from the Silicon Valley Media Office in Boston, Massachusetts. It's theCUBE. Now, here's your host, Dave Vellante. Welcome to CUBE Conversations, everybody. We're going to have a conversation about how customers are getting, gaining analytic insights and what role both infrastructure and software play in that equation. Jeff Kelly is here. He's a data strategist from Pivotal and he's joined by Ted Bartos, who's a Senior Director of Product Management for Hybrid Cloud Platforms at EMC Dell. Gentlemen, welcome to theCUBE. Welcome back, Jeff. Welcome back both of you, CUBE, both CUBE alums. Jeff, you've done a million CUBE interviews. I've done a few. Good to have you back here in the Wikibon studio. So, you guys have big announcement. We're going to talk about that. We're just, you know, fresh off strata, where we sort of had a full dose of what's going on in the ecosystem and some of the problems that we're seeing. So, Ted, let me start with you. Maybe you could sort of summarize off of strata and as well as what you've been seeing in the customer base, what are some of the big challenges that our customers are facing and then we can talk about how you guys are addressing those. Sure, thanks, Dave. And thanks for having me. You know, coming off of strata and actually even over the last year of really working on directed availability of our big data solution, what we've really seen is a couple of key things. One, customers are looking for an end-to-end analytics lifecycle solution. They're looking for someone to deliver them the software componentry and the infrastructure that can take them from discovering data, ingesting it, the analytics, surfacing the insights, and then actioning, having actionable insights, being able to action them so that they can ring the monetary value out of it and get the business value out of it. In that, so for that fully analytic lifecycle, they also want it to be self-service, right? The people in IT that we're talking to, they really want to be the hero to the data scientists. Right now, they're underserving them just because of the environment's so complex so when they get a request to stand up a Hadoop environment or a big data environment, it takes a long time and then sometimes those data scientists or the data science professionals go out to the cloud and that's through underserving them. So they're looking to get to a governed, quota-managed self-service environment so they can really empower data scientists at the time that they wanna really investigate insights, prove out hypotheses. And then the third part of it really is to deliver that as a fully engineered turnkey solution so that we can really help them and out of pivotal and James Waters talks about above the value line in development, there's also an above the value line in big data that we really want to take the data science professional and bring them to the point at which they're really focusing on how they deliver value to the company and we take the burden off of them in terms of the infrastructure and software stack gymnastics that they might need to give. Jeff, when you think about sort of the evolution of the whole big data ecosystem, it sort of started with Hadoop, really started it all and people will debate, well Hadoop doesn't equal big data and vice versa but that really was what it got started and the beginning is what is Hadoop and then it was, we saw the distro wars, everybody was jumping in and now the ecosystem is exploded, there's an explosion of complexity and a lack of applications. That's in part anyway, why Pivotal was formed. So where are we and how are you helping address both the complexity problem and the lack of applications? Well, you're absolutely right. From a complexity perspective, I mean, if you were at the floor, Strata Hadoop wrote last week through our, I don't know, 100 vendors, you know, half of them I hadn't heard of before and a number from last year weren't there anymore. So there's a lot of complexity going on, there's a lot of different components required from the technology perspective from to address the entire data life cycle. So that's absolutely true. I think you need to step back though and when we talk to customers is think about first and foremost, what's the business problem you're trying to solve and if you start there and then work back to the technology I think that's probably the better approach rather than I think what we saw in the early days especially with Hadoop, you know, people were deploying Hadoop and they're so-called data lakes and they were filling it with data but ultimately they didn't know what to do with it and it was very difficult to monetize that data because they just didn't know what the use case was. So, you know, when I was here at Wikibon our research thesis was that the companies that really gonna get the most value from data they're gonna do it through applications. And Pivotal really was in part created to help facilitate it, facilitate that, help that actually become a reality. So really going from managing your data to analyzing it to coming up with insights and then ultimately delivering those insights in context to users through applications. And if you think about, you know, if you think about the disruptors in Silicon Valley, they do this really well. So somebody like Uber, somebody like Netflix, you know, they, I'm sure they use data in the traditional sense in the background they're running data warehouses and reports but ultimately they would, they impact the customer experiences through surfacing insights and their applications. So, you know, with Uber you request a car, you get a little pop-up, this says it'll be here in three minutes. There's a lot of data science behind that little pop-up. It seems simple, but there's a lot of data science happening and ultimately you don't need to be trained on how to use that app. It's just in the context of what you're trying to do is get from point A to point B. So Pivotal, we're trying to help our enterprise customers do the same thing. And that's really what we're all about. Well, the early days as well of Hadoop and Big Data where sort of the ROI was reduction on investment. We sometimes joke, but it was true. It was that big sucking sound from the enterprise data warehouse. And you're right, people just throw stuff in the data lake and people again tongue in cheek, they joke about the data swamp, but there's a lot of truth to that. So what are you guys specifically announcing? How does it help people get insights from analytics and how does it help with that sort of data flow, data pipeline? Sure, thanks. So we're announcing the analytic insights module at Dell EMC World. And what it really provides is it provides that full analytics lifecycle coverage. So it provides capabilities for data scientists as they're looking to build out and discover the data that they need to fill out their analytics model. It provides them the ability to see what's in the data lake as well as to be able to go out and sample data stores, content stores in the enterprise and even in the cloud. And within a button click to be able to see how that data model is coming together in completeness to see the relations that are done. So for the full analytics lifecycle on the front end, one of the key bottlenecks is that 80% of the time data scientists has spent finding and blending wrangling data. So we're focused on the full life cycle, really some help on the front end so that we can help them not necessarily have to push everything into the data lake but what's in the data lake is high use but then on demand by being able to investigate, analyze, sample, analyze and bring in data on demand. So the full life cycle, a tailored user experience. So we built the user interface using Pivotal Cloud Foundry. It's a PCF app and it's really a tailored user interface to those data science personas of the data scientists, the data engineer, the data architect, the business analyst and we deliver that as a solution as a by verse build proposition to our customers at both the infrastructure for the converged infrastructure as well as the solution stack on the top that provides the key solution components on there which we talked about data investigation hitting the 80% time, we also have the data ingestion, the data ingestion module that we're partnering with the company on and then one of the key things and especially as we penetrate the financial services, healthcare, highly governed verticals, really strong security component that has very deep granular security with attribute based access control so we can address things like data sovereignty at that level. And so it's the full life cycle, the tailored persona directed interface to really speed the discovery and delivery of insights. We're putting that on the converged infrastructure platform and then because we're a PCF app and we have our native hybrid cloud solution which is PCF on our converged infrastructure, the analytic insights module sits on top of that so that when the data scientists builds their data model and they build their modeling of the analytic model, they're on that same platform seamlessly working side by side shoulder to shoulder with the app developer that can then bind to that, connect to that data service and to be able to deliver the applications like Jeff was talking about those Uber applications, the ones that'll monetize it, right? Applications in a broad sense and software applications in that consumer market facing applications that give you a deeper relationship, more timely relationship with the customer, embedded systems, software applications that improve operational efficiency like predictive maintenance or IT operation analytics but then also even dashboards or reports that come out from software to help businesses make better strategic decisions. So it's an end to end solution based on the premise that data's going to be wherever the data is, you're bringing in models to actually help people understand what should go into the data lake and then you've got tooling to get insights out of the data and ideally operationalize those. So sort of end to end solution integrated sort of out of the box, if you will. What piece of that is Pivotal? So Pivotal Cloud Foundry is the platform which this runs. So Pivotal Cloud Foundry is a cloud native platform that supports that kind of agile application development process and continuous delivery. So you're continuously shipping code and that kind of modern application and software development methodology. So that's where one place that Pivotal comes into play from an analytics perspective. So the solution can call out to different data sources that can include Pivotal Green Plum, Pivotal HDB which is our Hadoop native SQL analytics database could even include more transactional type systems like Pivotal Gemfire which are in memory data grid. So it plays a role both on the platform side as well as on the analytics side. Okay, and what about other sort of ecosystem partners that are part of the solution? Maybe you could talk about that a little bit. Sure, so when we went with the directed availability of our big data solution, we really interacted with the model that's really what drove us to that persona-focused interface. You know, get the user, get the key persona users, data scientists, data engineers above the value line, get them really focusing on how we speed their time. And so when we took a look at the key components for the data discovery portion of it and the ability to not only see and be able to search at what's in the lake and in the enterprise data catalog but also go out and discover additional content stores in the enterprise or even in the cloud we've partnered with Tivio, a company out of Newton with a long pedigree in enterprise search and really they've been focusing on big data and the data discovery portion. For the ingestion capability, we're really looking for someone, when we took a look at ingestion, we wanted a couple of things. One, someone with a really open platform like a workflow engine for ingestion so that you could use different, whether it was streaming, whether it's batch, whether it's