>>From around the globe. It's the Cube with digital coverage of IBM think 2021 brought to you by IBM. Welcome back to the cubes coverage of IBM Think 2021 virtual. I'm john ferrier host of the cube. Got a great story here. Navigating Covid 19 with Watson advertising and weather channel conversations. Sherry back steen. Who's the gM of Watson advertising in the weather company. Sherry, thanks for coming on the cube. 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 working at home. Um normally you guys have been doing a lot of innovation around weather weather data um 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, just a little background about what your team has created because a lot of fascinating things here. Go ahead. >>Yeah. So when the pandemic started, you know 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 uh information from the C. D. C. And what was unique about it. It was to a local level. Right so state level information is helpful but we know that consumers uh 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 as 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. Um, really interesting. And so I want to understand how this all came together with you guys. Is was it something that has a weather data, a bunch of geeks saying, hey, we should do this for companies, but take us to the thought process with their 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, um some weather geeks included, um and you're absolutely right watching the Masters a few months ago was amazing to see, you know, some sense of normality happening here. But you know, we looked at, you know, IBM, 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, you know, 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, you know, aggregate from different sources whether it was the C. D. C. The World Health Organization uh State governments or county governments to provide this to consumers. But it was really really natural for us because we know what consumers want. You know we all want information around where we live, right? And then we want to see like 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. >>It's not obvious until you actually think about that. 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. I see you've got a lot of, 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 that we could use. But then how do you pull it in in an automated way? And the challenge was it with the State Department, the county departments that data came in all kinds of formats. Some counties used maps, some use charts, some use pds to get that information. So we had to pull all this unstructured data, uh, and then that data was updated at different times. So some counties did it twice a day, some did it once day, different time zones. So that really made it challenging. And so then, you know, so what we did is this is where the power of A I really helps because a I can take all of that data, bring in and 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 can 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 to 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 move fast by our Ai capabilities and then using IBM cloud and so really there's four key components are like four teams that worked on it. So first there was the weather company team um 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 A. P. I. 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 happened, so we still had severe weather record breaking hurricane season. And so those A. P. S. 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. Um And we used Watson NLP so natural natural language processing in order to create that automated pipeline. Then we had the corralled 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 have permission to use it uh and just know really that data governance. So it's all of that technology and all of those teams coming together to build this hub for consumers. Um And it worked I mean we would have about four million consumers looking at that hub every single day. Um and even like a year later we still have a couple 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 gotta I gotta imagine that these discoveries and innovations that was part of this transformation at scale have helped other ways outside the pandemic and you share how this is connected to um other benefits outside the pandemic. >>Yeah so absolutely um you know ai for businesses part of IBM strategy and so really helping organizations to help predict um you know to help take workloads and automate them. So they're high valued employees can work on you know other work. And also you know to bring that personalization to customers. You know, it's really a i when I look at it for my own part of a 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 um you know, pivotal part right now, a lot of turmoil and challenges because of privacy legislation because big tech companies are um you know, 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 you know, different players within the ad tech space, um 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 used Watson Ai um to connect health with weather. So we know that there's that connection, some health um you know, issues that people have can be impacted by weather, like allergies and flew. So we've actually used Watson Ai to build a um 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, um the risk of flu in your area or the risk of allergies. So help to manage your symptoms, take your prescription. So, um that's a really interesting way. We're using AI and of course weather dot com and our apps are on IBM cloud, so we have this strong infrastructure to support that. And then lastly, you know, our weather forecasting has always been rooted in a i you take 100 different weather models, you apply ai to that to get the best and most accurate forecasts that you deliver. Um and so we are using these technologies every day to, you know, move our business forward and to provide, you know, 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 and or not have on hand and how to adjust that. This, 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 is critical. >>Oh, absolutely. You know, every business needs a weather strategy because whether it impacts your supply chain, um agriculture, should I be watering today or not even around, you know, um, if you think about energy and power lines, you know, the vegetation growth over power lines can bring power lines down and it's a disruption, you know, to customers and power. So there's just when you start thinking about it, you're like, wow, whether really impacts every business, um, not to say just consumers in general and their daily lives. >>And uh, and there's a lot of cloud scale to that can help companies whether it's um be part of a better planet or smarter planet as it's been called, and help with with global warming. I mean, you think about this is all kind of been contextually relevant now more than ever. Super exciting. Um Great stuff. I want to get your take on outside of um the IBM response to the pandemic more broadly outside