On this episode of the Six Five Webcast Infrastructure Matters, hosts Camberley Bates and Dion Hinchcliffe discuss takeaways from AWS re:Invent, developments in Quantum computing, open source LLMs and more!
Their discussion covers:
- The American Society for AI and its discussions around open source LLMs
- AWS re:Invent announcements such as S3 Enhancements, Amazon Q, Bedrock and more
- Developments in quantum computing, including new quantum chips from Google and IBM
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Transcript:
Dion Hinchcliffe: Welcome, this is Dion Hinchcliffe, VP of CIO practice at The Futurum Group, and we’re here for another episode of Infrastructure Matters. This is episode 64, and I have my co-host, Camberley Bates with us. Welcome, Camberley.
Camberley Bates: Good day and welcome to the holiday season.
Dion Hinchcliffe: It is the holiday season and also means a little bit less travel for us analysts, which is kind of nice. But boy, have we been busy the last week and a half, two weeks, months, six months.
Camberley Bates: Months, months, months, months, months. In fact, Keith is not here because, well, he took some time off. He needed to take some time off, so there we go.
Dion Hinchcliffe: Well, I’ll miss his cowboy hat. I’m sure others will too as well. So let’s dive right in. There was a tremendous amount of news out of Las Vegas last week with the biggest show that caps off the end of the year. So that was Amazon’s, AWS’s re:Invent, a week-long extravaganza. I spent more time at that event than any other. I was there all week, which is unusual for me. Camberley, you and I even sat together at some of the announcements at the Analyst Summit, and they just kept coming fast and thick, too much for us to even cover here. But let’s dive into what we thought were the most significant or interesting announcements. Camberley, you want to go first?
Camberley Bates: Sure. I’ll just cover some top-level things that I thought were pretty cool. You know me, I’m data storage, so they announced for S3 some very, very significant items. They are Promoting S3 as the data lake. Bring your data to their data lake, and we’re going to enable this for your entire AI strategy. Now, that is to say you still may need Lustre to power through your GPUs, but the S3 is the source for data. The two big things they announced, is being able to do tables within there for your Iceberg as well, as the metadata processing. And they’re doing quite a bit within the S3 to improve the performance kind of level on there. I’m going to take a look at my notes here. In terms of the data layout as being optimized, they’ve done some things to simplify the table security. They are optimizing garbage collections and row deletion that you need to do for Icebergs.
So I’m kind of getting into the technical weeds here, but some really, really nice stuff, items that they have done. There I am with that technical term, stuff. The second piece of that was the S3 Metadata that’s going to be part of the Iceberg table. So there’s an entire sessions on that, so if you can go up and take a look at it, either at re:Invent, or we’re probably going to be publishing on a little bit more in terms of depth with our research on there.
Dion Hinchcliffe: Well, I really liked the metadata announcement, because S3 was the number two service they ever released and they shared some of the usage data, by how much people actually store in there, and people are cramming the kitchen sink into S3. And then with metadata, it actually tells you what you have. You can actually go in there and throw everything to a data lake and then go, well, what’s in there? And it will actually tell you. I thought that that’s really going to help make S3 much more self-service, much more useful to people who are not necessarily developers who are data architects who just want to work with the data they have in S3 and understand what’s in there. I thought that was a really good announcement.
Camberley Bates: Absolutely. And I think the number they put up there was 400 trillion objects today stored in S3. So it’s kind of like, no, there’s a bit up there. The other two things that was really cool, and I’m going to go into… Again, I’m looking at my notes here, was some two really cool customer stories. And I’ll start with the first one, which is Merck. Merck has been there, and it’s a non-AI one, Merck has been there for 13 years. They started what they call the Blue Sky Project, infrastructure as code project they were doing. What they were looking at is they just could not keep up with development. And so pretty much what they gave is AWS responsible for the maintenance, the patches, all those kinds of areas, while they could focus on modernizer apps. And which they did is, they retired, they quoted a 1000 apps in the modernization process that they’ve done. So now they feel like what they can do now is really focus on governance and guardrails, especially as they go into the AI space. The other one that was super cool was Novo Nordisk, which is a pharmaceutical out of Belgium, if I get that right.
