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You may not have heard of OpenSCG, but Amazon Web Services has. A week ago, AWS quietly acquired the PostgreSQL migration services company founded by PostgreSQL veteran Denis Lussier. While some PostgreSQL fans weren’t happy about the move, the OpenSCG acquisition is emblematic of a much larger move by AWS to serve a wide array of database needs.
AI and machine learning are going to start making a lot more decisions. They probably still won’t be used in the near future to make “big” decisions like whether to put a 25 percent tariff on a commodity and start a trade war with a partner.
However, nearly anything you’ve stuck in Excel and massaged, coded, or sorted is a good clustering, classification, or learning-to-rank problem. Anything that is a set of values that can be predicted is a good machine learning problem. Anything that is a pattern or shape or object that you just go through and ”look for” is a good deep learning problem.
Through the power of deep and machine learning, faster CPUs, and new types of sensors, computers can now see, hear, feel, smell, taste, and speak. All these senses take the form of some kind of sensor (like a camera) and some kind of mathematical algorithm, usually a supervised machine learning algorithm and a model.
Here is what is available.[ Go deep into machine learning at InfoWorld: 11 must-have machine learning tools. • 13 frameworks for mastering machine learning • Machine learning pipelines demystified • Review: 6 machine learning clouds • Which Spark machine learning API should you use? ] See: image and facial recognition
Recent research into image and facial recognition lets computers not only detect object presence but detect multiple instances of similar objects. Facebook and Google have really been leading the way here, with multiple open source releases. Facebook has stated that it has a goal of detecting things in video.
The Eclipse Foundation’s enterprise Java platform will be called Jakarta EE, which was the favorite of voters in a recent poll.
With 6,959 responses tallied, Jakarta pulled in 64.4 percent of the votes, far exceeding the other choice, Enterprise Profile. A new name had to be chosen because Java EE (Enterprise Edition), the longstanding name of the platform, remains an Oracle trademark.[ The new Java versions are here! Learn everything you need to know about what’s new in Java SE 9 and what’s new in Java EE 8. | Keep up with hot topics in programming with InfoWorld’s App Dev Report newsletter. ]
Permission to use the Jakarta EE trademark will be contingent upon technologies passing a compatibility program, which has yet to be developed. The program will be run by EE.Next, Eclipse’s working group for enterprise Java.
The Eclipse Foundation is preparing the next round of technologies to be added to enterprise Java, which it now runs. (Last year, the foundation was charged with developing Java EE (Enterprise Edition), in the wake of Oracle’s abdication of its stewardship of the project.)
Eclipse expects about 35 to 40 new projects as part of its open source enterprise Java implementation.
The foundation expects Eclipse Enterprise for Java (EE4J) project to ship a Java EE 8-compliant project as soon as possible, with a release of the GlassFish application server and related projects. GlassFish has served as a reference implementation of enterprise Java. Java EE 8 has been set as the baseline for Eclipse’s development of new enterprise Java standards.
If you looked at TensorFlow as a deep learning framework last year and decided that it was too hard or too immature to use, it might be time to give it another look.
Until very recently, when you shopped for a database you had to choose: Scalability or consistency? SQL databases such as MySQL guarantee strong consistency, but don’t scale well horizontally. (Manual sharding for scalability is no one’s idea of fun.) NoSQL databases such as MongoDB scale beautifully, but offer only eventual consistency. (“Wait long enough, and you can read the right answer”—which isn’t any way to do financial transactions.)