In the news this week: A bevy of partnerships to bring artificial intelligence (AI) and machine learning (ML) to medical applications, and more. Keeping pace with news and developments in the real-time analytics market can be a daunting task. We want to help by providing a summary of some of the items our staff came across each week. The use of artificial intelligence (AI) and machine learning (ML) in healthcare and medical diagnosis is perhaps one of the most promising applications of the technology for the public good. Frequently, the main inhibitor to the use of AI in these fields is the lack of internal familiarity with the technology.

Infinia ML announced today that it had been named a Hot Vendor in the field of machine learning by HfS Research. The HfS report notes Infinia's "mission to link ML development to measurable business impact for its clients", its "distinguished leadership team", and its "dedication to research and innovation." According to HfS, Infinia ML's "experience, talent, and IP has earned it the HfS Hot Vendor tag." The report highlights Infinia ML client projects in contract analysis, pay benchmarking, ultrasound image identification, cancer detection, and more. HfS says its Hot Vendors, chosen via a five-step assessment process, "display truly differentiated offerings and out-of-the-box thinking that can be both inspiring and useful."

Most examples of artificial intelligence in the enterprise today are just on the fringe of what's possible with the technology in the future, according to a group of 10 industry thought leaders who met in New York City on Monday as part of the latest edition of Think Tank by Adobe. Kathryn Hume, VP of product and strategy at Integrate.ai, offered some early perspective by saying that AI is not a new concept. In fact, the exploration of AI has been going on for well over 50 years. "We are swimming in data," Hume said. "There's a tremendous amount of it, and we are seeing an increase in the importance of the machine-learning algorithm. However, we're still in the early days of a true AI revolution, with many questions yet to be answered around what the tech is and is not, according to Susan Etlinger, an industry analyst at Altimeter Group, who also moderated the panel. AI Today AI's impact in the enterprise today is twofold. The first is AI-powered analytics systems built using data and algorithms, and whose decision-making gets better over time. These systems enable organizations to collect, store, and process data at scale, which, in turn, helps them make informed decisions for the future, Hume said. AI also is helping organizations become more efficient with its ability to "sense, think, and act to achieve a set of objectives," said Anand Rao, partner and global AI and innovation lead at PwC. He pointed to natural language processing, the ability to identify and classify objects, reasoning, problem solving, planning, and even simulating as examples of capabilities. "We as humanity are having this awakening," added Chris Duffey, head of AI innovation and strategy at Adobe (CMO.com's "There is this technology out there that accelerates and augments our thinking.

Mice brains and machine learning may lead to a new way to treat depression, according to a new paper published in the journal Cell and co-authored by Infinia ML Chief Scientist Larry Carin, Ph.D. The paper describes how scientists measured electrical signals in the brains of both observably resilient, active mice and observably depressed, inactive mice. The complexity and scale of the available data, gathered from 18 regions of the brain, then required advanced machine learning for analysis. In effect, scientists trained a learning algorithm to map each brain's connections. They found a pattern in the resilient mice that differed from the depressed. "We wanted to understand the traffic flow of a healthy brain," said Carin, the project's machine learning lead.