Dion Hinchcliffe: Yeah, they’re famous.
Camberley Bates: Very famous. They are known… They have 50% of the insulin business. We won’t even talk about that. That’s another issue. But anyway, what they talked about is how they’re using AI for regulatory filing. So there are about 200 or a 1000 documents that have to be prepared for filing, and that would be to the FDA or France’s FDA or England’s FDA, etc. And it can take them 12 to 15 weeks to prepare and to submit. What they have done is they have applied AI, and this is taking this down to… Ready for it?
Dion Hinchcliffe: Mmm.
Camberley Bates: 10 minutes.
Dion Hinchcliffe: Wow.
Camberley Bates: 10 minutes. They have reduced their staff that’s doing the writing from five to three medical writers. They have redeployed those into other things. They have reduced a total of 27 full-time equivalents. What they used is Bedrock, MongoDB, Anthropic and some other foundation models and enhanced the tagging and the metadata on the documents that they have. They’ve changed how they’ve organized the company in terms of submitting this. So there’s more collaboration between the scientists, I guess they’re doing the clinical trials and the people that are doing the solutions. So it’s a really big change. What they’ve looked at is they’ve moved from being content writers to tech experts on the content. Great case study about what AI can do. So when people ask me, is this stuff real? That to me is a real fabulous-
Dion Hinchcliffe: We’re starting to really see the first real concrete stories about AI transformation that’s been successful. And yeah, I agree with you. That’s one of the top ones. And it was interesting how Amazon’s really come from being on the back foot with AI, they were trying to play catch-up and they were late with Bedrock, arguably compared to their hyperscaler competitors, but they’ve been working very hard and that was on evidence at re:Invent last week. And they’ve also announced their own set of models, the new Nova models of various different sizes. And they’re really focusing on trying to create cost-effective models that provide highly accurate, grounded answers. And this is what a lot of folks are working on. And from a CIO perspective, which is really my primary focus, the announcements that really caught my eye was Amazon Q index.
Now Amazon Q is not a household name, but it’s their enterprise AI. It’s kind their version of ChatGPT, except that it’s taught with your enterprise knowledge. And so Q index is a way of creating access through a natural language interface to all of your enterprise data. And they came out of the gate with 40 different connectors to all your top enterprise systems, whether that’s ERP or CRM or whatever. You now have this single place, you can use Amazon Q to go and safely access all your corporate knowledge across all these major systems. And more connectors are coming, it’ll take years for them to fully realize that vision. But Q index is how if you are an Amazon customer, and AWS is still the top dog in cloud, how you can bring all your data together into one place and start using it, start delivering that to customers. I thought that was one of the most important announcements from an enterprise AI perspective, how you’re really going to deliver AI infrastructure across all your silos.
And so Q index was the big news around that. And they have the same thing with SageMaker, which is their very successful analytics product. They now have SageMaker index, the same thing, allowing you to access all your analytics across SageMaker in a single place. And so this is… Now they’re starting to show their hand on a more comprehensive enterprise class vision, not just point AI solutions, but actually starting to think about enterprise AI across all of your IT systems. And this is kind of the early maturity we need to have, that CIOs need to have in order to really start delivering AI value to their internal stakeholders and to external customers. So those are some of the ones that really caught my eye.
Camberley Bates: Yeah. And did you take a look at the Q Developer one, which is their tool for the developer side of the house?
Dion Hinchcliffe: Yes, I know. And we can spend a whole show on that.
Camberley Bates: Yeah, we could. Absolutely. Anyway, guys, it was just a phenomenal show. So much in there. It was overwhelming, my poor brain was hurting.
Dion Hinchcliffe: Yeah. No, exactly. I think that you can… Safe to say, well, the things like Bedrock guardrails, where they’re really going to say you can run all your different models that you have, everything that’s been certified to work with Bedrock, we now can put guardrails on it to make sure that it’s all safe and follows the same AI policy. And when it goes out out of permissions or out of policy, you’ll catch it. And you can do that consistently across all your models. This is exciting stuff from an AI perspective, for those who have to make it work, actually deliver it. So I was really thrilled to see all that. But that was re:Invent. I have a super thread on X that you can see that has every single announcement that I was able to track. I’m sure I missed a few. And we also have, Futurum has full coverage coming out starting this week and next week on re:Invent. So please catch it at thefuturumgroup.com. So Camberley, what’s up next? You were talking about the American Society for AI. Tell us a little bit about that.
