I met Abby at an HRUndergroundX meetup hosted by Nick Larche. She told me about a new technology she was using to recruit candidates for her start-up clients. "Abby, it was nice to meet you the other night. I'd love to get together and have coffee." "… Amy CC'd has my schedule and will reach out to coordinate with you. She'll also send you a calendar invite once confirmed. Amy, please block this as a 30 minute coffee meeting. If Crema is not a good location for Greg, please let him select our meeting spot. Does Monday, Jul 18 at 4:00 PM work? Alternatively, Abby is available Tuesday, Jul 19 at 11:00 AM or 4:00 PM. Abby likes Crema Coffee House, 2862 Larimer St, Denver, CO 80205, USA, for coffee. I am open at 11am on July 22nd. I received and accepted the invite. Just want to confirm that Abby is still available for our appointment tomorrow at 11AM?"

An anonymous reader writes: MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) says that while many'analyst-driven solutions' rely on rules created by human experts and therefore may miss attacks which do not match established patterns, a new artificial intelligence platform changes the rules of the game. The platform, dubbed AI Squared (AI2), is able to detect 85 percent of attacks -- roughly three times better than current benchmarks -- and also reduces the number of false positives by a factor of five, according to MIT. The latter is important as when anomaly detection triggers false positives, this can lead to lessened trust in protective systems and also wastes the time of IT experts which need to investigate the matter. AI2 was tested using 3.6 billion log lines generated by over 20 million users in a period of three months. The AI trawled through this information and used machine learning to cluster data together to find suspicious activity.

Artificial Intelligence will make society smarter, leaner and more efficient. But first, startups and businesses must enable the workforce of the future and pivot business models to incorporate AI. Mundane tasks such as driving, scheduling and logistics will all be handled by an AI assistant with multiple input points, such as microphones around your house and smartphones. The AI assistant will be the central nervous system of your life and connected smart home. In the future, when you summon a shared autonomous car from your phone to go out to dinner, your AI assistant will automatically notify the restaurant of your ETA and dietary restrictions.

Michael Cavaretta (top right) is the Director of Analytics Infrastructure at Ford Motor Company. He is conversant and curatorial on Twitter and regularly shares links regarding artificial intelligence, in transportation and beyond.

The two week wait (2ww) pathway exists to improve the clinical outcomes of patients with suspected cancer. In head and neck cancer, a difficult diagnosis domain, only 10% of referrals to the pathway require further treatment, significantly effecting the delivery of this service. At LifeQueue, we hope to build tools to address this problem by enhancing the way GPs refer, and how these referrals are prioritised in secondary care. To achieve this we have applied machine learning methods to data representing the symptoms of 5,000 referrals with 400 positive cancer diagnoses. This talk will elaborate on the methods explored, and discuss how they might be applied in other diagnosis situations.

Wine tasting is a fine art which enables classification of Wine. When it comes to classification of wine, the practice is quite varied based on region of origin and time. It is one of the most tasteful traditions which is also protected by law of its own in certain regions. The classification varies based on vintage, sweetness, appellation, vinification styles, varietal or blend. Is it possible to teach something about the classification of different variety of wines to Neural Networks? Well, I intend to do exactly that and get hands on with code as well.

I often come across data science teams that are fascinated by deep learning, compressive classification, and self-driving cars, and that are eager to employ the algorithm du jour. For instance, I was recently working with a large financial institution on increasing its cybersecurity and, before we even got started with basic monitoring, a data scientist on my team was talking about k-means clustering and neural networks. We must always remember to understand the problem and opportunity first, and then apply the right system or algorithm. Sometimes self-learning neural networks may be the best alternative; however, sometimes you'll have to go with a classic: the expert system. An expert system is a rule-based engine based on the collective wisdom of experts.

The field of artificial intelligence is so huge, and the potential applications so numerous, that it would be folly to try to explain it all in one -- no, wait, IBM just did. In June, the White House published a formal request for information, or RFI, about the possibilities and risks of AI. "The views of the American people, including stakeholders such as consumers, academic and industry researchers, private companies, and charitable foundations, are important to inform an understanding of current and future needs for AI in diverse fields," the summary read. IBM took the suggestion and ran with it. Each topic is given a solid enough explanation that after reading through the whole thing, you'll more than likely be the best-informed person in the room on it. We believe that many of the ambiguities and inefficiencies of the critical systems that facilitate life on this planet can be eliminated.

Not long ago, artificial intelligence was something you read about in science fiction; today it's all around us. The smartphone or tablet you hold in your hand is jam-packed with artificial intelligence. Whenever you use a mobile device to pull up Google and perform a search, you're using advanced algorithms that help you find the information you're seeking. When you open Netflix, or Spotify, or Amazon, AI is predicting the shows, movies, music, and merchandise you'll like based on your previous behavior within those apps. These are just a few examples of weak (or narrow) AI and they literally surround us.

Artificial intelligence (AI) is quickly becoming the backbone of many software features and services we use everyday. Anytime you search for specific image in Google Photos or read through Facebook's (NASDAQ:FB) NewsFeed, you're using a form of AI software and algorithms. These are just small AI examples, but there are much larger artificial intelligence trends that are changing how we drive our cars, use energy, answer questions, and connect with others. The companies behind these AI trends are pushing the technology forward like never before, and they (and their investors) could see major benefits just around the corner. Driverless cars are coming, there's no debating that.