF's Fourth Industrial Revolution analysis would suggest, human intelligence and machine learning will merge to create something we don't yet have a name for.