Question Answering

I'm pleased to say that the IDC MarketScape has positioned the IBM Watson IoT Platform as a leader in the IDC MarketScape: Worldwide IoT Platforms (Software Vendors) 2017 Vendor Assessment (doc #.US42033517, July 2017). IDC MarketScape: Worldwide IoT Platforms, 2017 Software Vendor Assessment stated, "IBM has created a strong analytics brand with Watson and can demonstrate the power of cognitive analytics in the IoT." Additionally, through Watson IoT solutions for Connected Products, Connected Operations and Industry-specific IoT environments, IBM has a clear advantage in delivering an IoT platform designed to directly support the number one driver of IoT platform decisions by clients -- clear contribution to defined business outcomes. If you'd like to read an excerpt of the IDC MarketScape's report to find out why Watson IoT Platform was named a leader, you can read more about the IDC MarketScape Report here.

A new study, in which IBM Watson took just 10 minutes to analyze a brain cancer patient's genome and suggest a treatment plan, demonstrates the potential of artificially intelligent medicine to improve patient care. Both the NYGC clinicians and Watson identified mutations in genes that weren't checked in the panel test, but which nonetheless suggested potentially beneficial drugs and clinical trials. Both Watson and the expert team received the patient's genome information and identified genes that showed mutations; went through the medical literature to see if those mutations had figured in other cancer cases; looked for reports of successful treatment with drugs; and checked for clinical trials that the patient might be eligible for. IBM's Parida notes that the cost of sequencing an entire genome has plummeted in recent years, opening up the possibility that whole-genome sequencing will soon be a routine part of cancer care.

Three years later, in 2014, IBM created the Watson business unit to figure out ways to use the technology to actually make money. Now "Watson" represents a whole array of AI technologies built and acquired by IBM--including sentiment analysis, voice recognition, and natural-language processing. IBM's Watson Takes On Cancer, Diabetes," "The Toronto Raptors Are Using IBM's Watson to Draft A Winning Team," "IBM's Watson has published a cookbook," "Watson helped make a trailer for a horror movie about AI," "The Latest Job for IBM's Watson Is as a Hotel Concierge," "IBM Watson Helps Create Sculptures Inspired by Gaudi," and "IBM's Watson is making music, one step closer to taking over the world." There are two main branches within Watson Health--Watson for Oncology, which essentially suggests cancer treatments based on the patient information that a doctor inputs, and Watson for Genomics, which works similarly but based the genomic sequencing data of a patient's tumor.

In this article we're going to learn what does it take to save time to our customer support team. To do this we'll build a chatbot to automate answers to frequently asked questions, eventually saving precious time to your customer support operators so they can focus on more complex requests. This is important to define the way answers will be organized and stored, knowledge bases can be quite large so we prefer to manage them in a separate database rather than inside Watson's conversation dialog model. The small talk intents can be defined directly on Watson because the answers to these questions will be inside the dialog model.

IBM has just made their new Watson Machine Learning (WML) service generally available this week. It's capable of two different functions of machine learning: training and scoring. Developers, of course, want to build smart apps that can use predictions made by the machine learning algorithms. So, if you're interested in trying it out, head on over and give IBM's Watson Machine Learning a whirl.

This would mean loading the system with a huge volume of curated known-true facts then comparing new material using the logic of Question Answering Machines (QAMs) like Watson. Remember, that aside from the UX implications of Fletcher's comment, a successful Watson implementation requires constantly adding to and deleting from the corpus of knowledge. In other more successful Watson implementations the knowledge base like tax law or sample images of cancerous tumors simply doesn't change as fast as the news. Their training set of about 5,000 articles is on the small side but their site claims 84% accuracy based on voluntary user provided feedback.

Chatbot technology, based on recent advances in natural language processing and continuous learning algorithms, can perform better than many human operators. IBM Watson Analytics, based on Watson's question answering machine, is one of the most advanced solutions that allows users to receive data-driven responses to questions regarding any aspect of the business, such as sales, finance, human resources and marketing. AI companies like Marketo are already offering AI-enabled systems to build marketing campaigns, attract and retain customers more efficiently by using predictive analytics, provide sales forecasting, identify potential clients and predict user behavior. Modern anomaly detection algorithms leverage the power of machine learning to learn patterns of fraudulent transactions and behavior.

After testing the powers of some of the latest in voice search on streaming media devices, I think I have a few answers. What all that adds up to is a somewhat disjointed experience for the heaviest users of these devices: film and television fans. What all that adds up to is a somewhat disjointed experience for the heaviest users of these devices: millions and millions of happily obsessed film and television fans. But until voice search can handle the widest range of tastes that cover any number of weird names and titles (that, I repeat, are actually available in these databases via text search), voice search will be more clever add-on than heavily used anchor that drives up streaming media device usage.

Over the last couple of days, I have seen a bunch of articles on my social media feed that are based on a research report from Jefferies' James Kisner criticizing IBM Watson. As much as I am a geek who wants to make my opinions known on technology topics, I am also an IBM executive, and I run a part of IBM GBS business in North America that also includes services on IBM Watson (including Watson Health) . IBM Watson does not share one client's data with another client This design principle is very key to enterprise clients. Beyond oncology, Watson is in use by nearly half of the top 25 life sciences companies.

A scathing report from investment bank Jefferies claims that from an earnings per share perspective "it seems unlikely to us under almost any scenario that Watson will generate meaningful earnings results over the next few years". While exact figures for Watson aren't given, Jefferies pulled together a range of information, including market research data and public filings, to build financial models predicting Watson's future prospects. "Watson services are offered on either a subscription or a pay-per-use basis and everyone can get started for free," an IBM spokesperson told WIRED. "Watson is clearly part of IBM's Strategic Imperatives, whose figures are reported," an IBM spokesperson told WIRED when quizzed on whether the supercomputer is making any money.