From theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. Predictions about the future of enterprise tech have never been more uncertain. Predictions become even more challenging when you try to make forecasts that are measurable. I mean, generally our belief is that we should be able to look back a year from now and say with some degree of certainty, whether the predictions that we're sharing with you today came true. With some quantifiable evidence to back that up. Hello and welcome to this week's theCUBE Research Insights powered by ETR. In this Breaking Analysis, my friend Eric Bradley of ETR and I update our Enterprise Technology Predictions for 2024. We're gonna cover the macro, IT spending environment, the state of gen AI, AI ROI, cybersecurity, M&A, data quality governance skills, momentum, and momentum from legacy players and 2024 technology priorities. Eric Bradley, welcome. Good to see you again. Always good to see you too, Dave. I enjoy being on the show every time I get the chance. Thank you. All right, so check this out. I have, again, like every year, over a thousand inbounds from companies, from VC firms, from friends, predictions for 2024. I have been through every one of them with a highlighter for those that I feel like are inspiring and where possible, I'll give credit to those. I mean, there were so many good ones. In a way, I feel like a VC, getting all these inbounds and, you know, only... You shouldn't tell everybody that you read every one, Dave. You're gonna get five times more next year now. I know, I do. I go through them. I scan them. I've been doing it for weeks now and I print them all. I'm sorry, I'm killing trees here, but it's really the only way I can manage it. I was thinking this year of using AI to try to prioritize and sift, but I just, you know, the input range was just too big. But any rate, huge, huge inbound. We have a graphic on this to help you understand it relative to last year. So I bucketize them as best I could. Obviously a big jump in AI. Cybersecurity's down, but it's still huge. In the cloud and data center, we even got some predictions around liquid cooling, which I'm not gonna use, but I love that. Liquid cooling's back. Remember the old mainframe days? It was all liquid cooling. Had a smattering of DevOps again and digital and digital was actually, you know, sort of down, but still some stuff in there. SAS and some other tidbits. So, and then let's just do a quick rundown with the next slide of this year's predictions. Okay, and then we'll really get into it. We're gonna talk about tech spending, like we always do. Gen AI, you know, we got this ROI focus here and you can sort of see here.  But Eric, I'm super excited to be with you and really want to get into it. So let's start with the macro. The first prediction you see on this first slide number one, tech spending increases. If you bring that slide up, Alex, tech spending increases. Nope, next one. Tech spending increases 4% to 5% in 2024. So when you take a look at this data, so what I did here, Eric, is I took all the macro drill downs and the expectations for the full year spending increase and I plotted them here. So we exited the isolation economy, very enthusiastic. People thought their tech budgets were gonna increase 7.5%. We know what happened. Ukraine, Fed tightening and all through 2022, we saw those expectations for the year go down. And then we saw that through, even after the Fed stopped tightening, we saw it flatten out at 2.9%. We actually ended up at 3.4% in 2023. And you can see the forecast for 2024 is 4.3%. But it's back loaded. So that's a little bit, Eric, of a concern. You got 2.4% and 3.1% in Q1 and Q2 of 2024 respectively. So we got some work to do to get to 4.3, Eric. Yeah, there's a lot of takeaways on that slide. I feel like we could probably do a whole post on that. But one of the main things I think we have to stay positive about and optimistic is there does seem to be a thaw in the spending of what we went through over the last six quarters, where the spending got a business, Fortune 500 at one point was less than half a percent. It got down to 0.3. Then one of the things I like here is not just the overall spend rising, but the largest companies are starting to participate and getting closer to the mean. Now it's still small companies that are leading the way at about 6.5%, but Fortune 500, for example, has gone from 1% to 3% rise in budgets just since July. So we're starting to see the world's largest organizations participate as well, which is really optimistic. Yeah, and that said, you still have SMB significantly ahead of the global 2000, almost double the rate. So that's something that we're watching. I think generally, Eric, organizations are just, there's a lot of uncertainty. I think people are waiting for earnings. I think people are afraid that earnings estimates are maybe a little bit too high. So they're just going to take it quarter by quarter. Yeah, there's some positive signs, but the trepidation isn't over, not even close. There's still people wondering if there's going to be a soft landing or hard landing, or even if we're just going to continue to grow at all. But as you said in that slide, the Fed still kind of controls the reins here, and it's a wait and see game with them. But one of the things that is positive is in speaking to our IT decision makers in our community, the cloud audit seems to be over. They spent an entire year just answering to their CEO and CFO about where their spend was, and that seems to be easing. We're also seeing in the macro survey data that new IT projects are on the rise. So there's a lot of optimistic signs. We're seeing increased net score spending in IT consulting and command services, which is always a leading indicator. So based on the data, I am cautiously optimistic that this spend and this rise will continue throughout the year. Okay, let's bring up the next prediction. Number two, AI is not a rising tide that lifts all ships. Look, there's this narrative out here that AI is going to benefit everybody. We don't think so. We think AI is a two-edge sword in some cases. It's helpful and you see companies obviously like OpenAI and some others that are really taking advantage of it, notably some of the cloud vendors, but 40% of customers say that their AI budgets are coming from elsewhere. So this chart is just selective here. It shows net score or spending momentum on the vertical axis and the overlap in those 1700 accounts. So it's plotted by the end. So it's a measure of sort of presence in the dataset here. And we just selectively plotted some companies and that red line at 40% indicates a highly elevated spending level. And our premise here is that there's going to be haves and there's going to be have nots. There's going to be some me too AI that lags. And so you can see this is from the January data. It's the spending momentum in 662 ML and AI accounts. So you can see where there's AI affinity, obviously Microsoft with Azure and AWS up to the right and well above that 40% line, notably Google is below it, despite their AI chops. And again, this is selective.  And it's really interesting here, Eric. You got laptops, Dell laptop and Apple laptops. And we're hearing a lot of talk about AI and laptops and GPUs and more cost effective NPUs and laptops. You got some, we added a SAS player like Workday. You got UI path, that two-edge sword. You got some other observability and security companies like Zscaler and Cloudflare in there. You got Mongo, a data company. And then you got some of the legacy guys that we're going to talk about SAP, Dell, VMware, Oracle, Cisco and HPE. Now, these guys are going to be able to take advantage of AI selectively either because of their market leadership or because they have acquired assets in the case for instance, Cisco and Meraki, right? HPE is acquiring Juniper because of the missed AI. And so you really have, I think a mixed bag here. It's not just, oh yeah, throw your glove in the field and AI is going to save you. We don't believe that narrative. Eric, what do you think? Again, so much there to unpack. The hyperscalers clearly are the ones that are benefiting the most at the moment. And then of course, when you have sophisticated data companies like Snowflakes and Databricks, also very important at this point in the journey in AI. I thought your comment around Cisco Meraki was interesting, Dave, because when I just recently did the quarterly report for Cisco and Meraki by far was the bright spot in that data set and really shining in not only networking but also in unified endpoint management. So I think it's really interesting your case. Gen AI is certainly not lifting all boats. And I think the biggest battleground right now is an RPA. Really kind of curious to watch and monitor that and see what happens. You would think that Gen AI would boost RPA but it could also just sort of piggyback it and just kind of jump right over it. And Gen AI and in itself it's embedded properly could end up just basically taking RPA out of the market and just do it itself. I think that's the battleground I'm most intrigued to watch this year. It was interesting, you and I talked this week actually about the open AI alignment and you guys have a data set on that. We're not going to show it because it's a little too sophisticated for a half hour show like this. But what you saw with the RPA guys and the automation guys is the three leaders. Power Automate, UiPath and Automation Anywhere had strong alignment and affinity to open AI and the others not so much. And so there was some, seemed to be some spending momentum around that. You know, we'll see. But I mean, I think generally our sentiment is that market leaders are going to be the AI leaders if they embed AI, they embrace AI, they apply it, they don't AI wash, they partner and they execute. Mike Finley, CTO of Answer Rocket said, you sent in the prediction and the quote, me too AI vendors will sink. Okay, let's go to the next prediction. Number three, 2024 is a year of AI ROI. But payback is not assured. This is a chart from one of ETR's drill downs. It asks how soon after the initial deployment did your organization achieve or does your organization hope to achieve ROI and Gen AI? 57% expect ROI inside of a year, 40% inside of six months. But you look at things like data quality, skill sets, legal and privacy concerns, those remain challenges and headwinds. And look, if payback may not be high enough to fund massive budget growth, we've seen AI stealing from other areas, we've seen some compression, as Eric was just pointing out, it's a two-edged sword in some sectors. And you should expect pushback on co-pilot seat pricing. ETR has some data on that as well, which I saw in the data set. Eric, very interesting that some of the customers are saying, you know what? We don't want to pay all that extra per seat per co-pilot. Yeah, it depends on how widely you're gonna roll it out, right? If you're just gonna allow it to be in a couple of departments, no big deal. But if you're gonna use it at enterprise-wide, that's a lot of licenses to add $30 per seat to. Right now, I think in the testing phase, there isn't too much pushback on pricing. But when it goes into full-scale implementation, I think you're right, it's gonna be difficult. We'll see how they handle that there. Just in general, we've been doing a lot of work on generative AI. If anybody wants to hop into our data and our custom surveys, I'd be happy to go through it. But I think it's amazing to watch the evaluation rates. Only 25% of our