FREMONT, CA – The rapid growth of automobile technology has enhanced connectivity in modern vehicles. The digital revolution in the automobile industry has made it possible for manufacturers to integrate AI-powered services to improve navigation and functionality of their products. The integration of artificial intelligence (AI) and the internet of things (IoT) has enabled vehicles to communicate with digital devices. However, the integration of complex networks in the connected cars has opened new pathways for hackers, escalating the risk of cyberattacks.

A new type of artificial intelligence has been developed, which is said by its inventors to see like a human. This has been a achieved by building on existing forms of AI and filling in the blanks that have previously limited full visual perception.

The reintroduction of the Artificial Intelligence in Government Act this month is a much needed response to concerns that the United States is lagging behind both foreign governments and American industry in reaping the promise and perils of artificial intelligence. Sponsored by a bipartisan group of senators, the bill promotes the adoption of artificial intelligence in the federal government, while addressing the potential negative consequences. A companion bill was introduced in the House. Central to the bill is the creation of an Artificial Intelligence Center of Excellence within the General Services Administration, which will provide the technical expertise, research, and advice to federal agencies on the acquisition and use of artificial intelligence technology, including all of the accompanying "economic, policy, legal, and ethical challenges and implications." A key part of its mission is to direct and assist the agencies in developing and maintaining governance plans for their use of artificial intelligence.

AMAZON: Has opened an AI-powered convenience store in Seattle. The premise of Amazon Go is simple: to eliminate everyone's least-favorite part of the shopping experience, checking out. With ceiling-mounted sensors and cameras backed by artificial intelligence, Amazon is able to track every interaction a customer has with a product. It knows exactly when a product is picked up or put back. Go works like a physical manifestation of Amazon's 1-Click checkout, where you "click" by taking an item off a shelf.

This PetroTalk was presented at the 2018 Petroleum Engineering Colloquium held August 13–14 in Houston, Texas during Session 1: Data-driven analytics and the concepts of artificial intelligence? Designed to support competency development and knowledge transfer, PetroTalks capture presentations made by academic thought leaders and subject matter experts addressing current and future industry challenges.

In response to the 11 February 2019 US "Executive Order on Maintaining American Leadership in Artificial Intelligence," NIST is requesting information about technical standards and related tools for artificial intelligence during an open comment period ending 31 May. Comments may be submitted via email to ai_standards@nist.gov. More information can be found on the Federal Register. In this article, SPIE/OSA Congressional Fellow Benjamin Isaacoff lays out the goals and gaps of the current US strategy for AI. In February, US President Trump issued an executive order laying out the "American AI Initiative" (AAII).

Artificial intelligence (AI) and its many related applications (ie, big data, deep analytics, machine learning) have entered medicine's "magic bullet" phase. Desperate for a solution for the never-ending challenges of cost, quality, equity, and access, a steady stream of books, articles, and corporate pronouncements makes it seem like health care is on the cusp of an "AI revolution," one that will finally result in high-value care. While AI has been responsible for some stunning advances, particularly in the area of visual pattern recognition,1-3 a major challenge will be in converting AI-derived predictions or recommendations into effective action. The most pressing problem with the US health care system is not a lack of data or analytics but changing the behavior of millions of patients and clinicians. Physician behaviors, including ordering tests, procedures, pharmaceuticals, and other treatments, are responsible for 80% of health care costs.

Governments around the world are under pressure to operate more efficiently, serve citizens better, and provide more satisfying working environments for their employees. Lessons from the private sector show automation at scale has the potential to serve those purposes, but to get there governments must become more strategic in their approach, embrace new technologies, and be prepared to act at scale. Process automation and technologies based on artificial intelligence can bring benefits across numerous functions of government, including much lower operating costs, more efficient processes, and less wastage and errors. McKinsey estimates that as many as four out of five processes in HR, finance, and application processing are at least partially automatable, with the potential to reduce costs by at least 30 percent. The benefits of automation can be achieved relatively quickly.

We are excited to kick off our first Embedded ML workshop - a combination of presentation and ideathon. Firstly, we will talk about the promise of light-weight deep neural networks for energy-efficient and low-cost IoT applications. We discuss some examples of accelerated and low-memory version of deep learning models for real-time use, predictive maintenance, time-series analysis, and demand forecast. We focus on AI methods for turning IoT data into insights and actions. After the introductory talk about Edge AI we will build teams of 3-5 people and have 1.5 hours to come up with project ideas for embedded ML scenarios that include use case, feasibility assessment, workflow, allocation of resources (human, time, computation, ...).

The government has unveiled the membership of its first AI Council as it attempts to position the UK as a leader in the burgeoning sector. The panel includes representatives from Google, Microsoft and Amazon, as well as data protection groups, academia and the public sector. "[Our AI Council will leverage] the knowledge of experts from a range of sectors to provide leadership on the best use and adoption of artificial intelligence across the economy," the digital secretary Jeremy Wright (pictured) will say in a speech at Viva Tech in Paris on Thursday (16 May). "Under the leadership of Tabitha Goldstaub the Council will represent the UK AI Sector on the international stage and help us put in place the right skills and practices to make the most of data-driven technologies." It is expected that the council will eventually draw together a wider group of representatives to address issues facing the UK's AI sector, such as data and ethics, adoption, skills and diversity.