Spring XD or whatever you wanna use there, Kafka, that those could be woven into a workflow and we chose Zoloni as our partner for that. Open API, great workflow, great pedigree in the market. Another thing about them in the Tivio is both have a long pedigree of services delivery to the market so they really get it, right? They've been out at companies really solving problems and that's pragmatically, that's how we wanna approach it is very pragmatically. On the security side, as we're bringing all this data together and you have your data lake and then you're gonna go out to content stores, you're gonna be able to sample them, as soon as we're working with a financial institution or anybody, HIPAA help, they're saying, well, okay, great, you can break down the silos, you can bring all the data together, how do I make sure that only the right people can see the data, right? I think the statistic is in breaking down silos and big data, 70%, north of 70% of the people are seeing data they shouldn't have access to. So we partnered with a company called Blue Talent and they were at Strata Adoop, they won awards at the last few and they provide very deep, very granular cell row column level security. They provide the ability to obfuscate, redact or even tokenize data so you can still do joins with tokenized data. But it's all policy driven and it's at attribute-based access control. So beyond role-based access control, but it provides attributes. So you can say for any attribute of someone in ADL or LDAP, what country are they in, right? Do you think of data sovereignty and data that's authored in Germany needs to only be viewed by people in Germany. So you're able to have a very flexible, very rich, very deep security model that you can apply to the different content sources through a policy enforcement point. And those three companies, when we went out on top of that experience and we looked at that workflow, we first went through the workloads, the key needs. Then we identified the key characteristics and capabilities that we wanted. Then we went out, looked at a range of buy, build partner. And that's how we came up with the three partners we chose. It was really pragmatic. And I purchased this solution from Dell EMC, right? I don't have to cobble together all these solutions. Ah, yeah, great point, yes. So one of the key assets of us delivering a fully engineered, validated solution is that there's a single line of support. So some type of complexity, as Jeff was mentioned, you walk around Strada Hadoop and you see all of the different applications. And that's where that complexity comes in and it's what's really stalled a lot of companies and setting up the right environment. So we set up that environment, we engineer it, we test it and we stand right behind it with a single line of support. So to the end user customer, this rolls up on the dock, it gets set up, it gets stood up. You have the full workflow, you have the persona and you only have one number to call if anything happens to the system. Jeff, I want to explore this notion of personas. So you have the data scientist, you have data engineer, you have a business analyst, you have an application developer. How are you guys seeing those personas evolve? How are they related? They're gray lines, unpack that for us. Well, that's part of what really excites me about this solution, that it helps bring that world of data and applications together. So traditionally those worlds were very separate. So you had your data warehouse team, your BI team, creating reports, ingesting data, cleaning the data and then you had your application development team that was creating your enterprise applications and the two very rarely taught. Data went from your transactional, operational applications over to the data warehouse but other than that, there wasn't much of a relationship. Insights from your data warehouse very rarely made it back to your applications. So what I really like about this solution is trying to bring those worlds together. In terms of how those roles are blurring, you know, it's still evolving. I mean, if you go to most enterprises, it's still the case that they don't talk very much. You know, part of what we're trying to do at Pivotal, you know, our mission is to transform how the world builds software and kind of bring the way Silicon Valley companies build software, bring that to the enterprise.  They're working very closely together. They don't look at it as, you know, one or the other. And so we're trying to bring that mentality to enterprises. And frankly, it's a learning process for a lot of our customers. But we, you know, we work very closely. We do through our Pivotal Labs organization, through our Pivotal Data Science organization, working side by side with our clients, data scientists and application developers, helping them learn to work together, educating application developers about, to start thinking about when they're building applications where analytics and insights might actually improve their application. Start thinking about the outcomes you're trying to achieve and how data might be able to help that. And similarly, from a data science perspective, start thinking about, you know, this isn't just a science experiment. Think about, you know, as you're getting to the point where you're creating some really interesting insights, how could this actually impact the business? And then creating those lines of communication between the two. So it's just as much about culture or communication as it is about platforms and technology. Well, and as well, to what extent can you automate that cleansing part where data scientists spend 80% of their time wrangling, you know, and figuring out if this data even has the quality necessary, which in part, by the way, has to involve the line of business, to say, okay, is this right? How can you help or are you helping? Well, I think the way we look at it is, in a lot of ways, you can look to new advances in machine learning to help with that, help classify data. That's really a role that that can play. You know, but it's still, there are still areas where it's somewhat a manual process. There are tools out in the market that can help you, you know, cleanse data. There are data quality tools, data quality vendors out there. I think from Pivotal's perspective, if you look at our data science team, for example, and when they're doing engagements, you know, they really try to put machine learning and data science itself to work to solve the data quality problem. You know, machine learning can help you understand what data you have, can help classify data, things like that. So that's one way to approach it. I think ultimately that's the direction the market's going, versus kind of more manual tooling. Still pretty early, you know, there's a lot left to do to kind of crack that nut. But I think machine learning is going to play an important role in data quality. Ted, you're part of the solutions organization at Dell EMC, which has had sort of a long history. What specific industries are you going after? You're building solutions for, you know, those various industries? Yeah, great. We are, we're targeting it and we're really looking to build out the platform very pragmatically.  And you know, so what we're doing is we're really targeting specific verticals and using that to pragmatically build out and extend the platform itself by saying, okay, these problems really is the one problem that only affects one market, but let's really go in and deliver value in those particular verticals. And the verticals that we're targeting have shown a good appetite of consuming big data well and going into production with it. Telco, telecommunications, healthcare, financial services, oil and gas and manufacturing because of the IoT influence on streaming analytics and also core and core analytics. So we're really focusing on those markets and the partners and some of the success that we've had, you know, partners, healthcare, where we really sped their ability to get to better health results for people using their services, that those are good examples of, you know, how we're targeting a specific business outcome, delivering value, but then taking that back to the platform and then extending it. So that's just even out much easier for the personas that are using it. Historically, Jeff, if you go back, data and applications were very tightly intertwined and all the data was locked inside the application and then the enterprise data warehouse emerged and, you know, the next generation decision support systems came out and you had business analysts, which was all well and good, but it was like insights for a few that by the time they got to the business were outdated, we all sort of know and lament that problem.  So, but the concept of an analyst or a business person that can be at least a quasi, you know, data geek is seems to be happening. So do you sort of agree with that progression of business outcomes, data tied to business outcomes and are we close to actually seeing that data operationalized and much more widely distributed throughout the organization to have business impacts? Well, I agree absolutely that any, you know, worker, business worker, business knowledge worker can do a better job if they have better information at their fingertips. So that's absolutely true. The question I guess is how do you get to that point?  And to do that, it gets right back to that whole point about integrating insights into your applications, delivering them in context. So whether that's, you know, if I'm a sales person, I'm in my CRM application all day, if I can deliver some insights through that, through that application, that's not necessarily a bar chart or a graph but actually give you some recommendations on the next actions you can take. Maybe for this customer you should call them and make an offer for this or maybe this is a customer that might be a little angry, you might want to reach out to them. If you can turn those insights into actual recommendations that they can take action on, I think that's the most valuable. You know, that said, there's still value in, you know, kind of self-service dashboards and visualizations, you know, companies like Tableau and Click are very popular because of that and there's definitely still value in that as well, kind of taking a step back and saying, hey, I'm going to examine some data, see if I can find some insights. But I think on a day-to-day basis, you know, we're all short on time and I think the more you can use insights to actually help people be more efficient and do their jobs in a smarter way, I think that's really where the big benefit comes in in terms of business users. How, go ahead please. Yeah, I just wanted to interject one thing on the platform and a response to that and your question directly. So, you know, one of the things we found is the ability to turn, you know, raw data in the enterprise out in the cloud into a real digital asset, right, is one of the key things we kept hearing from customers. So, one of the capabilities we had was that, to kind of speak to your question, you have the data scientists and they're building these models and they're targeting a specific outcome, but that data model in itself, once they pull that data together, blended it, wrangled it, cleansed it, we have the ability in the platform based off the customer, you can actually publish that into a data catalog that we have. So, it's one way to sort of leverage the data scientists to do, you know, some of the deep data science, but then take that model and publish it with full security so they can bind a tableau to it or if they want to do some further analytics or whatever, they can have a good starting point instead of having to start all the way from the beginning and finding the data. And that, you know, a couple of things is we talked with customers, some of the wow factors, right, of the analytics, you know, the self-service is good, IT loves it because now they can be the hero to the data scientists and the business from maintaining governance, but some of the wow factors are the publishing, the ability to do that so that raw data becomes an asset. And then the other one is really the interaction between the analytic insights module and native hybrid cloud and that when we show customers the fact that they can take those data models and then bind to them directly and really break down that barrier, right, to a deliberate platform between data science and application development. You know, that's the one where they're like, okay, we want to see you demonstrate that to us. That is really exciting, right?  