ITDM communities say that their organization isn't evaluating at all. I haven't seen a technology ramp up this fast. It's really incredible. But as you said, over a quarter of these people aren't sure there's any ROI at all. That's still a high number, that's a little scary. The other thing I think that's interesting is where is the budget coming from to fund this? Right now, it's split. About half of our organizations are saying that they're funding this with new money. The other half saying they're stealing it from somewhere else. And where it's being stolen from is common sources include non-IT departments and productivity applications. So it's interesting to see as this continues, I want to watch the evaluation rates go into actual use cases, and I want to see where the money's coming from. I'll give you another stat on that when I was digging into some of the RPA data, because that is kind of the obvious two-edge sort area. And only 7% of the customers said they're stealing from the RPA budget. But two other points there. One is when you look at certain industries like financial services and manufacturing and industrials, the figure doubled. So that was a bit of a concern. And when you just mentioned it's coming from other budgets like non-IT budgets and line of business budgets and other sort of productivity budgets, many of those could be automation related. So those categories aren't necessarily mutually exclusive. Yeah, agreed. And anecdotally, we did a panel on this and one CIO laughed at the pushback on the pricing and he said, what do I care about $30 per license if it saves me 100 full-time employees? So it's really a wait-and-see game. If the promise of Gen AI actually delivers, I think the pricing demand is gonna be pretty strong. Okay, let's take a look at number four. The next prediction, the power law begins to take shape in 2024. Now, let's explain this because it's really nuanced. The power law really describes, it takes an example from the music industry where you had a very hard right angle where just a few labels dominated the industry and you had this kind of long tail of music producers. And we see something similar with Gen AI but different. We see the torso, the cloud guys dominating and we take liberties, by the way, with the term power law. We've got here in the dimensions, the vertical dimension is size of model. The horizontal dimension is model specificity and we've identified some industries where we think we're gonna see specific models and potentially on-prem models or likely on-prem models emerging. We're already seeing some of that. And the idea being the cloud guys and the big AI, LLM vendors, they're gonna have very large models and they're gonna initially, they're the ones that are dominating, they're getting all the discussions. But you've got this open source, this red line pulling the torso up and to the right. Lama two is the obvious one, but you've got some other independence and other third party and open source players that are pulling that up to the right. And then the long tail is specialized AI. So cloud continues to outpace on-prem, no question, but we're seeing that privacy use cases are emerging and open source pulling that torso up. Based on the ETR data, just playing around with some of it, I can infer that about 30% of the Lama two deployments appear to be on-prem. Meta has indicated it could be as high as 50%. And I don't think, Eric, that in ETR, you're surveying three letter government agencies. So they're probably doing a lot of stuff on-prem. And we're also seeing the emergence, initial emergence of model integration, like private model gardens. Think things like bedrock, but building your own bedrock. So right now it's sort of a very mixed environment. I guess the prediction really is that you're gonna start to see signs of this power law emerge in 2024. What are your thoughts here, Eric? Yeah, it's a very interesting model and theory that we're kind of rolling out on this one. I do still think that there's a little bit of a bifurcation of what's happening and I think it's too early to tell, but very clearly there's gonna be a long tail to this. We forget how early we are in this. It was just a year ago that OpenAI came out, that OpenAI, excuse me. There's a lot more to come. I think the most important thing that you said there for me is the data that we're seeing right now in cloud is not just public cloud. We're seeing a real resurgence on the hybrid cloud with a strong leaning towards private. And we're hearing this a lot from our CIOs as well. We just recently did a series of eight interviews on 2024 top trends and private cloud was spoken about by six out of eight of those CIOs. And I do think there's a lot of data concern. There's a lot of regulatory concerns still around GenAI and being in control of that data and having that sovereignty in your own private cloud is one way to handle that. Yeah, and you think about companies that have competitive data and they're trying to use foundation models to give access to their internal sales teams on things like knockoffs and other sort of competitive information, pricing information and they want that to be available. They're very nervous about putting that in the cloud. They're very nervous about bringing in other data sources. They're nervous about the legal requirements and so it's going to take some time. Well, they should be too. As well they should be. As well they should be. It's way too early for people to just be going around and throwing that data around and trusting where it's going to end up. Just some quick hits from some of the other predictions that came in. Some of the thousand. John Rose from Dell. He's the CTO of Dell. He said that GenAI dialogue is going to move from theory to practice and is going to focus more on inference. Quentin Clark from General Catalyst of BC predicts that specialized AI will take shape and open source models will emerge. That's consistent with the power law. Bert Greifender who's the CTO of Dynatrace predicts that hypermodal AI which combines different AIs with other data sources will emerge and much of that is going to happen on-prem in our view. It's interesting. We sometimes forget there's more AI than just GenAI and Brian Harris is the CTO at SAS predicts that GenAI has to be viewed as a feature of industry solutions not a solution in and of itself. Again, we agree that these domain specific AIs are going to see that long tail. Patrick McFadden of DataStacks predicts that we're headed more toward a GenAI monopoly. So that's sort of counter to the long tail. We hope not, but we kind of agree that hyperscalers right now are in the driver's seat. He predicted actually back in November that regulators are gonna come raining down on these big internet companies and that prediction has already come through with Lena Kahn this week, taking recent actions. Okay, let's get- One quick thing to add, Dave, I can on that. I think it's really interesting in the recent GenAI study that we did, it's split 50-50 between people saying that they're going to develop their own AI solutions using open source, whether it's Anthropic or OpenAI. And the other 50% are still hoping that it'll become embedded in their already trusted vendors. And those vendors, they've got a window, but it's not that large of a window. They need to really start rolling that out and start embedding AI into their offerings if we're gonna see that continue. I just thought it was an interesting data point that came from the study I wanted to sneak in. I'm glad you said that. Five years ago, I predicted and worked with, collaborated with my friend, David Michela, who wrote, he's an author, and we kind of predicted, pulled out his prediction that AI, you're going to buy it, you're not going to build it. And then of course, GenAI comes out and it becomes, wow, this stuff is actually pretty easy, even though there's still some barriers and skills issues. But like for instance, the Cube AI, you go to thecubeai.com, you can see our RAG, our Retrieval Augmented Generation Model that we built, and most people haven't done that. You know, we got a development team, but you're going to see RAG out of the box and you're going to be able to point that at your data sets. And so it's going to become easier and you have to build your own AI.  It's going to be interesting. Okay, let's bring up number five back to basics in cybersecurity. You know, AI gets all the headlines, but it's going to be embedded into cyber and it's going to support these areas shown. We're seeing identity, single sign-on, vulnerability management, endpoint, network security. These are the areas of information security that are the highest priority in organizations and it's a lot of the same stuff. And we think that consolidation trend is going to continue. We also think that the VCs are going to keep funding cybersecurity startups because it's still broken. So that's counter, but the consolidation trend is going to favor the consolidators, Palo Alto Network, CrowdStrike, Zscaler, even though consolidation of vendors, of redundant vendors was the number one method of reducing costs last year and it's way, way down. There's a premise that we're putting forth here that that is not going to hit as hard in cybersecurity because of the crowded space. The identity crisis remains in play and is a major challenge, pun intended. And again, AI is going to be embedded and begin to change the SOC analyst experience. We saw this at CrowdStrike with the announcement of Charlotte, their LLM, which is very, very powerful. Eric, your thoughts on this data? Yeah, it's very interesting what we're seeing right now in the security space that everyone is really progressing. We're seeing all these vendors roll out different feature sets, really pushing the envelope. And at the same time, we're seeing consolidation happen. And there's so many startups and my CISO friends are much more likely to take a look at a startup than my CIO friends. They're just always looking for an edge and an advantage. So they're willing to test out those series A through C companies where sometimes you don't see it in the rest of technology. I think we're going to just continue to see importance and explosion of new technologies, new features in this space. And I think some of the bigger players are going to have to get a little bit more M&A active if they're going to keep up. We're seeing that a little bit, but I think we're going to see more of it. I think that environment is stalling out. The other thing I want to point out is anecdotally, and I speak to a lot of security experts, their focus this year is not so much on the tool set. You know, we used to talk all the time about, I want best of breed. I want layers of defense. I need this tool, I need that tool. Right now, all they're talking about is employee training, penetration testing, asset management, vulnerability, patching. They really are getting back to the basic hygiene of security and that's where their focus is going into this year. And it's not just one. It's almost everyone I speak to. So I think it's going to be an interesting year and I like the way you phrase that and back to basics and security. I agree 100%. Yeah, thanks for that. That's some good data points and perspective. Just some predictions and trends from the marketplace. Again, the inbounds of Dell's annual data protection survey that Rob Emsley and Michael Wilkie shared with me, says 65% of organizations are not confident that their organization, not very confident that their organizations could fully recover from a data loss incident. The Veeam data protection trend report found that 52% of production data is backed up on tape still. So everybody says tape is dead. No, it's not. And 61% of production data is also backed up on the cloud. Dave Russell and Jason Buffington presented these stats to me recently. Let's see, voice is going to become the new fingerprint according to Aaron England, the CPO and CTO of Rev and Nick Schneider of Arctic Wolf predicts that over-hyped tools driving the need for security operations, which of course are driving the need for security operations of course, which Arctic Wolf provides as a managed service. So some thank you for sending those stats in everybody. Okay, number six, private market shifts, M&A and IPOs pick up. Here's a chart. This is all private companies from the emerging technology survey, ETS, that ETR does, I believe it's quarterly. Again, spending momentum in the vertical axis, actually sorry, net sentiment, which is intent to engage. Do you know the company and you're going to do anything with them? Are you going to evaluate them? Are you going to deploy them? Are you going to deploy them further? So intent to engage on the vertical axis and then mind share. You know about this company and the horizontal axis. And then we've just picked and chosen some names here that showed up on like the top names in each axis. So you can see here, open AI off the charts, Docker, Figma, which I guess was supposed to be acquired by Adobe and they canceled that acquisition. Databricks, OneTrust, BeyondTrust. You got NetScope in there. We've talked about them.  