Camberley Bates: Yeah. American Society for AI, they’re a fairly new organization. They’ve been around for a little bit over a year and a half, two years. It is by invitation kind of a think tank group. There’s 125 members, they come from all over. We’re talking tech people, we’re talking State, Local, Federal government. I think we have three House of Representatives on there, Military. In this session here, we had one of the lieutenant generals that was there that had been involved with AI. We have professors from MIT, Oxford, George Washington, Stanford, you name it, they’re all there. We’ve got legal.
Dion Hinchcliffe: Cross section of who’s who, which is what you need if you’re going to have any kind of real society.
Camberley Bates: And artists, and sociologists.
Dion Hinchcliffe: Nice.
Camberley Bates: Really, really some amazing folks that bring on… Just super smart people. I’m like the dumbest person in the room. I just was like… Also, VCs were there.
Dion Hinchcliffe: I’m sure that’s not true.
Camberley Bates: But from a think tank group, it was great. And one of the things that we do is debate topics. So we do five-minute, five-minute debate questions, and that kind of stuff. And we had a couple of things. And what I want to touch on is when you bring this very diverse group together, what are the things that they felt were the big issues and where are those going? One of them, open source of LLMs, should we or should we not? And it went on both sides of it, arguing it, where it’s going. Another, who owns the data that’s in those LLMs? Who owns the data that comes out of the LLMs? And this is especially true from when we started talking about the artists and copyrights, those people.
Dion Hinchcliffe: Well, my content goes into an LLM. I want fair compensation. I think that’s only reasonable.
Camberley Bates: Yep. And then there’s other people that talk about it differently. Another thing is the accountability for the actions of the agent or the agent assistant. Where’s the liability? That was a lively discussion with the lawyers in the room and us in the room and where this goes and that kind of stuff. And basically right now we’re using negligence principles. Have you been negligent with what you’re doing? But what happens when we let these things go and start making the decisions? And we came back and started talking about Wamo. We started talking about auto driving, where we have no tolerance for an accident, where you and I have probably had maybe an accident. I know I have, and how that plays out. Another one was something called hybrid AI. And I know you’re going to talk about quantum here in a bit. But talking about how what we do have now, transformers, symbolic type of technologies, mixing that with your rule-based technology and mixing it with quantum. And how we’re going to probably see these things come together to address some of the stickier problems. And one of the sticky problems we talked about was logistics. And a gentleman got up and talked about how they’re using hybrid and they would never have been able to do what they’re doing, which is a company called SavantX, which is doing logistics management.
Dion Hinchcliffe: You can tackle traveling salesman problems and other things that are too difficult for traditional or classical computing to handle if you can augment it with quantum.
Camberley Bates: Yep. So we talked about that. And then the talent issue was a big discussion as well. And then talking about how… The professors that were talking about how they’re trying to train up these people to come up, the Gen Zs or whatever, and the difference between you and I, who have been around this technology for a long time, and what it means for Gen Z to come up in here in terms of this world and how do we apply. So those are all debated topics, and there’s no time to hear to kind of go into those things. But what society will do is start to push things out in terms of recommended policies, research kind of things that we’ll see over time. It’s self-funded, there’s nobody dropping money in here, so we’re not being influenced by the government or some sort of lobby.
Dion Hinchcliffe: And that’s why those associations or societies are so important, is that they can be impartial arbiters, and bring a lot of expertise that doesn’t have necessarily a giant tech company behind it, for example.
Camberley Bates: Right. And the rules are in terms of anonymity, whatever those rules are, where you can’t bring who said what, but you can bring what was said.
Dion Hinchcliffe: The old Chatham Rules.
