AI is being built into more systems and software as organizations attempt to compete in the algorithmic age. With the level of machine intelligence reaching new heights, the number of experts is not growing proportionally. To compensate, AI libraries, APIs, systems and software are becoming easier to use so more people can take advantage of them. However, ease of use does not necessarily diminish risks. At present, there's no minimum competence level one must have to operate an AI system, except perhaps data scientists with graduate degrees in math, statistics or computer science who use the most sophisticated tools.

Antoinette Ellis's five-year-old daughter, Zariah, already knows what she wants to be when she grows up. Her main gig will be scientist, but she plans on earning extra income as an opera singer and a part-time DJ. This future may not sound particularly realistic, but Ellis is nonetheless doing all she can to foster her daughter's interests. Zariah watches videos of opera singers, she's taking music lessons and she's often conducting little experiments, as she did this past summer, when she planted strawberries and vegetables in her grandfather's backyard. Whether Zariah ultimately becomes a multi-talented scientist-entertainer remains to be seen, but Ellis is confident she'll succeed at whatever she chooses to do.

September 05, 2019: The Central Board of Secondary Education (CBSE) has announced that it will conduct Capacity Building Programs for high school teachers in association with Microsoft India with an aim to integrate cloud-powered technology in K12 teaching. Meant for teachers of grades 8-10, the program will be conducted in 10 cities across the country, starting September 11, 2019. AI and intelligent technologies are becoming all-pervasive today, transforming organizations across sectors and redefining the way we work. To equip the workforce of tomorrow, it is critical to the ramp up the institutional set-up and build capability among educators as well as integrate advanced technologies into the teaching process. This program will provide teachers better access to the latest Information and Communication Technology (ICT) tools and help them to integrate technology into teaching in a safe and secure manner, thereby enhancing the learning experience and 21st century skills of all students.

Andrew Yan-Tak Ng (Chinese: 吳恩達; born 1976) is a Chinese-American computer scientist and statistician, focusing on machine learning and AI. Also a business executive and investor in the Silicon Valley, Ng co-founded and led Google Brain and was a former Vice President and Chief Scientist at Baidu, building the company's Artificial Intelligence Group into a team of several thousand people. Ng is an adjunct professor at Stanford University (formerly associate professor and Director of its AI Lab). Also a pioneer in online education, Ng co-founded Coursera and deeplearning.ai. With his online courses, he has successfully spearheaded many efforts to "democratize deep learning."

It was written as an advanced text to serve as a basis for a graduate course, and/or as a reference to the researcher diving into this fascinating world at the intersection of optimization and machine learning. Such a course was given at the Technion in the years 2010-2014 with slight variations from year to year, and later at Princeton University in the years 2015-2016. The core material in these courses is fully covered in this book, along with exercises that allow the students to complete parts of proofs, or that were found illuminating and thought-provoking. Most of the material is given with examples of applications, which are interlaced throughout different topics. These include prediction from expert advice, portfolio selection, matrix completion and recommendation systems, SVM training and more.

Most research on lifelong learning (LLL) applies to images or games, but not language. Here, we introduce LAMAL, a simple yet effective method for LLL based on language modeling. LAMAL replays pseudo samples of previous tasks while requiring no extra memory or model capacity. To be specific, LAMAL is a language model learning to solve the task and generate training samples at the same time. At the beginning of training a new task, the model generates some pseudo samples of previous tasks to train alongside the data of the new task. The results show that LAMAL prevents catastrophic forgetting without any sign of intransigence and can solve up to five very different language tasks sequentially with only one model. Overall, LAMAL outperforms previous methods by a considerable margin and is only 2-3\% worse than multitasking which is usually considered as the upper bound of LLL. Our source code is available at https://github.com/xxx.

This paper investigates trajectory tracking problem for a class of underactuated autonomous underwater vehicles (AUVs) with unknown dynamics and constrained inputs. Different from existing policy gradient methods which employ single actor-critic but cannot realize satisfactory tracking control accuracy and stable learning, our proposed algorithm can achieve high-level tracking control accuracy of AUVs and stable learning by applying a hybrid actors-critics architecture, where multiple actors and critics are trained to learn a deterministic policy and action-value function, respectively. Specifically, for the critics, the expected absolute Bellman error based updating rule is used to choose the worst critic to be updated in each time step. Subsequently, to calculate the loss function with more accurate target value for the chosen critic, Pseudo Q-learning, which uses sub-greedy policy to replace the greedy policy in Q-learning, is developed for continuous action spaces, and Multi Pseudo Q-learning (MPQ) is proposed to reduce the overestimation of action-value function and to stabilize the learning. As for the actors, deterministic policy gradient is applied to update the weights, and the final learned policy is defined as the average of all actors to avoid large but bad updates. Moreover, the stability analysis of the learning is given qualitatively. The effectiveness and generality of the proposed MPQ-based Deterministic Policy Gradient (MPQ-DPG) algorithm are verified by the application on AUV with two different reference trajectories. And the results demonstrate high-level tracking control accuracy and stable learning of MPQ-DPG. Besides, the results also validate that increasing the number of the actors and critics will further improve the performance.

Press Release – BOULDER, CO – September 6, 2019 – YWCA Boulder County, one of the first two YWCA branches in the country to be awarded a grant by Google to increase black and Latina students' access to computer science and artificial intelligence education, has announced a Google JAM session series to kick off the organization's STEM E3 program. Three JAM sessions will be offered from 1– 6 p.m. at Google with the first session scheduled for September 16, 2019 (followed by sessions on October 14, 2019 and November 11, 2019). The program will provide an opportunity for young women of color between the ages of 9 to 14 to be introduced to a STEM E3 (Education, Employment and Entrepreneurship) program, which works with young women and girls in science, technology, engineering, and math (STEM). YWCA STEM E3 curriculum helps young women and girls of color build the confidence and skills required for future careers in computer science and artificial intelligence. "We're thrilled to have been chosen as one of two YWCAs in the country to launch the pilot STEM E3 program," said Debbie Pope, CEO of YWCA Boulder County.

"(AI) will rank among our greatest technological achievements, and everyone deserves to play a role in shaping it." Encompassing all facets of AI, the General Secretariat of MONTREAL.AI introduces, with authority and insider knowledge: "Artificial Intelligence 101: The First World-Class Overview of AI for the General Public". AI opens up a world of new possibilities. This AI 101 tutorial harnesses the fundamentals of artificial intelligence for the purpose of providing participants with powerful AI tools to learn, deploy and scale AI. Theoretical Physics in 1 (one) year, followed by a Master's degree in Government Policy Analysis (1998) and a Master's degree in Aerospace Engineering (Space Technology) (2000).

A yearbook is a type of a book published annually to record, highlight, and commemorate the past year of a school. Our team at MyHeritage took on a complex project: extracting individual pictures, names, and ages from hundreds of thousands of yearbooks, structuring the data, and creating a searchable index that covers the majority of US schools between the years 1890–1979 -- more than 290 million individuals. In this article I'll describe what problems we encountered during this project and how we solved them. First of all, let me explain why we needed to tackle this challenge. MyHeritage is a genealogy platform that provides access to almost 10 billion historical records.