 From around the globe, it's theCUBE with digital coverage of IBM Think 2021. Brought to you by IBM. Welcome back to theCUBE's coverage of IBM Think 2021 virtual. I'm John Furrier, host of theCUBE. We've got a great story here navigating COVID-19 with Watson advertising and weather channel conversations. Sherry Backstein, who's the GM of Watson advertising and the weather company. Sherry, thanks for coming on theCUBE. My favorite part of IBM Think is to talk about the tech and also the weather company innovations. Thanks for coming on. Hi, happy to be here, John. So COVID-19, obviously some impact for people that are working at home. Normally you guys have been doing a lot of innovation around weather, weather data. Certainly huge part of it, right? And so lots been changing with AI and the weather company and IBM. So let's first start before we jump in. Give us a little background about what your team has created because there's a lot of fascinating things here. Go ahead. Yeah, so when the pandemic started, we looked at the data that we were seeing. And of course in weather accuracy and accurate data is really important, trusted data. And so we created a COVID-19 hub on our weather channel app and on weather.com. And essentially what it was is an aggregated area where consumers could get the most up-to-date information on COVID cases, deaths in their area, trends, see heat maps, information from the CDC. And what was unique about it, it was to a local level, right? So state level information is helpful, but we know that consumers, me included, I need information around what's happening around me. And so we were able to bring this down to a county level, which we thought was really helpful for consumers. Share has watching sports on TV and recently, a few months ago, the masters was on and you saw people getting back into real life. It's almost like a weather forecast now. You want to know what's going on in the pandemic. People are sharing that they're getting the vaccine. Really interesting. And so I want to understand how this all came together with you guys. Is was it something that as a weather data, bunch of geeks saying, hey, we should do this for companies? But take us to thought process with your team. Was it like you saw this as value? How did you get to this? Because this is an interesting user benefit. I want to know the weather. I want to know if it's safe. These are kind of a psychology of a user expectation. How did you guys connect the dots here for this project? Well, we certainly do have a very passionate team of people, some weather geeks included. And you're absolutely right. Watching the masters a few months ago was amazing to see some sense of normality happening here. But we looked at IBM and the weather company, like how do we help during this pandemic? And when we thought about it, we looked at there's an amazing gap of information. And as the weather channel, what we do is bring together data, give people insights and help them make decisions with that. And so it was really part of our mission. It's always been that way to give information to keep people safe. And so all we did is took a different data set and provided the same thing. And so in this case, the COVID data set, which we actually had to aggregate from different sources, whether it was the CDC, the World Health Organization, state governments or county governments to provide this to consumers. But it was really, really natural for us because we know what consumers want. We all want information around where we live. And then we want to see where our friends live, where our relatives live to make sure that they're okay. And then that enables people to make the decisions that are right for their family. And so it was really, really natural for us to do that. And then of course we have the technology to be able to scale to hundreds of millions of people, which is really important. Yeah, it's not obvious until you actually think about it. Then it's so obvious, congratulations. What a great innovation. What were the biggest challenges you guys had to face? And how did you overcome it? Because I'm curious, obviously you got a lot of large scale data dealing with diversity of data with weather. What was the challenges with COVID and how did you overcome it? So again, without a doubt, it was the data because you're looking at one, we wanted that county level data. So you're looking at multiple sources. So how do we aggregate this data? So first finding that trusted source that we could use, but then how do you pull it in an automated way? And the challenge was it with the state departments, the county departments, that data came in all kinds of formats. Some counties use maps, some use charts, some use PDFs to get that information. So we had to pull all this unstructured data and then that data was updated at different times. So some counties did it twice a day, some did it once a day, different time zones. So that really made it challenging. And so then, so what we did is this is where the power of AI really helps because AI can take all of that data, bring it in, organize it and then we could put it back out to the consumer in a very digestible way. And so we were able to do that. We built an automated pipeline around that so we could make sure that it was updated, it was fresh and timely, which was really important. But without a doubt, looking at that structured data and unstructured data and really helping it to make sense to the consumer was the biggest challenge. And what's interesting about it, normally it would take us months to do something like that. I challenged the team to say, we don't have months, we have days. They turned that around in eight days, which was just an amazing, herculean feat. But that's really just the power of, as you said, passionate people coming together to do something so meaningful. I love the COVID-19 success stories when people rally around their passion and also their expertise. What was the technology that the team used? Because the theme here at IBM Think is transformation, innovation, scale. How did you move so fast to make that happen? So we moved fast by our AI capabilities and then using IBM Cloud. And so really there's four key components or like four teams that worked on it. So first there was the weather company team. And because we are a consumer division of IBM, we know what consumers want. So we understand the user experience and the design. But we also know how to build an API that can scale because you're talking about being able to scale not only in a weather platform. So in the midst of COVID, weather still happens. So we still had severe weather, record-breaking hurricane season. And so those APIs have to scale to that volume. Then the second team was the AI team. So that used the Watson AI team mixed with the weather AI team to again bring in that data, to organize that data. And we use Watson NLP, so natural language processing in order to create that automated pipeline. Then we