It would be almost impossible now to put the brakes on the enthusiasm generated by artificial intelligence (AI) within the health care industry. The global market for AI in health care stood at $1.3 billion in 2018, but it is expected to grow to $13 billion by 2025 and see a CAGR growth rate of 40.6% from 2019-2025. As the CEO of a company that provides computer vision and image processing R&D, we make our living off the fact that the possibilities of machine learning and AI in technology are limitless. So, naturally, this optimism extends to the health care industry. The overarching reason is the exponential explosion of data.

Of course, I'm kidding, how can anybody get sick of dog pictures on Facebook? Nvidia's research teams have been doing some pretty crazy stuff with AI the last few years. This latest one is pretty funny from an amusement level standpoint but quite groundbreaking from a technical one. It's a challenging task for computers, although it has been done in the past. Previously, though, it required many images in order to make it work.

The artificial intelligence industry has skyrocketed in recent years, powering technologies behind smart speakers and self-driving cars, but that growth is coming at a cost. Researchers at the University of Massachusetts Amherst recently conducted a study assessing the energy consumption required to train several common large AI models. The study revealed that the training process can emit over 626,000 pounds of carbon dioxide, nearly 5x the lifetime emissions of an average car, or the equivalent of about 300 round-trip flights between New York and San Francisco. The benefits from the advancements in AI and other emerging technologies at the expense of the environment are simply not worth it, say many industry experts who are urging big tech companies to ramp up their sustainability efforts. Failing to do so could leave the companies' reputations at risk, they said.

A section of the DNA fragmentation profile of cell-free DNA from a cancer patient plotted over a healthy profile. Imagine, taking a simple blood draw to find out if you have cancer, and if so, the cancer's location and molecular type. While this scenario may have sounded like science fiction not long ago, liquid biopsies are now an exciting, tangible, area of cancer research. I spoke with two researchers who have developed an approach to detect cancer from cell-free DNA by looking at DNA fragmentation: Robert B. Scharpf, PhD, associate professor of oncology at the Sidney Kimmel Cancer Center and Biostatistics at the Johns Hopkins Bloomberg School of Public Health and Victor E. Velculescu, MD, PhD, professor of oncology, pathology, and medicine at the Johns Hopkins University School of Medicine. Their study, published in Nature earlier this year, demonstrates the feasibility of liquid biopsies using DNA fragmentation profiles.

The XTRD team will take part in AI & Emerging Tech for Finance conference that will be held by Corinium on November 12–13 2019, in Convene at 101 Greenwich, New York City. The theme of the conference is "Embracing the Machines: The Future of Emerging Technologies for Finance". Participating in this event will allow the XTRD team to meet senior leaders and decision-makers from industry leading organizations, and broaden our professional networking in general. Corinium is the world's largest community designed to inspire and support the emerging C-Suite executives focused on Data, Analytics, Customer and Digital Innovation. They produce industry leading conferences like Chief Data & Analytics Officer Fall, Chief Data & Analytics Officer Spring, Chief Data & Analytics Officer Finance and others.

Massachusetts Institute of Technology and Stanford University researchers recently found that three commercial facial analysis programs were producing different results for different skin types and gender. They found that error rates for determining the gender of light-skinned men were 0.8 percent while error rates for darker-skinned women increased to up to 34 percent. Unfortunately, this is not the only example where AI seems to lose neutrality. Biased algorithms threaten to erode trust in AI platforms. Problems can arise when bias exists in the original data on which the algorithm is trained.

Massachusetts Institute of Technology and Stanford University researchers recently found that three commercial facial analysis programs were producing different results for different skin types and gender. They found that error rates for determining the gender of light-skinned men were 0.8 percent while error rates for darker-skinned women increased to up to 34 percent. Unfortunately, this is not the only example where AI seems to lose neutrality. Biased algorithms threaten to erode trust in AI platforms. Problems can arise when bias exists in the original data on which the algorithm is trained.

People have more trust in robots than their managers, according to the second annual artificial intelligence at Work study conducted by Oracle and Future Workplace, a research firm preparing leaders for disruptions in recruiting, development and employee engagement. The study of 8,370 employees, managers and HR leaders across 10 countries, found that artificial intelligence has changed the relationship between people and technology at work and is reshaping the role HR teams and managers need to play in attracting, retaining and developing talent. Contrary to common fears around how artificial intelligence will impact jobs, employees, managers and HR leaders across the globe are reporting increased adoption of artificial intelligence at work and many are welcoming artificial intelligence with love and optimism. Research findings are based on a global survey conducted by Savanta between July 2 to August 9, 2019. In total, 8,370 completed the survey.

SAN JOSE, Calif., Oct. 31, 2019 -- Samsung Electronics Co., Ltd. and IBM announced today at the Samsung Developer Conference, a new joint platform leveraging IBM Cloud and AI capabilities, and Samsung's mobile offerings. The collaboration between the two companies brings together IBM's capabilities with the Samsung Galaxy ecosystem for today's enterprise customers. "The mobile industry is undergoing a dramatic transformation and opening up new ways of business by bringing innovative technologies like 5G, AI and IoT to enterprises," said DJ Koh, President and CEO of IT & Mobile Communications Division, Samsung Electronics. "We believe open collaboration is central to unlocking these opportunities and look forward to driving digital transformation for our enterprise clients in the 5G era with IBM and Samsung's mobile devices and connected services." Today's announcement is designed to bring together IBM's cloud innovations and Samsung's Galaxy devices ecosystems, including Galaxy Tabs, Galaxy smartphones, and Galaxy Watches.

Being virtually hooked up to a human could help robots respond to disasters or other situations that would put human responders' lives at risks. The researchers say that a system like this could be used to help in robotic clean-up operations such as the one after the Fukushima Daiichi nuclear power plant disaster in Japan in 2011. Humans could have guided robots to navigate around the site more accurately, from a safe distance. And while there's currently no machine learning involved in the process, Ramos believes the data captured from the system could be used to help train autonomous robots.