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) …
Artificial intelligence (AI) technology may be more easily accessible through Google Cloud's new AutoML service, the tech giant said in a blog post Wednesday. Cloud AutoML helps tech professionals build custom machine learning (ML) models, using techniques like transfer learning and learning2learn, the post said. While Cloud AutoML requires limited ML experience, the service could help businesses, especially SMBs, overcome talent shortages and cost barriers and utilize the emerging technology. "Our goal was to lower the barrier of entry and make AI available to the largest possible community of developers, researchers and businesses," Google Cloud AI's Fei-Fei Li and Jia Li said in the post. Even for larger businesses that have both the talent and budget to work with AI, they may not have the time to create machine learning models, the post noted.
Chess is an antique, about 1,500 years old, according to most historians. As a result, its evolution seems essentially complete, a hoary game now largely trudging along. That's not to say that there haven't been milestones. In medieval Europe, for example, they made the squares on the board alternate black and white. In the 15th century, the queen got her modern powers.1
A recent, most-excellent post over at the Objective-See blog (seriously, go and read it) details how the author, Patrick Wardle, dissects and manipulates the antivirus (AV) signature mechanism present in the macOS version of a traditional, signature-based antivirus software suite to achieve arbitrary false-positive detection. The flavoring of his post, of course, is the ongoing fracas surrounding the product's alleged potential for misbehavior in identifying and exfiltrating sensitive government documents on a computer protected by the product – a claim the suite's developers deny vehemently. Wardle elects not to comment on it – as do I – choosing instead to ask and answer the question, "Can an AV product be induced to: (1) arbitrarily and incorrectly identify a file as desired by an adversary, and, if (1) then (2) exfiltrate the files identified?" As detailed in the blog, Wardle reversed the AV product's scanning engine's behavior, which enabled him – and presumably any other sufficiently skilled attacker – to modify (he writes'extend') the way in which the product identified malicious files when scanning. Once understood, Wardle utilizes a method for writing bytes into remote processes to patch what the AV engine is looking for.
JetPack Aviation, the firm behind the'world's only true jetpack,' has unveiled its latest prototype at CES in Las Vegas. The team showed off a massive new design geared toward short, fast trips using six turbo jet engines to travel over 150 miles an hour. JetPack Aviation teamed up with Insta360 to show off the upcoming JB11 jetpack at the Las Vegas Convention Center. JetPack Aviation, the firm behind the'world's only true jetpack,' has unveiled its latest prototype at CES in Las Vegas. JetPack Aviation's creations are capable of vertical take-off and landing, unlike other types of wearable flight systems.
This year, the chief technical officer of Aptiv APTV 1.21% PLC wants to demonstrate how the technology might actually be deployed in real life. Aptiv, the automotive-technology company formerly known as Delphi Automotive, is partnering with ride-hailing startup Lyft Inc. at this week's show to give free rides in self-driven cars between the convention center and most of the big hotels. The goal is to show how its technology could be deployed in a self-driving car service. "This year is kind of pivoting away from technology demonstrations to really showing the applications," Mr. DeVos said. The convergence of Silicon Valley and the Motor City has helped propel CES, held here every January, into an automotive industry event that rivals the North American International Auto Show, taking place next week in Detroit.
Microsoft arrived on the graph-database scene last month. Already on that scene are Neo4J, MarkLogic, Oracle, SAP and Teradata - among others. Driving Microsoft, like those before, is the desire to connect - to establish connections between things and derive some kind of gain. Those "things" could be people, "likes", online sales – tech firms are almost literally trying connecting the dots or as they like them to be called "nodes." But that's so last year.
Ever since software development progressed from compiler code, there have existed a range of tools to help make developing easier and more effective. A number of projects point in an interesting direction for the sector however. For instance, Amazon recently announced the launch of Cloud 9, an integrated development environment that directly connects to the cloud computing platform provided by the company. It's a strong sign that machine learning is becoming a strong presence in software development on the cloud. Developers using the platform can easily tap into the cloud-based AI baked into the software to create the next generation of apps.
At least, that's what Google Arts & Culture artist-in-residence Mario Klingemann did. He used a neural network called Pix2Pix that tries to anticipate the next frame in a video, and trained it using pairs of consecutive frames from his fireworks videos. Because the algorithm only knows what occurred in the previous frame, it often doesn't work very well. For instance, Klingemann has experimented with this technique before using a video of human motion. Instead of creating a visually interesting movie, it "just became a beige soup," he tells Co.Design in an email.
Search engines are among the most successful applications on the web today. So many search engines have been created that it is difficult for users to know where they are, how to use them, and what topics they best address. Metasearch engines reduce the user burden by dispatching queries to multiple search engines in parallel. Not too surprisingly then, the most successful applications on the web to date are search engines: tools that assist users in finding information on specific topics. The first decision requires reasoning about the available resources and the second about ranking the search engines.
A wide range of sensor-rich, networked embedded systems are being created that must operate robustly for years in the face of novel failures by managing complex autonomic processes. These systems are being composed, for example, into vast networks of space, air, ground, and underwater vehicles. Our objective is to revolutionize the way in which we control these new artifacts by creating reactive model-based programming languages that enable everyday systems to reason intelligently and enable machines to explore other worlds. A model-based program is state and fault aware; it elevates the programming task to specifying intended state evolutions of a system. The program's executive automatically coordinates system interactions to achieve these states, entertaining known and potential failures, using models of its constituents and environment.