had the Corral-Ald infrastructure. So that platform team that built that architecture and that data repository on IBM Cloud. And then the last team was our data privacy office. So making sure that that data was trusted, that we had permission to use it and just know really that data governance. So as all of that technology and all of those teams coming together to build this hub for consumers, and it worked. I mean, we would have about four million consumers looking at that hub every single day. And even like a year later, we still have a couple of million people that access that information. So it's really kind of become more like the weather, checking the weather's come, that daily habit. That's awesome. And I got to imagine that these discoveries and innovations that was part of this transformation and that scale have helped other ways outside of the pandemic. Can you share how this is connected to other benefits outside the pandemic? Yeah, so absolutely, AI for business is part of IBM strategy. And so really helping organizations to help predict, to help take workloads and automate them so their high valued employees can work on other work. And also to bring that personalization to customers is really AI. When I look at it for my own part of IBM with the weather company, three things where I'm using this technology. So the first one is around advertising. So the advertising industry is at a really pivotal part right now. A lot of turmoil and challenges because of privacy legislation, because big tech companies are getting rid of tracking pixels that we normally use to drive the business. So we've created a suite of AI solutions for publishers, for different players within the ad tech space, which is really important because it protects the open web. So like getting COVID information or weather information, all of that is free information to the public. We just ask that you underwrite it by seeing advertising so we can keep it free. So those products protect the open red. So really, really important. Then on the consumer side of my business, within the weather channel, we actually use Watson AI to connect health with weather. So we know that there's that connection, some health issues that people have can be impacted by weather like allergies and flu. So we've actually used Watson AI to build a risk of flu that goes 15 days out. So we can tell people in your local area, this one actually goes down to the zip code level, the risk of flu in your area or the risk of allergies. So help to manage your symptoms, take your prescription. So that's a really interesting way we're using AI. And of course, weather.com and our apps are on IBM Cloud. So we have this strong infrastructure to support that. And then lastly, our weather forecasting has always been rooted in AI. You take 100 different weather models, you apply AI to that to get the best and most accurate forecast that you deliver. And so we are using these technologies every day to move our business forward and to provide weather services for people. I just love the automation and as users have smartphones and more instrumentation on their bodies, whether it's wearables, people will plan their day around the weather and retail shops will have a benefit knowing what the stock are not have on hand and how to adjust that this is the classic edge, computing paradigm, fascinating impact. You wouldn't think about that, but that's a pretty big deal. People are planning around the weather data and making that available as critical. Oh, absolutely. Every business needs a weather strategy because whether it impacts your supply chain, agriculture, should I be watering today or not? Even around, if you think about energy and power lines, the vegetation growth of our power lines can bring power lines down and it's a disruption to customers and power. So there's just, when you start thinking about it, you're like, wow, whether it really impacts every business, not to say just consumers in general in their daily lives. Yeah, and there's a lot of cloud scale too that can help companies, whether it's be part of better planet or smarter planet as it's been called and help with global warming. I mean, you think about this has all kind of been contextually relevant now more than ever, super exciting. Great stuff. What did your take on outside of the IBM response to the pandemic more broadly outside of the weather? What are you guys doing to help? Are you guys doing anything else with industry? How could you talk a little bit more about IBM's response more broadly to the pandemic? Yeah, so IBM has been working with government, academia, industries really from the beginning in several different ways. One of the first things we did is it opened up our intellectual property. So our IP and our technology are super computing to help researchers really try to understand COVID-19, some of the treatments and possible cures. So that's been really beneficial as it relates to that. Some other things though that we're doing as well is we created a chat bot that companies and clients could use. And this chat bot could either be used to help train teachers because they have to work remotely or help other workers as well. And also the chat bot was helping as companies started to reenter back to the workforce and getting back to the office. So the chat bot's been really helpful there. And then one of the things that we've been doing on the advertising side is we actually have helped the ad council with their vaccine campaign. It's up to you as the name of the campaign. And we delivered a ad unit that could dynamically assemble a creative in real time to make sure that the right message was getting out at the right time to the right person. So it's really helped to maximize that campaign to reach people and encourage them if it's the right thing for them, where the vaccines are available and that they could take those. So a lot of great work that's going on within IBM and actually the most recent thing just actually in the past month is we released the digital health pass in cooperation with the state of New York. And this is a fantastic tool because it is a way for individuals to keep their private information around their vaccines or some of the COVID tests they've been having on a mobile device that's secure. And we think that this is gonna be really important as cities start to reopen to have that information easily accessible. I'm sure a great insight, great innovation navigating COVID-19, a lot of innovation transformation at IBM and obviously Watson and the weather company using AI. And also, when we come out of COVID, post COVID as real life comes back, we're still gonna be impacted. We're gonna have new innovations, new expectations, tracking, understanding what's going on, not just the weather. So thanks for doing that great work. Awesome, thank you. Great, thanks John, good to see you. Okay, this is theCUBE's coverage of IBM Think. I'm John Furrier, the host of theCUBE. Thanks for watching.