It dies in PowerPoint somewhere. You give a presentation to the board or the C level and they're like, this is great, but there's no way to actually turn that into an application that's gonna do something to help your business. I think that's one of the big challenges that the industry faces. And I think that's, you know, one area that we're really trying to help. And being able to improve that over time. Oh, absolutely. It's a learning process. The more interactions that happen, the smarter the algorithm becomes. And that metadata catalog is your technology? That's the deli and C? It is. That's what we built on top of. We built that on top of that infrastructure. We have partner software. We have the solution software that really provides the workflows. We're actually patenting some of those workflows and integrations as a method and apparatus patent. We built the data catalog on the top. We do, you know, in the data catalog, one of the things you're gonna immediately do is go, as a data scientist, you're gonna say, well, I don't wanna start from the beginning. What's in the lake? What's in my catalog? That is, we do leverage the search capabilities of Ativio.  And that'll search across the lake, across any of the attached content stores and in that data catalog. So we can present you, hey, I've got curated data already that has the majority of the content you're looking for. And that allows them no faster way to speed an 80% bottleneck than to take it out of the game. You mentioned machine learning before. Are we getting to the point where machine learning and techniques can actually recommend to the data scientist which algorithm to use and what the best fit is?  It's a little meta, but yes, we're getting to that point. Where, I mean, in fact, that's, I think, one of the real killer use cases for machine learning is, in fact, the data quality question, data classification, kind of the discovery process where you're just trying to figure out what you have. Machine learning can play a huge role in that. And in fact, we're seeing that with our customers, our data science team, you know, it's been around for years now, started way back in the Green Plum days, has now grown out to a quite a large team. You know, they use those kind of techniques, whether it's something like Apache Madlib or other machine learning libraries to actually do that kind of early classification process. I'll run out of time, Ted, but go ahead, please. And just one last thing on there. So when we're, you know, as Dell and EMC came together, you know, one of the key areas that is just a beautiful sort of, you know, peanut butter and chocolate, a one plus one equals three is around IoT, right? Is around Dell's presence in the gateways and our presence in the core and being able to weave those together. The reason why I bring that up is that's a big area for machine learning, right? The ability to at the edge have your analytic model, you know, giving you near real time feedback at the edge, but then taking, you know, longer term time series and more of the data back to the core and then using machine learning to actually improve that analytic model out at the edge. So we really have this beautiful situation where we can have this like continuously improving loop, right, through deep learning. Well, it opens up the door for a manufacturing vertical solution as well, where, you know, there's a backlash in a lot of the products that are coming from overseas. You know, consumers in the United States are saying, wow, they don't have the quality that I expected. And you are seeing a slow shift in some industries back to, you know, onshore manufacturing. Perhaps, you know, data science can either solve the problem of quality, you know, overseas or, you know, bring some of the manufacturing back to the States. We'll see. So before we close, you mentioned a directed availability a couple of times. What's the availability of these products? You know, when do they go GA? So we're going to be launching and announcing the analytic insights module, analytic insights on native hybrid cloud at Dell EMC World, which is from October 18th to the 20th. And the GA, the complete availability, you'll be in the first week of November. And so people will be able to, you know, get to their EMC sales person, will be out in GA availability. And how do you price these solutions? Is it sort of small, medium, large? Is it? Well, it is. We have models, because it's such a scalable business, right? In either way, how many federal cloud foundry application instances do you need? How many, how much storage do you need for your big data? How many cores do you need to process that big data? We price it. We have kind of a pinpoint as a starting point for companies. One AI pack, so 50 AI instances. 75 terabytes of usable HDFS storage. About 90 or so cores on a converged infrastructure platform. And that really, that's kind of the seed. A lot of companies can start right there. They have everything, we deliver it, they open it up, and then they can scale out in any direction. More pivotal cloud, more application instances, more storage, or more cores. And so we're prepared to go on that journey with them and give them a really nice model that they can extend in any direction. So that's the starter kit. Have you announced pricing for that starter kit at this point? We'll announce it at EMC Dell, EMC World. All right, Gents, great to see you again. Thanks very much for coming on theCUBE. Jeff, Jeff, welcome back. Good to have you. Thanks for watching everybody. We'll see you at Dell EMC World. This is theCUBE. Thanks for watching CUBE Conversations.


Life is good all this month at Appalachian Wireless. Get the LG G5 for just one penny with sign up or renewal of a two year service agreement. That's almost $100 off the regular price. Better service, bigger savings. That's today's Appalachian Wireless. Hundreds came out to the Carl D. Perkins Job Course Center in Prestonsburg today to attend college and career day. Floyd County Schools, community members and job course students were able to visit over 45 vendors that ranged anywhere from healthcare professionals to fast food. Officials say more than 400 participated in today's college and career day, making it the largest one yet. Well, of course, jobs have been down in this area and it's very important for our students here too because that's what we do is we're job course.  So we like to bring the community in and bring the vendors in and let them see we can produce students for you and there's also people here that need jobs. And some vendors have already noticed what working with the job corps can do for their business. For us personally here, they have an outstanding security program where they're teaching their students security procedures which falls right in line with what we do in our line of business. Many vendors were able to explain how to work your way up from a starter job. Here in Easter, Kentucky, we do have some unemployment issues. So just to get the word out there, there's places you can work, McDonald's and there's a lot of other businesses here today, but there's a lot of careers that the kids can get into at McDonald's, advertising, our food prep, service related jobs, things like that. The Carl D. Perkins Center hosts two college and career days a year. Reporting in Prestonsburg for EKB News, I'm Shelby Steele.


Hey what's up guys welcome to our trending reviews so these are the mixed that e10 wireless active noise cancellation headphones let me go ahead and give you an unboxing a setup and a review of actually how they sound so let's get straight into it. All right so in the box you can find that it comes with the actual wired 3.5 millimeter headphone adapter cable it also comes with a micro usb charging cable and you also get a free airplane adapter as well so if you wanted to listen to this on flights then you can do that perfectly well and it also comes with this really cool sticker as well if you want to use this wherever you'd like to you also get a user guide to help you set up and get up and running now just to give you a bit of a overview on the design you can see the actual earpieces on the side they've got this nice metallic finish it's got a plastic casing around where the buttons are and it has some very comfortable memory foam padded earpieces along the top the actual headband is quite rubbery and it's padded as well so that gives you comfortability and then also you get the mixed logo with a metal casing for adjusting the actual headband size on the left earpiece you only have one port there it's the micro usb charging port on the right earpiece you have a few buttons you have the actual headphone jack you have the left and right playback buttons and then you also have the power button which doubles up as a multifunction button as well so one thing I really like about these headphones is that they give you a massive 30 hours of battery life by all means it's not the longest battery life on headphones like these but it does an excellent job giving you all the power you need now this comes with something called msc which is mixed up super charging technology now what that means is within five minutes you'll get up to three hours of battery life in this to give you some awesome playback although it's not usb c which is a bit of a shame but they've compensated that with that msc technology in there now one thing I really like about these headphones is that it comes with apps x low latency technology now what that is that is a chip that goes into these headphones which is developed by qualcomm and that gives you a full synchronization between the audio and video playback when you're using these on the bluetooth and wireless settings so if you're watching a movie let's say on your laptop you have this connected through your bluetooth and you're using this wirelessly sometimes in wireless headphones you have a bit of a lag in between the audio coming through compared to the video and sometimes you can pick it up sometimes you can't but that technology in this the aptX low latency technology it's just completely blown all the other mixed headphones out of the water now it's got full synchronization it's instantaneous you're barely not going to notice any difference with the synchronization now I'll leave a link in the description below on where you can learn a bit more about that technology from the actual qualcomm website they've got more information and some really good other products that actually utilize this technology as well so definitely check that out now overall this comes in at 90 pounds on amazon now I'll leave a link in the description if you guys want to check that out maybe purchase that as well but let me go ahead and connect this to my phone and give you a review of how it sounds so I will be turning on the active noise cancellation as well to see how much this cancels up because one thing I really like about it once you turn on the ANC button there on the right earpiece this actually cancels up to 96% of noise in the background now that's probably the highest I've seen on a lot of these ANC wireless headphones there's other headphones that have about 85 or 80 percent noise cancellation but this is 96 so pretty much almost the whole world around you is just going to be blanked out so looking forward to trying that let me go ahead and connect this and give you a review okay so I've just connected it to my phone now just before I start playing something I just want to give you guys a look on the design of when you're wearing it so this is the left side view this is how it looks straight on now it's not too bulky it's actually quite