Samuel Holmes Doten of Plymouth, Mass., was born June 5, 1812, so after the Civil War ended in 1865, he would joke that he "served in the infantry in the war of that date." William Kendall Crossfield, a Peterborough, N.H. native, was having a rest during the battle of Fredericksburg when he was shot in the neck while turning over. The blanket he had pulled up to his chin miraculously cushioned the bullet, but he passed out from the shock of the blow. Vermonter Almeron C. Inman was recommended for the Medal of Honor of Feb. 9, 1887, "for intelligent coolness and bravery" in two 1864 engagements. After going missing for three months in 1895, he was found dead, thought to have killed himself.

WASHINGTON – Facial recognition systems can produce wildly inaccurate results, especially for nonwhites, according to a U.S. government study released Thursday that is likely to raise fresh doubts on deployment of the artificial intelligence technology. The study of dozens of facial recognition algorithms showed "false positives" rates for Asians and African-Americans as much as 100 times higher than for whites. The researchers from the National Institute of Standards and Technology (NIST), a government research center, also found two algorithms assigned the wrong gender to black females almost 35 percent of the time. The study comes amid widespread deployment of facial recognition for law enforcement, airports, border security, banking, retailing, schools and for personal technology such as unlocking smartphones. Some activists and researchers have claimed the potential for errors is too great and that mistakes could result in the jailing of innocent people, and that the technology could be used to create databases that may be hacked or inappropriately used.

Smart cars may make our lives easier on the road, but they are also easily hacked by cyber criminals. Scientists have found'holes' in these systems that lets digital deviants access your data or worse, take over the vehicle. The first hole is when users plug their smartphone into their smart car, which is an open door for hackers to breach vehicle systems. However, another vulnerability lets users access features in order to take over the system and could ultimately crash the car. Experts are now calling on carmakers to release constant updates for the software in order to put an end to data breaches and save lives.

Our approach to time series anomaly detection is computationally efficient, automatically learns how to update probabilities and adapt to changes in data. As we describe in the next section, this approach has yielded successful attack detection at high precision. The proposed time series anomaly detection model was deployed and utilized by Microsoft Threat Experts to detect RDP brute force attacks during threat hunting activities. A list that ranks machines across enterprises with the lowest anomaly scores (indicating the likelihood of observing a value at least as large under expected conditions in all signals considered) is updated and reviewed every day. See Table 1 for an example.

The field of law has evolved surprisingly little since the days of Oliver Wendell Holmes, Jr. ... [ ] (1841-1935), considered by many to be the greatest U.S. Supreme Court justice in history. Virtually everything that companies do--sales, purchases, partnerships, mergers, reorganizations--they do via legally enforceable contracts. Innovation would grind to a halt without a well-developed body of intellectual property law. Day to day, whether we recognize it or not, each of us operates against the backdrop of our legal regime and the implicit possibility of litigation. At close to $1T globally, the legal services market is one of the largest in the world.

As a recent CIO article observed, artificial intelligence has been "the next big thing" for a long time now. It has promised to relieve us of many mundane, day-to-day tasks while simultaneously helping us achieve feats of science and engineering we can barely imagine. There have also been the more dystopian visions of AI displacing wide swaths of the human workforce, leading to millions of people whose jobs are taken over by the AI-powered machines. While neither of these visions is likely for a long time to come, there are practical applications of AI that are coming of age. So how will organizations use artificial intelligence and machine learning to transform themselves and become more competitive?

NVIDIA today introduced groundbreaking inference software that developers everywhere can use to deliver conversational AI applications, slashing inference latency that until now has impeded true, interactive engagement. NVIDIA TensorRT 7 -- the seventh generation of the company's inference software development kit -- opens the door to smarter human-to-AI interactions, enabling real-time engagement with applications such as voice agents, chatbots and recommendation engines. It is estimated that there are 3.25 billion digital voice assistants being used in devices around the world, according to Juniper Research. By 2023, that number is expected to reach 8 billion, more than the world's total population. TensorRT 7 features a new deep learning compiler designed to automatically optimize and accelerate the increasingly complex recurrent and transformer-based neural networks needed for AI speech applications.

Sign in to report inappropriate content. Graham MackIntosh is a pioneer in the field of advanced analytics, working as an AI consultant for NASA and the SETI Institute. Hear how NASA is using AI to understand solar events, detect failures and expand our understanding of the universe.

Google-owned DeepMind is to collaborate with a UK hospital to help doctors spot more than 50 different eye diseases using AI. When it isn't creating artificial intelligence (AI) capable of destroying human opponents in a game of Go, Google-owned DeepMind is trying to build other systems that could transform healthcare, among other things. Now, the UK-based company has revealed a joint research partnership with Moorfields Eye Hospital that could help spot sight-threatening eye diseases much quicker than before. Publishing its findings in Nature Medicine, the company said that its latest AI can quickly run through eye scans taken from routine clinical practice and identify more than 50 serious diseases as accurately as world-leading expert doctors. Under existing systems, ophthalmologists use 3D images called optical coherence tomography (OCT) to create a detailed map of a person's eye.

Paige, a NYC-based leader in computational pathology transforming the diagnosis and treatment of cancer, today announced it has closed its Series B funding round of $45 million, bringing the Company's total capital raised to over $70 million. Healthcare Venture Partners brought the largest contribution to the round, with Breyer Capital, Kenan Turnacioglu, and other funds participating. Paige will use this new capital to drive FDA clearance of its products and expand its portfolio, delving deeper into cancer pathology, novel biomarkers, and prognostic capabilities. Additionally, the Company will accelerate commercial efforts in the U.S. and expansion in Europe, Brazil, and Canada. Pathology is the cornerstone of cancer diagnoses.