In early 2016, the Office of Personnel Management, the human resources agency for federal employees, began researching software that would track the social media accounts of security clearance applicants. The agency was reportedly looking to contract with companies that could do searches with almost no need for human input and had a "robust identity-matching algorithm" to cut down on mixups. The company's chief competitor is a 10-minute walk from FiscalNote's office, just south of Dupont Circle. Quorum was founded in 2014 by Alex Wirth and Jonathan Marks while they were still Harvard undergrads. Now employing up to 46 people, stuffed into a buzzing glass-partitioned office space marked by caramel-colored wide-board wood floors, the office has a map of the D.C. Metro system embedded in tile on the wall of the open kitchen space.

Newer technologies such as Artificial Intelligence (AI), robotics and automation, 3D printing, mixed reality that combines virtual reality and augmented reality, and blockchain are not only disrupting and transforming business models and the lives of individuals, but also ushering in the so-called gig economy which envisages an environment in which temporary positions are common and organizations engage independent workers on short-term contracts. Lounge takes a look at how these technologies will affect us in the years to come. It was only in December that the US' National Aeronautics and Space Administration (Nasa) announced that a solar system with as many planets as our own had been discovered with the help of its Kepler space telescope and AI. Closer home, Microsoft and the International Crops Research Institute for the Semi-Arid Tropics are using an AI-based sowing app that is expected to help about 4,000 farmers in Andhra Pradesh and Karnataka during the kharif season. HDFC Bank's AI chatbot Eva, built by Senseforth AI Research, now works with the Google Assistant in Indian English.

The use of Artificial Intelligence (AI) is on the rise in the technology sector and has become a buzz-worthy topic in many corners of our digital world. The application of AI in the medical field holds great promise for improving patient health, but will doctors and patients feel comfortable using it? Young startups have begun leveraging this technology to prove better health outcomes, but there's still a lot to do before we'll see AI used pervasively in the clinic. To date, the sweet spot in healthcare AI has been pairing algorithms with structured exercises in reading patient data and medical images to train machines to detect abnormalities. This training is called "deep learning." In the same way, algorithms are being used to sift through vast amounts of medical literature to inform treatment decisions where it would be too onerous a task to have a human read through the same journals.

In 2018, we will see a rise in artificial intelligence-powered cyberattacks. TechRepublic's Dan Patterson met with IBM Security's vice president of threat intelligence Caleb Barlow to discuss what this means for businesses. Artificial intelligence (AI) and machine learning can be used to help defenders, however the bad guys can also use it to find vulnerabilities in all of our systems, Barlow said. "As we move into 2018, we enter a world where we start to see AI vs. AI, and this is all about staying one step ahead of the bad guys with newer technology, better approaches, and better analytics," he added. Hackers and enterprises have different resources to AI, and they use it for different reasons.

The 100 startups on our list have raised $11.7B in aggregate funding across 367 deals. Today, CB Insights unveiled the second annual AI 100 -- a list of 100 of the most promising private companies applying artificial intelligence algorithms across 25 industries, from healthcare to cybersecurity -- at the A-Ha! conference in San Francisco. The companies were selected from a pool of 2,000 startups based on several criteria, including investor profile, tech innovation, team strength, patent activity, mosaic score, funding history, valuation, and business model. The market map below categorizes the AI 100 companies based on their industry focus. Please click on the image to enlarge.

Welcome in 2018 and a Happy New Year! New AI weekly focuses mainly on China (probably biggest investor in AI right now) and some predictions for upcoming months. But that's not all, you can find here also new cool summaries of AI related events and libraries from 2017. Enjoy your weekend reading other AI news and don't forget to share it with your friends The 5 Most Interesting Artificial Intelligence Trends for Entrepreneurs to Follow in 2018 -- The current pace of innovation makes it almost impossible to stay on top of the AI trends, but understanding these advancements is a must for business owners who want to stay ahead. China is building a giant $2.1 billion research park dedicated to developing A.I. -- China is planning to build a 13.8 billion yuan ($2.1 billion) technology park dedicated to developing artificial intelligence (AI), state-backed news agency Xinhua reported Wednesday.

Geospatial data is the building block of the modern web map, but its production has evolved rapidly in recent years with a vast quantity of user-created content. What once was the realm of experts has now been democratized for the common user, but crowdsourced and volunteered data faces criticisms over its quality. Machine learning is offering an intelligent and objective way to enhance collaborative work and bring added precision and accuracy. But which source will be the one providing the maps of the future? "Art is a lie that makes us realize truth, at least the truth that is given us to understand." -- Pablo Picasso I recently visited a small bookstore in Riga, Latvia, which boasts some underground fame among mapping enthusiasts for its collection of vintage Soviet maps of the world. I found Cyrillic writing detailing the location of airfields and rivers in my home state of Montana, inspiring me to ponder the way such information was gathered and stored in the Cold War era.

Self-paced learning and hard example mining re-weight training instances to improve learning accuracy. This paper presents two improved alternatives based on lightweight estimates of sample uncertainty in stochastic gradient descent (SGD): the variance in predicted probability of the correct class across iterations of mini-batch SGD, and the proximity of the correct class probability to the decision threshold. Extensive experimental results on six datasets show that our methods reliably improve accuracy in various network architectures, including additional gains on top of other popular training techniques, such as residual learning, momentum, ADAM, batch normalization, dropout, and distillation.

Researchers at an Oxford hospital have developed a system that uses artificial intelligence to diagnose scans for heart disease and lung cancer – potentially saving billions of pounds by enabling the diseases to be picked up much earlier. The technology is due to become available for free in NHS hospitals this summer, and the results from clinical trials have found that the system can do a lot better than consultants. At the moment, of the 60,000 heart scans carried out each year, 12,000 are reportedly misdiagnosed at an estimated cost of £600 million. Geneticist Sir John Bell, told BBC News that AI could "save the NHS". "There is about £2.2bn spent on pathology services in the NHS. You may be able to reduce that by 50%. AI may be the thing that saves the NHS".

This year the Canadian government will start using artificial intelligence to help track social media posts that could indicate someone is at risk of suicide, according to a contract. The Canadian government recently signed a contract with Ottawa-based AI firm Advanced Symbolics to monitor social media posts for suicidal behavior. In the first phase of the partnership, Advanced Symbolics will work with the government to define "suicide-related behavior," according to the contract. This is typically defined through thoughts, behaviors, and communications. The company will then identify patterns that are associated with these behaviors based on online data.