Camberley Bates: Chatham Rules. Thank you very much. Yes, it was definitely Chatham Rules there. Which made for very lively discussion, especially when we had somebody from the State of California, the heads-up with AI stuff, talking about what they’re doing and how they’re experimenting with it, the areas that they’re going. Last time we had folks from New York City when we were in New York talking about it.
Dion Hinchcliffe: Well, these are all the conversations of the day. And in fact, we’re doing a big study on CIOs and AI right now at Futurum. And one of the things that’s… As we talked to a bunch of healthcare CEOs, what’s really come out is there’s a big tension between… The clinicians will be using their AI models to determine what the care should be, and the insurers will have their own model about whether somebody should be treated or not. And the biggest concern that’s emerging is how do you decide whose model is right? Which is the right one? And so that has massive societal implications, because everyone receives healthcare and pretty soon all of that is going through models. We heard how United Health has used AI models to deny care, and that’s been quite controversial. And that’s going to be a hot topic, and hopefully your society there can help us navigate that challenge there for us.
Camberley Bates: Well, and that gets back to the LLM open-source piece of it. Should that be open-source enough so we can peer in to see how they have made those decisions and made those things. When we talked about, for instance, thinking of genomics, shouldn’t genomics be an open-source LLM, except for then we pop into saying, well, what if the bad guys get a hold of that?
Dion Hinchcliffe: Well, of course, and then you’d have the whole commercialization of scientific research. This is a whole other topic about a lot of that. And that information is no longer freely available anyway, so what do you do? So moving along, Camberley, you have other news for us, Cohesity. Will you walk us through the news there?
Camberley Bates: Right. So we had two big announcements from data protection companies. I know, it’s kind of boring data protection, the last thing on the thing, but-
Dion Hinchcliffe: That was the number one thing out of my CIO survey, was all cyber topics is the hottest thing.
Camberley Bates: Right. And that’s why we’re seeing a transition of people upgrading or changing out their data protection systems, et cetera. So what just happened is Cohesity, which has been a startup, pretty small, and Veritas, long-time data protection guy, been around, not, et cetera. They had announced about a year ago that they were going to join. What happened is that Veritas split in two. So things like the enterprise side, technology, MBU, and a few of the others is now part of Cohesity. Cohesity is the big company. So Veritas was owned by a PE firm, so this is the wave that moved over there. And then another firm was formed called Arctera, which owns the backup exec technology as well as a few other technologies.
So we now have this Veritas. Now the name is going to be Cohesity. Veritas is bigger than Cohesity. So you’re looking at, okay, so how is this going to work? What’s going to be happening here is Cohesity has done quite a bit of work with AI. So what you’re going to look at is saying, okay, so can I take all that Veritas data that’s stored in backup kind of stuff, and can I start using that in terms of an option for starting to use for training? And that’s kind of where this is going over the long haul. So not only just protection, but also in that file system kind of environment. So that was pretty cool. The other one that was really big, and you kind of go Holy crud, is a company called Veeam, and they are about a billion dollars in size firm. They just issued a new equity offering, which is a secondary offering, oversubscribed.
Dion Hinchcliffe: Oh, interesting.
Camberley Bates: The valuation is now 15 billion, expect them to go public sometime in the next 18 months. But they have made some huge bets on where we’re going with things like protecting 365, Salesforce and some of the other as a service kind of software offerings. And that’s where we’re kind of expect them to explode in the business that they do. So kind of like, wow.
Dion Hinchcliffe: Yeah, right. Well, I think all of that, what’s old is new again, in terms of infrastructure. And we saw this with quantum computing. GPUs made compute exciting again, and now quantum computing appears to be perhaps on final approach to actually getting into the data center. Now we’ve had these big bespoke quantum compute devices in the data center, in the hyperscaler clouds for a while, but they have very limited access. They haven’t really been able to scale it up and there hasn’t really been a lot of demand, because the chips can’t do much yet. And in fact, they’ve just now arrived in chip format, so the last few years. But Google had a major announcement, their new Willow quantum chip has 104 qubits, I think it is. It’s in the low 100s. And they made a splash. Because they announced that they believe that its performance is so high, it must prove that the multiverse exists and that quantum computing is the way to access it. I don’t know if you saw that, but it created quite a bit of hoopla with both scientists on both sides saying yes and no.