Cohere, an LLM player, Entropic has gained a lot of VC and other investments from the likes of Amazon in particular, $4 billion investment also Google. You got Hugginface in there that a lot of people are doing work with. So we also think you're going to see more smaller seed rounds. Great time to start a company and VCs love it too because they don't have to put as much in all this AI hype and you can do more with AI. We think cyber and AI are going to continue to get all the attention just like all of our inbound. And we think M&As and IPOs accelerate potentially Databricks, Sneak, Arctic Wolf, Beyond Trust. Last year I think there were probably, I want to say 150 IPOs down from the previous year. We think we're going to see more IPOs and more IPO action this year, but we're not going to get back to 2021 levels where we saw a thousand IPOs. Eric, your thoughts. I completely agree. On the private equity side, particularly, they had a lot of money heading into this recessionary period where the headlines got bad and they stopped spending, but they still had the cash. And I think that environment's really warming up where we're seeing a lot on the private equity side. I mean, heck, New Relic got taken private, Ford Rock and Ping are about to be joined and probably rolled back out again. I think you're still going to see a ton of happening on the private side. And I think, yes, IPOs are finally going to warm up again. It's just crazy when you think about a company like Rubrik or Databricks still being private. So I definitely think we're going to see some IPOs. And as far as that M&A activity, there's some names on that list that are just right for the picking. I mean, Cohere, Hugging Face, particularly on that side, I can't believe they're there. And we're constantly seeing Wiz and Sneak, incredible data for young companies, really strong, growing their provision, growing their mind share. You need to take a look at these.  And Mark Sassen of Pinpoint Search Group shared that, I believe this was just a cyber only, 437 funding rounds and M&A transactions with $8.6 billion raised over 346 rounds of 91 total acquisitions last year. So we'll keep an eye on that. Okay, let's go on to the next one. Number seven, data quality and governance concerns favor trusted ecosystems. Let's talk about this. This chart from ETR asks, which aspects of the organization's data and analytics programs are your organization prioritizing? The most to support GNAI goals select up to two options, data quality, data lakes, data diversity, data literacy, data integration, governance, metadata management. And we think these, this favors trusted platforms that have ecosystems to support these types of activities. AWS, Azure, obviously Google, the hyperscalers, even though AWS and Azure are well ahead of Google Cloud, but Snowflake and Databricks, even Oracle, it's a trusted platform, it's got transactions. When you start to think about the sixth data platform that we've talked about moving beyond just separating compute from storage, separating compute from data, actually unifying metadata. This gets complicated because of all these other factors, as well, when you have different data types like transaction data and unstructured data and distributed data and different query types. And when you bring together transactions and analytics at scale, you got to throw an Oracle in there because they're the company with the transaction data I would throw in IBM as well. We're going to talk about them a little bit later. But so you've got some interesting activity going on here where people are really focused on data quality improving. And we think, I don't know if you agree, Eric, that this is going to favor some of those established platforms. Without a doubt, and the data, we're going to get to it in a minute so I don't want to kind of steal the headline. But I love that you're bringing up Oracle, IBM, Dell. Their data set looks fantastic, heading into 2024, something I haven't been able to say in quite some time. But when we talk about this particular aspect, it all comes down to data quality. That's what we're hearing. I don't care who you are. If you want to use a large language model, any sort of AI at all, it comes down to your data quality.  You have to have good quality data. After that, it's about the ecosystem. It's about your ETLs, your pipes, and then you can finally get into analysis and getting into your hands of your business users. But I still think we're at the stage of data quality. I think it's utmost importance, and you could see in our data set, I think it was two to one favored, any other aspect in that answer option in that survey. Okay, great, thank you. Let's bring up number eight, renewed importance of new data literacy and skills and yes code, which I'll explain, but this came in from Eric Bradley and I'll just read it verbatim. Gen AI as well as more business user friendly self-service capabilities like low code, no code, RPA and Gen UI tools code generated from screen grabs. That's my little addition. Bring with it new sets of skills that will be in demand in the market, watch for the rise in offerings from IT training companies like Pluralsight, SkillSop, LinkedIn, Learning, Coursera, et cetera, that focus on things like Gen AI, prompt management or ethical responsible use of Gen AI, et cetera, we'll start to see new roles like, I love this, Gen AI prompt engineering Eric, you write on on that in the market, as more orgs let Gen AI proliferate, there will need to be more data literacy training in general across the workforce so that the outputs from Gen AI are used properly and Gen AI hallucinations are seen with a critical eye or minimize and yes code is Gen AI plus front end tools equal generative UI, that's from Lee Robinson, VP of product at Bursell. But Eric, this is your wheelhouse, you shared this prediction with me, thanks for doing that, maybe you can elaborate. Yeah sure, first of all I gotta give all credit to my senior analyst, Dr. Darren Brabham, this was him, he's the one who leads all data aspects for us here at ETR and he's fantastic so I'm gonna give him credit before he sees that and gets mad at me. So this was Darren's but I completely agree with him and one of the things I wanna add anecdotally which I find really interesting is I'm seeing Gen AI prompt as a skill set listed in job descriptions and even in resumes that we're getting, I've never seen that before, that's something that's just new in the last month or so but basically what this comes down to is there's a lot of non-technical business users that need to become more data literate and develop those skills just to stay relevant in their own jobs, whether it's me at age 49 or whether it's somebody young, you have to figure this out and there's a lot of forces that are happening whether it's low code, no code apps or the rise of Gen AI, it's all converging to make sure that the business users themselves can actually handle this type of workflow and you have to become data literate, it's not gonna be difficult because the vendors are making it easy but you do have to make a little bit of an effort to actually stay relevant in today's world and as we're seeing the majority of the budget for AI right now is coming from the business departments themselves, non-IT related so I think this is a trend that's here to stay, I would urge any young people out there to go ahead and make sure you get yourself at least a little data literate. Great, thank you for that, Eric and Darren. Okay, let's bring up number nine, legacy rebound powered by AI, laptops, cloud and acquired assets, so this is really interesting. So first of all, we're showing you a chart, it's a shared net score on the vertical axis and overlap which is plotted, it's informed by the end so it's really a measure of presence and overlap within that 1,700, 1,766 N in the accounts and we plotted, Eric, I just, I picked some legacy companies and legacy I guess is a derogatory term, it's a pejorative but to me it's not, I mean you build a legacy, I got a friend who is a financial earner legacy, he calls it legacy, I mean he's been in business 30 years, he's a very successful financial planner. Anyway, you got Cisco on here, Oracle, IBM, Dell, HPE, but IBM, IBM Watson, SAP HANA, really one of the few up over that 40% mark but in Maraki we talked about before, Red Hat which is the asset, Aruba which is an acquired asset. The most interesting thing here is the momentum that we're seeing in the market on laptops and we know there's a new Windows cycle coming, there's a laptop refresh cycle, Apple has had NPUs in its systems for a long, long time, Dell laptops, I think are gonna power that company this year. Cisco acquiring Maraki, really doing more with that asset, now acquiring Splunk, IBM getting its act together with Watson, you saw its recent earnings announcement, looks like Arvin Krishna really has that company on the right track, it's got the Red Hat acquisition so you're seeing these legacy companies, these established companies, in the case of Oracle investing, they've certainly done a lot of R&D work, they're making huge acquisitions like Cerner and whereas in the old days, Eric, you had situations where the big established companies would poop who the next wave, we saw that with the Dex, the Primes, the Wangs, the DGs, companies that young people in this audience have never even heard of, they were high flyers, sun microsystems, they were the hottest companies going, they're gone now because they pooped the future. These leaders today, they don't dismiss the future, they invest in it because they're paranoid, only the paranoid survive, as Andy Grove said. But I'll throw it to you, this is something that you put on my radar, what are you seeing in the ETR data and what makes you sanguine about some of these legacy companies? Yeah, I haven't been excited about these companies in a very long time, the data looks incredible across the board and it's amazing the breadth of the rebound we're seeing in their spending trajectory, it's not just one area, it's coming from cloud, it's coming from the data side, in the instance of IBM and Red Hat and Ansible, they're just doing fantastic.  