One of the most difficult challenges faced by businesses in asset-intensive industries is how to control and scale the half billion and growing "smart" devices that make up the Internet of Things (IoT)? As much as 80 percent of IoT data in any organization is unstructured. And, let's be honest, "smart" devices really aren't that smart yet. As part of its giant rollout of AI solutions pre-trained for specific industries and professions, IBM Services is launching a new Connected Manufacturing offering that includes a method and approach to help clients accelerate their IoT transformation–from strategy, implementation, and security to managed services and ongoing operations. This combined capability, IBM said, will help its clients connect all of their manufacturing equipment, sensors, and systems to enable business improvement across OEE, quality, lead times and productivity.

IBM is introducing a number of "AI-powered solutions" intended help brands better manage the balance between human intelligence and machine learning. For marketers, IBM's WEATHERfx Footfall with Watson represents a new AI ad solution that's specifically designed to help drive in-store traffic by optimizing marketing campaigns. By improving conversion rates with contextually relevant advertising to reach the right audience at the right time, Subway successfully increased sales and attracted new clients. Subway's WEATHERfx Footfall with Watson work involved designing ads based on shifting weather patterns. "Why advertise hot sandwiches when it's 100 degrees out?" is the thinking behind the creative ad units.

IBM has ushered its customers into the era of enterprise data science for more than a decade, starting with the investment of the ILOG CPLEX and SPSS acquisitions. As the data science market evolved, new macro trends developed, and IBM invested in advanced technologies and platforms to respond to this shift. In 2016, IBM introduced Data Science Experience and several Watson offerings, which blurred the lines between our new and old technologies. We have now made the decision to simplify our portfolio for our customers under one single brand -- IBM Watson Studio. IBM Watson Studio was first announced in the IBM Public Cloud at our Think Conference in March 2018, which included the integration of the capabilities of Data Science Experience Cloud and a new interface for SPSS Modeler.

The IBM Watson AI XPRIZE is a four-year competition where teams work to improve the world with artificial intelligence. The competition began in 2017 with 148 problem domains in sustainability, artificial general intelligence, education, and a variety of other grand challenge areas. 59 teams advanced to the second year of the competition and ten teams earned special recognition as “milestone nominees.” The properties of the advancing problem domains highlight opportunities and challenges for the “AI for Good” movement. We detail the judging process and highlight preliminary results from cutting the field of competing teams.

State Farm is moving forward with several digital initiatives as the largest personal lines P&C insurer in the U.S. by market share rides the digitalization wave shaking up the industry. The company has launched a $100 million fund, State Farm Ventures, with the goal of increasing its involvement in and adoption of insurtech. Led by innovation executive Michael Remmes, the unit will focus on "acquiring startups or strategic alliances that support our core products," says spokesperson Angie Harrier. With a major thrust of insurtech being use cases for artificial intelligence, State Farm is beginning to explore that technology as well. The insurer is running an ad campaign along with the Weather Company and IBM Watson through Halloween that uses Watson's cognitive computing technology to deliver relevant storm-preparation content to affected customers.

Las Vegas, HR Technology Conference & Expo #HRTech -- LEADx, Inc., the world's leading Conversational Learning (CL) platform for leadership enablement, today launched LEADx Coach Amanda, an executive coach virtual assistant powered by IBM Watson Assistant. "We believe every manager deserves a coach," said Kevin Kruse, LEADx founder and CEO. "Traditional leadership development, based on workshops and online tutorials, has long failed enterprises and managers alike. Executive coaches work well, but due to their cost they are ironically reserved for the leaders who have the most experience. But now, we've tapped the power of AI to democratize leadership development."

That's the message of a big Wall Street Journal post-mortem on Watson, the IBM project that was supposed to turn IBM's computing prowess into a scalable program that could deliver state-of-the-art personalized cancer treatment protocols to millions of patients around the world. Watson in general, and its oncology application in particular, has been receiving a lot of skeptical coverage of late; STAT published a major investigation last year, reporting that Watson was nowhere near being able to live up to IBM's promises. After that article came out, the IBM hype machine started toning things down a bit. But while a lot of the problems with Watson are medical or technical, they're deeply financial, too. IBM is shrinking: In 2011, when the company first introduced the idea that Watson might be able to one day cure cancer, its revenues were $107 billion. They've gotten smaller every year since, ending up at $79 billion in 2017.

Business leaders understand the advantage of using the power of artificial intelligence and machine learning to stay ahead of their competitors. However, understanding the power of AI is a lot different than actually successfully implementing it in companies. For example, in 2017, Gartner estimated that Big Data projects have a success rate of only 15%. While organizational factors may be a primary reason for this poor success rate, another reason for such a high failure rate could be due to a lack of AI / Machine Learning talent needed to successfully pursue these types of projects. Specifically, it's been shown that there is a lack of advanced machine learning talent among data professionals; less than 20% of surveyed data professionals said they were competent in such areas as Natural Language Processing (19%), Recommendation Engines (14%), Reinforcement Learning (6%), Adversarial Learning (4%) and Neural Networks – RNNs (15%).

We warmly invite you to read the presentation given to the INSEAD alumni à BCG Paris site to understand what is going on!.

I've been using Jupyter Notebooks with great delight for many years now, mostly with Python, and it's validating to see that their popularity keeps growing, both in academia and the industry. I do have a pet peeve though, which is the lack of a first-class visual debugger similar to these available in other IDEs like Eclipse, IntelliJ, or Visual Studio Code. Some would rightfully point out that Jupyter already supports pdb for simple debugging, where you can manually and sequentially enter commands to do things like inspect variables, set breakpoints, etc. -- and this is probably sufficient when it comes to debugging simple analytics. To raise the bar, the PixieDust team is happy to introduce the first (to the best of our knowledge) visual Python debugger for Jupyter Notebooks. As advertised, the PixieDebugger is a visual Python debugger built as a PixieApp, and includes a source editor, local variable inspector, console output, the ability to evaluate Python expressions in the current context, breakpoints management, and a toolbar for controlling code execution.