If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
Published Sunday, Jun. 24, 2018, 12:48 pm Dear EarthTalk: What are some ways artificial intelligence is being used to fight climate change and otherwise protect the environment? Artificial intelligence (AI), defined as the capability of machines to imitate intelligent human behavior and learn from data, is considered by many to be the final frontier of computing. And environmentalists and tech companies are now harnessing the power of AI to service to the environment. To wit, Microsoft announced in December 2017 that it is expanding its "AI for Earth" program and committing $50 million over the next five years to put AI technologies in the hands of individuals and organizations working to solve global environmental challenges, including climate change as well as water, agriculture and biodiversity issues. Lucas Joppa, Microsoft's first Chief Environmental Scientist, is convinced that AI is now mature enough and the global environmental crisis acute enough to justify the creation of an AI platform for the planet.
After the fall of the Berlin Wall, East German citizens were offered the chance to read the files kept on them by the Stasi, the much-feared Communist-era secret police service. To date, it is estimated that only 10 percent have taken the opportunity. In 2007, James Watson, the co-discoverer of the structure of DNA, asked that he not be given any information about his APOE gene, one allele of which is a known risk factor for Alzheimer's disease. Most people tell pollsters that, given the choice, they would prefer not to know the date of their own death--or even the future dates of happy events. Each of these is an example of willful ignorance.
An experiment was initially performed in 2011 where both humans and AI were "asked" to identify what was shown in a blurred image. Human error rated at 5% while AI at 26%. In 2013 the experiment was repeated and AI error dropped to 3%. In 2015 an AI managed to almost beat the top Poker players in the U.S. (and poker is a strategic "thinking" game where not merely the cards "have a role to play". The main point was that it learned how to "bluff", … yes, … really!
Several years ago, when I was at university, I was involved in the theater. One day, in an exercise linked to the interpretation of a character, I asked my teacher if what I was doing was "perfect". He suggested that in the theater, the concept of'accuracy' was better than'perfection'. No actor is'perfectly' Romeo or Caligula. Instead, the image of the character emerges from the actor's interpretation of a text written perhaps a century or more ago.
It's no great revelation that we live in a surveillance society. A U.S. citizen is reportedly captured on CCTV around 75 times per day. That figure is even higher elsewhere in the world. In the United Kingdom, this number is considerably greater, with your average Brit likely to be caught on surveillance cameras up to 300 times in the same period. But a lot of existing CCTV networks still rely on people to operate them.
There are so many tools, platforms and resources available, MLEs can focus their time on solving problems critical to their field or company instead of worrying about building platforms and hand rolling numerical algorithms. Google Cloud has easy means of building and deploying TensorFlow models including their new TPU support in beta, AWS has an ever evolving suite of deep learning AMIs and Nvidia has a great deep learning SDK. In parallel, Apple's coreML and Android's NN API make is simpler and faster to deploy models on phones; this will continue to push the boundary for developing and releasing ML apps. With all of the above, there is healthy competition among big players in the cloud space pushing the whole ecosystem forward. And yet, most of them are finding ways to collaborate towards open standards like ONNX.
Artificial intelligence technology will revolutionize every area of human lives if well exploited by app developers. Here are some of the areas where technology has already made a tremendous impact. App developers have developed so many gaming apps that are built on artificial intelligence. In most of those games, you can either play with fellow players or play with computer and the response of the game itself depends totally on your own input. This is exactly where artificial intelligence comes to play.
In this study, we predict the outcome of the football matches in the FIFA World Cup 2018 to be held in Russia this summer. We do this using classification models over a dataset of historic football results that includes attributes from the playing teams by rating them in attack, midfield, defence, aggression, pressure, chance creation and building ability. This last training data was a result of merging international matches results with AE games ratings of the teams considering the timeline of the matches with their respective statistics. Final predictions show the four countries with the most chances of getting to the semifinals as France, Brazil, Spain and Germany while giving Spain as the winner. The objective of this study is to build a predictive model that will allow us to make good predictions for the coming World Cup 2018 so we looked for dataset with historic data for match results, for this purpose we chose a dataset from Kaggle with data of almost 40,000 international matches played between 1872 and 2018.
"I never forget a face", "She's got an honest face", "You could see it in his face", and "She looks young for her age" are just a few of the often-used phrases suggesting that faces are important for our interactions with other people and what we think we know about them. But can people really remember faces as well as they think they do, and can we really tell someone's age from their face? Or can artificial intelligence (AI) do it better? And can we really tell if someone is trustworthy just by looking at their face? Research shows that humans exhibit a wide range of facial recognition abilities.
Artificial intelligence has been shaking up the marketing world for the last few years, helping automate menial, repetitive tasks, inform better creative decisions, and predict revenue projections. But many of the tools available for that latter category, namely, predictive analytics, have a less-than-stellar accuracy rate. South Africa-based Xineoh has developed a platform for predicting customer behavior with AI. The company claims its technolgoy is more accurate than any other solution available. Xineoh was founded in 2010 and raised $2 million from U.S. and Canadian investors in June 2017.