These are the presentations that were made by the IBM Decision Optimization team at the INFORMS Annual Meeting, Seattle, October 2019. Andrea Tramontani, Recent Progress In CPLEX Benders Decomposition In this talk we present the Benders decomposition branch-and-cut that is implemented in CPLEX for Mixed Integer Linear Programming (MILP). We illustrate the main algorithmic components behind our implementation and discuss the latest improvements that are currently work in progress. Finally, we present an extensive computational analysis on some classes of decomposable MILP problems, to assess the performance of Benders branch-and-cut in comparison with the default branch-and-cut of CPLEX. The results show that some models that are out of reach for a "standard" branch-and-cut can instead be solved by Benders decomposition.

As part of my Technology and Innovation MBA program at Ted Rogers School of Management, I took a data and knowledge management course which teaches students the principles and practices of knowledge management. The second part of the course delves on tools used in data management and analytics. Although the theoretical part of the course was a bit dry, the hands-on portion was very interesting and exposed students to several different tools to capture, clean and analyze data. One of the tasks given to students was to capture and analyze twitter data. Although students had access to Netlytics, which is a neat cloud-based text and social network analysis tool that also collects Twitter data, students were encouraged to find other ways to collect Twitter data.

Machine learning is everywhere these days. Whether it's recommending your next movie on Netflix or beating Ken Jennings at Jeopardy, ML is here to stay. But how do you get in on this wave? IBM has just made their new Watson Machine Learning (WML) service generally available this week. I do have to point out that you will need to create an account with Bluemix to start playing around with the service, but there's a 30 day free trial and it's pretty fun.

A collaboration between an 11-year-old East Northport boy and his IBM inventor father has given voice to cybersecurity tools using that company's Watson artificial intelligence system. In November, Mike Spisak, whose title is chief transformation architect and master inventor, IBM Security, was joined by his son, Evan, as he worked in his basement "laboratory." Spisak was seeking to apply artificial intelligence tools to the problem of cybersecurity. He was typing to a "chatbot" -- a computer program that simulates human conversation -- in the hope that it could develop into a tool that could provide cybersecurity answers to IBM's corporate clients. That's when Evan, inspired by J.A.R.V.I.S., the AI assistant of comic book and movie hero Tony Stark, aka Iron Man, piped up: "Dad, why can't you talk to it with your voice?"

When it comes to public cloud, Amazon and Microsoft enjoy the mindshare of enterprise decision makers. While Amazon's AWS is considered the category leader, Microsoft has not left any stone unturned to become a cloud-first company. Given the breadth and depth of the portfolio, industry veterans agree that AWS and Azure are the top public cloud platforms for enterprises. These two companies have been making steady progress to consolidate their position in the market. Microsoft is inching closer to Amazon, which is widening the gap between the second and third slots.

When it comes to public cloud-based IoT platforms, Amazon and Microsoft have fierce competition from an unexpected corner – IBM. While the company hasn't seen much traction with SoftLayer (IaaS), and Bluemix (PaaS), it's upping the ante on IoT and Cognitive Computing. IBM Watson is slowly but steadily gaining customer adoption. From Visa to BMW to Bosch to Kone, Watson now boasts of some impressive partnerships. IBM recently hosted a two-day briefing at its newly minted IoT facility in Munich.

As part of my Technology and Innovation MBA program at Ted Rogers School of Management, I took a data and knowledge management course which teaches students the principles and practices of knowledge management. The second part of the course delves on tools used in data management and analytics. Although the theoretical part of the course was a bit dry, the hands-on portion was very interesting and exposed students to several different tools to capture, clean and analyze data. One of the tasks given to students was to capture and analyze twitter data. Although students had access to Netlytics, which is a neat cloud-based text and social network analysis tool that also collects Twitter data, students were encouraged to find other ways to collect Twitter data.

ARMONK, N.Y. - 18 Nov 2016: IBM (NYSE: IBM) today announced several cloud data services and features on Bluemix designed to help organizations accelerate the migration of their data to the cloud and more easily generate business insights. Now available on Bluemix, IBM Decision Optimization, Bluemix Lift and dashDB for Transactions can help organizations overcome this challenge and make more informed business decisions by enabling them to more easily aggregate, ingest and analyze expanding workloads. "Cloud is the platform that enables cognitive intelligence," said John Murphy, Vice President, IBM Watson Data Platform. "We're continuing to grow our catalog of cloud data services on Bluemix so that we can help developers and data scientists better manage and more quickly interpret data for business innovation." IBM Decision Optimization on Cloud (including the CPLEX engines) is now in beta on Bluemix. It can ingest large amounts of data including predictions, master and transactional data, business goals, and business rules to prioritize and rank business decisions such as plans and schedules.

As part of my Technology and Innovation MBA program at Ted Rogers School of Management, I took a data and knowledge management course which teaches students the principles and practices of knowledge management. The second part of the course delves on tools used in data management and analytics. Although the theoretical part of the course was a bit dry, the hands-on portion was very interesting and exposed students to several different tools to capture, clean and analyze data. One of the tasks given to students was to capture and analyze twitter data. Although students had access to Netlytics, which is a neat cloud-based text and social network analysis tool that also collects Twitter data, students were encouraged to find other ways to collect Twitter data.

Those who have been chomping at the bit to use IBM's Watson machine-intelligence service with their apps need gnaw no longer. Watson APIs are now available for public use, albeit only through IBM's Bluemix cloud services platform. IBM's Watson Developer Cloud now offers eight services for building what IBM describes as cognitive apps, with more services promised later on. Of the services offered so far, Visualization Rendering seems the most immediately useful and powerful, since it isn't limited by data training many of Watson's other services rely on. Most of the services rely on a "corpus," or cultivated body of data that Watson can use as raw material, so the breadth of several Watson offerings is limited by the size of their existing corpora.