of the weather. What are you guys doing um 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 you know working with government academia, industry is really from the beginning uh in several different ways. Um you know the first one of the first things we did is it opened up our intellectual property. So R. I. P. And our technology our supercomputing 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. Um Some other things though, that we're doing as well is we created a chat bots that companies and clients could use and this chat but could either be used to help train teachers because they have to work remotely or help other workers as well. Um and also the chatbots was helping as companies started to re enter back to the workforce and getting back to the office. So the chatbots been really helpful there. Um and then, you know, 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. Um It's up to you is the name of the campaign and we delivered a ad unit that can dynamically assemble a creative in real time to make sure that the right message was getting out the right time to the right person. So it's really helped to maximize that campaign to reach people um and encourage them if it's the right thing for them, you know where the vaccines are available. Um and that you know, they could take those. So a lot of great work that's going on within IBM. Um and actually the most recent thing just actually in the past month is we release the Digital Health Pass in cooperation with the state of new york. Um and this is a fantastic tool because it is a way for individuals to keep their private information around their vaccines or you know, some of the Covid test they've been having on a mobile device that's secure and we think that this is going to be really important as cities start to reopen um to have that information easily accessible. >>Uh sure, great insight, um great innovation navigating Covid 19 a lot of innovation transformation at IBM and obviously Watson and the weather company using AI and also, you know, when we come out of Covid post, post Covid as real life comes back, we're still going to be impacted. We're gonna have new innovations, new expectations, tracking, understanding what's going on, not just the weather. So thanks >>for absolutely great >>work. Um, awesome. Thank you. >>Great. Thanks john good to see you. >>Okay. This is the cubes coverage of IBM. Think I'm john for a host of the cube. Thanks for watching. Yeah.

>> Announcer: From around the globe. It's theCUBE with digital coverage of IBM Think 2021, brought to you by IBM. >> Oh, welcome back to theCUBE's coverage of IBM Think 2021 virtual, I'm John Furrier, your host of theCUBE. We've got a great story here. Navigating COVID-19 with Watson advertising and weather channel conversations, Sheri Bachstein, who's the GM of Watson Advertising in the weather company. Sheri, 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 working at home. Normally you guys have been doing a lot of innovation around weather, weather data, certainly huge part of it. And so lots been changing with AI and the weather company and IBM, so let's first start before we jump in just a little background about what your team has created because 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 >> Sheri's 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. Was it something that as a weather data and a bunch of geeks saying, Hey, we should do this for companies but take us to thought process 113. 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, a state governments, our 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, right? And then we want to see like where our friends live, where our relatives live to make sure that they're okay. And then if 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, I see 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, 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 used 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 can 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 I'll, 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 did the team use? 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 the 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 happen. 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 collateral 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 have permission to use it and just really that data governance. So it was 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 4 million consumers looking at that hub every single day. And even like a year later, we still have a couple million people that access that information. So it's really kind of become more like the weather checking the weather, that daily habit. >> That's awesome. And I got to imagine that these discoveries and these innovations that was part of this transformation that scale I've 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 they're 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 a 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 saying advertising so we can keep it free. So those products protect the open read. 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 it 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 an 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 a hundred 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 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 to stock or not have on hand and how to adjust that this 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, weather really impacts every business not to say just consumers in general and their daily life. >> 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, with global warming. I mean, you think about this is all kind of been contextually relevant now more than ever super exciting, great stuff. I want to get 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. The first, one of the first things we did is it opened up our intellectual property. So our IP and our technology, our 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 Chatbot that companies and clients could use. And this Chatbot could either be used to help train teachers because they have to work remotely or help other workers as well. And also the Chatbot was helping as companies started to reenter back to the workforce and getting back to the office. So the Chatbot has 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 can dynamically assemble a creative in real time to make sure that the right message was getting out the right time to the right person. So it's really helped to maximize that campaign to reach people. And they 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 going to be really important as cities start to reopen to have that information easily accessible. >> Awesome Sheri, great insight, great innovation navigating COVID-19, lots 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 going to be impacted. We're going to 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. >> This is theCUBE's coverage of IBM Think, I'm John Furrier, the host of theCUBE. Thanks for watching. (upbeat music)