We see with IBM’s Heron chip, which has only a handful, only a couple dozen more qubits. We’re getting to the point where we now have quantum chips that can begin to do things beyond just simple random number generation and things like that, because that’s all you can do. A 100 and some odd qubits is not very much. And China this week also announced their own quantum chip with 504 qubits, which is four times more than both Google and IBM have. So quantum is really developing… These new chip packaging of quantum is really important, because that’s going to allow them to enter the data center. And we’ll see, we were talking about hybrid AI and be able to supercharge AI by adding quantum to the compute mix at the infrastructure level in our data centers and in the cloud. It’s getting close to being real. The error rates are dropping to the point where you actually can use these for business applications. Not quite yet, but we see, you can plot all the trajectory forward. I would agree with Arvind Krishna, the CEO of IBM, that we’re likely to see these really being a usable offering in the next couple of years. And these are all great proof points for that. I don’t know, what do you think Camberley?
Camberley Bates: Well, as I said, at the American Society for AI, there was a VC there. That’s all his company focuses on is quantum. And then there was also, one of the members is the CEO of a company called SavantX, I’m giving him lots of airtime here, which is quantum. And they have implemented systems that are doing logistics management for the LA, I believe it’s LA Harbor, container trucking. They’re doing something that he won’t talk about for, I think it’s the Air Force. And they’re about to do a deployment for one of the trains. I think it’s one of the train systems. And that is about the container loading onto the trains and scheduling them. So these are real apps. These are real, that are creating some significant value proposition for these organizations. So it’s real, it’s here.
Dion Hinchcliffe: No, that’s here. Well, we’ll have to title the show, The Quantum is Here.
Camberley Bates: Quantum is here. What scares me a bit is hearing you talk about 500 qubits with China. Because if I recall correctly, the government has moved up the timeframe in terms of when people need to be quantum secure, because of this. And so at one time I thought it was 2030, and now they’re moving, I think they moved it to 20-
Dion Hinchcliffe: They’d have to, because you only need about 1000 qubits, maybe 1200 qubits to break basic RSA security.
Camberley Bates: Oh, geez. Okay. So we’re right there. We’re right there.
Dion Hinchcliffe: Yeah. We’re one or two chip generations away from… That’s the basic, RSA 256 can’t be broken for a while yet, but still.
Camberley Bates: So the CIOs that you work with, are they aware of this? Especially since cyber-
Dion Hinchcliffe: It’s on their risk. They have a list of risks, they know that all of a sudden everything, all their secrets will become readable here in about five years. That’s how they’re looking at it. So yeah, it’s on the list of risks that they’re managing. Are they investing a lot on it? No, they’re expecting their vendors to be able to dig them out and re-encrypt everything or whatever they have to do.
Camberley Bates: To be quantum secure. Wow.
Dion Hinchcliffe: Yeah. Actually, the whole thing with China is really heating up because we’re now really blocking China’s access to AI chips. And we just had a new regulation came out this week to block third countries from being intermediaries for that. So we’re really trying to tamp it down. And as a result, China, I think at the beginning of the week, blocked our access to their sources of antimony, gallium and other things that we need to make those chips, the AI chips. So a real battle is at a slow level right now, but it’s brewing, in terms of China’s now said, well, we’re going to have to build our own AI chips. We’re not going to be able to source them from the West. So we’re going to see what happens. Might be the West gets to GPUs and quantum is done with China, but we’ll see what happens.
Camberley Bates: Yeah. And then all the stuff with Intel kind of blends right into that same kind of discussion there that’s happening. So anyway. Okay, cool.
Dion Hinchcliffe: Yeah. Well, to round out the show this week, Camberley, unless you have anything else after this, is Google made a major AI announcement, Gemini 2.0 was out. This is a major model upgrade. It’s fully multimodal. I’m watching it climb the AI leaderboards. But what’s really significant is they have associated with it something called Project Mariner, which shows off the agent-based capabilities. Agent-based AI is the hottest topic right now. AI doesn’t just produce content for you but does things for you. And Google, Gemini 2.0 really focuses on that. And Project Mariner is an interesting plugin. It actually connects to your Chrome browser and then on your behalf, you can make a request to Gemini 2.0 and it will use your browser with all your access that your browser has and passwords, everything to go out on the internet and do things for you.