And what we're seeing right now is so much share shifting away from that to some of these other people and they're trusted, they're already entrenched in an organization and what happened, at least what I'm hearing anecdotally, is a couple of years ago, people were saying, I'm sorry, Oracle, IBM, Dell, SAP, you guys are great, but you didn't keep up and I'm really gonna shift over to the cloud, I'm gonna take a look at this. And then what happened, the world kind of paused, spending paused and they didn't do it. Now two years later I'm talking to them and they're saying, you know what, these things kind of got a little bit better, they caught up, I actually think it's a pretty good product now and is it really a priority for me to spend all this time and capital and resources to shift off what's an improving product to go to the cloud. And at the same time, they just went through a cloud audit and found out the cloud's not always as cheap as you think it is. So what we're seeing right now is that these companies were all given a second life without a doubt and we're seeing the data broadly improved for them in many areas and it's gonna be great to see what they do with it. They've gotten a second chance and I hope that they just continue investing using R&D wisely and going after some M&A and just keeping their footing because no one wants to see a world where it's just Microsoft and AWS and the enterprise. Yeah, so I'll share as well just some pros from a recent report you guys just put out. Don't call it comeback. They've been here for years. ETR has data rebound on legacy companies like IBM, Oracle and Dell working thesis. The recessionary environment and budget crunch stopped the planned lift and shift of core mission critical apps to cloud providers giving these companies time to catch up. Now coming out the other side, the existing functionality is good enough and replacing them no longer is the top priority. You know, let's see what they do with this. Second chance as you just mentioned and the legacy names that we just talked about asserting their presence back in the cloud race like Oracle with OCI, IBM sort of in a different way really focusing on the hybrid cloud which seems to be working. Dell as well has got its cloud in the form of Apex HPE with its GreenLake asserting their presence back in the cloud race can be something to watch this year. And with that comes other renewals of legacy software footprints, hardware refreshes, software servers, storage, et cetera. And then as we saw in that chart, laptops and we're going to see a laptop refresh cycle we think we heard it in Intel's Intel had very disappointing earnings but they did point to growth in future quarters really due to PC sales. Okay. The data, real quickly, the data on that is very strong. I easily we could have put a full hardware refresh cycle into this prediction post. I think maybe just it might be a little bit well known so we chose not to but the data across the board in all areas of hardware, not just the laptops and PCs but we're also seeing in storage and servers. There's definitely a refresh cycle coming in the hardware space. And that's good news for these companies and look, there's so much territory that we could cover on these. What we try to do and thank you again everybody who's sending in these literally thousands and thousands and thousands of inbound's we really appreciate it. We try to find predictions that A can be quantified so they're kind of binary where we're right or wrong and B does it align with some data that we have we can actually go back and do that look back but so thank you again. Okay, the last one let's bring up number 10 tech priority cyber analytics, AI, collaboration cloud networking automation remain the top tech priorities. Look, this chart you guys run this this is an end of 890 cyber has always been the top priority. Yeah, it's maybe down a little bit but no matter what industry you look at no matter what geography you look at it's right up there. Analytics holding strong, data warehousing, data matters and even given all the Gen AI hype what you can see is on a nice steep uptake here it's still people got to get their data act together before they can really take advantage of that. Collaboration was obviously top dog or a top dog during the pandemic, still important. Cloud, yeah, it's tapered off a little bit. Cloud optimization was a big thing last year but cloud is still where a lot of the innovation is happening, the optionality in cloud the ecosystems in cloud are still really powering innovation. Networking becomes more important in the world of AI it's like the new bottleneck and we've talked about RPA it's been a hot market for a long, long time so it makes the cut here and as you can see it's picking up a little bit it's the classic two-edged sword Eric with RPA. Your thoughts on this? I think the most interesting aspect in that and we do run this all the time and it doesn't change that often so even a small integer movement is actually of interest and that cloud migration number that's a big drop. To me that's the main takeaway when I first ran the study and we looked at it I always expect security to be the number one I was not shocked by the movement and machine learning and artificial intelligence cloud migration was. So after we ran the survey I did eight interviews, top trends series which I'll be releasing that on Tuesday it's an amalgamation of all the findings and we asked people about this why is cloud migration showing it's slowing and they said basically that everyone always anticipated their cloud workloads to get to 60, 70, 80% but it's happening much, much slower than they ever anticipated. It's still happening it's just not happening as fast and the majority of the people I interviewed again were talking more about building out private cloud assets they wanted more of a hybrid model not directly going to cloud migration in the public cloud. Yeah, this is interesting because I think that is a somewhat of a concern I've been forecasting we saw last quarter Amazon's growth rate the deceleration of that growth rate stabilized and I'm expecting an uptick this quarter not a huge but an uptick maybe a couple points in growth really from Gen AI I would expect the same for Azure and we saw a little Azure action or Gen AI action last quarter from Microsoft, Microsoft announced I think on the 30th or Amazon shortly thereafter I think you're right I think a couple things is I think the prevailing narrative that 90% of the work remains on prem a big chunk of that is telco and that telco and that whole telco market that communications market is probably as big as the traditional IT market. So if you take that out a much higher percentage of the workloads are actually already in the cloud. So it's not so much a story of migration anymore it's a battle for new work, new workloads, new spending much of that AI work is being done in the cloud today but because of the reasons that we mentioned before and the whole discussion that we had talked about around the long tail of the Gen AI power law and the fact that budgets just aren't going through the roof like they were in 2020 and 2021 people have to make choices and they have to make trade offs. I'll give you the last word on that Eric. Yeah very interesting on that I agree. I also I just wanted to point out your comment about AWS anyone that actually follows our data you wouldn't have been surprised in the slowdown on AWS in the cloud. You really wouldn't. I'm looking at my chart right now just going straight down to the right went from 70% down to 40% over the course of 2022 and 2023. What we are seeing now however was a really significant rebound. So that cloud audit does seem to be over and it totally when I speak to people and I do think your comment was spot on. It's not anymore about the migration of it's just actually what work is being done there and it's going to have a very long tail. The digital transformation is not over it's a long tail game and I still think cloud is healthy but you can't really keep those growth rates up forever. Yeah that's definitely the new way but it's not about cloud migration anymore that lift and shift occurred where we squeezed a lot of juice from that lemon there's maybe some left but now it's all about innovation and I think a lot of that is coming from Gen AI. We've noticed, I've noticed just anecdotally looking at the data from the drill downs and the ETR data that when a company announces a Gen AI and it goes of GA, you get a big uplift. We saw this with Vertex at Google Cloud Next. We certainly saw this at Microsoft. I would expect we're going to see this with Bedrock going GA. I think it went GA late last summer maybe September, maybe even October time frame so I would expect to see that in the Q4 numbers. Yeah but hey, as always, Eric, appreciate your time and we're going to be here tracking this on an ongoing basis. You guys do tremendous work. Really appreciate the collaboration. I think this is our third predictions, right? Third year. It's a therapy in a row, yeah. Always enjoy it. So thanks again. Okay, that's it for now. Thanks to Alex Myerson and Ken Schiffman on production Alex also manages the podcast. Kristen Martin and Cheryl Knight they'll get the word out on social media and in our newsletters and Rob Holt is our EIC over at siliconangle.com. Thank you all. Remember these episodes are all available as podcasts wherever you listen, just search, breaking analysis podcasts. I publish each week on the Q research.com formerly Wikibon and siliconangle.com and you can email me at david.balante at siliconangle.com or DM me at dbalante comment on our LinkedIn posts and definitely check out etr.ai. Not only do they have the best survey data in the business, we're going to market together. You know, we're working very closely with the Q research analysts and the ETR data. So check that out. This is Dave Boulante for the Q research insights powered by ETR. Thanks for watching. We'll see you next time on breaking analysis.


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Hi, I'm Columbia Mayor Steve Benjamin. The City of Columbia, like so many great cities, has had to overcome two hurdles resulting from the COVID-19 public health crisis. The first was asking our citizens to quickly and dramatically change everything about their lives, the way they work, go to school, worship, shop, and entertain themselves. We were successful and inspired by the way the people of Columbia unselfishly changed their lives for the better good of community health. The second hurdle was overcoming the severe economic downturn. It was devastating to see so many working citizens lose their employment and income and watch so many businesses shutter their doors, uncertain if they could ever reopen. Again, we rose to the challenge, assisting hundreds of small businesses with millions in emergency funding. Now that we've made progress in reducing the spread of the virus and our businesses have begun to reopen, I encourage everyone to maintain social distancing to prevent a resurgence. Everyone should stay at least six feet away from others, wash or sanitize your hands often, and please wear a mask or other form of face covering when you're out in public.