compact I've seen some wireless headphones that are huge I feel like they're very comfortable so it doesn't really feel like anything's on my ear because the memory phone pads are softer than a lot of the previous wireless headphones I've reviewed now I've reviewed a lot of mixed headphones as well I'll link them down below if you want to check those up but some of them after a long period of time they do start hurting your ears obviously it depends on the size of your ears but do they sit on top of them do they completely cover all of them that's something you need to be aware of this one sits slightly on top of the actual ears as well but I have larger ears than most people let me go ahead take my hat off okay let's go ahead play some music some top quality even with ANC off and the volume about 65 percent it's still quite hard to hear myself now I'm going to turn on ANC and see the difference I absolutely cannot hear myself speaking right now it's crazy a lot of the previous headphones I've had with the ANC feature on I can slightly hear myself here nothing it feels like I'm moving my mouth and nothing's coming out now the bass in it I think is actually really good as well so I can feel the punch coming through the speakers are very top quality and I can see myself wearing this especially when I go on flights it will do an excellent job I can imagine this is not going to start hurting my ears from wearing this for at least like two three hours in a row and if I'm going to be wearing it in the gym no problems I probably don't even need the ANC on to be honest and it does a really good job without that so very comfortable quite compact I would see myself using this long term probably one of the best mixed headphones I've had I'll leave a link in the description below on where you guys can check that out if there's anything else you want to know about this headphones or any of the other mixed headphones I've reviewed then do drop a comment below otherwise I have a lot more headphone reviews coming out in the future I hope you subscribe so you won't miss those ones I hope you like this video and I will catch you next time take care


What's going on everyone? Sam here with Leighton Sports Cards and I am doing a four box mixer for Brett S. That includes 1-21-22 Don Russ Elite Basketball, 1-22 Tops Pristine Baseball, and 2-21-22 Court Kings Basketball. So here we go. Start off with the Elite. That's gonna double check. I think all card ship on this, but let's see. Yep, all card ship. Okay. So just pretty much the numbered stuff and autos out of this I would say unless there's a big short print, but not a lot to talk about here which is good. All right. I remember right when we first started we were doing six boxes of this all the time. That was tough. Got David Johnson on the Hollow Rookie to 999 for the, what is this? The Raptors. I couldn't think of that for a second. Oh, JOK out of 30. Velocity auto. Nice. Yeah. Yeah, Caleb had a really nice Black Pandora Newsome yesterday. He pulled Anthony Schwartz RPI too. James Hardin prime numbers. Yeah, he did. He did pretty well actually. Yeah, Ari, we're excited for some more optic too. Got gold to 10. Power formulas Julius Randall. Nice one there, Brett. Congrats on that, man. Brad, I'm assuming you're an easy, you have easy card fan. Are you Sons and Diamondbacks, I guess? Is that what you're looking for? That's the only one I've seen, to be honest, Jim. Yeah, Caleb pulled the RPA out of optic yesterday, which I haven't seen. Really? Yeah. I mean, those like aren't even case hits. It's weird. Orange Devante Graham Pelicans. Base. All AZ teams. Got you. All right. Let's pull a, Sons don't have a ton of rookies this year. Maybe we'll be able to pull like a, some sort of veteran auto. Right on cue. Kevin Johnson impact impressions. Nice hit there. Little bit of a PC hit right there for Brett. Congrats, man. Nice. That works. All right.  Nice Kevin Johnson auto. That's why I was literally like, I was like, maybe we'll pull you a vet. Boom, right there. There you go. Brett, Congrats on that. We've got Bradley Beal. The acetate insert. Thank you, Vaughn. I appreciate that. Vaughn said I was impressive. That means a lot coming from Vaughn. Got red. Patrick Beverly to 79. Pat Bev.  Base on the end there. Fresh orders really quick before I go on to this next one. Orange and Free Simons. Base. Star status. James Harden. Base. Yeah, we will be. We'll be doing breaks at night in the store, Jen. So national breaks start tomorrow. Got Jason Tatum primary colors. Nice hit there. Nice card there. So we'll be doing daytime at the national. And then we will be doing nighttime this week. So Brad and Matt will be breaking. I'll be here training. Sean will be here top loading most of it because I'll be doing Miles McBride to 210. Nice little color match rookie there for the Knicks. So I'll be training to do group breaks in the near future when, you know, people are out or they just want to throw me on a day. And then Matt will be breaking most of the time as well as Brad. Power formulas, Kwi. Not numbered. Base. Ooh, redemption. This is a redemption. Yohkich, Griffin, and Bobby Portis. See, what do we got here? Honoris Elite. Passing the torch signatures. That's going to be a dual auto, I believe. Passing the torch. Card number 10. James Book Knight, Ray Allen. That is so sick, dude. I'm from Connecticut and I'm a huge Yukon fan. That's the Yukon connection right there. That is so sick. Congrats on that one, Brett. That is awesome, man. Book Knight and Ray Allen. Wow. So that'll be Book Knight Hornets. And I have to imagine Allen probably either Sonics, Box, Heat, or Celtics wherever he played. That is so cool. Congrats, man. Nice hit there. Yeah, it's a lot of fun, Bexcon. Yeah, it's always been my dream since I was like a little kid. Since I was like 11 years old and I was trading cards with people on Instagram. I've always wanted to do this. Got LeBron James on the Spellbound. Nice one there. Yeah, definitely, definitely. I know you always jump into a lot of the football stuff, Jim. So I know what we'll be doing mostly. It'll be pretty much the same like baseball, basketball, football at night. Got Orange Jeremy Grant. So there'll definitely be some cool stuff to jump into. A couple new releases in the coming weeks as well. Like Select comes out soon. Clint Capella Orange. So there's definitely some cool stuff to look out for. I know we got some soccer coming out this week. No impeccable soccer comes out, which should be pretty cool. Spellbound. Dicut. Chris Paul, not numbered. Sons. Sons fan. That's CP3. Got Chris Paul again. This time the Clarity Insert. Nice one there. That is an acetate. Kind of like a see-through thing. Based on the back there. Two packs to go. See something else numbered here. See a numbered Sons guard. James Hardin on the... Ooh! On the dimensions! Case hit! James Hardin! Congrats on that one, Brett! That's awesome! Yeah, isn't that like the holographic thing? That's so cool. Well LeBron one's really cool. It has like him in the calves. How do you do that? It's him on the Lakers. So cool, man! What a card right there! Heck yeah!  That's sick! It really does like something straight out of the early 90s. That's so true, Randy. Yeah, that's like a super, super short print. Kevin Herger on the orange and base. The Houston Rockets as the team. Let's do pristine next and we'll finish with Corkings. We'll break up the basketball a little bit here. All right, so you're looking for diamond backs. I don't know. I don't think there's a lot of diamond backs in this product. I gotta be 100% honest with you. Maybe Randy Johnson has an auto in this as a d-back. I don't know, to be honest. I can't imagine it's a huge checklist. Yeah, that was a pretty good box of elite for sure. Good, really good auto. Pretty, and then a PC auto and then a case hit, which is sick. So definitely pretty cool there. Maybe we can get a former diamond back hit. That'd be nice, Brett. You can even think that that's a possibility. Got Refractor, Chas McCormick, and Andrew Benintendi. Kyler and Book PC. Gotcha. Okay, that's fully something cool then. It's like a wander auto. Why not? Brandon Marsh rookie. Angels. Wander Franco rookie. There you go. There's a wander. Pure power taquise. Then we've got Blue 275, Andrew McCutcheon as a filly. Nice one there. That is 11 of 75. Nice one there. Okay, they're testing my patience with this bag. Geez, man. There better be something good in here if I'm going to make that that difficult. Oh, okay. That'll do. Oh, yeah. Okay. That shall work. We'll put a pack over that. That'll work. That will work. I think you will be pleasantly surprised here, Brett. Tony Gwynne and nice Joe Carter on the Slice of Stars patch auto. Part of the bat there. Manuel Rodriguez. Freddie Peralta. Gary Sheffield again. Bass. All right, here we go. I think you're going to be okay with this one here, Brett. Juan Soto. Boom. Let's go. Heck yeah. Not numbered on the Soto. Nice hit there, Brett. Congrats, man. Let's go. That's so sick. Jim, they really did, to be honest. You should have seen how much of a mess it was the first week of this. We were having some trouble for sure. We were having some serious trouble. It's delaying everything. Oh yeah. We had me opening packs when Forest was showing them to people. It was just the whole thing. Got Cow Rally rookie and Purple 299 Wilson Contreras. Heck yeah, definitely, Brett. Jump in if you feel like it. Absolutely, man. Always fun. Hopefully pull some more heat for you tonight and out of these next boxes. Shohei. Got Marcus Strowman on the Bass Auto 299. It's kind of like a Silverish right there for the Metz. Nice one there. Got Refractors of Eddie Rosario and Corbin Burns, Purple 299. That is Book End 99 of 99. I honestly don't know. I'm not sure, Joe. I'm sure there's probably some on eBay for sure. Oh for sure, Vaughn. Absolutely, man. It just Pure Power Jesse Winker. Got the original Todd Father, Gold Todd Helton. 45 of 50 for the Rockies. Nice one there. Nice Todd Helton. It just doesn't make much sense. That's the issue with the the packaging of this. Like it's just, it's bizarre. Ion Moncada and Tim Anderson Purple to 99. That's 22 of 99, White Sox. One more Wander. Tony Santien rookie and Clayton Kershaw on the borders. Got Jesse Winker on the Encased Bass Card for the Reds. Not numbered on the Winker.  Good luck. Not bad. Michael Confordo, Luke Garig on the Refractors. Not bad. Take that. Reed Detmer's rookie base. Last card of Pristine is going to be Manny Machado on the Pulsar base. Padres in case. Bless you. Bless you. All right. Core King's time. Here we go, Brett. Let's see what we got in here. Full of big, big rookie auto out of this. It'd be cool. Because like Scotty is live in this. Oh yeah. I mean the cards are beautiful. Like I like the product. The cards are beautiful. Like Personals, I have no issue with them. Like completely okay with doing Personals of what's it called? Pristine. It's just like a little bit. The packaging's a little tough. Ingram, George. Level one rookie, Bones Highland. Level, that's not for it. Level four is, or level three, excuse me, Trey Mann, Thunder. Got a big ticket. Kevin Garnett read to 149. 116 of 149 of Graffiti Grates, KG. Got Davion Mitchell, rookie expression. Jersey card not numbered. Kings. Got Jaden Springer, heir apparent rookie autograph for the 76ers. Nice one there. We've got works in progress, Cade Cunningham rookie. There you go. That's not numbered. And first steps, warriors, Moses Moody rookie. Again, not numbered. Nice one there though. Box two. Good luck here, Brett. Powery, Randall Maxey. Got Jalen Suggs, level one rookie. Quinton Grimes, level two rookie. Got Alfred Shengun, works in progress, rookie to 149. That's 72 of 149. Got rookie Jersey. That is Jonathan Kaminga, warriors. Nice Kaminga. Got heir apparent rookie Otto, Jason Preston that is going to the Clippers. It's Clippers hit right there. Got Maestro's of Ant-Man and Graffiti Grates jaw, Morant. So how to do it for your break there, Brett. Congrats on all the hits. Thanks again for jumping in, man. We'll get those right out to you. Appreciate it.


