Lifeboat Foundation

A year after announcing an aggressive plan to dominate artificial intelligence, China’s vice premier has called for international collaboration.

Surging productivity and the general rise in incomes it brings would be welcome, of course, but that isn’t sufficient. The same questions being raised about the advance of robotics in the workplace apply to machine learning. While new jobs would be created, many existing jobs — from doctors and financial advisers to translators and call-center operators — are susceptible to displacement or much-reduced roles. No economic law guarantees that productivity growth benefits everyone equally. Unless we thoughtfully manage the transition, some people, even a majority, are vulnerable to being left behind even as others reap billions.

Whether it’s for the better and for the many is up to human intelligence.

SAN FRANCISCO — Orbital Insight, a Silicon Valley geospatial analytics company, announced the purchase Sept. 18 of FeatureX, a Boston-based artificial intelligence firm specializing in computer vision for satellite imagery. The terms of the purchase were not disclosed.

It was the first acquisition made by Orbital Insight, a firm that has raised $78.7 million to date, including $50 million in a Series C funding round completed in May 2017.

FeatureX founder Gil Syswerda will join Orbital Insight as its technology research vice president, working in the company’s Boston office. FeatureX specializes in applying computer vision to satellite imagery to detect objects, enhance images and facilitate deep learning.

Recently, there has been an explosion of interest in applying artificial intelligence (AI) to medicine. Whether explicitly or implicitly, much of this interest has centered on using AI to automate decision-making tasks that are currently done by physicians. This includes two seminal papers in the Journal of the American Medical Association demonstrating that AI-based algorithms have similar or higher accuracy than physicians: one in diagnostic assessment of metastatic breast cancer compared to pathologists and the other in detecting diabetic retinopathy compared to ophthalmologists.

While promising, these applications of AI in medicine raise a number of novel regulatory and policy issues around efficacy, safety, health workforce, and payment. They have also triggered concerns from the medical and patient communities about AI replacing doctors. And, except in narrow domains of practice, general AI systems may fall far short of the hype.

We posit that the applications of AI to “augment” physicians may be more realistic and broader reaching than those that portend to replace existing health care services. In particular, with the right support from policy makers, physicians, patients, and the technology community, we see opportunities for AI to be a solution for—rather than a contributor to—burnout among physicians and achieving the quadruple aim of improving health, enhancing the experience of care, reducing cost, and attaining joy in work for health professionals.

Alphabet’s healthcare and tech company Verily will use a sex-sorting computer vision algorithm to help Singapore battle mosquitoes.

Over its 60-year history, DARPA has played a leading role in the creation and advancement of artificial intelligence (AI) technologies that have produced game-changing capabilities for the Department of Defense. Starting in the 1960s, DARPA research shaped the first wave of AI technologies, which focused on handcrafted knowledge, or rule-based systems capable of narrowly defined tasks. While a critical step forward for the field, these systems were fragile and limited. Starting in the 1990s, DARPA helped usher in a second wave of AI machine learning technologies that created statistical pattern recognizers from large amounts of data. The agency’s funding of natural language understanding, problem solving, navigation and perception technologies has led to the creation of self-driving cars, personal assistants, and near-natural prosthetics, in addition to a myriad of critical and valuable military and commercial applications. However, these second wave AI technologies are dependent on large amounts of high quality training data, do not adapt to changing conditions, offer limited performance guarantees, and are unable to provide users with explanations of their results.

To address the limitations of these first and second wave AI technologies, DARPA seeks to explore new theories and applications that could make it possible for machines to adapt to changing situations. DARPA sees this next generation of AI as a third wave of technological advance, one of contextual adaptation. To better define a path forward, DARPA is announcing today a multi-year investment of more than $2 billion in new and existing programs called the “AI Next” campaign. Agency director, Dr. Steven Walker, officially unveiled the large-scale effort during closing remarks today at DARPA’s D60 Symposium taking place Wednesday through Friday at the Gaylord Resort and Convention Center in National Harbor, Maryland.

“With AI Next, we are making multiple research investments aimed at transforming computers from specialized tools to partners in problem-solving,” said Dr. Walker. “Today, machines lack contextual reasoning capabilities, and their training must cover every eventuality, which is not only costly, but ultimately impossible. We want to explore how machines can acquire human-like communication and reasoning capabilities, with the ability to recognize new situations and environments and adapt to them.”

By tapping robotic and sensor technologies, a small free-flying spacecraft is being demonstrated to autonomously investigate lava tubes on the Moon.

Astrobotic Technology of Pittsburgh, Pennsylvania is partnering with scientists from the RIS4E node of NASA’s Solar System Exploration Research Virtual Institute (SSERVI), led by Stony Brook University.

If your truck is completely autonomous, why would you need a cab? Volvo Trucks believes that you don’t and that’s why they built a new all-electric and autonomous truck without a cab called Vera.

Claes Nilsson, President of Volvo Trucks, the idea behind Vera:

“The full potential of the transport industry is yet to be seen. Everything suggests that the global need for transportation will continue to significantly increase in the coming decade. If we are to meet this demand in a sustainable and efficient way, we must find new solutions. In order to secure a smoothly functioning goods flow system we also need to exploit existing infrastructure better than currently. The transport system we are developing can be an important complement to today’s solutions and can help meet many of the challenges faced by society, transport companies and transport buyers,”

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