Thank you. OK, so this is a talk which Ron Sutton advertised the other day. So he promised that I'll show you that the Norfolk antics about to return to the 1960s. I'm not sure I can quite promise that, but the Norfolk antics been doing some pretty interesting things recently. And I'm just going to take you through some of that now and some of the evidence. So this is work I've been doing with Pablo Ortegu and Ron Sutton ready. So thanks to Gokhan and Tom, os ydych chi'n gweld o'i eu cyfrofiadau'n meddwl i'r holl yn yng Ngwyllt Aeol. Felly, mae'n gweld o chyflodd arno i gyd yn ysgolwch a'i gael ei wneud o'r hwy. Mae'n gweld o'r ffordd a'i wneud o'r hwyl yn y Cymru, ac yn y Llywodraeth, ac arall o'r rhan i gyfrofiadau, mae'n gweld o'r hwyl yng Ngwyllt Aeol yn y Llywodraeth, ac y Llywodraeth yn y Llywodraeth, ac yn y Llywodraeth, but we're still not really sure what's been driving it. Of course, there's lots of evidence of the A mark in ocean circulation, it's important there's obviously evidence of arisol are important changes in surface fluxes, etc. However, what Rowan did show is that we're actually think we're getting quite confident we can predict certain aspects of this A and B. So in particular the ocean, the large ocean heat content changes in the sub-polo gyF our quite predictable. So this is a plot from one of my studies which just The black is the observations. This is large warming in the mid 90s which is so Shaded with this shift in the ANV SST. And this red lines and initialised prediction made with the U.K met office Model and so it's quite it captures it quite well. We see this in lots of other models as well so we have some confidence that we can predict these changes Ysgríut Oeward Cymraeg a Lleidwyr Change is now quite a few studies and the last couple of years has started to come out saying that we should be expecting a cooling so a flip in sign of this A and V, maybe even perhaps to this cold state. So the key question is if this will happen and when we might enter a cold phase. So we're gonna start this story in looking at this switch to the warm phase of A and V for the mid-1990s into the early 2000s. This plot here shows on the left is just a linear trend in SST data in the middle. effeithi blade head yw'r holl honi hwn yw'r ysgrifiad o gyllid y Llanthag Llanthag i wneud eich holl hyn arweinydd byddwch ar y holl 700 m ac mae'r holl hwn yn bryd y teimlo yn llunio'n cyffredig Felly, mae'r holl hwylol yn rhoi Llanthag Llanthag sportwyr nifer 90s y holl y postroff o'r holl y mae'r holl hwyl ffocaid ar y taithiaf a grannig gyda gynnog mae yna ni'n groes yma Wythno ar fy mwyaf yw'r holl hwyl You saw this really large change in ocean heat content, that you also see SST changes across the rest of the basin. And you also see this increase in salinity. If we look at what was happening in the atmosphere at the time, So there was this trend to negative NAA, which Tom was talking about. So here, you see a slackening of wind across the North Atlantic. This is all annual means by the way. ac mae'r cyhoeddi anodd yn ymhwyloedd yn ymweld a'r cyhoeddi anodd yn ymweld, a'r gwirdd yn cyfnodd yn ymddill o gyllidiaeth, ac mae'r cyfnodd yn ddorol, i'r ffordd yma, felly yn ymhyfru'r cyflwyno'n gyfrifiad, felly mae'r cyfrifiad yn ymweld. Mae'r cyfrifiad yn ymweld i'r cyfrifiad yn ymweld i'r cyfrifiad. Ond mae'n gwybod i'r gwerthu'r cyfrifiad o'r cyfrifiad o'r cyfrifiad. Mae'r oedden nhw'n meddwl ar y ffath, mae'r oedden nhw'n ei wneud ar y cyfnodau o'r cyflwytoedd o'r hyfforddiadau ar y dyfodol o'r newid yn ymddangos. Rydyn ni i'n cael ei adnod o'r cyflwytoedd, yn ymdweud yn ymddiadau'r cyflwytoedd. Wrth gwrs, ydych chi'n gweithio'r cyflwytoedd o'r cyflwytoedd o'r ddechrau, mae'n ddweud yn ym 2014, ac ydych chi'n gweithio'r cyflwytoedd o'r cyflwytoedd. ychydig o'r swyddo'r afglau'r cyd-ddiogel, ychydig o'r sefyllfa ar y Gair. A'r cyd-ddiogel yn oedon hefyd ac yn gwybod a'r s messiol, yn oedon hefyd. Mae'r gweithio bod yn anod ymhyng yn y gwirionedd yno. Mae'r cyd-ddiogel yn y Nôr Fylltig. A'i gydig i'r ysgrifenniau, sy'n rhoi'n rhoi'n rhoi'n rhoi'n rhoi'n rhoi'n rhoi'n rhoi'n rhoi'n rhoi'n rhoi'n rhoi'n rhoi. Felly'r ystyried, mae gwneud drwy'r syrniol surwadol yn y clwydd diwrnod ar y cyfnod ond yma, ond ond ry'n golygu, yn y cael ddefnyddio'r awtioon yn ysgrifion ffeithleid. Mae'n rhoi yn ysgrifion yn y ffwrdd yw 4'n wedi'u cyfrif… …ö at ynfertydd—命afelau bwyr. Mae yna'r rai un o'n gwneud ydynt, fe wnaeth ein bodai'n gwneud y ffyrdd yma. Gyda'r gweithio'r ffwladol y ddoch. Mae'r gweithio'r ffwladol a'r ddysgu'r gweithio'r newid yn ddweud. Mae'r gweithio'r gweithio'r sphaneol wedi'i gwaith. Mae'n ddiwethaf, ac mae'n cael ei ddweud bod yn ei wneud yn dda'r ffwladol o'r oesig, ond mae'n cyfwladol yn gweithio'r oesig. Felly, sy'n bod yn ni fynd i'r gweithio, sy'n bod yn ni'n meddwl'r ddweud i'r negatif oedd FNAO, Over the last few years we have had these quite large, positive NAO-like events. Is this just some sort of inter-annual variability? It's quite sensitive to these years. If we just do something quite simple, we take out the last, well, the winter 2013-2014, which was quite extreme in the surface heat loss of the North Atlantic. What you find is that many of these trends are quite sensitive to this winter, especially SST, sea level pressure, wind chest curl, and surface heat flux. So if I just flick back and forth, does this work? Okay, so that's the full 10-year trend, and then this is the 9-year trend. You can see that the SST in particular is quite sensitive. But what's not sensitive is this change in the ocean heat content and the change in the salinity. So they're not sensitive really at all. So this does bring confidence. This is some kind of longer decade of timescale change which is going on in the North Atlantic at the moment. So what is going on? Well, so we know there's been some ocean circulation changes in the North Atlantic. So the top plot here is a plot from the rapid science team. So this is from the observations, the only continuous observations of AMOC trans basin, which is at 26 North. And this showed over since 2004 this declining trend in the AMOC in the North of Transport of the ocean. And so one of the things is the question is, is this wind force? Is it just random? Or is it some parts of some longer term trend? And we wrote this paper last year, which basically looks in the models. So Gokhan talked about this. One of the key predictors of AMOC in the models is this density in the Labrador Sea. So this shows on the left, density normally is averaged between 1,000 and 2,500 meters preceding a minimum in the AMOC. So it's a negative, negative density anomies preced a minimum in the AMOC. And you see that this Labrador Sea really sticks out basically. And if you take an average over this region in the observations, what you find is you see a peak in a density here in the mid 1990s, which is associated with this trend, a positive NAO, which peaked in the mid 1990s, increased surface heat fluxes, more dense water formation. But since then, this density index has really dropped off. So to the extent that if you believe these observations, it's now at its weakest point. So this would really suggest that there is kind of a large scale weakening of this kind of thermohaline circulation in the North Atlantic. So if we now kind of try and build on this and plot these two things together, so the red line now on this plot is this density index in the steep Labrador Sea region. The black line is temperatures in this North East Atlantic region. So the region which is cooling basically and the blue line is a salinity times by 10 just so to overlay. And so what you see is after this peak in a density in the mid 1990s, you see this warming of this region to its warmest ever levels observed. And then if this model relationship is true as we suggested, then we should get this cooling. And so this is what you see. So after 2005, you see this cooling. It's pretty large in this area of the ocean. So it's so the this this North East Atlantic region is actually cooled down to kind of conditions that we last saw in the early 1990s. I just before the shift to this positive A and B. It's about a cooling of almost half a degree C on average and about 1.5 times 10 to 22 joules. And that as it says that one that's equivalent to a surface flux economy about minus 4.5 watts per square over a decade or 0.05 petawatt. And that 0.05 petawatt is about half of the deficit that we're seeing at 26 north just for context. So it seems consistent anyway with this kind of idea of this firma hailine circulation forcing weakening. But is it similar to what we'd expect from the models? So we've also looked in the model. So Pablo has done this analysis. This is basically a composite analysis in the latest. Hadley centre model had gen three GC2. It's a high resolution couple climate model. We've got 300 or so years of this. And basically he's picked out the nine largest 15 year trends or declines in the Labrador Sea. And then composited the lagged trends onto that. So that we lagged the trends by five years in the model. And so what we see after you get a reduction of density in the Labrador Sea is a cooling in SST on the left, a decrease in heat content in the middle and this freshening on the right. And particularly in this eastern sub pelagia. And so if you correlate this across all of the timescales in the model, it's a correlation of about 0.5 between a Labrador Sea density index and this eastern sub pelagia region. So again, yeah, so this is consistent with the weakened heat and salt transport in the model. Surface fluxes do play a role again in the model. But you cannot explain this cooling that we see in the model. Just like in observations. So this is my last slide before a summary actually. So what are the implications? Well, so one of the things is that this density trend in the deep Labrador Sea is still negative. So if this model relationship is true between the ocean circulation and the ocean circulation and heat content is real then we'd expect this area of the ocean and the North Atlantic to cool further. If it does, we might expect to see a return to our anomalous cold SSTs over the next decade. But that's where the question mark lies. And so we'll be watching this space. But of course, if this does, given the big, the important climate impacts across a whole range of variables then of course this could have quite large impacts on the surrounding region. So that was my quick tour of what's been going on in the North Atlantic over the last 10 or say years or well, or longer. So the North Atlantic has did warm significantly in the mid 1990s and that followed this peak in this deep Labrador Sea index. So it's consistent with a spin up of the ocean circulation pumping more heat into the North Atlantic. But the North Atlantic heat content really peaked in 2005 and since then there's been quite a considerable warming in quite a large area of the North Atlantic to again to kind of to heat content levels that we last saw in the early 1990s. So this cooling is not simply explained by changes in the atmosphere, contemporaneous changes in the atmosphere. And it's consistent with what we'd expect at least from a reduction in the ocean circulation due to the deep Labrador Sea density. But that's where the big question lies. We're not really sure exactly from the observations what exactly what the changes in the ocean circulation are overturning compared to gyre, et cetera. So that's one of the big questions. And then finally this density trend has continued to decline. So we should expect further cooling over the next 10 or so years. So that's it. Thank you.