What we do here, we do initial attack on fires where we cut hotline. Our goal is to protect people's properties and lives and do good for the community. It feels really good knowing front line like what we see directly impacts the community. When you're saving people's lives, protecting their homes, it's such a great feeling knowing that you're making a difference. It brings a sense of accomplishment knowing that you're protecting this state and the country that we love.


Consider this program, which calls a function that multiplies a number by 3 and prints the result. Let's run this program and we find out that 14 times 3 is 42. What do you think will be in the variable number when we finish this code? Number is being passed in to parameter n and we change n inside the function body. Will that change the value of the number variable? Let's put in some code to find out. Rebuild. And when we run the program, we find that number has not been changed. That's because functions use something named call by value. Here's what's happening behind the scenes. First, number is set to 14. The next line calls the triple function with number as the argument. When the triple function is called, it needs an integer parameter n and it creates that variable. This variable n belongs to the function. It is local to the function. The value of the argument is copied into the parameter. The multiplication does change the value of n, which is a copy of the original. The printf statement prints the value of n, which is now 42. When the triple function ends, the parameter and any variables you might have declared in the function body go away. We return to the main function and proceed to the next statement. It prints the value of number, which is still 14. It hasn't been modified. But wait, you might ask. If functions get a copy of the original, how can scanf change the value of a variable? Scanf works because it gets a copy of the memory address of the variable and can access that location directly. In later chapters, you'll find out how to do this trick in your own functions. But for now, remember that c uses call by value. Parameters always receive a copy of the argument's value.


Live from Washington, D.C., it's theCUBE. Covering .conf, 2017. Brought to you by Splunk. Welcome back inside the Walter Washington Convention Center we're at .conf, 2017 and Washington, D.C., the nation's capital, it is alive and well and thriving, tell you a little warm out there, almost 90 degrees, but hot topic inside here, Dave. There's a lot of heat in this city. Yes. Especially this week. A lot of hot air. Yeah, absolutely. We'll just leave it at that. No politics aside, of course. Joining us is Ben Miller, who is the director of high throughput screening at Recursion, rather, Pharmaceuticals. Ben, thanks for being with us here on theCUBE. We appreciate the time and first off, many questions. First off, let's talk about the company, what you do and then what high throughput screening means and how that operation comes into play when you have this great nexus of biology and engineering that you've brought together. Yeah, so Recursion Pharmaceuticals is treating drug discovery as a facial recognition problem. We're applying machine learning concepts to biological images to help detect what types of drugs can rescue what types of diseases. And we're one of the few companies that's both generating and analyzing our own data. So as the director of the high throughput screening group, what I do is generate images for our data science teams to analyze. And that means growing human cells up in massive quantities, perturbing them with different types of disease reagents that cause their morphology to change, and then photographing them in the presence of compounds and in the absence of compounds. So we can see which compounds cause these disease states to revert more to a normal state for the cell. Okay, and HTS then, I mean, so... That's our high throughput. You can walk us through that if you would. Yeah, yeah, so HTS is a general term that's used in the pharmaceutical industry to denote a assay that is executed in very large scale and in parallel. We tend to work on the order of multiples of 384 experiments per plate. So we're looking at hundreds of thousands of images per plate and we're looking at hundreds of plates per week. So when we say high throughput, we mean six to 10 terabytes of data per day. Just extraordinary amounts of data. Yeah, gotcha, gotcha. Okay, so, and the mission, as we understand it, I mean, you're looking at very rare genetic diseases. Your goal is to find cures for these over the next 15 to 20 years, up to 100 of them. And so that's why you're going through these multiple examinations of vast amounts of data, human data. Yeah, there's been a trend in the pharmaceutical industry over the last years where the number of dollars spent per drug developed is increasing. And it now takes over a billion dollars to bring a drug to market. And every year it costs more to bring a drug to market. We believe we can change that by operating in a massively parallel scale and also analyzing image data at a truly deep level, looking at thousands of different features per image instead of just a single feature in the image. Yeah, I mean, that business is just like this vicious cycle going on and you guys are trying to break it. Yeah, exactly. So, what's the state of facial recognition, Ben? I've had mixed reviews about it, right? Because I rave about, oh my God, Facebook tagged me again. Must be really good, but then others have told me, well, you know, it's not really as reliable as you might think. What has your experience been? You know, so the only experience I've had with facial recognition has been like yours on Facebook and things like that. What we're doing is looking more at cellular recognition, being able to see differences in these cellular morphologies. And I think there are some unique challenges when you're looking at images of thousands of cells versus images of a single person's face. Okay, so you've taken that concept down to the cell level and it's highly accurate, presumably, right? It's highly reproducible is what I would say, yeah. Okay, so then you take some work to get it to be accurate and once you get it there, then you can reproduce that. Is that right or how does the sequence work? Yeah, so, I mean, there are two parts to the coin. One part is how consistently we can produce these images and then how consistently those images represent the disease state. My focus is on making the images as consistent as they can be while realizing that the disease states are all unique. So from our perspective, we're looking at thousands of different features in each image and figuring out how consistent those features are from image to image. So paint a picture of your data stack, if you will, infrastructure kind of on up to the apps and where Splunk fits in. Sure, so I mean, I guess you could say our data stack actually begins at hospitals around the world where human cells are collected, from various medical waste samples. We culture those up, perturb them with different reagents, add different potential drugs back to them and then photograph them. So at the beginning of our stack, we've got biological agents that are mixed together and then photographs are generated. Those photographs are actually TIP files and we have thousands and thousands of them. They're all uploaded into Amazon web services, their S3 system. We spin up a near infinite number of virtual computers to process all of that image data within a couple hours and then produce a result. This drug makes this disease model look more like healthy and doesn't have other side effects. We're really reducing those thousands of dimensions in our image down to two. How much does it look like a healthy cell and how much does it just look different than it should? And where's Splunk fit into that stack? Yeah, so all of those instruments that are generating that data are equipped with Splunk forwarders. So Splunk is pulling all of our operational data from the laboratory together and marrying it up with the image analysis that comes from our proprietary data analysis system. So by looking at the data that we're generating, how many cells we're counting, how bright the intensity of the image is, comparing that back to which dispenser we used, how long the plates set at room temperature, et cetera, we can figure out how to optimize our production process so that we get reliable data. And you say essentially storing machine data in the Splunk data store and then you have an image database for? Yeah, yeah, and the image database is incredibly large. I wouldn't even guess at the current size. And what is it? Is it something on Amazon service? Yeah, so right now all of our image data is stored on AWS. See, this is one of those interviews, Dave. We have these that the subject matter, kind of to me trumps the technology because I want to know how it works. But you need the technology obviously to drive it. And so I'm trying to figure out, all right, you're taking human cells and you're taking snapshots right in time and then looking at how they react to certain, you said perturbed actions. But how does that picture of maybe one person's cell reacting to a reagent to another person's? Like what are you using? Or how does, I guess, your data analysis provide you with some insight because Dave's DNA is different, my DNA different than everybody in this building. So ultimately, how are you combing through all that data to make sense of it? Yeah, that's true. I mean, everybody has a unique genetic fingerprint, but everybody is susceptible to the same sets of major diseases. And so by looking at these images, and really that's the billion dollar question, is how representative are these individual cellular images? How representative are they of the general human population? And the effects that we see at a cellular level, will they translate into human populations? And we're very close to clinical trials on several compounds, but that's when we will really find out how much proof there is in this concept. Okay, and you can't really predict it. Do you have a timeframe or is it just sort of keep going, keep getting funded until you reach the answer? Is it like survive until you thrive? I personally don't maintain that kind of timeline. My role is within the laboratory, producing the data as quickly as we can. Yeah, we do have a goal of curing or treating 100 different diseases in the next 10 years. And it's really early days, we're about two and a half years into that goal, and it seems like we're on track, but there's still a lot of work to be done between now and then. Okay, so it's all cloud, right? And then Splunk is throughout that stack, as we talked about. How do you envision, or do you envision using it differently? Are you trying to get more out of the Splunk platform? What do you want to see from Splunk? Yeah, that's a good question. I think right now we are using really the rudimentary basic features of Splunk. Their Database Connect app and their machine learning toolkit are both pretty foundational to the work that we do. But right now a lot of our data models are one time use. We do a particular analysis to find the root cause of a particular problem, we learn that, and that's the last time we use that model. So continuous implementation of data models is something that is high on my list to do, as well as just ingesting more and more data. We're still fairly siloed. Our temperature and humidity data is separate from our machine data, and bringing all of that into Splunk is on the list. Why are your models disposable? Is it, it sounds like it's not done on purpose. It's more of some kind of infrastructure barrier. You know, we're really at the cutting edge of technology right now, and we're learning a lot of things that people haven't learned that in retrospect are obvious. To figure out the true cause of a particular situation, a data model or a machine learning model is really valuable, but once you know that key salient fact, you don't need to keep track of it over time. You don't need to know that when your tire pressure is low, your car gets less