Every summer, technologists turn to Gartner's Hype Cycle for Emerging Technologies, which has become a barometer of sorts for gauging the state of various hardware and software innovations that are expected to impact business and society over the next decade. This year, Gartner analysts have their eye on all manner of artificial intelligence technologies, including "smart machines" that can learn by themselves. After relieving "big data" from its hype-cycle duties last year–ostensibly due to the all-encompassing pervasiveness of data in this pervasively digital age–Gartner analysts this year are talking up a swath of related "smart machine" technologies. Together, Gartner refers to these technologies as key enablers of "the perceptual smart machine age" that is currently unfolding. "Smart machine technologies," the analyst group says in a press release, "will be the most disruptive class of technologies over the next 10 years due to radical computational power, near-endless amounts of data, and unprecedented advances in deep neural networks that will allow organizations with smart machine technologies to harness data in order to adapt to new situations and solve problems that no one has encountered previously."

Microsoft announced today that it acquired Genee, an AI-powered scheduling assistant bot that specializes in planning meetings for large groups or when organizers don't have direct access to the calendars of everyone involved. Genee's app is a chatbot accessible via an iPhone app, email, SMS, FB, Twitter or Skype, and it understands natural language input, so you can just text it the kind of event you want to schedule, when you want to happen and who you want to include, and it should theoretically output a proper meeting invite. The standalone service is going to be shut down on September 1, 2016, as a result of the acquisition. It originally debuted in August last year. Genee co-founders Ben Cheung and Charles Lee explained in a blog post announcing the news that easing calendar entries created by the service will still function, but it won't create any new ones or send reminders or agendas related to upcoming events. The team also says they "consider Microsoft to be the leader in personal and enterprise productivity, AI, and virtual assistant technologies," hence their excitement about teaming up with Redmond.

It's been two and a half years since we let Genee out of the bottle. In our drive to deliver large productivity gains through intelligent scheduling coordination and optimization, we often found ourselves on the forefront of technology involving natural language processing, artificial intelligence (AI), and chat bots. We were extremely fortunate to find many who believed in the vision and supported us with their resources, talent, time, and advice along the way, which made Genee possible. Today, we are pleased to announce that Genee has signed an agreement to be acquired by Microsoft. A new beginning means the end of another.

SAN DIEGO, CA--(Marketwired - Aug 15, 2016) - DB Networks, a leader in database cybersecurity, today announced that that it will be exhibiting at the NSA Information Assurance Symposium (IAS) from Aug. 16-18 in Washington, D.C., in booth number 724; and at the CyberTexas Conference from Aug. 23-24 in San Antonio, Texas, in booth number 110. At these upcoming events, DB Networks will hold booth demonstrations of the DBN-6300, an artificial intelligence (AI)-based database security appliance that non-intrusively discovers databases, immediately alerts when databases are under attack and pinpoints credentials that have been compromised. IT security teams are severely understaffed, and presently there's a shortage of more than 200,000 security professionals in the U.S. In addition, security operation centers (SOCs) are deluged with alerts each day and security personnel are able to respond to only a small fraction of the alerts. AI-based security solutions address these issues by being extremely accurate at identifying actual attacks, thus eliminating false positive alerts, and also by alleviating overworked staff from creating and maintaining white lists/black lists. DB Networks is dedicated to protecting mission critical databases through its patented AI technologies that utilize machine learning and behavioral analysis.

Linear Discriminant Analysis (LDA) is most commonly used as dimensionality reduction technique in the pre-processing step for pattern-classification and machine learning applications. The goal is to project a dataset onto a lower-dimensional space with good class-separability in order avoid overfitting ("curse of dimensionality") and also reduce computational costs. Ronald A. Fisher formulated the Linear Discriminant in 1936 (The Use of Multiple Measurements in Taxonomic Problems), and it also has some practical uses as classifier. The original Linear discriminant was described for a 2-class problem, and it was then later generalized as "multi-class Linear Discriminant Analysis" or "Multiple Discriminant Analysis" by C. R. Rao in 1948 (The utilization of multiple measurements in problems of biological classification) The general LDA approach is very similar to a Principal Component Analysis (for more information about the PCA, see the previous article Implementing a Principal Component Analysis (PCA) in Python step by step), but in addition to finding the component axes that maximize the variance of our data (PCA), we are additionally interested in the axes that maximize the separation between multiple classes (LDA). So, in a nutshell, often the goal of an LDA is to project a feature space (a dataset n-dimensional samples) onto a smaller subspace (where) while maintaining the class-discriminatory information.

IP Cores Designed for HSA Historically GPT has developed IP specifically for the China market. The company recently announced a range of new IP licensing offerings along with an enhanced geographical licensing program. With the company-wide adoption of HSA standards, GPT now licenses IP worldwide. All GPT processors include HSA support and the company is now offering world-class HSA-enabled processors to its customers. The HSA enabled IP core which is sampling now in silicon is a first implementation of GPT's 3-in-1 Unity architecture designed for multidimensional signal processing including image and video processing.

Early Bird passes are available until 16 September! Book now to receive a discounted rate on your ticket.

Dataiku, the maker of the all-in-one predictive analytics software platform Dataiku Data Science Studio (DSS), has today announced the release of Dataiku DSS 3.1, which now enables transformations in Apache Spark's Scala, adds additional external integrations, an improved UX interface, and includes 5 machine learning engines in its visual analysis section. Dataiku DSS 3.1 introduces new visual machine learning engines that allow users to create incredibly powerful predictive applications within a code-free interface. Users of all skill levels can now leverage HPE Vertica machine learning, H2O Sparkling Water, MLlib, Scikit-Learn, and XGBoost directly from within the visual analysis section of Dataiku DSS 3.1 to apply powerful machine learning algorithms to their data science projects without having to write a single line of code. The blending of visual code-free and free-form code-based transformations is one of the main strengths of Dataiku DSS for the prototyping and production of data applications. In addition to Python, R, SQL, Hive, Impala, and Pig, Dataiku DSS 3.1 now enables Apache Spark users to write transformations and interactive notebooks in Scala, bringing the power of Spark's native and most performant language to the data teams using Dataiku DSS.

On Friday, one of China's leading tech companies, Cheetah Mobile, announced the 57 million acquisition of New Republic--a move that signals its "journey of a transformation," according to CTO Charles Fan, highlighting its investment in AI and transition into a mobile content company. Founded in 2010, Cheetah Mobile began as a mobile tools provider. Over the last six years, it has become a major player in China's tech scene--and made a big impact, globally. Fan told TechRepublic that the company has over 650,000,000 monthly active users, internationally, in Q1. Fan said he sees the company as a "bridge between China and the world." What makes Cheetah Mobile different, he said, is that 80% of their mobile users are outside of China.

Silicon Valley is full of chatter about artificial intelligence, deep learning neural networks, and machine learning. And Intel, the world's biggest chip maker, is becoming a lot more conversant in that chatter today. Intel executive Diane Bryant announced today that the company is working on a next-generation version of its high-end server chip, the Xeon Phi, for A.I. applications. Baidu will use the upcoming Xeon Phi chips in the data centers it is building for its Deep Speech platform, where its networks will be able to parse natural language speech as quickly and accurately as possible. By 2020, there will be more servers handling data analytics than any other workload, Bryant said.