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) …
The Google Pixel 2 and Pixel 2 XL devices, which were revealed earlier this month, are highly focused on imaging, just like their predecessors, the first Pixel devices. On Wednesday, the smartphone company released its first developer preview for Android 8.1 -- Oreo OS, which will make use of the Pixel 2 series' high-end camera capabilities. The Pixel 2 series builds on the success of the first Pixel devices, which were awarded the best smartphone camera of 2016 by DxOMark. The company has, in the past year worked with DxOMark on the cameras for the Pixel 2 and revealed the device on Oct. 4. One of the new features of the device is its neural networks API which is its artificial intelligence based software, that the company says will "enhance the on-device machine intelligence."
"(Samsung) is in the middle of developing several types of chips that will be capable of processing massive data from AI applications on devices, eliminating the need to communicate with cloud surveys," a source from Samsung's partners said. At present, AI devices store data produced from voice recognition and machine learning operations in the cloud as a database. Chinese manufacturer Huawei has already been given that credit when it announced that its Mate 10 flagship phone will be debuting next month along with the tech industry's first AI phone chip, called the Kirin 970. This new information on Samsung's plans surfaced following the launch of the South Korean tech giant's new flagship smartphones, Galaxy S8 and Galaxy Note 8.
The Italian conductor Andrea Colombini trained the robot prior to Tuesday night's concert so that it would be prepared with the correct motions for each song it conducted. The conductor trained YuMi by holding its arms and hands and guiding it through the movement of conducting and the robot recorded these movements. "Setting up the interaction between the elbow, forearm and wrist of the robot, making use of its versatility in repeated and demanding attempts to break down the upbeats and downbeats, was very successful," Colombini said, according to an ABB press release. Not only did YuMi conduct the orchestra, it also conducted the world-renowned singer Andrea Bocelli.
Huawei has unveiled an artificial intelligence based chipset -- the Kirin 970 which would be featured in its upcoming Mate 10 and Mate 10 Pro smartphones. According to the company, it might be able to preserve battery up to 50 percent, due to the fact that, it will come with a neural processing unit (NPU) which will make for better computing, graphics, image and digital signal processing. It brings together classic computing, graphics, image and digital signal processing power that have typically required separate chips, taking up more space and slowing interaction between features within phones," Yu stated. Most devices already have an artificial intelligence based voice assistant nowadays, but employing an NPU inside the chipset is a whole other gambit.
An artificial intelligence application beat a top player in the multiplayer online game Dota 2. At The International championship in Seattle earlier this week, a program developed by firm OpenAI managed to beat top Dota 2 player Danil Ishutin, better known as Dendi, in a series of 1 vs. 1 matches. In a pre-roll segment, OpenAI's bot was shown beating several other top Dota 2 players in matches. OpenAI's Dota 2 bot is also the latest example of artificial intelligence bots beating humans in gaming.
Intel on Thursday launched its Movidius Neural Compute Stick, which will enable users to easily develop artificial intelligence and deep learning applications, and even use the technology in research. "The Myriad 2 VPU housed inside the Movidius Neural Compute Stick provides powerful, yet efficient performance -- more than 100 gigaflops of performance within a 1W power envelope -- to run real-time deep neural networks directly from the device. At this price, the device would make it much easier to develop AI, as it would make it easier to add deep learning capabilities to existing computing platforms. The company claims the device will make it easier to develop, tune and deploy AI applications.
Catalyst proposes to circumvent the on-chain performance issue by routing orders through off-chain payment channels and using hashed timelock contracts (HTLCs), the same vein as the Lightning or proposed Raiden networks. To begin trading, users open payment channels with a chosen liquidity provider, in the currencies they wish to trade. In order to do algorithmic trading today in crypto markets, as opposed to stock markets, you have to work as an engineer, curate data sets and build testing tools. The type of data suggested include historical time series market data, initial coin offering data and sentiment data from news, social media subreddits and crypto forums.
Dr Marc Ettlinger, chief data scientist, AI Labs, added: "We use innovative neural network models to build our sentiment analysis engine, far surpassing previous approaches for understanding the meaning of millions of stock articles and their relationship to stock price." A huge innovation in data science over the past five years has been the ascendance of neural network models, rebranded as deep learning models, over symbolic, rule-based expert systems. Another aspect of why hedge funds have been seeing poor returns, specifically those who tout algorithmic trading strategies and systematic trading, is due to their inability to continuously refine and upgrade their strategies, noted Mehrotra. "I was in the research sphere before I was at Artificial Intelligence Labs and I experienced how quickly technological research [quantitative finance, artificial intelligence, etc] was done and the effects and implementations of that research in systematic trading strategies.
Neuroscientists have suggested this resource could be neural activity, with different parts of the remembered information having varying amounts of activity devoted to them, depending on current priorities. The prefrontal cortex is associated with a wide array of other important functions, including personality, planning and decision-making. A theory of cognitive architecture, called Global Workspace Theory, relies on working memory. It suggests that information held temporarily "in mind" is part of a "global workspace" in the mind which connects to many other cognitive processes and also determines what we are conscious of in any given moment.
But the city's new effort seems to ignore evidence, including recent research from members of our policing study team at the Human Rights Data Analysis Group, that predictive policing tools reinforce, rather than reimagine, existing police practices. Machine-learning algorithms learn to make predictions by analyzing patterns in an initial training data set and then look for similar patterns in new data as they come in. Our recent study, by Human Rights Data Analysis Group's Kristian Lum and William Isaac, found that predictive policing vendor PredPol's purportedly race-neutral algorithm targeted black neighborhoods at roughly twice the rate of white neighborhoods when trained on historical drug crime data from Oakland, California. This should start with community members and police departments discussing policing priorities and measures of police performance.