Ever wished there was a way to know if your favorite Ben and Jerry's ice cream flavor is currently available in a grocery store near you? Instacart's machine learning team has built tools to figure that out! Our marketplace's scale lets us build sophisticated prediction models. Our community of over 70,000 personal shoppers scans millions of items per day across 15,000 physical stores and delivers them to the customers. These stores belong to our grocery retail partners like Aldi, Costco, Krogers, Safeway, and Wegmans.

Depiction of fusion research on a doughnut-shaped tokamak enhanced by artificial intelligence. Artificial intelligence (AI), a branch of computer science that is transforming scientific inquiry and industry, could now speed the development of safe, clean and virtually limitless fusion energy for generating electricity. A major step in this direction is under way at the U.S. Department of Energy's (DOE) Princeton Plasma Physics Laboratory (PPPL) and Princeton University, where a team of scientists working with a Harvard graduate student is for the first time applying deep learning -- a powerful new version of the machine learning form of AI -- to forecast sudden disruptions that can halt fusion reactions and damage the doughnut-shaped tokamaks that house the reactions. "This research opens a promising new chapter in the effort to bring unlimited energy to Earth," Steve Cowley, director of PPPL, said of the findings (link is external), which are reported in the current issue of Nature magazine. "Artificial intelligence is exploding across the sciences and now it's beginning to contribute to the worldwide quest for fusion power."

The most important aspect of a successful business is the ability to provide a customer experience that exceeds expectations. According to a GrooveHQ Blog Post on customer experience, 86% of customers are willing to pay more for better customer experience. These same customers have a 60%- 70% probability of recommending new customers to your business if they have a great customer experience. As a customer-centric organization, how do you know what makes the best experience for your customers? How do you know what works?

Underline the presenter's name - Affiliation: Provide authors' institutions and addresses. In the case of multiple institutions, identify them by roman numbers - The main body of the abstract should be structured with the following sub-headings: Background, Aim, Methodology, Findings, and Conclusion. It's important to also include the corresponding author's contacts: e-mail and telephone number.

The potential for artificial intelligence to transform health care is huge, but there's a big catch. AI algorithms will need vast amounts of medical data on which to train before machine learning can deliver powerful new ways to spot and understand the cause of disease. That means imagery, genomic information, or electronic health records--all potentially very sensitive information. That's why researchers are working on ways to let AI learn from large amounts of medical data while making it very hard for that data to leak. One promising approach is now getting its first big test at Stanford Medical School in California.

The Paris-Saclay Autonomous Lab project was initiated by Groupe Renault, Groupe Transdev, IRT SystemX, Institut VEDECOM and the University of Paris-Saclay. Its purpose is to develop new autonomous (i.e. The Paris-Saclay Autonomous Lab was inaugurated on 15 May 2019 at the SPRING 2019 innovation event by Grégoire de Lasteyrie, Île-de-France Regional Councillor, Special Delegate responsible for New Mobility and Mayor of Palaiseau; Francisque Vigouroux, Vice-President of the Paris-Saclay urban community responsible for Mobility and Transportation and Mayor of Igny; and Michel Bournat, Mayor of Gif-sur-Yvette and President of the Paris-Saclay urban community. The inauguration ceremony was attended by Thierry Mallet, Chairman and CEO of Groupe Transdev; Arnaud Molinié, Senior Vice President, Mobility Services, Groupe Renault; Paul Labrogere, CEO, IRT SystemX; Sylvie Retailleau, President of the University of Paris-Saclay; Philippe Watteau, Managing Director, VEDECOM; and Elizabeth Crepon, Director, ENSTA. This first stage of the Paris-Saclay Autonomous Lab project is one of the SAM4 experiments selected by the French government on 24 April 2019 following the EVRA5 call for projects under the Investments for the Future (PIA) program.

NEW DELHi: The NITI Aayog has drawn up a plan for creating an institutional framework for artificial intelligence (AI) in the country. It has circulated a cabinet note to provide Rs 7,500 crore in funding for creation of cloud computing platform called AIRAWAT and research institutes. A senior government official told ET that the Aayog has already circulated the note for consideration by the Expenditure Finance Committee, which is expected to take it up soon. The note proposes that the new government pump in Rs 7,500 crore initially over a three-year period and set up a high-level taskforce to oversee roll-out and implementation of AI, the official said on condition of anonymity. "A cabinet note is ready... We would present it to the new government as we want an institutional framework as well as a transparent policy in place for AI," said the official.

Dr. Daniel Stauffacher and Regina Surber of the Zurich Hub for Ethics and Technology (ZHET) participated at the discussion event'Mensch oder Maschine – Wer stellt die Diagnose?, co-organised by the pharmaceutical company Roche and the University ETH in Zurich, on 8 May 2019. One of the firsts of its kind, this very important panel opened the discussion about the transformative change of current and future healthcare through new technologies. Artificial Intelligence (AI) and Robotics are already a given in our modern technological lives. Those technologies – and others – also fundamentally influence the healthcare sector, a fact that raises pressing questions, such as: What is the role of future medical doctors? Which human medical aspects are quantifiable and might therefore be outsourced or supported by, e.g., AI-enabled technologies, and which are not, and will still require human power and discernment? The panel was moderated by Marina Villa, SRF.

There's great potential in using both drones and ground-based robots for situations like disaster response, but generally these platforms either fly or creep along the ground. Not the "Flying STAR," which does both quite well, and through a mechanism so clever and simple you'll wish you'd thought of it. Conceived by researchers at Ben-Gurion University in Israel, the "flying sprawl-tuned autonomous robot" is based on the elementary observation that both rotors and wheels spin. So why shouldn't a vehicle have both? Well, there are lots of good reasons why it's difficult to create such a hybrid, but the team, led by David Zarrouk, overcame them with the help of today's high-powered, lightweight drone components.

As San Francisco moves to regulate the use of facial recognition systems, we reflect on some of the many'faces' of the fast-growing technology Last week, San Francisco became the first city in the United States to ban the use of facial recognition technology, at least by law enforcement, local agencies, and the city's transport authority. My immediate reaction to the headlines was that this was great for individuals' privacy, a truly bold decision by the San Francisco board of supervisors. The ordinance actually covers more than just facial recognition, as it states the following: "'Surveillance Technology' means any software, electronic device, system utilizing an electronic device, or similar device used, designed, or primarily intended to collect, retain, process, or share audio, electronic, visual, location, thermal, biometric, olfactory or similar information specifically associated with, or capable of being associated with, any individual or group.". The ban excludes San Francisco's airport and sea port as these are operated by federal agencies. Nor does it mean that no individual, company or other organizations installing surveillance systems that include facial recognition, and the agencies banned from using the technology, can cooperate with the people allowed to use it.