miles to the gallon. You have the answer. Right, but there are a lot of problems like that in our field that have not been discovered yet. Okay, but if I inferred from your answer, you do see the potential to have some kind of ongoing model evolution for new use cases? Yeah, in the extreme situation, we have a set of hundreds of operational parameters that are going into producing this image of cells, and then we have thousands of cellular features that are extracted from that image. There's a machine learning problem there. What are the optimal parameters to extract the optimal information? And that whole process could be automated to the point where we're using machine learning to optimize our assay. So to me, that's the future of what we want to do. Were you with recursion when they brought in Splunk? Yeah, yeah. Okay, did you look at alternatives? Did you look at maybe rolling your own with open source? I mean, was that even feasible? I wonder if we could talk about that. Yeah, so I'd already been introduced to Splunk at my previous job, and at that previous company, before I'd heard of Splunk, I was starting to roll my own. I was writing a ton of Perl scripts and all of these regular expressions and searching network drives to pull log files together, and I thought maybe that would be a good business model behind that. You were building Splunk. Yeah, yeah, and then I found Splunk, and those guys were so far ahead of the things I was trying to do on my own in the lab. So for me, it was a no-brainer, but for our software engineering team, they are really dedicated to open source platforms whenever possible, so they evaluated the Elk stack. Some of us had used Sumo Logic and things like that, but for me, Splunk had the right license model and I could get off the ground really, really rapidly with it. What about the license model was attractive to you? Unlimited users and only paying for the data that we ingest, the ability to democratize that data so that everybody in the lab can go in and view it, and I don't have to worry about how many accounts I'm creating, it's really powerful. So you like the pricing model? Yeah. So some users have shared about the pricing. I saw some Wall Street concerns about the pricing. The guys that we've talked to in the cube today have said they like the pricing model, that there's value there, and you're sort of confirming that. Yeah. You're not concerned about the exponential growth of your data, causing your license fees to go through the roof or? Yeah, I mean, in the laboratory, the image data that we're generating is exponentially growing, but the operational parameter data is more linearly growing. Right, okay. So it's under control. Yeah, for our needs it is, yeah. You're not paying for the images, you're paying for the metadata. Yeah. Well, it's a fascinating proposition. It really is very eager to keep up with this, keep track and see the progress, and good luck with that, and look forward to having you back on the cube to monitor that progress, all right, Ben? Great, yeah, thank you. Very good, thank you so much. Ben Miller, joining us from Salt Lake City. Good to have you here. Back with more on the cube here in just a bit, you're watching our live coverage of .conf 2017.


a little bit. I don't want us to go so fast that we don't have enough time to hear important information from our witnesses. So working from the bottom of the schedule up with the tax acceptances, they might have to S55, we'll reschedule for tomorrow. And just looking at who is, who travels versus who's local. So, Chair, Mr. DeVall, I don't know if you can in ten minutes to learn your conversation. Rather reschedule. I think the thing that we're trying to, we're taking up weatherization and the reason you're the lead off witness is that there's a much larger context for the weatherization conversation. And I thought that you could help us establish that context and then help us understand what weatherization goals might look like. We have 10 VSA 581, but we also have other things like the Paris Accord, 90 by 2050. So is it 10 minute window, so ridiculously narrow that you can't work with it? I can help set the context in ten minutes. I think what I want to make sure is that people don't sort of dive into our current weatherization programs and not see the ability to get around it, nor that we need to know about all of the events that we're going to get involved. Do you want me to receive that in a minute? There's an electronic program, so anyone would like to follow along with the paper copy? I have those as well. So thanks for your possibility. Thank you Chairman, members of the committee. Glad to be with you. My name is Jerry Duvalli, I serve as the Executive Director of the Energy Action Network, which is a diverse network of nonprofits, businesses, fuel dealers, utilities, low-income advocacy groups, a very diverse composition across Vermont that works together to achieve Vermont's energy and emissions reduction commitments. That broad network of over 200 members and state partners is supported by a small backbone nonprofit organization that works with state partners who are in the room to track progress towards our total energy commitments as a state and our emissions reduction commitments. So what I was hoping to do today was just briefly review what those are and where we stand now in the role that weatherization plays in meeting them. So if you look at page three of the presentation, you're all familiar, I believe, with the 2016 Comprehensive Energy Plan, which sets our long-term goal of 90% renewable by 2050. Currently, Vermont stands as of the end of last year at 19% renewable overall, and it's important to remember that that's a total energy figure, so including electricity, transportation, and thermal. And each of those sectors have different shares of renewability. When we get to the emissions reduction commitments, the fastest approaching is what Governor Scott committed to, which was keeping the U.S. in the United States Climate Alliance with the Paris Climate Accord, which would require a 26 to 28% reduction in greenhouse gas emissions below 2005 levels by 2028. As of the most recent data from the Agency of Natural Resources emissions inventory, we are just 2% below 2005 greenhouse gas emissions levels. You can see on page five oftentimes we talk about these three sectors of our energy, economy, and energy use, as though they're relatively similar, but they have very different profiles when it comes to the amount of energy used, the amount of emissions they produce, and the energy burden that they put on Vermonters in terms of the bills we pay for energy. I won't get in depth into that, but if you're interested in comparing transportation, thermal, and electricity by use, emissions, and energy burden, that is on page five. So going directly to what you asked me to review, Chairman, about the different emissions goals and commitments that the state has set, there are many that we track. If you see on page six, there is a green dot that says 7.46. That refers to million metric tons, and that's the level we would have to get to over the next six years to meet Vermonters or Governor Scott's Paris commitment. There are, of course, other goals that have been set. There are the statutory goals, one of which had a 2012 deadline that has been passed, but there is the 50% reduction in emissions below 1990 levels by 2028, which you can see is the 4.3 dot on this. And then, of course, the Comprehensive Energy Plan and the statutory goals end up lining up more or less when you get out to 2050. But one of the things that we've found is that it's really difficult to look out that far into the future. And so we've tried to bring the horizon forward to 2025, the most recent commitments the state has made in terms of the Governor with the Paris Climate Commitment, and then also the first milestone of the Comprehensive Energy Plan is in 2025, 25% renewable. And so we have done analysis based on, I should say upfront, the Energy Action Network, because we have such a diversity of members, we do not take positions on specific bills or policies. We remain neutral and we serve as a neutral convener in an objective track of working with state partners of the data. So we focus less on policy and more on what are the proven and available technologies and best practices for reducing emissions and for keeping more of our energy dollars in state. If you look at page 11, this is our analysis that we call the path to Paris. It is not prescriptive, it is not, I should not say the path to Paris, it is a path to Paris that helps show the scale of emissions reduction that would be required across our energy sectors to achieve it. And you can see that the thermal sector in the middle of that chart added together is the largest single opportunity for emissions reduction in Vermont. If in addition to weatherization, we also look at what is sometimes called fuel switching or moving off of fossil fuels and towards heat pump water heaters, heat pump, co-climbing heat pump systems for heating and advanced wood heating systems, including both pellet boilers and efficient wood stoves. So I want to focus on the role that weatherization plays among those top drivers. So it was mentioned that, I'll make sure I cite this correctly. So I'll share copies of this at the end of the presentation, but this is EAN's 2018 annual report and on page 28, there is a listing of all of the administrative and statutory targets related to energy that we've been able to find and track. And 10VSA 578 is the emissions reduction target that I referenced earlier, and then on the thermal side, 10VSA 581 is set the goal of improving the energy fitness of at least 20% of the state's housing stock by 2017, which has passed in 25% by 2020. Based on reporting from the public service department, we stand at about 25,400 housing homes weatherized. To meet that goal in the next two years would require an additional 55,000 homes weatherized. In the next two years, what did you say? By 2020. 2020, thank you. And that data is, I think, reported a year behind. So that 25,400, I believe, is through 2017. But the current pace has been about 2,000 a year. So we are orders of magnitude away from what it would take to meet the state's commitments. If you look at what it would take to meet this path to Paris modeling, which you can see, and the weatherization is just one component, but you can see on page 14, we modeled that you would need additional 90,000 homes weatherized over the next six years. And our modeling shows a slow and steady ramping up of that going from basically a tripling of where we are now in the 2,000 or so homes per year to about 6,000 in the next year, just under 8,000 after that, but continually increasing year after year to meet these targets. The last thing I want to say before concluding is that this is not just about helping meet emissions reduction and renewable energy commitments. This is a massive economic development opportunity. 