Thank you very much, you know, I'm I cannot think of any box that is not ticked by this award First of all, it's an award and it's always nice to receive an award, but it's not in your world, you know, it's It's from my peers and from some of my peers. I most like and respect and You know being recognized by people is one thing being recognized by your family It's harder to achieve and it is so much more worthy that that it is really something I'm very happy and you know, and I guess I'm talking for many of us here six months ago having a presidential conference seemed unthinkable and I will not say, you know, I see all the masks and Be all the blue faces. So it's not normality, but it's so close to normality. That's something, you know I'm tremendously happy to be here, but a little bit more about next flow. So I'm assuming everybody knows everything about next flow, but of course, that's not true Many of you here may not even have heard about next flow So I should really start by explaining what next flow is. So next one is a pipeline language You can write your pipelines with next flow your genomics pipeline typically But it could be anything and you can run them anywhere with next flow It will be your your your it will organize your your your your computation And that's on the cloud on an HPC on a laptop next flow will take care of parallelization in some, you know Relatively straightforward way. I'll explain a little bit and more importantly. It supports containers reproducibility and therefore contributes to the fair concept, you know this idea of reproducibility findability accessibility Interability and reproducibility and so next flow contribute to the are now You know, you've seen all of these things a lot You know, there are plenty of things claiming to do the same thing So I'll try to explain to you a little bit why I think next flow is special and obviously I think next way special Obviously I'm biased so you'll have to to make your own research on this before trusting me But why is it special? So let me very briefly touch on Unix which most of you are familiar with so in Unix We pipe all the time and that's something actually computer scientists really don't like about biologists. Biologists love, you know Barf marriage and to be more precise. They love the concept of piping. So what does this mean? You have a process a that is producing bits of data elements of Identifiable data and you have a B process that will be consuming this data and The bits of data will go through the pipe sign And so the most is the easiest explanation is the easiest example of this is when you cut a file into less the unit of data is a line and it goes line by line and less Receives the data through the pipe and we'll flash it one line after one line That's a very powerful concept. If you think about it, it links. It can link. That's bad that style Whoops, that's where I tell my students to leave the room, please. I Hope I have to figure out a way to put this in silent mode. Yes, okay So so pipe is similar to something that is called reactive programming Which means that you have a program that waits and waits, you know, it's just sign and suddenly something arrives It wakes up and consumes it and then it waits again. The program doesn't need to know When things will arrive, it does not need to know how many things will arrive It simply needs to know that things will arrive packet after packet That's how it works and you can imagine very very complex networks Connected just that way and that's exactly how next floor works and for those of you familiar with Unix make file. It's exactly the opposite of a Unix make file in the make file world You define a graph of dependency and before doing anything you have to compute the entire graph and when you're done You start the computation and so the difference between next floor and make file is that next floor flows without any Big picture knowledge make file prepares and I insist on this distinction because there are really two tools That are on the same niche this day snake make and next flow And it's quite interesting to me to observe that they belong to exactly they use exactly opposite principles And there are plenty of reasons why in some situations you want to do a make fight lie thing And others when you want to do a next-floor style thing In fact, we wanted to start with make file like everybody But if you have very tiny operations, but zillions of Sam the make file was a killer snake Make people found nice way nice tricks to go around this But you know, it's interesting to insist that these two approach are based on absolutely opposite principles so This is what next floor looks like this is probably our first-ever pipeline and what I like quite like about it Is that you know all you have to do is that you have to take? Thing that we're already working bits and pieces of pipeline and you just wrap Sam a bit like you will do with HTML you're saying what kind of input they expect and what kind of output they will generate and then all of these things get Automatically linked to one another by the description of their output this graph here that I'm showing here gets automatically Generated by next floor once you have decided when you have defined who goes where you know What goes in and what goes out and then automatically all of these things get connected and of course the computation is happening here So this thing here will be waiting for it's a little bit occurred. I may be missing something So here this thing here will be generated multiple alignment And what is it? It's just a process waiting and when sequences come in blue It generates an alignment if you deploy this thing on the large number of processors Implicitly it becomes parallelized. You know, this is this is an implicit implementation of Embarrassingly parallel problems which are the problems we encounter most of the time in biology these days You know your typical situation is that you have a matrix to process where every row is independent from the others And you can throw all of these things That's what next for does that's really the core of next floor But there's more to it and the reason it made it in nature biotech is actually here You have all heard about the reproducibility crisis in in research these days We usually think of wet lab and and and gels difficult to reproduce and all these things But this also happens in computer science in computerized analysis They are difficult to reproduce and as it turned out with next floor with the Continuization we address this problem and that's how we could make it in nature biotech I've just posted a blog entry where I explain a little bit how the story went and that's quite an interesting story It's Evan Floddan who figured out this thing and Evan figured out at the time with Calisto And I'm glad that Liar never never hit on us for this because you don't want to have a fight with Liar but the beauty with Calisto is that you know you run it on on Amazon linux on our Maco x6 You're gonna get roughly the same results, you know on the differentially expressed genes, but slight differences These differences are very tiny. They will not change the Interpretation of your results But if six months later you have to rerun exactly the same pipeline to get exactly the same results, you're in trouble Why is it? We don't know think of a computer like a machine with moving parts where every line of code in the operating system Will be a moving part. It's a huge machine. We've never built machines larger than this. You're talking about hundreds of millions of moving part It will be unexpected that two alternative Operating system give exactly the same results for very very low level reasons and that's just what we catch here And the solution the solution is very simple. You just dockerize everything I don't know if Mac OS 6 or Amazon linux is better and I don't care. I know the differences are neglectable I simply want to have exactly the same result anywhere I don't want to go into an hospital with my genome or my exam and be told This is the driving gene and go into another hospital with exactly the same data the same software analysis and them telling me This is your driving gene and the two genes being different. You want these things to be harmonized and that's what? Containerization does for you next floor also allows you to bundle amazingly complicated things with with with a container this thing It's not us. It's what really got us excited. It's a companion Pipeline at the singer. I think they have something like 40 packages that are all bundled together I mean, it's just crucially complicated and they nailed it with next floor You know, we were very excited about six months one year after we put the code online This thing appeared and this was so nice and when you compare when you dockerize it you can see here This is a gene prediction pipeline you get exactly the same number of genes predicted on any platform So that's what you want for reproducibility. It's very important now Of course giving bad news is only fun if you have bad news for everybody, right? Otherwise and so Maria sheds you in my group just figured out that not only was this true for the companion paper Pipeline of the singer, but it was also true for phylogenetic tree. These are tiny variations We have here. They you know on most of your trees. It will not even change the topology They will Neglectively change the branch length But if you think that in the next data sets like the kinases for instance when you'll have finished the Earth by your genome You will have about one point one point five million Species for nearly a billion kinases to align and to classify the topology will change for sure with these tiny variations and so What can you do exactly what we have been proposing with next floor? integrating integrating your integrating your computation with Dockerized version of your pipelines and then that allows you know everything is quite smoothly integrated in next floor You can simply automatically check out what you need from github and all these kind of things Now you know over my career. I've often had to I've had a few successful projects But you know when you're successful you always have to ask yourself. Why is this successful and more often than not I have to admit that I did not find the true reason for success And that's very important because if you know why you've been successful You can keep pushing in the right direction But if you don't know exactly or if you don't find the true reason for your success You may be pushing in the wrong direction and this happens every once in a while So I had to ask myself what made next floor so successful because it's true 500 site We did not expect it to be that successful frankly and so why is that first of all? This is the urgency It's easy to use for very urgent problems. We had in the lab You know, we didn't we didn't sit with a team of computer scientists and and wrote the documentation and implemented it in C++ and all these Kind of things no we were just in a hurry. I just started the lab in Barcelona I had tons of pipeline that were important for my production And I had to get this thing in production now because and the students were long gone and they were very good students who had better Things to do than writing documentation and therefore I had no idea how to run this pipeline I took all the pipeline then I tell to Paolo here are the pipelines Please do a miracle and he did and this really was made by users for users And that that's really I think if I had to say what I believe to be the main reason for the success of this project It's a small-scale project by users for themselves the alternatives were excruciatingly complicated CWL was a killer and the user community, you know The small people immediately recognized themselves with us, you know, they recognize that you know It's a lot like ours and they've developed and I think you know, they make Roughly the same trajectory for the same reasons There is another point that I want to stress because it's very important as you can see here No, you cannot it's readability and You know, I'm sorry. I'm French And so I I I tend to think that I'm allowed to consider myself a philosopher for a few minutes every once in a while So I'll do a little bit of French philosophy. And so why is readability so important, you know All of us in this room and maybe unfortunately some of us already Some medical pipeline will soon decide on our future And within five to ten years maximum, you will get your exam done or some part of your genome and This will go into a pipeline and the pipeline will spit out a number and If this number is below some threshold, well the social security will deny you Access to the magic treatment that fuels everybody and has no side effect, you know Like for instance, the hepatitis C New drug or this kind of thing, you know, if you're above the magic number, you will get the treatment now The sense of unfairness that will will unfortunately feel when this happens to us will be Devastating, you know, it's like a double punishment. You're sick and you don't have access to the correct treatment to the best treatment What you think will should be the best treatment if you do not believe In the fairness of the pipeline