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 effort points to ways in which Amazon and other companies could try to improve the tracking of trends in other areas of retail--making recommendations based on products popping up in social-media posts, for instance. For instance, one group of Amazon researchers based in Israel developed machine learning that, by analyzing just a few labels attached to images, can deduce whether a particular look can be considered stylish. An Amazon team at Lab126, a research center based in San Francisco, has developed an algorithm that learns about a particular style of fashion from images, and can then generate new items in similar styles from scratch--essentially, a simple AI fashion designer. The event included mostly academic researchers who are exploring ways for machines to understand fashion trends.
Michal Kosinski – the Stanford University professor who went viral last week for research suggesting that artificial intelligence (AI) can detect whether people are gay or straight based on photos – said sexual orientation was just one of many characteristics that algorithms would be able to predict through facial recognition. Kosinski, an assistant professor of organizational behavior, said he was studying links between facial features and political preferences, with preliminary results showing that AI is effective at guessing people's ideologies based on their faces. That means political leanings are possibly linked to genetics or developmental factors, which could result in detectable facial differences. Facial recognition may also be used to make inferences about IQ, said Kosinski, suggesting a future in which schools could use the results of facial scans when considering prospective students.
Last week, the WannaCry ransomware attack crippled their network -- one report suggested people with life-threatening injuries were told not to come to the hospital. In the future, security systems could use artificial intelligence to monitor user behavior, track activity, suggest when there may be a danger and even mount an attack against the ransomware purveyors, effectively rendering the deadly malware client inoperable. Raja Mukerji, the cofounder and Chief Customer Officer at ExtraHop Networks, equates how an AI can block ransomware to how airport security stops people from using water bottles. A new technique using AI in airport security would not block all water bottles.
More overlooked machine learning and/or machine learning-related projects? OpenAI Gym is a toolkit for developing and comparing reinforcement learning algorithms. From Intel comes a(nother) deep learning framework, optimized for distribution over Apache Spark. BigDL is a distributed deep learning library for Apache Spark; with BigDL, users can write their deep learning applications as standard Spark programs, which can directly run on top of existing Spark or Hadoop clusters.
Artificial intelligence (AI) is more than a stylish trend. One by one, B2B vendors are rolling out their AI chops -- targeting platform Demandbase, CRM and marketing platform Salesforce, account engagement platform YesPath, conversational platform Conversica, and B2B predictive marketer CaliberMind, among a growing list of others. To get some insight into what this means for businesses selling to businesses, we talked with Raviv Turner, CEO and co-founder of CaliberMind. First of all, selling to a business is complicated.
Five years ago, researchers made a sudden leap in the accuracy of software that can interpret images. The technology behind it, artificial neural networks, underpins the recent boom in artificial intelligence (see "10 Breakthrough Technologies 2013: Deep Learning"). Yann LeCun, director of Facebook's AI research group and a professor at New York University, helped pioneer the use of neural networks for machine vision. That's what would allow them to acquire common sense, in the end.
Programmer Harrison'Sentdex' Kinsley created the AI (or "convolutional neural network"), named it Charles, and set it loose in the game to teach itself through deep learning. As Kinsley describes in the Twitch description, Charles "learns and takes all actions based on single frames at a time, and bases his decisions on just pixel data. What the AI can't do yet is remember: Kinsley didn't program in memory, forcing it to make split-second decisions one frame at a time, like so. Whether this AI becomes a better driver and validates educating neural networks through simulation, at least we can chuckle that even machines have trouble driving these games.
Note that, while there are numerous machine learning ebooks available for free online, including many which are very well-known, I have opted to move past these "regulars" and seek out lesser-known and more niche options for readers. The book has wide coverage of probabilistic machine learning, including discrete graphical models, Markov decision processes, latent variable models, Gaussian process, stochastic and deterministic inference, among others. The material is excellent for advanced undergraduate or introductory graduate course in graphical models, or probabilistic machine learning. One of these target audiences is university students(undergraduate or graduate) learning about machine learning, including those who are beginning a career in deep learning and artificial intelligence research.
To help accelerate AI research, Pichai announced that the Tensor Processing Units (TPUs) it uses to train machine-learning models is available in the Google Cloud Platform for anyone to use via the Google Compute Engine today. "We want it to be possible for hundreds of thousands of developers to use machine learning," Pichai said. Our new Cloud TPUs accelerate a wide range of machine learning workloads, including training and inference https://t.co/aWvTVMn54Q The CEO also announced that Google will be using the neural nets it creates to build other neural nets with AutoML. The system takes a set of candidate neural nets (Pichai called them baby neural nets) and iterate them using a reinforcement training approach until the best one is found.
The human mind is no longer capable of keeping up with the velocity, volume, and variety of Big Data streaming through daily operations, making AI a powerful and essential tool for optimizing the analyzing and decision-making processes. Using all this information, it makes a data reservoir of relevant insights that may contain solutions to a wide range of critical issues, faced by IT operations and DevOps teams on a daily basis. The real-time obstacles DevOps engineers, IT Operations managers, CTOs, VP engineering, and CISO face numerous challenges, which can be mitigated effectively by integrating AI in log analysis and related operations. Quickly find the needle in the "IT operations" haystack and eliminate the main problems The good AI integration can yield Using AI driven log analytics systems, it becomes considerably easy to find the needle in the haystack, and efficiently solve issues.