The American Physical Society (APS) has recognized a summer intern at the U.S. Department of Energy's (DOE) Princeton Plasma Physics Laboratory (PPPL) for producing an outstanding research poster at the world-wide APS Division of Plasma Physics (DPP) gathering last October. The student, Marco Miller, a senior at Columbia University majoring in applied physics, used machine learning to accelerate a leading PPPL computer code known as XGC as a participant in the DOE's Summer Undergraduate Laboratory Internship (SULI) program in 2019. The modifications, which will enable the XGC code to calculate more quickly, could help expand the physics included in detailed simulations of the plasma that fuels fusion reactions. The poster, prepared under the mentorship of PPPL physicist Michael Churchill, showed how Miller used machine learning techniques in his research and was presented at the APS-DPP conference in Fort Lauderdale, Florida. "It felt great to get the award," Miller said.
We are in the midst of an unprecedented surge of interest in machine learning (ML) and artificial intelligence (AI) technologies. These tools, which allow computers to make data-derived predictions and automate decisions, have become part of daily life for billions of people. Ubiquitous digital services such as interactive maps, tailored advertisements, and voice-activated personal assistants are likely only the beginning. Some AI advocates even claim that AI's impact will be as profound as "electricity or fire" that it will revolutionize nearly every field of human activity. This enthusiasm has reached international development as well.
HMD Global has announced that its new Nokia 2.3 smartphone is now available for pre-order in the United States. The Android 10 device offers a 6.2″ HD screen and a 13MP/2MP dual camera with a "Recommended Shot" feature that will automatically take a few additional photos before and after the camera shudder is pressed. The feature is supposed to help users select the optimal version of their photo, which is to say that it will recommend the shot in which everyone is smiling and generally looks their best. Other Nokia 2.3 highlights include a dedicated Google Assistant button and a battery that can last for up to two days thanks to its Adaptive Battery technology. The tech uses AI to gain a better understanding of a user's app behavior and optimize the performance of the phone.
As part of an annual look at global AI investment trends, CB Insights today reported that AI startups raised a record $26.6 billion in 2019, spanning more than 2,200 deals worldwide. That's compared to roughly 1,900 deals totaling $22.1 billion in 2018 and about 1,700 deals totaling $16.8 billion in 2017. The reported high recorded by CB Insights in the AI in Numbers report is in line with analysis by other organizations keeping an eye on investment in the AI ecosystem. The National Venture Capital Association earlier this month said that although overall venture capital spending took a dip last year, investors spent a record $18.4 billion on AI startups in the United States in 2019. With investment highest in fields like autonomous driving, drug research, finance, and facial recognition, the AI Index 2019 report released last month found more than $70 billion in global private investment in AI.
You've spent months studying data science, now it's time to find a job in the industry. Fortunately, companies all over the world are looking to hire data scientists -- and fast. According to LinkedIn's 2020 U.S. Emerging Jobs Report, skills related to Machine Learning, Deep Learning, TensorFlow, Python, Natural Language Processing, etc. seen more than 70% annual growth. According to an IBM survey, the openings for data and analytics talent in the US will continue to increase, reaching 133% growth in 2020, and creating more than 700,000 openings. Qualified candidates will have a multitude of vacancies to choose from when ready to seek out a new position in the field.
Casino executives, industry analysts and lawyers attended a conference at the UNLV Boyd School of Law to consult on how biometrics, AI and machine learning could shape the future of Las Vegas casinos, writes the Nevada Independent. While there are many opportunities for the gaming industry, most machine learning and facial recognition-enabled product ideas addressed customer service and customer recognition. These include slot machines that leverage facial biometrics to recognize important or banned players, and reduce fraud attempts, or facial recognition-equipped tables to help pit managers identify and track known players. "What we're seeing is this introduction of technology into the gaming industry in ways we've never seen before, and because of it, it started to raise issues -- or questions -- as to how this works and what the ramifications could be for things like patron privacy, anonymity and data protection," said Anthony Cabot, Distinguished Fellow in Gaming Law at the UNLV Boyd School of Law and event organizer. While speakers focused on presentations about competing laws and technology problems, there was not enough discussion on how to solve these problems, according to the report, yet Cabot hopes the gaming industry and regulators will join forces to deliver solutions.
In this talk, we will take an in-depth look at various mechanisms of attack detection, from signatures and regular expressions to machine learning. Attack detection is critical for most security solutions, whether we are talking about a load balancer-based (NIDS, WAF), host-based or in-application solutions (HIDS, RASP). Interestingly, regardless of the differences in architecture and data flow, most solutions use similar detection principles and techniques. We will explore how the detection architecture evolved over time and how the new generation of detection logic, such as the architecture implemented by some of the advanced application security tools, are principally different from that of the legacy solutions.
Cohort of 14 U.S. and international startups to relocate to Bentonville for 12 weeks PRESS RELEASE – The first-ever Arkansas-based artificial intelligence and machine learning accelerator will launch later this month, with the goal of helping a cohort of startups within these fields connect to regional enterprise partners. The Fuel Accelerator, in its second iteration, will provide regular, hands-on education and workshops to a cohort of 14 companies from across the United States, Europe and Asia. These 14 companies will make their way to Northwest Arkansas, at the foot of the Ozark Mountains, for a 12-week, enterprise-ready accelerator that will provide them with access to other startup founders, industry experts, institutions of higher education, and public policy officials. Fuel launched in late 2018 with eight startups participating in a supply chain-focused, 16-week program. The program helped its first cohort nurture relationships with key Fortune 500 companies through feedback sessions, training, pilots and demos.
A group of high school students was one of the top teams to emerge from the recent AI Tech Sprint by the Department of Veterans Affairs, delivering a web application that could help match cancer patients to clinical trials. The three students from Northern Virginia entered their work in a competition that included software companies like Oracle Healthcare and MyCancerDB. Digital consulting company Composite App took the $20,000 first place prize for its solution -- a tool for helping patients stay on track with their care plan -- but the clinical trials team got an honorable mention. The tech sprint was organized by the VA's new AI institute, and it focused on partnering with outside organizations and companies interested in applying artificial intelligence tools and techniques to VA data. The high school team's members -- Shreeja Kikkisetti, Ethan Ocasio and Neeyanth Kopparapu -- met as part of the Northern Virginia-based nonprofit Girls Computing League.
"We are already at the point where you can't tell the difference between deepfakes and the real thing," Professor Hao Li of the University of Southern California tells the BBC. We are at the computer scientist's deepfake installation at the World Economic Forum in Davos which gives a hint of what he means. Like other deepfake tools, his software creates computer-manipulated videos of people - often politicians or celebrities - that are designed to look real. Most often this involves "face swapping", whereby the face of a celebrity is overlaid onto the likeness of someone else. As I sit, a camera films my face and projects it onto a screen in front of me; my features are then digitally mapped.