Allegheny County


Powerful antibiotics discovered using AI

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A pioneering machine-learning approach has identified powerful new types of antibiotic from a pool of more than 100 million molecules -- including one that works against a wide range of bacteria, including tuberculosis and strains considered untreatable. The researchers say the antibiotic, called halicin, is the first discovered with artificial intelligence (AI). Although AI has been used to aid parts of the antibiotic-discovery process before, they say that this is the first time it has identified completely new kinds of antibiotic from scratch, without using any previous human assumptions. The work, led by synthetic biologist Jim Collins at the Massachusetts Institute of Technology in Cambridge, is published in Cell1. The study is remarkable, says Jacob Durrant, a computational biologist at the University of Pittsburgh, Pennsylvania.


These are the top 15 emerging jobs of 2020, according to LinkedIn

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LinkedIn also notes that Washington DC and the surrounding metros are attracting new tech talent, including cybersecurity, data science, and artificial intelligence experts, "nearly in line" with the major tech hubs of San Francisco and New York. And mid-size US metros such as Austin, Texas, Raleigh-Durham, North Carolina, and Pittsburgh, Pennsylvania, are continuing to attract tech talent thanks in part to lower costs of living and increased remote-work opportunities.


A trash talking robot hurling 'mild insults' was able to put humans off their stride

Daily Mail - Science & tech

Trash talk has been part of sport and human competition for as long as people have been competitive, but now robots are getting in on the game. Researchers from Carnegie Mellon University, in Pittsburgh, Pennsylvania, programmed a robot called Pepper to use mild insults such as'you are a terrible player' and'your playing has become confused'. It would then use these insults while challenging a human to a game called'Guards and Treasures' that is designed to test rationality. Even though the robot used very mild language, the human player's performance got worse while they were being insulted, according to lead author Aaron M. Roth. The team say tests like this could help work out how humans will respond in future if a robot assistant disagrees with a command, such as over whether to buy healthy or unhealthy food.


PGH Lab Program for Local Startups Announces Fifth Cohort

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PITTSBURGH, PA (November 7, 2019) Mayor William Peduto, the City of Pittsburgh Department of Innovation & Performance, the Urban Redevelopment Authority of Pittsburgh, the Housing Authority of the City of Pittsburgh, and Allegheny County Airport Authority today announced the fifth cohort of the PGH Lab program. PGH Lab connects local startup companies with the City of Pittsburgh and local authorities, and independent institutions to explore new ways to use technology and innovative solutions to help improve city operations. The program provides an opportunity for local startups to test their beta-stage products and services in a real-world environment for three-four months. The City of Pittsburgh and the participating authorities have successfully completed four cycles and engaged 21 local startups, putting forth a variety of technological and innovative solutions ranging from waste management and composting to business processes and automation to immigrant inclusion initiatives. For the fifth cycle, three different startups will be joining PGH Lab.


Being Optimistic to Be Conservative: Quickly Learning a CVaR Policy

arXiv.org Artificial Intelligence

Being Optimistic to Be Conservative: Quickly Learning a CV aR Policy Ramtin Keramati 1, Christoph Dann 2, Alex T amkin 3, Emma Brunskill 3 1 Institute of Computational and Mathematical Engineering (ICME), Stanford University, California, USA 2 Machine Learning Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA 3 Department of Computer Science, Stanford University, California, USA {keramati,atamkin,ebrun } @cs.stanford.edu Abstract While maximizing expected return is the goal in most reinforcement learning approaches, risk-sensitive objectives such as conditional value at risk (CV aR) are more suitable for many high-stakes applications. However, relatively little is known about how to explore to quickly learn policies with good CV aR. In this paper, we present the first algorithm for sample-efficient learning of CV aR-optimal policies in Markov decision processes based on the optimism in the face of uncertainty principle. This method relies on a novel optimistic version of the distributional Bellman operator that moves probability mass from the lower to the upper tail of the return distribution. We prove asymptotic convergence and optimism of this operator for the tabular policy evaluation case. We further demonstrate that our algorithm finds CV aR-optimal policies substantially faster than existing baselines in several simulated environments with discrete and continuous state spaces. Introduction A key goal in reinforcement learning (RL) is to quickly learn to make good decisions by interacting with an environment. In most cases the quality of the decision policy is evaluated with respect to its expected (discounted) sum of rewards. However, in many interesting cases, it is important to consider the full distributions over the potential sum of rewards, and the desired objective may be a risk-sensitive measure of this distribution. For example, a patient undergoing a surgery for a knee replacement will (hopefully) only experience that procedure once or twice, and may will be interested in the distribution of potential results for a single procedure, rather than what may happen on average if he or she were to undertake that procedure hundreds of time. Finance and (machine) control are other cases where interest in risk-sensitive outcomes are common. A popular risk-sensitive measure of a distribution of outcomes is the Conditional V alue at Risk (CV aR) (Artzner et al. 1999). Intuitively, CV aR is the expected reward in the worst α -fraction of outcomes, and has seen extensive use in financial portfolio optimization (Zhu and Fukushima 2009), often under the name "expected shortfall".