that generates this output, you will not only be devastated You will be angry against the system, you know, there will be a lot of anger Therefore, you must have people you trust you will not be able to read the pipeline But you must have access to people whom you trust Who will be able to read the pipeline and the larger the community of people you trust able to read these pipelines The more likely you as a citizen ought to trust the system and to accept that this is not a system being unfair It's life being unfair to you and life being unfair to you is something we can accept and comprehend. Okay That's why I think that making pipelines readable, you know, we always talk about open source pipeline But we have to go beyond they also have to be readable and I believe that's one of the things next floor contributes to you know And you know, we are in the COVID era. We've all heard about fake news and that's really a pain And I have this, you know, you can quote me on this probably a lot of people I've thought about this But if news were alleles fake news will be the fittest by far It's unbelievable that the fitness of a fake news is amazing and why do we get fake news? It's because we have black boxes things that are not transparent enough and the Conservationists have a very good time a very easy time putting anything they want in these black boxes and The only way to fight against all of this is not the government telling you this is true. This is not true No, it's full transparency. This is our only defense against black against fake news And I believe that readability of decision-making processes is just as important as anything that will allow us You know in France we have this strange algorithm for assigning students to to to universities and For some time the algorithm was not open source and this created a lot of tension So this has to be open source all of these things have to be open source And I'm very happy to to to mention NF core Which is a follow-up of next floor not driven by us It's driven by sign life lab in Sweden and especially feel you well And these guys have generated an amazing collection of reference pipelines very well annotated Very well documented extremely readable and transparent by my own standards And this is not only a collection of pipeline. It is also a Standard for next floor and this is having a huge influence on how these things are being used We are we are big users of NF core with something called Bovrag, which is one of the H 2020 Project for a better. It's it's kind of encode for farm animal and this is meant to help ensuring better sustainability With farming under under the fang umbrella and and NF core is a big thing for us because this is allowing us to Exchange to to to make a lot of things interoperable across all of these consortiums now One of the things that that made me the happiest with next floor is how successful my students have been you know, you run a lab and The people going through your lab are meant to be successful when they leave the lab They are meant to be successful Academically or in business and in this case for former members of my lab went on to incorporate two highly successful companies life beats by Maria Chazoo and Paolo Pablo Prieto and Sekira labs by Paolo de Tomasso and Evan Flodan and you know these guys have been tremendously successful they've raised money and These two guys Sekira lab have just raised five million euro dollars or well five million euros I think and five point five dollars and they secured to Shan Zuckerberg Initiative grants, you know, that's how successful this project have been has been in such a small amount of time now You know like boring used to say Predictions are difficult especially for the future and so I'm not going to tell you that they will become a unicorn or not But I secretly dream that they may become the first Catalan unicorn It's it's certainly not something I called Guarantee But it's something that has suddenly become possible and that it's extremely exciting to think that such a success has been coming out of Such a low-scale, you know hands-on projects like next floor was in its early days And so what is next on our table? And what are we going to do is and actually I have to thank the award Even though it's not a huge amount of money It's it's the best money you can get in academia because it's soft money So all the things that you have to justify and that are complicated to buy become easy to do with this thing So this is really a very important lubricant. I have to just take a second to thank the surgery You know, I will never have secured any grant on next floor. I'm not a 90 guy My lab is not a 90 place And so we try to get a little bit of money, but we never manage the reason next for exist It because it's because we have a core budget We have a good core budget at the surgery and with this core budget I can do what I want and if I fail, you know every five years I get evaluated and the surgery has the possibility to tell me, you know You're using the resources, but you're doing things good enough You have to leave the place for someone who would but as long as you can achieve things you get Supported unconditionally and that's what a core budget is all about and that's why next flow is here And that's why we've been successful in quite a few projects actually thanks to this core budget And so the next thing is something called NF benchmark, which is about the interoperability of benchmark This was actually if I go back in time, this was the original intention behind next flow I think building blocks that are easy to connect with one another and you can measure a lot of things And now with deep learning this is getting very exciting and this is going to change a lot There is also another development, which I'm very happy about it's now genomics and mathematics We want to start, you know, I started this journal about three years ago now Some members of the SEB are on our board like like Philip and Philip Boucher And we are going to start a section dedicated to pipelines So that's a section where this will be application notes But really centered on pipeline and making sure the pipeline or deposited the way they should be They are documented the way they should be so that they can be programmatically used and combined with one another You know, and all this IT plumbing that is so beautiful when it works well And, you know, the kind of things you'd like never to have to know about because they work so well Because that's what IT is really about, you know, you want to forget It's like electricity, do you know how electricity is produced? I have no idea 150 years ago there was an electricity chief officer in every company in, well, 120 years ago There was an electric chief officer in every company And you don't want to have an electricity chief officer in your institute, right? That's the last thing you want And we'll have also something we'll deploy called Ocean Which is a cool thing, you know, about the reproducibility of papers With paper coming along with all the codes interoperated And so let me finish by thanking all the people who made this possible And especially Evan Flodon and Paolo Di Tommaso Who really were the leaders on this project Jose has just joined us and he's working on an NF benchmark And a lot of that stuff is available on nextflow.io, the code and everything if you want to run it I'll mention here that the Swiss bioinformatics is going to run a nextflow workshop Mid of November, this will be run jointly with a CRG I don't have the pointers, the page is not up yet But get in touch with Diana Marek at CIB And she will give you, this will be online, and this will be online, so this can be worldwide There is a limitation in that tendency because we provide support to the users And so we have a limited number of people who can help with this Thank you, thank you for your attention and thank you again to the CIB for awarding me this award


The Jack Benny program, presented by Lucky Strike. Lucky Strike and Lucky Strike alone offers you important evidence gathered in the tobacco country by the world-famous Crossley Pole. This evidence reveals the smoking preference of auctioneers, buyers, and warehousemen. The men who really know tobacco. Here's what the Crossley Pole found. For their own personal smoking enjoyment, independent tobacco experts again name Lucky Strike First Choice. Lucky Strike First Choice over any other brand. These experts know their business. Their overwhelming preference for Lucky Strike, we believe, has a direct relationship to the quality tobacco we purchase for Lucky's. And to the real, deep-down smoking enjoyment you may expect from fine tobacco. And when these veteran tobacco experts name Lucky Strike First Choice for their own personal smoking enjoyment, then you know L-S-M-F-T, L-S-M-F-T. Lucky Strike means fine tobacco. And in a cigarette, it's the tobacco that counts.  Remember, independent tobacco experts again name Lucky Strike First Choice. Lucky Strike First Choice over any other brand. Sarring Jack Benny with Barry Livingston, Phil Harris Rochester, Dennis Day, and yours truly, Don Wilson. Ladies and gentlemen, as there are only eight more programs left in the current Lucky Strike series, at this time I would like to pay tribute to a man who for the past 30 weeks has brought joy and happiness into millions of American homes. Don't forget the 569,000 trailers. A man whose wit, charm, and personality have endeared him to the hearts of his public. Keep going, Don. We have a half hour. A man who is loved, admired, and respected by every member of his cast. How true. A man who every year at this time picks up our options, Jack Benny. Thank you. Hello again. This is Jack Benny talking. And Don, since you brought the matter up, I suppose you received the contract I mailed you for next season. Yes, I did, Jack. And I'm not quite satisfied with some of the clauses.  Well, and just what is your complaint, Mr. Wilson? Well, here's the situation, Jack. Now, you get a lot of laughs at the expense of my being fat. And this year, my weekly salary has been at the rate of $2 a pound. So I think it's only fair that next year I get $3 a pound. Three bucks a pound.  Anyway, the raise I offered you is as high as I can go.  I can't sign the contract now, Jack. I'll have to talk it over with the little woman.  Haven't you got a mind of your own? Yes, but I respect my wife's opinion. I'm very devoted to her. I see. After all, I'm at home with her every day except Sunday. Well, I can fix that, too. Now, look, Don, I've been very fair about this whole thing. And I... Oh, hello, Mary. Hello, Jack. Oh, Don isn't satisfied with his new contract for next season. He isn't? No. Oh, my goodness. And after all you've done for him. Well, that's the way it goes, Mary. There isn't much gratitude in this business. Why, Don Wilson, you ought to be... Never mind, Mary. Thanks just the same. By the way, have you read your new contract? Yeah. What are you trying to do? Bring back slavery? Of course. I'm going to have trouble with you, too. What's wrong with your contract? I don't like Clause 7. Clause 7? Oh, Mary. Mary, I mean, it only happens once or twice a year. I don't care.  Mary, can I help it if I'm sentimental? You're not sentimental. When you pay for a whole turkey, you hate to chop anything off. Oh, stop. Sanimental. You even use the head for badminton. I stopped doing that. I mean, I couldn't stand the way it came over the net staring at me. Mary, you've got a lot of nerve complaining about your contract. After all... Hiya, Jackson. Hiya, Don. Hello, Livy. Phil, it's about time you got here. What made you so late? It ain't my fault, Jackson. I had plenty of time to get here, but just I left the house. Alice fainted. Oh, my goodness. That must have scared you to death.  Oh, brother. That's what she said as she hit the floor. Phil, Phil, do you really have that effect on Alice? Jackson, she won't even let me shave with a mirror. She don't want my love divided.  You know? Now, look, just pick up your baton and let's have a bad one. Hold on a minute. Nah, you don't, Jackson. I ain't making with no downbeat till I talk to you about that new contract you sent me. My lawyers don't like it. Your lawyers? Who are they? Kerchy, Bagby, Fletcher, and Fink. Well, Phil, just what is it you and your lawyers object to in the contract? We don't like the clause that says I got to get to bed on Saturday night before 3 a.m. Well, it's for your own good, Phil. After all you have a program to do on Sunday, I want you to look bright and fresh. I know, but if I lose that red glow in my eyes, I ain't got no personality. Phil, I've been playing badminton with a turkey head for two years, and it looks better than you do. Anyway, I'll talk to your lawyers about your contract later. But right now, let's have a band number. Okay, Jackson, what would you like to hear? Henry Bussey, but I'm stuck with you. Mr. Kitzel, it's certainly nice to see you. I'm sorry to bother you, but I wonder if you could spare our ticket to your next week's broadcast for my uncle who's visiting me from the east. Oh, you have an uncle visiting you, eh? Uh-huh. What part of the, uh... What part of the east is he from? Pomona. Well, anyway, Mr. Kitzel, I'll be very glad to give your uncle a ticket. You have wonderful, boy. You know for this, he'll give you a box of oranges. He owns an orange grove. An orange grove? Oh, of course. Pomona is in the citrus belt. Suspenders during the drought, they lost his pants. Oh, well, that's too bad, huh? Thank you. Anyway, Mr. Benny, I hope my wife will have better luck. Your wife? Yeah, she's opening a restaurant on Oliveira Street called Mama Kitzel's Adobe Hacienda. But Mr. Kitzel, that's Spanish. Can your wife cook Spanish food? Whoo-hoo-hoo! She specializes in tamales with sour cream and shellakis with chopped lever. Chili, corn, beef, and Spanish smorgasbord. Spanish smorgasbord, what's that? A herring that's taking our C.S. down top of a slice of onion. Well, that sounds novel, huh? And the tortillas, you'll be crazy about it. The tortillas? Yeah, that's a crepe suzerbe that shouldn't happen to a dog. Well, Mr. Kitzel, let me know when you open your restaurant. I'll come down and visit you. Buenos dias, señor. Goodbye. What did I say? I don't know. I think Kitzel's Adobe Hacienda. That's a cute name. All right, Phil, let's have the number.  