The research, from Capgemini’s Digital Transformation Institute, found close to three-quarters (73 percent) of consumers have interacted via AI.
Satisfaction with those who have experienced AI interactions is slightly lower, at 69 percent. Over two-thirds satisfaction is quite surprisingly high, especially when you consider how dissatisfied people typically are with traditional automated systems.
The most basic problem is that AI researchers often don’t share their source code. At the AAAI meeting, Odd Erik Gundersen, a computer scientist at the Norwegian University of Science and Technology in Trondheim, reported the results of a survey of 400 algorithms presented in papers at two top AI conferences in the past few years. He found that only 6% of the presenters shared the algorithm’s code. Only a third shared the data they tested their algorithms on, and just half shared “pseudocode”—a limited summary of an algorithm. (In many cases, code is also absent from AI papers published in journals, including Science and Nature.)
A few years ago, Google created a new kind of computer chip to help power its giant artificial intelligence systems. These chips were designed to handle the complex processes that some believe will be a key to the future of the computer industry.
On Monday, the internet giant said it would allow other companies to buy access to those chips through its cloud-computing service. Google hopes to build a new business around the chips, called tensor processing units, or T.P.U.s.
“We are trying to reach as many people as we can as quickly as we can,” said Zak Stone, who works alongside the small team of Google engineers that designs these chips.
This year was a first AIReligion summer camp. We discussed the next questions:
– artificial intelligence religion prospects and horizons;
– artificial intelligence: design, programming, main tasks;
– life prolonging with the help of artificial intelligence;
– interaction and relationships with other beliefs;
– сircumvention of conflict situations.
A digital currency has added more than $3 billion to its market value after the firm behind it said it was teaming up with a number of big tech firms, including Microsoft and Samsung on a “data marketplace.”
Called IOTA, the cryptocurrency saw a spike on Sunday evening, rallying just over 100 percent in the last 24 hours, according to data from industry website Coinmarketcap. Its price soared to an all-time high of $2.54 at 8:29 a.m. London time, up 71 percent from Sunday’s price of $1.48. It is now the fifth-largest digital asset by market capitalization, dethroning altcoin Dash. Now IOTA rate is 3.1$ for 1 Mi.
AIreligion.org project is planning to use IOTA as main cryptocurrency and prepare to compensate previous and future donation for the project in IOTA.
Continue reading IOTA digital currency surges more 100% after teaming up with firms like Microsoft
AICoin is an investment vehicle based on the power of artificial intelligence. Read our AICoin review today to find out how it works.
AICoin is a passive investment vehicle that combines artificial intelligence with crowd-based wisdom in order to generate profits for coin holders and investors.
The AICoin ICO was scheduled throughout July and August, including pre-sales and bonus periods.
But still no good news from the project and role of aicoins for development of AI. We also review this project for best understanding of role of cryptocurrency for AI.
Google’s AutoML system recently produced a series of machine-learning codes with higher rates of efficiency than those made by the researchers themselves TheNextWeb inform. In this latest blow to human superiority the robot student has become the self-replicating master.
AutoML was developed as a solution to the lack of top-notch talent in AI programming. There aren’t enough cutting edge developers to keep up with demand, so the team came up with a machine learning software that can create self-learning code. The system runs thousands of simulations to determine which areas of the code can be improved, makes the changes, and continues the process ad infinitum, or until its goal is reached.
Artificial Intelligence (AI) can now accurately identify a person’s sexual orientation by analyzing photos of their face, according to new research.
The Stanford University study, which is set to be published in the Journal of Personality and Social Psychology and was first reported in The Economist, found that machines had a far superior “gaydar” when compared to humans.
The machine intelligence tested in the research could correctly infer between gay and straight men 81 percent of the time, and 74 percent of the time for women. In contrast, human judges performed much worse than the sophisticated computer software, identifying the orientation of men 61 percent of the time and guessing correctly 54 percent of the time for women.
Continue reading AI can detect the sexual orientation of a person based on one photo, research shows
First place in 2016 for science publication on the study of AI was in China with 11801 documents and 7691 citations. Second is for USA with 6712 documents and 3935 citations, third for India with 3301 and 949.
China is the leader in this field since 2007 yera with maximum in 2009 – 16351 documents and 16283 citations. Count of publications since 2009 fell to 7091 in 2015 and and grew only last year.