Princeton's two-year master in finance programme was established in 1998. It is run within the Bendheim Center for Finance, the university's interdisciplinary research hub. Its typical intake of students is around 30 – deliberately smaller than some larger rivals, says Wendell Collins, programme co-ordinator. Princeton is a small university; so is the programme. There's a customised collegial atmosphere where people really get to know each other: the faculty members, alumni mentors.

Reaching the technological singularity is almost certainly going to involve AI that is able to improve itself. Google may have now taken a small step along this path by creating AI that can build AI. Speaking at the company's annual I/O developer conference, CEO Sundar Pichai announced a project called AutoML that can automate one of the hardest parts of designing deep learning software: choosing the right architecture for a neural network. The Google researchers created a machine learning system that used reinforcement learning--the trial and error approach at the heart of many of Google's most notable AI exploits--to figure out the best architectures to solve language and image recognition tasks. Not only did the results rival or beat the performance of the best human-designed architectures, but the system made some unconventional choices that researchers had previously considered inappropriate for those kinds of tasks.

This paper introduces self-paced task selection to multitask learning, where instances from more closely related tasks are selected in a progression of easier-to-harder tasks, to emulate an effective human education strategy, but applied to multitask machine learning. We develop the mathematical foundation for the approach based on iterative selection of the most appropriate task, learning the task parameters, and updating the shared knowledge, optimizing a new bi-convex loss function. This proposed method applies quite generally, including to multitask feature learning, multitask learning with alternating structure optimization, etc. Results show that in each of the above formulations self-paced (easier-to-harder) task selection outperforms the baseline version of these methods in all the experiments.

In this paper we combine one method for hierarchical reinforcement learning - the options framework - with deep Q-networks (DQNs) through the use of different "option heads" on the policy network, and a supervisory network for choosing between the different options. We utilise our setup to investigate the effects of architectural constraints in subtasks with positive and negative transfer, across a range of network capacities. We empirically show that our augmented DQN has lower sample complexity when simultaneously learning subtasks with negative transfer, without degrading performance when learning subtasks with positive transfer.

Machine learning was the fifth and latest guide. And now I'm back to conclude this series with even more resources. For each of the five major guides in this series, I spent several hours trying to identify every online course for the subject in question, extracting key bits of information from their syllabi and reviews, and compiling their ratings. My goal was to identify the three best courses available for each subject and present them to you. The 13 supplemental topics -- like databases, big data, and general software engineering -- didn't have enough courses to justify full guides. But over the past eight months, I kept track of them as I came across them. I also scoured the internet for courses I may have missed. For these tasks, I turned to none other than the open source Class Central community, and its database of thousands of course ratings and reviews.

Artificial intelligence, augmented reality and virtual reality are here to stay, but what impact will they have on jobs and training? A new study by Pew Research Center and Elon University's Imagining the Internet Center asked more than 1,400 technologists, futurists and scholars whether well-prepared workers be able to keep up in the race with artificial intelligence tools, and what impact this development will have on market capitalism. According to Elon University, most of the experts said they hope to see education and jobs-training ecosystems shift in the next decade to exploit liberal arts-based critical-thinking-driven curriculums; online courses and training amped up by artificial intelligence, augmented reality and virtual reality; and scaled-up apprenticeships and job mentoring. However, some expressed fears that education will not meet new challenges or -- even if it does -- businesses will implement algorithm-driven solutions to replace people in many millions of jobs, leading to a widening of economic divides and capitalism undermining itself. "The vast majority of these experts wrestled with a foundational question: What is special about human beings that cannot be overtaken by robots and artificial intelligence?" said Lee Rainie, director of internet, science and technology research at Pew Research Center and co-author of the report.

Starred articles are candidates for the picture of the week. A comprehensive list of all past resources is found here. We are in the process of automatically categorizing them using indexation and automated tagging algorithms. Check out our previous selection of articles.

As such, it was only natural for them to decide to enroll in the Japanese language and culture course that Makati Science High School has been offering ninth- and 10th-graders over the past few years. "My reason for joining the nihongo (Japanese-language) class was initially for anime. But halfway through, I realized I can use it to be able to experience going to Japan," 16-year-old Franza, who took the elective course for two years starting in 2015, said in a recent interview. Chee, who is a year younger than Franza, said, "One of my life goals (includes) watching anime without subtitles. The Filipino Department of Education started offering the Japanese language and culture program to high school students in 2009, together with Spanish and French, to prepare young Filipinos for both local and international opportunities that would require communicative competence in a second foreign language, after English. Mandarin Chinese and German have subsequently been added. The foreign language programs are offered in selected schools across the country, with Japanese taught in 38 schools, mostly in Manila. So far, more than 3,000 students, nearly all avid viewers of Japanese anime, have enrolled in the Japanese program while in grades nine and 10. "We have to recognize the fact that the globe is getting smaller and smaller," Education Secretary Leonor Briones said of the program's relevance. Many students want to go on to further their studies, both at the undergraduate and graduate levels, and Japan is one of the preferred overseas destinations, given the availability of many scholarships to study there, the secretary said. "So it helps if they take lessons.

Interest in Artificial Intelligence is exploding, and for good reasons. Computers in cars, phone apps, and on the web can do amazing things that we simply could not do before 2012. This is an attempt to explain the current state of AI to a general audience without using mathematics, computer science, or neuroscience; discussions at these levels would focus on how AI works. Here I will discuss this at the level of Epistemology and will try to explain why it works. "Epistemology" sounds scary, but it really isn't. It's mostly scary because it is unknown; it is not taught in schools anymore.

The USC Center for Artificial Intelligence in Society (CAIS)--a joint venture of the USC Suzanne Dworak-Peck School of Social Work and USC Viterbi School of Engineering--will host its first Visiting Fellows Program this summer focused on employing AI to help solve complex societal problems. As part of the Fellows Program, visiting researchers from all over the world will come to USC this summer for up to three months to learn from a working model established by the Center's co-founders, Eric Rice of the USC Suzanne Dworak-Peck School of Social Work and Milind Tambe of the USC Viterbi School of Engineering. The two had successfully collaborated by employing AI to ensure that homeless youth shared important public health information among peers in the youths' own social networks. "Using artificial intelligence to promote the greater good is an emerging area of study with huge potential," said Eric Rice, co-director of CAIS and associate professor at the USC Suzanne Dworak-Peck School of Social Work. "Our goal in establishing this fellowship is to bring together the best and brightest scholars in artificial intelligence and social work to explore breakthrough solutions to age-old problems plaguing many of our cities and communities." Topics to be studied by fellows this summer include suicide prevention among college students; social support for North Korean refugees to help their integration into South Korean society; wildlife conservation through poaching prevention in developing nations' national parks; HIV and substance abuse prevention for homeless youth; and predicting and reducing gang violence in Los Angeles.