70 to 80 cents of every dollar that we spend on fossil fuel, which is 100 percent imported in Vermont, leaves the state. And it doesn't just leave the state for other states or for the broader region. Oftentimes it leaves the state through multinational fossil fuel companies where those profits are going to places like Russia or Saudi Arabia or Venezuela or pick your foreign oil export. In contrast, all of the efficient and renewable energy solutions that we model keep far more of Vermont's energy dollars here in state, recirculating, supporting our neighbors, helping create local jobs and helping folks save money in the long term. There are charts here, for instance, that show the relative costs of different ways to heat your home. If you look at chart, the graph on page 18, it shows you the average heating fuel prices for the last 20 years. The two that are consistently the highest cost and the most volatile, putting the most strain on family budgets, are in purple, the propane, and blue, the fuel oil. In contrast, the efficient and renewable options of advanced wood heat, whether that's chips or pellets or cordwood and EPA certified stoves, or whether it's cold climate heat pumps, are all much more stable costs and lower for Vermonters over time. And what that transition is in terms of investing in weatherization versus fuel switching, there are different percentages of dollars that stay in state or not, but it's generally two to three to four times more of our dollars staying local and helping grow Vermont's economy when we make those investments. Thank you. Thank you very much for your insight. Take a picture. What's been going on? What's been going on? What has been going on? That's my question. Actually, Mr. Wilcox will be showing us a chart, but how many months ago are there with home hands? You've told us what we already know. So where? You've depended the table. We're scheduling for that. It's not us. That's an important conversation to have. There are people who can speak better to that in the room and beyond the room. If anyone does not have a hard copy of the full 2018 annual report from EAN, I'm happy to. I've got one at home, but everybody can have a second one here. Thanks. Thank you very much. Can we do a little switch up here and ask Mr. Wilcox to jump in? As you know, let's tip of the bat over to Mr. McNamara. Sure, it can be two minutes. A lot of professionals come in to speak to your presentation. Good morning. My name is Ed McNamara. I'm planning director for the Department of Public Service. And I'm just going to quickly touch on the 2019 annual energy report we submitted this January 15th this year. It's a new requirement part of the Conference of Energy Planning Statute basically asking us to report on where we're at and what we should do moving forward. Jared did a great job explaining the background where we are and how short we are in meeting the 581 goals. So I'm not going to go through that. The Climate Action Commission, I understand all of you will be here tomorrow to talk about the Climate Action Commission or recommendations. So really the annual energy report that we submitted only touched on a couple of tweaks around the edges in terms of weatherization mostly to do with efficiency remodeled. One recommendation was to consider using the energy efficiency charge associated with heat pumps and taking that, instead of having that energy efficiency charge used for reducing kilowatt hours, switch that money so it's used for weatherization. And then another aspect that we recommended as well was efficiency remod uses weatherization eligible funds for heat pumps and we'd recommended that those weatherization eligible funds be used just for weatherization. Other entities focus on heat pumps. As I'm saying that I'm recognizing I should back up a little bit. Funding sources for efficiency remod, efficiency charge raises money for kilowatt hour reduction. Something on everybody's bill. For weatherization related activities and any thermal activities, that money comes from two different sources. Regional Greenhouse Gas Initiative and the Ford Capacity Market. So that's money that's outside of the state's control. Regional Greenhouse Gas Initiative, however many allowances get sold and what the costs are, that's going to be what we get for reggie money. Ford Capacity Market, again, that's run by ISO New England. We have very limited control over what the outcome is. This is a funding source that efficiency remod, the PUC, the department, nobody has control over in that amount sort of rises and falls depending on those revenue sources. We're actually likely to see a reduction in those funding sources primarily because Ford Capacity Market the clearing price was reduced significantly from where it had been previously. Good for electric ratepayers, not so good for funding for weatherization. So overall the department recognizes that Climate Action Commission has made some recommendations regarding how to potential pathways to significantly increase weatherization efforts. I'm not here to talk about that, Paula Costello can talk about it and if you would like an administration viewpoint on that Peter Wach from A&R is the best person. I think following up on perhaps Senator McDonald's question I'm wondering if you could tee this up a little bit more for us. I think people sat down, we're talking about weatherization, we're not really responding to anything. I think we just need some context for some of this that we're hearing today before we move forward a little bit. That's helpful. Thank you. So there's a bill that's going to be turned into a draft form that basically lets pick up the pace on weatherization and increase the funding in response to the department's report, the Climate Action Committee report on spad kits. So that bill will formally we'll have it as a drafting request we can work through for the balance of the week. The goal is to So today, for example, we're asking folks not to come in to respond to the bill. Thank you. Before we start to look at the details of any particular bill for instance, one of the things that always draws attention is how are you going to raise more money and before we get stuck on that I wanted us to be able to back up and say well actually there's there are five different actors all delivering weatherization services in the state and who are they and what are they doing and where's the money coming from and how does the department's report there's levels of nuance that Mr. McNamara is talking about now in terms of it's annoying when four capacity dollars flowing in and so if we we have really two different sorts of programs going out there so programs that focus on low income weatherization Title 33 but then throughout Title 30 our energy statute we keep on referring to doing weatherization and thermal load work and so we need frankly both and before we start getting pulled into details on just one program and the other I thought it would be good for us to look at the big picture and then imagine how we would do both lower income weatherization as well as moderate a win for anyone who does weatherization work so thank you for the question sorry so I want to give you a very quick overview of what the department recommended sounds like we're in much more nuance than where you folks are at the moment so we'll be certainly back to that I think so the goal about the corner left or right corner of the page 24 to 30 days left is my guesstimate based on my normal adjournment so we'll be working along a good flip not too fast not too slow but first we'll get the big picture straight and then I think we need to do it for the department adjustments that you laid out in your report which was very helpful also suggest talking to the folks from Efficiency Vermont and Vermont Gas as well so you're on our schedule for later great thank you thank you Mr. Manager so I wonder I mean for me personally if you could help and I know I signed down to the bill maybe by tomorrow we'd just have it in front of us perhaps just so we can start asking questions if that makes sense we will be able to okay so thank you Mr. O'Connor morning hello handouts here thank you thank you so you know where I signed but I you can lay out the weather decisions sure so I can do a 10 minute explanation of what our program does who we serve so my name is Jeff Wilcox I work for the Office of Economic Opportunity in Waterbury at the State Office we're part of the Agency of Human Services and the Department for Children and Families I worked in weatherization 21 years the last 10 at the State Office 11 at the Community Action Agency in the local weatherization program so so my handout is on top that I'm going to kind of work through so our program creates safer, healthier and more efficient homes we're an anti-poverty program that puts money back in clients' pockets by saving energy for them on their heating and electric bills I work for the, like I said the Agency of Human Services and the Office of Economic Opportunity you may ask we're not an energy office why is the program located here but it's because we do a lot more than just energy savings we provide a lot of benefits for clients through saving energy and we've had the program for 40 years and there's three full-time staff at our office, myself included our job is to provide guidance for the agencies training, quality control quality assurance and we do that with three folks in Waterbury so who do we work with we work with the five local weatherization programs that are situated throughout Vermont to serve the state four of them are Community Action Agencies and the organization program and the other is NEDO the Northeast Employment Training Organization who is not a cap, they're a non-profit so each of those I want to just state the obvious so this program is no cost to low income clients so I'll get to the funding in a bit but we have about $9 million a year to provide services for clients, they have no out-of-pocket expense so with that said our five sub-grantees we call them are program providers they employ about 100 workers statewide so each employ about 20 weatherization workers that include energy auditors crew workers, office folks as well as the director of each office they employ or sub-grant out to many contractors, plumbers electricians and we hire a significant amount of contractors throughout the state to fully serve our clients who do we serve Vermont homeowners and renters with household incomes 80% of median income are below so for example if you're a family of four if your gross income is 63,760 or below you are eligible for the program we do have a wait list statewide approximately seven months if you averaged all five agencies because of that we've developed a mechanism to prioritize who we serve based on need some of it comes from the department of energy requirements but a lot of it is state statute so those priorities are clients who receive fuel assistance who are in the lower income bracket less than 60% and actually if you're less than 25% you have even higher priority families with elderly disabled families with children and as well high energy usage homes so I want to talk quickly about how the process works so a client applies for weatherization immediate to each five agencies so they apply to capstone community action the capstone weatherization program will deem if the clients are eligible or not and if they're eligible they will send them a letter stating which and then they will start the process with an efficiency coach visit which efficiency coach goes out to the home sits down with a client talks to them about the weatherization process what's going to happen coaches them on energy conservation looks around the home for any things that may prohibit or make weatherization more difficult like vermiculite a wet basement stuff like that or significant structural repairs but they also sit down with the client and do what a one touch screening and referral for other health and social programs service programs that's a process we created a few years ago to try to be as holistic and comprehensive through our weatherization program so we refer clients if they're willing and need that referral to the lead based pain program head start aging services Vermont put hotline in many others the next step is a separate visit by the energy auditor and this is kind of critical to how we spend our money the energy auditor goes out there's a lot of diagnostic testing infrared cameras, lower door testing tests all heating system appliances for safety and efficiency so they're out there to test and gather information and to bring it back to the office and then you know with their energy modeling program determine what's going to be the best return on investment the big bang for our buck is the slogan we use in weatherization we want to spend our money most effectively improving the any healthy safety issues but then getting a significant return on investment, a lot of energy savings for the dollars we put into the home so that's the energy audit the energy audit determines that with use of the energy state energy auditing tool and then they write a work scope that they then hand over to their their manager who then sends out and gets heating systems cleaned and tuned or repaired we do that first to make sure everything's operating safely so we then go into the home and weatherize it we