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#IBMWoW: Ginni Rometty Keynote: Building a Cognitive Business

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Last session for me at IBM’s World of Watson is the keynote from IBM CEO, Ginni Rometty. Another very slick video on the different ways IBM’s cognitive, cloud and analytic solutions are being used around the world got us started. And again, IBM emphasized “with Watson” as part of their ongoing positioning of Watson as additive to people, not a threat to them. Then it was time for Ginni Rometty. The market for better decisions, she says, is $2T by 2025 – and better decision making is the name of the game. Ginni wants to show us three things

  • That Watson is the best AI platform for business
  • That Watson will let you build a cognitive business
  • That this is going to transform industries

She points out at once that Watson has rapidly achieved a critical mass – with hundreds of millions people being impacted already through medicine, shopping, insurance, weather, education and more. IBM she says has made three critical choices:

  1. That Watson is about augmenting and extending expertise – augmented intelligence
  2. That your data matters and you should be able to learn from this data, not others
  3. That Watson was going to be at the heart of a rich ecosystem with others also delivering value on Watson not just IBM – and that IBM would develop industry-specific infrastructure to make this work

Five areas for competitive advantage she says:

  • Deeper human engagement – with customers, employees, partners
  • Scaling expertise – make everyone perform at their best level, especially when people are retiring. And scale imagination – fashion, movies, cooking, music.
  • Embedding in every product to make those products more effective, more reliable
  • Change the operations in your company – make processes real-time aware, real-time learners.
  • Anywhere there is discovery and research where Watson can find new connections

And companies she says are working in all these areas and across hundreds of projects they have four lessons:

  1. Better data, better outcomes – and you need new kinds of data too
  2. Training is not programming – more upfront work but then it keeps learning
  3. Cloud and cognitive go together and add more value used together
  4. You must address people’s concerns around ethics, transparency, jobs etc.

Ginni was joined onstage by Mary Barra CEO of GM. GM has been developing OnStar for many years, connecting some of its cars to services. Automotive is being transformed by the explosion in connectivity, the electricification of cars, autonomous vehicles and the sharing economy. GM is trying to bring all these things together as part of reinventing itself moving forward. While some of these may change the relationship people have to car ownership and usage but, regardless, the vehicles themselves are going to be changed completely. People spend 46 minutes a day in their car and GM want to safely give people this time back. OnStar Go is the new service that GM and IBM are working on together. This takes the connectivity and monitoring of OnStar and adding Watson capabilities to act as a personalized assistant around things like picking up prescriptions or groceries, get gas, pre-order drive-through and more. And in 2017 model cars not some distant future.

Next up is the impact of Watson on education. Teacher Adviser uses Watson to become an individualized assistant for teachers – providing best practices but also learning about a teacher’s individual preferences and their students. John King Jr, Secretary of Education, came up to join Ginni. John began with the good news – highest high school graduation rate, more minority students going to college, more Pre-K and more school’s have STEM teachers and broadband connections. All good but there’s more to do – poverty continues to be a predictor of poor education outcomes and there is a disconnect between skills students learn and what companies need. There are many things that companies can do and ways thing can be improved but one possibility is something like Teacher Adviser. There’s a lot of advice out there but its hard to navigate and its tough to match specific best practices to specific students. Teachers, he says, really like the ability to use it to find the right thing to help specific students. He also likes the way it will learn from each teacher to help all teachers. And the ability to drive achievement broadly and deeply is a critical factor moving forward. Very inspiring conversation.

Healthcare is, Ginni says, IBM’s next moonshot and is therefore a real focus for IBM and its Watson business. As a data point, she says, it takes 12 years to get a drug to market at a cost of $1Bn and that few make it to market at all. Dr Yitzhak Peterburg of Teva Pharmaceuticals joined Ginni to discuss this. Teva is the world’s #1 generics company and serves 200M people. Patients are also customers and thinking of them as such – meeting their consumer expectations – is a challenge. They want a personalized, appropriately priced, convenient and transparent treatments.

Teva sees big data opportunities in things like biosensor data and the potential for analytic/cognitive technologies like Watson to personalize medicine and find new uses for existing drugs among much more. For instance, identifying patients at risk of asthma attacks using a cloud-connected inhaler can really help people manage this chronic disease. Alerting them in advance so they can find their inhaler and be prepared to use it or even take steps to prevent it. And the investment in a cloud, cognitive, big data infrastructure is designed to create more opportunities like this. In the future, they can even see 3D printing to deliver tailored doses, identify that a pill has been taken or even control the dose a pill releases – all controlled by the system in a personalized way.

A clip from the 60 Minutes show on cognitive discussed how Watson tracks all the papers in cancer research and advises doctors on what care to suggest to patients for whom existing treatments had failed. The back test found 99% of their suggestions matched by Watson but another 30% had additional recommendations.

Continuing with the healthcare theme, Ginni is joined by Prof Miyano from Japan to discuss their use of Watson in cancer treatment. They have been scanning the genomes of patients, identifying mutations and then using Watson to find the best fit. This is hard because a typical genome has many mutations anyway and cancers can introduce many more. Huge numbers of new papers discuss treatments that might be suitable but there are millions of mutations. Watson makes it possible to find the right treatment, even in very difficult cases, giving the medical team critical information and insight.

Final section was a little lighter, with a discussion of hit songs. Alex Da Kid has been working with Watson to see how one might develop a hit song. Alex likes to ask people about very personal, very emotionally powerful moments and then use those to drive songs. He’s collaborating with Watson to analyze what people have been writing, lyrics from billboard songs and musical patterns. The result is a new song – Not Easy – that is doing well and he says he has several more resulting from the collaboration. A great change of pace.

And Ginni wrapped it up – we are, she said, changing the world and we are just getting started.

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