And they claim they can handle complex multistep tasks across multiple applications to do things on your behalf directly through the browser. And why I have actually a lot of reservations about directly handing AI control over our IT systems… It’s still an impressive tech demonstration, I watched what it can do. And so agent-based AI is here, folks. The question is, can we control it? Can we protect ourselves from it? So it’s going to be interesting.
Camberley Bates: So when you say it does something for you, what kind of things will it do?
Dion Hinchcliffe: You can ask it to book the cheapest vacation trip to Europe. So go and search all the different sites. Get me hotel and flights, send me an email just to confirm everything and I’ll give you yes or no, go off and do it, and then you go get coffee.
Camberley Bates: So you still have the expert. And that’s what I call that, the person that looks at what happens and says, okay, go do that. It’s not automatically executing for you.
Dion Hinchcliffe: It will absolutely. Yes, yes, you can have it do that for you. You can say, go find the cheapest place to buy this item and buy it for me, and it’ll do it without asking, if that’s what you want.
Camberley Bates: Well, and that gets back to the negligence principles and the legal issues and everything else that we talked about, there we go. Okay. Wow. Okay. I feel sorry for people that are not in the tech industry, to a bit, that are spending time looking at this thing. One of the beauties of this podcast is I’ve learned so much from you guys. I know we don’t have Keith here, but I would open my brain and pour a little bit more in.
Dion Hinchcliffe: Exactly.
Camberley Bates: But there’s no way you can track all this. It’s just crazy.
Dion Hinchcliffe: No. Even if you do it full-time, and we do. That’s what’s so funny, right.
Camberley Bates: Yeah.
Dion Hinchcliffe: Well anyway, it was an amazing week in infrastructure and we hope that you’ll join us for our next episode. Camberley, when is our next episode?
Camberley Bates: I think we’re recording on Friday next week.
Dion Hinchcliffe: Okay. Yep. Great. I’ll be there too.
Camberley Bates: Okay.
Dion Hinchcliffe: All right, well thanks for stopping by everyone. Have a great week.
Camberley Bates: Okay. Thank you. Bye.
Author Information
Dion Hinchcliffe is a distinguished thought leader, IT expert, and enterprise architect, celebrated for his strategic advisory with Fortune 500 and Global 2000 companies. With over 25 years of experience, Dion works with the leadership teams of top enterprises, as well as leading tech companies, in bridging the gap between business and technology, focusing on enterprise AI, IT management, cloud computing, and digital business. He is a sought-after keynote speaker, industry analyst, and author, known for his insightful and in-depth contributions to digital strategy, IT topics, and digital transformation. Dion’s influence is particularly notable in the CIO community, where he engages actively with CIO roundtables and has been ranked numerous times as one of the top global influencers of Chief Information Officers. He also serves as an executive fellow at the SDA Bocconi Center for Digital Strategies.
Camberley brings over 25 years of executive experience leading sales and marketing teams at Fortune 500 firms. Before joining The Futurum Group, she led the Evaluator Group, an information technology analyst firm as Managing Director.
Her career has spanned all elements of sales and marketing including a 360-degree view of addressing challenges and delivering solutions was achieved from crossing the boundary of sales and channel engagement with large enterprise vendors and her own 100-person IT services firm.
Camberley has provided Global 250 startups with go-to-market strategies, creating a new market category “MAID” as Vice President of Marketing at COPAN and led a worldwide marketing team including channels as a VP at VERITAS. At GE Access, a $2B distribution company, she served as VP of a new division and succeeded in growing the company from $14 to $500 million and built a successful 100-person IT services firm. Camberley began her career at IBM in sales and management.
She holds a Bachelor of Science in International Business from California State University – Long Beach and executive certificates from Wellesley and Wharton School of Business.