tighten up the home with spray foam, caulking, weather stripping we're very illicit and meticulous about tightening up the home and especially in certain places like the attic we always want to start at the attic so the air seal which changes how the home works and how it integrates with heating systems and combustion appliances and then they insulate so the crew does and then when the crew work is all done the agency sends out their quality control inspector who goes out and verifies all the work was done as specified to be done and installed to our statewide technical procedures manual so that's kind of the process then the agencies report those jobs to us monthly as well as an invoice at our office we review that monthly, monthly, daily and verify that the work was done to our standards and one of the folks in our office goes out and does monitoring of the five agencies so he inspects 10% of the completed work of each of the five agencies goes out meets with the client, talks to them asks them how things went if they notice a difference tests certain items like a blower door test to verify what the agencies have sent us for information and if they find something that wasn't done quite up to spec they'll have the agency go back out and fix it and then so that's kind of the process of weatherization we do that 850 times a year well we weatherize 850 homes a year yep and you asked for a chart of what we've done for the last few years I didn't prepare that but the second handout on the bottom line shows the number of units we've weatherized for the last number of years so I want to talk about who will weatherize or what homes so we do weatherize single family and multi family homes so owner occupying rental the caveat is you know the home has to be lived in by an income eligible family when it's owner occupied like I said earlier there's no cost to the client for the homeowner if it's a rental all energy saving work is paid for by the weatherization program all health and safety matters like indoor air quality, bathroom fans cleaning tubes cleaning tubes, heating systems are paid for by the owner of the building if they aren't income eligible themselves so our programs require the landlord to do that work before we set foot on the property to install insulation in the air ceiling we do invoke a rent stabilization agreement for rentals that requires the landlord or the owner to make sure the rent doesn't go up for either one or three years one year if the owner pays the heat or the client pays the heat three years if the owner of the building is paying the heat so let's see here the funding comes from two different places essentially the department of energy weatherization program created our program in the late 70s and there's a program in every state in the country that receives DOE department of energy funds we typically get 1.1 million to this year we have 1.4 million and our state weatherization program has gone by different names over the years it used to be called the weatherization trust fund and now it's the home weatherization assistance fund which is created from a tax and the fuel two cents per gallon gross receipts on natural gas electricity so we typically 1.3 to 4 million from DOE and then 7 or so with our state program within that 7 million we do a lie heap swap in recent years I don't want to get into that right now I'm going to keep moving here so the big picture just so you know Mr. Faisy agreed to come back tomorrow so you're better coming up to this sorry Richard so the big picture things I want to convey is cost effectiveness of our program we're all about testing and confirming testing to determine what's going to be the measures that are going to be the best for the client and the household and also what's going to have the best return on investment from energy savings so a lot of folks think I need to replace my windows well we've never replaced windows and weatherization unless they're broken and it's done more for health and safety so air sealing and insulating poorly insulated surfaces and drafty surfaces is what gives us a much better return on investment and savings for the client we're all about testing and evaluating and then setting your work scope based off those results our average savings per year like 27% the numbers are flashing through my eyes I know it's around there and that's not based on a fuel study because our clients typically are using different sources of fuel and it's hard to do a fuel study in Vermont with bulk fuel delivery modeling program which is approved by the Department of Energy we enter all our pre data and then our post data and it estimates savings and that's where we get our savings comprehensive you know we're really comprehensive when we go into a home we change how the building works and if we aren't comprehensive and we don't test we can harm people cause back drafting cause mold and melt from tightening up the home so health and safety and testing is really critical to when you do this type of work holistic you know the efficiency coaching and the one touch referral we're trying to benefit our clients as much as possible not just by energy savings and money in their pocket by weatherizations proven to really improve the health of the home and the household to make it comfortable better air quality and I think there's one of the attachments is a one two-pager from the Department of Health and they have a longer version of that that's very good then there's a national study done by Oak Ridge National Laboratories that really talks about the non-energy benefits of weatherization and they're believe it or not they're more significant than the energy benefits of weatherization if you pause just for a moment people hear it and then it's surprising enough that they don't necessarily take that saying that the investment that's made in the energy investment and more than being compensated by savings in healthcare not necessarily healthcare but we'd love to get that done to show the healthcare profession but I'm not going to give you numbers they're swirling in my head but that study will show but just by improving the indoor air quality and the safety we go into homes that the heating systems are spilling and backdrapping into homes you know, knob into wiring or wiring is dangerous we're improving the safety the indoor air quality which results in less days sick for clients they miss school less they're healthier when they go to school able to learn better so it's hard to quantify exact savings dollar wise but there's some studies that do a pretty good job of it and there's a larger study that we didn't include but I mentioned to you I can email that to you so yes, it's some pretty good organizations that have crunched those numbers and shown that the non-energy benefits are significant so challenges I want to mention challenges to our program in any given year these are the challenges we face when we weatherize homes we have one of the oldest housing stocks in the state and we're at the roughest housing homes in the state so we deal with leaking pipe in the country yeah, oldest housing stock in the country but of the homes we're serving in Vermont we're in the lowering of folks who have deferred maintenance so we're in the roughest of the rough and the challenges that we have to face are vermiculite insulation that has asbestos wet basements leaky roofs, rotted sills, knob and tube wiring which we can't insulate around asbestos pipe wrap that's come frayed and it's all over the place that we can't disturb mold hoarding leaky pipes so our weatherization funds have some ability to address some of those things but we can't address all of them so we're all often trying to leverage funding from other sources help clients apply for low income low interest loans etc we can't take care of all those things with our own funds so in a lot of the homes we go out to have those issues so that's something important to remember with our low income folks there are a lot of challenges let me mention you have to treat all of them wholeheartedly if they can't find funds necessary repairs you can go ahead yourself I should explain a little better so those issues prohibit our weatherization because we can't go and install measures that are going to get wet or get ruined and we can't tighten up the home if there's a wet basement or rain getting the house damp but it'll just create a lot of mold and mildew in an unsafe condition so yes then we'll have to defer the home until it is taken care of we're working on a process to defer as few as we can but every year we do defer some homes at each agency would be able to replace something like a roof so that you could easily yep there's the USDA 504 loan program that's a grant or loan program depending on the age there are some obstacles depending on the size of the house that allows some clients to receive a loan or grant individual homes so people, families would apply and if they're eligible they could get a really low interest loan or if they're over 62 or 5 they could get a grant would you help them in that process? so you notify them of the possibility yes definitely part of our process when we have to defer a job or before we had to defer a job we're trying to link those clients to home ownership networks who have home repair funds we have set aside a little bit of funding with each agency called the HWAP home repair program and the HWAP vermiculite funding so that we can leverage those other sources to help clients so we don't have so many deferred homes yep one of the things that there's been a lot of people talking about doubling, tripling, quadrupling, etc yep I guess we're concerned probably everyone in the room shares how quickly can we increase the program while not overwhelming the capacity of those programs to receive new monies and spend them well do you have any thoughts about how we think of the pace and what kind of capacity do we have just to do more of the current personality of hire more, train more we've Sarah the director of the office behind me we produced kind of a plan because we've been asked these questions before is that in the attachment Sarah? yeah so in general I would say weatherization you've got to do it right to be effective to get the savings and the benefits for the clients which requires on-the-job training as well as specific training you know part of the retreating off the streets except we expect them to know how to insulate addicts and then air seal up to our standards so training is important you know so ramp up all depends on the workforce and the ability to train stuff like that so thanks again I apologize to everyone especially our guests that we are short time we're going to read the handouts we've got and Mr. Facy's rescheduled if we have more questions we'll send them on but thank you for helping us see how this program runs I think for a lot of people they think this is the only program in the state when I'm here people talk about weatherization they think it's only capstone we're the only low income somebody you know there is confusion and we're the office that administers and runs the statewide program thank you for your work I know that when I've talked to people who've had your assistance it's been a profound change for them if I could mention one more thing and I typically read a thank you note that's in your handout that explains the benefits to the clients it's pretty holistic and pretty amazing a lot of faces so the brief story I heard from a witness before was they were visiting a capstone weatherized home and the woman who lived there said it's so great to be able to sleep in my bedroom which was right off the kitchen and he said well why weren't you sleeping in your bedroom before she said well it was far too cold in there she spent a year sleeping in her kitchen floor in front of the oven the door opened and the oven running and I had to stay warm to make it through so that's the kind of thing that's an eye-opener yeah I've heard you've seen many stories yes that's not a movie of occurrence a lot of stuff like that so thank you sure thank you so committee and committees will be taking this up and diving right back in tomorrow morning thank you all