IBM Watson has talked tennis with Serena Williams and music with Bob Dylan. Now it wants to talk to you -- via online ads. The Weather Company, acquired by IBM in January, will begin bringing Watson-enhanced interactive advertisements to The Weather Channel and Weather Underground apps on Android and iOS and to weather.com and wunderground.com The ads, powered by Watson's artificial intelligence, will prompt consumers to ask questions such as "What would be good to cook for dinner?" or "Is this medicine safe for my child?" The first companies with Watson-enabled ads will be Campbell Soup, GSK Consumer Healthcare and Unilever.

Google employees, squeezed onto metal risers and standing in the back of a meeting room, erupted in cheers as newly arrived executive Andrew Conrad announced they would try to turn science fiction into reality: The tech giant had formed a biotech venture to create a futuristic device like Star Trek's iconic "Tricorder" diagnostic wizard -- and use it to cure cancer. Conrad, recalled an employee who was present, displayed images on the room's big screens showing nanoparticles tracking down cancer cells in the bloodstream and flashing signals to a Fitbit-style wristband. He promised a working prototype of the cancer early-detection device within six months. That was three years ago. Recently departed employees said the prototype didn't work as hoped, and the Tricorder project is floundering. Tricorder is not the only misfire for Google's ambitious and extravagantly funded biotech venture, now named Verily Life Sciences. It has announced three signature projects meant to transform medicine, and a STAT examination found that all of them are plagued by serious, if not fatal, scientific shortcomings, even as Verily has vigorously promoted their promise.

SAN DIEGO, CA--(Marketwired - Jun 6, 2016) - KnuEdge Inc., a neural technology innovation company that launched today, introduced its KNUPATH LambdaFabric processor technology enabling ground-breaking scalability, latency and workload performance in next-generation data centers. With a fundamentally different architecture than legacy products, KNUPATH can operate alone or be integrated with other devices, and it is available now to both end customers and technology vendors seeking to create data center neural computing capabilities to support advancements in machine learning, IoT and signal processing. "Many of today's CPUs, GPUs and FPGAs force system designers to either create workarounds with last-generation chip sets or reduce their requirements for advanced-compute projects," said Dan Goldin, Founder and CEO of KnuEdge. "After ten years of stealth development and rigorous testing, LambdaFabric enters the market as mature technology which enables system designers to meet the most demanding requirements now, and also helps them rethink what is possible with neural computing in the future." As evidenced by recent announcements such as Google's Tensor Processing Unit, there is increasing industry interest in targeted processor acceleration for machine learning and other growing workloads. KNUPATH LambdaFabric is inherently designed to scale up to 512,000 devices and beyond, and offers rack-to-rack latency of only 400 nanoseconds, approaching half the latency of existing high speed interconnects.

Forget about interactive iPad newspapers, mobile apps and catchy television graphics. The future of news may be far less complicated than anyone could have imagined -- as simple as a conversation with a friend. We're on the cusp of a chatbot revolution, with tech giants Facebook, Google and Microsoft all competing to create the brainiest robotic agent powered by artificial intelligence. "We think you should be able to message a business in the same way you message a friend," Facebook CEO Mark Zuckerberg recently said, announcing the launch of a chatbot store during the social network's annual developers conference. "And you shouldn't have to install a new app."

Learn machine learning for free, because free is better than not-free. This website is inspired by the datasciencemasters/go and open-source-cs-degree Github pages. This one is specifically for machine learning and features textbooks, textbook-length lecture notes, and similar materials found with a simple google search. This repository is meant as a general guide and resource for a free education. Note: Please report any broken links as an issue on the Github page.

BluVector is a next-generation machine-learning malware detection and cyber hunting solution. Kris Lovejoy has been recognized for a wide range of industry accolades, including SC Magazine's Reboot 25 issue in 2014 as one of the world's Top 25 Security Managers, a 2012 Compass Award Winner by CSO Magazine, an eWEEK 2012 Top Women in Information Security, a Top 25 CTO by InfoWorld, and a Top 25 Most Influential Security Exec by Security Magazine. Most recently, Lovejoy received the EWF 2015 Women of Influence Award, Private Solutions Provider. Lovejoy holds U.S. and EU patents for Object Oriented Risk Management Models and Methods.

Proof of this and also because XGBoost has an easy-to-use interface from both R and Python, XGBoost has become a favorite tool in Kaggle competitions. Besides feature engineering, cross-validation and ensembling, XGBoost is a key ingredient for achieving the highest accuracy in many data science competitions and more importantly in practical applications. We were fortunate to recently host Tianqi Chen, the main author of XGBoost in a workshop and a meetup talk in Santa Monica, California. First, we started with an advanced workshop in the afternoon for which anyone could apply to participate but there were only a dozen spots available (which got us some expert users of XGBoost, but unfortunately we had to reject some good people too, sorry). This advanced workshop had 2 sessions.

Those firms that have dipped their toes into artificial intelligence and blockchain technologies remain a significant minority of financial institutions, according to the results of a recent survey commissioned by industry consultancy Synechron. Although a vast majority of the 92 executives polled and who are directly involved in technology decisions at their firms, agreed that both technologies will be "hugely important" for the industry in the next 10 years, only a small portion have examples of technologies in production. Only 12% of the respondents claim to have an instance of a distributed ledger implemented within their organization while 3.5% of them have "actively deployed" artificial intelligence-based technology. However, 25% of those polled stated that they have actively use AI-based systems within their organizations. "I am unsurprised that a low percentage of institutions may have these technologies in active development, but the sheer potential of artificial intelligence and blockchain in the enterprise is tremendously real," said Faisal Husain, CEO of Synechron. Husain advised financial institutions not to delay embracing new technologies, even if the final return on investment is unknown.

You would think that if you were to develop an AI system or a brain of a robot that it would be highly complex. After all with all the different things we can think of and when it comes to problem solving, it would certainly involve complex algorithms and programming, right? However it seems that a recent discovery has suggested that maybe less is more. Scientists at the University of Sussex have discovered that snail brains could be the key to helping develop smarter robots. The scientists attached electrodes to the brains of snails and according to their findings, the snail only used two brain cells to make complex decisions.

The Future of Humanity Institute, University of OxfordStuart Armstrong is a philosopher at the University of Oxford and one of the paper's authors. Machines are becoming more intelligent every year thanks to advances being made by companies like Google, Facebook, Microsoft, and many others. AI agents, as they're sometimes known, can already beat us at complex board games like Go and they're becoming more competent in a range of other areas. Now a London AI research lab owned by Google has carried out a study to make sure we can pull the plug on self-learning machines when we want to. DeepMind, acquired by Google for a reported 400 million in 2014, teamed up with scientists at the University of Oxford to find a way to make sure AI agents don't learn to prevent, or seek to prevent humans from taking control.