Students use Google Assistant to create a voice-activated robot that makes grilled cheese toasties

Daily Mail - Science & tech

A voice-controlled robot that can make you perfect grilled cheese sandwiches on demand has been created by a team of students in the US. 'Cheesborg' is the brainchild of engineer Tayor Tabb, 24, and colleagues, who created the toastie maker at Carnegie Mellon University in Pittsburgh, Pennsylvania. The process begins with a voice command to a connected Google Home smart assistant. The cheesy contraption uses a vacuum to begin to assemble the sandwich -- loading two slices of bread and one slice of cheese onto its conveyor belt. Next, the conveyor moves the ingredients into a sandwich press and closes the lid ready for grilling.


Machine Learning Research Intern ai-jobs.net

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The Bosch Research and Technology Center North America with offices in Palo Alto, California, Pittsburgh, Pennsylvania and Cambridge, Massachusetts is part of the global Bosch Group (www.bosch.com), The Research and Technology Center North America (RTC-NA) is committed to providing technologies and system solutions for various Bosch business fields primarily in the areas of Human Machine Interaction (HMI), Robotics, Energy Technologies, Internet Technologies, Circuit Design, Semiconductors and Wireless, and MEMS Advanced Design.


Unbabel opens New AI Office in Pittsburgh

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Unbabel announces the opening of a new office in Pittsburgh, PA, USA, one of the world's most active hubs of Machine Translation and Natural Language Processing research and applied technology Led by Alon Lavie, VP of Language Technologies and an adjunct professor at the Language Technologies Institute at Carnegie Mellon University (CMU), the new office location aims to leverage the long-term ties and strong relationship between Unbabel and the university. Lavie believes that core Machine Translation technology has improved significantly in the past several years and that Unbabel's Customer Service Solution is a fantastic use case for it. "With multinational companies boasting customer bases throughout the world, the opportunity to use Machine Translation coupled with human feedback to provide a better level of customer support is exactly what we should be doing with the latest core technology," he added. Unbabel has already hired two Research Scientists and a Research Engineer to join the new team. Unbabel is recruiting for the office and has two full-time vacancies in Pittsburgh, one for Senior Research Engineer and another for a Senior Research Scientist.


Forget the porch. Walmart will deliver groceries right to your fridge starting this fall

USATODAY - Tech Top Stories

Walmart employees will start delivering groceries right to a customer's refrigerator in three cities this fall. Starting this fall, Walmart customers can not only buy groceries online, they can then have them dropped off right in their kitchen. More than 1 million shoppers in Kansas City, Mo., Vero Beach, Fl, and Pittsburgh, Pa. will be able to use Walmart's new "InHome'' service, the latest volley in the delivery wars being waged by retailers racing to woo customers with convenience and speed. Walmart employees will first pick the produce or other household items, ordered by a shopper online. They will then deliver food items into the customer's refrigerator, using smart technology that enables the homeowner to let them in and watch what they do while they're there "Once we learned how to do pickup well, we knew it would unlock the ability to deliver,'' Doug McMillon, Walmart's president and CEO, said in a statement.


New AI Research Hub to Leverage Artificial Intelligence to Tackle Major Military Challenges

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The U.S. Army Artificial Intelligence (AI) Task Force was inaugurated when Commander General John Murray applied the U.S. Army Futures Command (AFC) patch to the left arm of Brigadier General Matthew Easley's uniform with a hearty slap. Easley is now officially in charge of the new taskforce. In close collaboration with Carnegie Mellon University (CMU), the U.S. Army has also established the first AI Hub to be located in Pittsburgh, Pennsylvania and Carnegie Mellon's National Robotics Engineering Center. A key role of the AI Hub will be to increase collaboration with ANSYS and other academic, industry and government agency partners. The Army AI Taskforce will be focused on developing and prototyping AI capabilities for several critical areas of the Army -- including an on-going project focused on predictive maintenance.