Dennis, I don't know, but I hope he gets here pretty soon. I want to talk to him about his new contract for next year. A new contract for Dennis? Yeah. I thought you had him signed up till next Haley's Comet. Well, it's the same contract, Mary, but I added a new clause. Hey, Liv, you should have seen the clause Jackson tried to get into my contract. Never mind. What was it, Phil? If I ever find a dime before I can spend it, I gotta call Jackson and find out if he lost one. Well, I did that for a gag. Where's your sense of humor? I mean, just because... Hey, maybe that's Dennis. I'll get it. Hello? Hello, Mr. Bennett. This is Rochester. Hello, Rochester. What do you want? I've been listening to the program, boss. And it occurred to me we haven't discussed my contract yet. Well, Rochester, you've been working in my house for 10 years, and I feel there's no necessity for a written contract. Everything is perfectly clear. We have what is known as a verbal agreement. Uh-huh. That means we have a mutual understanding. Why put things on paper? The amount of money involved is too small. That's what I mean. Let's get it up. You'll be taken care of. And believe me, Rochester, there's no necessity for a written contract. But my attorneys advised it. Whereas and to with. Your attorneys, who are they? Remus, Beemas, Sugarfoot and Smythe. Well, tell Remus, Beemas, Sugarfoot and Smythe to get in touch with Kershi, Bagby, Fletcher and Fink. Let them handle it. It's the same farm they got a branch on Central Avenue. Rochester, you've got nothing to worry about. I'm giving you a substantial raise next year. Substantial?  I ain't a little bit. I'm skeptical. Well, you're getting it, so don't let it bother you. I'll see you later. Goodbye. Goodbye. Oh, say, boss. Now what? Are you still going to have company for dinner tomorrow night? Oh, yes. I'm glad you reminded me. You better run down to the store and get a leg of lamb. A leg of lamb? Why don't you get a turkey? Why? After dinner, they may want to play badminton. No, just get a leg of lamb and a small squab. Goodbye. Goodbye. Now, let's see. Where were we? Oh, Don, Don. Yes, Jack. I think right now would be a good time for a commercial. But Jack, the quartet isn't there. How are we going to get laughs? Well, it's simple. Remember a few weeks ago when you did the commercial wearing that old straw hat? People loved it. I know, Jack, but we don't want to do that again. We don't have to, Don. The idea is to give the people something different. What do you mean? Now, look, at every announcer and radio, Regis Commercial standing up at the microphone. Well, how else can you do it? You can lie down. What? Go ahead, Don. Lie down on the floor. I'll bet you the audience will be crazy about it. Oh, but Jack, I think it's silly to do a commercial lying down on the floor. But it's different, Don. Believe me, I know what I'm talking about. Lie down. Oh, OK. But do it gently now. You know, we don't want to... We don't want to disturb... We don't want to disturb the seismograph at Berkeley, you see? Now, um... Now, Don, I'll hold the microphone down to your face. Lucky strike means fire and tobacco, yeah? That's the tobacco that counts. So smoke the smoke tobacco, I think. So loud, so firm, so fully packed, so free and easy on the draw. Don, talk louder. The radio waves aren't getting over your stomach. I've been smoking lucky strikes for now to 25 years. Hey, folks, wasn't that clever? You see, Don, you did get laughs. And I got a Lulu for next week.  Don, we're doing that classy commercial. A note came for you. A note? Who's it from? Dennis Day. From Dennis, what does it say? It says, dear Mr. Benny, my mother won't let me be on the program until she talks to you about my new contract. Your loyal subject, Dennis Day. Well, how do you like that? Oh, wait a minute, Jack. There's more. More? Yeah. P.S. Well, let me know as soon as possible as a good humor man is waiting. I imagine Dennis not showing up. He's supposed to sing. What are we going to do for a song, Don? I mean, my contract with Lucky Strike says I've got to have a song every week. Oh, Jack, I've got an idea. What is it, Don? Well, Frank Sinatra's rehearsing a special broadcast in Studio B, and maybe he'll come over and help you out. Sinatra? Yeah. Say, that would be great. Oh, Mary, will you please go over to Studio B and have Sinatra's there? Ask him if he'll come over, will you? Will I? I'll be glad to. Gee, am I excited? I better see if my stockings are straight. Or maybe Franky'd like it better if I'd roll him down. That'll do it. Let's see. Studio B is at the other end of the hall.  No, that's Jack's tune. He's liable to sue me.  Going to see Frank Sinatra. But I don't feel any different. Hasn't this lightest effect on me at all? Steady, girl. Steady. Well, here goes. All right, fellas, let's rehearse but beautiful once more, huh? It's a good thing of his tearful. It's a problem. It's a harder... Sing you again. Nice seeing you. Gee, you sure look gorgeous today, Mary. I'm a steady girl, steady. Frank, I came to ask you to step over to our studio. Jack would like to see you. Well, that's a coincidence. I was just going over to see him myself. I'm a little peeved at him. He's ruining my singing on the hit parade. Oh, I don't understand. How can Jack hurt your singing? I can't hit those high notes anymore. He puts too much starch in my collars. Well, that's Rochester's fault. Jack especially is rough dry. Well, that isn't my only complaint, Mary. Yesterday, my bundle of laundry came back and two of my handkerchiefs were missing. And they were the handkerchiefs that Crosby gave me for my birthday. Well, how do you know they were the handkerchiefs Bing gave you? They had chloroform on them. Jack doesn't want to see you about the laundry. He'd like to have you sing a song on his program. Today? Yes, right now. Well, okay, come on, let's go over and have a talk with him. Where's Jack broadcasting from, Mary? Right here in Studio C. Let's go in. Okay, wait a second, Mary. I'll open the door for you. Thanks, Mary.  Well, he thinks he's that funny. He's got... Oh, hello, Frankie. Hi, Jack, do you want to see me? Yes, yes, come right in. By the way, you know my gang, don't you? Sure. Where's Don Wilson? Any place you'll look. Hey, Don, here's Frank Sinatra. Well, hello, Frankie. Holy smoke, I'm surrounded. Yeah, there's quite a difference in your size. Oh, I got a goose pimple bigger than him. Now, lie down, please. Now, Frank... Frank, I'll get right to the point. You see, Dennis couldn't be here today, so I'd like to have you sing a song on my program. Well, I don't know. It's strictly business, Frank. I mean, I intend to pay you.  Certainly. Frank, what are you doing? I'm calling RKO. This is another miracle of the bells. Well, you can hang up and we'll talk business. Now, how much would you want to sing just one song? $5,000. Doesn't he fall down? I know he fainted. $5,000. You sing both the verse and the chorus of a song, don't you? Uh-huh. Now, look, Frank, most people don't know the verse anyway. Now, what would you charge? What would you charge for just the chorus? $3,000. Well, you know, we wouldn't need a whole chorus. I would want to be cut off the air again. Now, how much, Frankie, how much would you charge me for? Say, 16 bars. $1,500. Yeah, that's almost $100 a bar.  Well, for $10, I can blow my nose and see sharp. That might help you out a bit. No, Frankie, I know you're short. Two Hank achieves. You know me? Now, look, Jack, what's the use of dickering? My price is $5,000. But, Frank, let's compromise. Look, I'll give you $500. $5,000. $4,999. $502. $4,998. $503. Mary, what are you doing? I'm calling Paramount. This is going to be another lost weekend. Now, Frank, since we're so close to an agreement on price, why don't you just do your song and we'll settle it after the program?  You know what? It makes you look cheap. Sing your song, huh? Well, okay, Jack. But who's going to accompany me? Phil Harris' orchestra. Oh, no. No, no. No, not that. Well, wait a minute, Frankie. A few weeks ago on my show, they accompanied Bing Crosby.  Tell you what, I'll accompany you on the violin and Frank Remley on the guitar. Frank Remley? Yeah. That's Phil Harris' nature, boy. Excuse me, Frank. Hello? Hello, Mr. Benny, this is Rochester again. Oh, what is it this time, Rochester? Well, I'm listening to your program and I just heard Frank Sinatra. That's right, he's here. What about her? Boss, you've got to get an Oscar to give back to Mr. Coleman. Yes? Well, Mr. Sinatra won an Oscar a couple of years ago with a picture called The House I Live In. Say, that's right. He did. Gee, I wonder if he'd lend it to me. He might have, he hasn't thrown it away. Now, why in the world would he throw an Oscar away? Could be jealousy. It weighs more than he does. Gee, Rochester, I'm glad you told me about him. By the way, I think you're putting a little too much starch in Mr. Sinatra's collars. He looks like a dehydrated Herbert Hoover. Be careful, will you? I will. Goodbye. Goodbye. Now, look, Frank. I'm ready now, Jack. You get your violin. Look, Frank, look, Frank, look. Let's hold the song for a minute. I want to talk to you about something very important. What is it, Jack? No, not here. Let's go out in the hall. Okay.  As you know, I lost Ronald Coleman's Oscar and I've got to get one to replace it. Yeah? Now, you won an Oscar, didn't you? Yeah, we won it for the house I live in, Jack. Well, look, Franky, you can do me a great favor. I'll only need it for a few weeks. You see, I got to get an Oscar back to Ronald Coleman before he comes over. Hey, would you guys mind moving over? We're trying to vacuum this hall. In a minute, in a minute. They're always cleaning up around here. Now, Franky. Yes, Jack? I've never been in such a spot in all my life. I'm asking you to give me the Oscar. I just want you to lend it to me until we get... Now, look, you guys! I'm trying to vacuum this corridor! I'm asking you once more to move!  Now, Franky, look. How about it? Let me have your Oscar. Well, Jack, as long as you're in that kind of a spot and it's only for a few weeks, maybe I can... Frank. Franky. He got too close to the vacuum. I'll have to go outside and wait till they empty the bag. Security bonds are vitally important in the nation's battle against price inflation and for the future welfare of all of us. It is important that we continue to build financial security for ourselves and for our children. Protect your future by extra security bonds now. The first here is Basil Riesdale. Independent tobacco experts again name Lucky Strike First Choice. Lucky Strike First Choice over any other brand. The famous Crosley poll has just completed an impartial survey in 11 southern tobacco states. This poll, taken among tobacco experts, reveals the smoking preference of men who really know tobacco. Yes? For their own personal smoking enjoyment, independent tobacco experts again name Lucky Strike First Choice. Lucky Strike First Choice over any other brand. These are the experts. Auctioneers, buyers, and warehousemen. These are the experts. Auctioneers, buyers, and warehousemen. And we believe their overwhelming preference for Lucky Strike has a direct relationship to the quality tobacco we purchase for Lucky's. You've heard the poll results. Now listen to what Mr. Carl Hartfield, 29 years and independent tobacco buyer recently said. At auction after auction, I've seen the makers of Lucky Strike by fine tobacco. Good-wrapped leaf that's got real smoking quality. I've smoked Lucky's 28 years. So for your own real, deep-down smoking enjoyment, remember LSMFT, LSMFT. Lucky Strike means fine tobacco. So round, so firm, so fully packed, so free and easy on the draw. Gosh, where could they have emptied that vacuum cleaner? I've looked in every rubbish can in the alley here. Frankie, Frankie! Frankie, where are you? Well, it's not in this one. Go away, kitty. I'm working this side of the alley. Frankie! Well, there's nothing left for me to do next week. I'll just have to go over and apologize to Ronald Coleman. Me, Ronald Coleman? Yes, yes. Good night, folks. This is NBC, the national broadcasting company.