The Classy Ivanka Trump joined Suzette Kent and Kelvin Droegemeier yesterday for the White House AI Summit. Ivanka Trump spoke about the need for American AI Leadership, development of AI workforce skills and Governmental wide AI initiatives. Lt. Gen Jack Shanahan spoke about the Department of Defense's Joint AI Center. "2020 is the year of AI for the department of defense, yet we have a long way to go" said Shanahan. The need to understand what AI is, and the threats the U.S faces from China's AI Weaponization goals are increasing day by day.

Artificial intelligence took center stage as African female technology experts met at Women in Tech Week in Ghana to promote women's involvement in the field. When Lily Edinam Botsyoe was studying computer science at a university in Ghana, students wrote programming codes on a whiteboard because there were not enough computers. This made it difficult to apply the coding skills they were learning, she says, and the problem continues today. "We have students coming out of schools having the theoretical background -- which is very important because you can't actually appreciate something practical if you don't have the theory. But, the industry-ready skills is lacking because they didn't have the hands-on experience," Botsyoe said.

Why it matters: Companies can use this data to juice workers' productivity and efficiency. Eventually, they could gather enough data from humans to train machines to mimic them." How often is an employee going out to smoke a cigarette? How long are they sitting in the lunchroom?" These are the questions clients want answered with AI software, says Kim Hartman, CEO of Surveillance Secure, a D.C.-area company that installs security systems.

We live in an age of increasing centralization that pervades all aspects of our culture. In today's world, centralization equates to control; centralization equates to power. Centralization gave rise to bureaucratic institutions where decisions, borne by a few, ran through a hierarchical structure. This ensured a system where one authority determined how systems were run and how objectives were met. This is symbolic of how authoritarian governments operate.

Actor and equality campaigner Geena Davis has announced that Disney has adopted a digital tool that will analyse scripts and identify opportunities to rectify any gender and ethnic biases. Davis, founder of the Geena Davis Institute on Gender in Media, was speaking at the Power of Inclusion event in New Zealand, where she outlined the development of GD-IQ: Spellcheck for Bias, a machine learning tool described as "an intervention tool to infuse diversity and inclusion in entertainment and media". Developed by the University of Southern California Viterbi School of Engineering, the Spellcheck for Bias is designed to analyse a script and determine the percentages of characters' "gender, race, LGBTQIA [and] disabilities". It can also track the percentage of "non-gender-defined speaking characters". Davis said that Disney had partnered with her institute to pilot the project: "We're going to collaborate with Disney over the next year using this tool to help their decision-making [and] identify opportunities to increase diversity and inclusion in the manuscripts that they receive. We're very excited about the possibilities with this new technology and we encourage everybody to get in touch with us and give it a try."

Researchers have created an AI model that analyses the citations of studies, predicting their potential for eventual clinical application. Researchers have developed an artificial intelligence (AI) model that can predict which scientific discoveries are more likely to translate to the clinic. The study was conducted by researchers from the Office of Portfolio Analysis (OPA), part of the US National Institutes of Health (NIH). The team say that their aim is to decrease the long interval between scientific discovery and clinical application. The new process determines the likelihood that a research article will be cited by a future clinical trial or guideline.

Business use of AI grew 270% over the past four years, according to Gartner, while Deloitte says 62% of respondents to its corporate October 2018 report deployed some form of AI. That's up 53% from a year ago, but what we've learned is that adoption doesn't equal success, and success is an evolving model in this phase of our digital revolution. Unfortunately, roughly 25% of companies have seen half of their AI projects fail. Failure, in heavily technical deployments, like AI projects, is incredibly expensive when data scientist and other team time, technical cost of computation, and resources wasted is accounted for. Statistics like these have generated tremendous buzz around the end results: success or failure, but we've reached a pivot point where we must widen our lens and shift our attention.

Newswire) GBT Technologies Inc. (OTCPINK: GTCH) ("GBT", or the "Company"), a company specializing in the development of Internet of Things (IoT) and Artificial Intelligence (AI) enabled networking and tracking technologies, including its GopherInsight wireless mesh network technology platform for both mobile and fixed solutions, announced that it is now implementing a new approach within its intelligent agent, recurrent relational reasoning (RRN). The new set of algorithms enables GBT's AI system to explicitly consider relations between objects (Static, moving), or abstract ideas. The RRN methodology will be implemented within Avant! AI within the next months, enabling it with logic analysis boost to handle vast information and data interpretation complexity. One of the key reasons for implementing this new method is to achieve outstanding image-based reasoning tasks for Avant!

National Crime Records Bureau (NCRB) under the Government of India has released a tender asking for bidders to help create Automated Facial Recognition System (AFRS). The objective is to leverage the power of facial recognition technology to make the security forces more efficient. The technology system which has been proposed will make an extensive database of photos belonging to Indian citizens using which machine learning models will be trained. The criminals will be identified using CCTV footage from the database, verified, and information will be distributed to all law enforcement agencies in real-time across the country. Experts have touted that using facial recognition technology to identify and solve crime may be one of the best applications of the technology.

Facebook today released the latest version of its deep learning library PyTorch with quantization and Google Cloud TPU support for speedier training of machine learning models. Tensor processing unit support begins with the ability to train a model with a single chip and will later be extended to Cloud Pods, Facebook CTO Mike Schroepfer said today. Also new today are PyTorch Mobile for deployment of ML on edge devices starting with Android and iOS devices; CryptTen, a tool for encrypted machine learning; and Captum, a tool for explainability of machine learning models. The news is being announced at the PyTorch Developer Conference today at The Midway in San Francisco. Available today, PyTorch 1.3 comes with the ability to quantize a model for inference on to either server or mobile devices.