Cloud Wars Live with Bob Evans

In today's Cloud Wars Minute, I explain how AWS is using AI-driven automation to reduce technical debt and free up budgets for innovation.

Highlights

00:03 — As the AI Revolution has kicked into full swing this year, we've heard a lot of stories — interesting ones — about companies blowing through their AI budgets because everybody loves this stuff; everybody wants to use it. That brings up this notion of technical debt.

00:46 — AWS has introduced an autonomous tool that's primary job is to slay the technical debt monster that is grinding up so much of so many companies' IT budgets and limiting their abilities to do the things going forward that they need to do. It said it consumes 30% of IT budgets, and this is a staggering number.

01:51 — This party that's been going on here now — the big AI kegger during the AI Revolution — is going to come to an end. And what always follows those parties is a hangover. That hangover is going to be centered on technical debt, budgets, and money decisions that have to be made.

02:44 — AWS gave a list of some of the benefits of it [the tool] but, AWS is missing a huge audience, business people who say, “God, we're spending incredible amounts of money on IT. Why are we not getting as much sort of innovation oomph out of this?” It's because so much has to be spent to sustain this already in place technology that's there, the technical debt that builds on that.

04:33 — I think AWS has to find somebody to package this as an agent, that if they call this agentic AI, it goes from being some sleepy thing with a ho-hum name to something that could be very cool. It's the technical debt killer agent, something like that. This is what it does: it autonomously operates, takes care of stuff, makes decisions, evaluates data, does all that.

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Highlights

00:08 — Now, in a slight tangent away from what we're used to from Microsoft, the company is developing two new AI-powered gadgets for workers that tap into AI for daily tasks. Both are currently in the concept stage.

00:22 — The first is a small cube designed to sit on a desk that can be activated by voice or touch. Second is a wearable access badge that would give wearers access to AI-driven workflows. Now, the two devices are already being used by a couple of hundred Microsoft employees, but the company has not said when they'll become commercially available.

00:44 — Both were showcased at the recent Build conference. They're part of Microsoft's Project Solara, and here's what Stephen Pattison, CVP and Technical Fellow, Applied Sciences Group at Microsoft, had to say about the overall project.

01:07 — "The mission of Project Solara, a new software platform coupled with tailored hardware solutions, is to pioneer agent-first experiences that are shaped around you, your agents, your tasks, your environment, under your control."

01:27 — "These new devices are not meant to run traditional apps. They're designed for agents, and that shift gives us more flexibility in the user interface because the experience can adapt to the device, screen size, content, and even the mode of interaction, whether visual, voice, touch, or multimodal."

02:07 — I think it's particularly interesting that Microso

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In today's Cloud Wars Minute, I look at why two of the fastest-growing Cloud Wars companies are joining forces around data, AI, and industry solutions.

Highlights

00:03 — When heavy weather rolls in, it's good to have friends around. It's good to have partnerships, and I don't think the AI Revolution is so much heavy weather, but that depends on how well prepared businesses are to take advantage of it, how aggressively, how thoughtfully they're moving into this AI Revolution.

00:41 — It's interesting, Google Cloud and Palantir, on the Cloud Wars Top 10, these are the two fastest-growing companies. Google Cloud grew 63%; Palantir grew 70%. Palantir's commercial business grew 133% in the first quarter, so they've got enormous momentum.

01:30 — The Palantir Foundry platform for enterprise data management is now available on Google Cloud infrastructure and on the Google Cloud Marketplace. Google Cloud and Palantir have built connectors between Foundry and Google Cloud's BigQuery, allowing data from those platforms and others to be pulled together for businesses to analyze.

02:09 — Not just the technical integrations, which have to happen, but also this desire for these two companies to say, "We're going to jointly develop industry-specific solutions around data and AI for vertical markets." The first two they picked are retail and financial services.

03:15 — This is a dream partnership, I think. And it's also probably an example of how, with the enormity of the prospects of what can happen here in the AI Revolution, we're going to see more of the Cloud Wars Top 10 companies form these sorts of wide-ranging partnerships.

04:19 — There's a big emphasis from both of these companies on keeping things open and fully accessible for whichever specific routes customers want to take. We're seeing these inextricably bound connections here through this partnership of data, which is the fuel for AI, helping companies transform into AI-powered enterprises.

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Highlights

00:27 — It's not just business as usual for these companies, their customers, and others who are tied into these extraordinary enterprises. We're also seeing booms in innovation, not just in technology but in go-to-market models, business models, and more.

01:32 — The big part of this is that it's not just big numbers, but big numbers driving widespread, deep, and profound innovation. Here's how the $2.1 trillion breaks out across the four hyperscalers:



Backlog
RPO Total Backlog
RPO Growth Rate




Oracle
$638 Billion
363%


Microsoft
$627 Billion
99%


Google Cloud
$462 Billion
93%


AWS
$364 Billion
49%


Total
$2.091 Trillion
 



02:32 — With this high level of innovation, we're seeing a convergence of industries including technology, energy, and construction. Because of extreme demands, the tech industry has to start getting into the energy business. Construction is entering the picture as well, as these facilities are some of the largest built in such a short period of time, meeting demanding specifications and aligning with supply and demand.

03:25 — This convergence is leading to the hyperscalers developing new business models. These companies are coming up with unique models to solve this unprecedented demand and business challenge. Customers are coming up with different models based on what's happening, too.

04:15 — I have been a huge fan of the potential of fusion energy to meet this need. The convergence of tech and energy is only going to accelerate what's happening to break even with fusion energy.

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In today's Cloud Wars Minute, I examine why the Google Cloud-EQT deal signals a major shift in how AI is being distributed at scale.

Highlights

00:03 — The rapid pace at which deals are being struck and portfolios are expanding among the leaders in the race for AI dominance isn't new. Significant partnerships are being forged, and contracts are being signed all the time. However, every so often, a deal comes along that stands out not only for its scope, but also for what it indicates about the direction of travel for the industry as a whole.

00:33 — One such deal recently announced is between Google Cloud and the Swedish private equity firm EQT. Ultimately, this partnership sees EQT commit to accelerating AI adoption through Google Cloud for over 300 companies within its portfolio, and this is, of course, a big win for Google Cloud, as it gains access to hundreds of potential enterprise AI customers.

01:04 — Beyond this, those companies will not only benefit from Google Cloud's wide-ranging AI offerings, including the Gemini Enterprise agent platform, as well as its cybersecurity portfolio, but also from its vast partner network, which includes over 330,000 consultants from major firms like Deloitte and KPMG.

01:27 — For me, the biggest takeaways here are that, firstly, agentic AI is clearly going mainstream, with equity firms eager to roll it out among their entire portfolios. We're obviously well past the experimentation phase now.

01:42 — Secondly, this really presents a major opportunity for AI infrastructure companies to leverage this growing acceptance to enhance AI distribution at the portfolio level. This shift could result in AI adoption accelerating much faster than when companies go down the traditional enterprise sales route.

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