PC industry's big dream: AI enabled PCs spur upgrade cycle

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

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PC giants are all betting that AI-enabled PCs will get sales growing again and create new use cases, but it's unclear whether technology buyers will play along.

Apple's launch of the new 13- and 15-inch MacBook Air with the M3 processor dedicated a good bit of space to AI applications. Apple noted:

"Combined with the unified memory architecture of Apple silicon, MacBook Air can also run optimized AI models, including large language models (LLMs) and diffusion models for image generation locally with great performance. In addition to on-device performance, MacBook Air supports cloud-based solutions, enabling users to run powerful productivity and creative apps that tap into the power of AI, such as Microsoft Copilot for Microsoft 365, Canva, and Adobe Firefly."

Get used to similar statements from other PC vendors. In fact, the AI PC talk is already starting as companies hope for a second half sales rebound. Here's a sampling of recent comments from earnings calls from PC giants HP, Lenovo and Dell.

HP CEO Enrique Lores:

"We remain extremely excited about the opportunity that AI PCs will bring in terms of both the customer value that they will deliver in terms of security, in terms of latency, in terms of cost and also the impact it will have over time in the company."

Lenovo CEO Yuanqing Yang:

"AI PC could represent an inflection point for the PC industry. It could drive a new product cycle with premium pricing, which is key to delivering premium to market growth, strong ASP and sustainable profitability."

Dell Technologies Chief Operating Officer Jeff Clarke:

"We have hardware enabled AI PCs with an application base coming that should make it an exciting opportunity to own an AI PC."

All of these executives said their take on an improving second half 2024 for PC sales was based on third party validation, notably an IDC report. IDC expects AI PCs will represent 60% of all PC shipments worldwide and grow from 50 million units in 2024 to 167 million in 2027.

The argument for the ramp of AI PC shipments is that the installed base is already long in the tooth and AI can change the future of work. These AI PCs will be able to improve productivity, offer faster performance and lower inferencing costs as they leverage compressed language models.

All that's missing is the killer application, which Microsoft is working to provide in the latest versions of Windows. Lenovo said it is starting to ship AI PCs and the portfolio will expand through 2025. Yang said AI PCs will be a win for users as well as their employers due to hybrid AI that will leverage local compute.

"AI PC comes with a personal intelligent agent using natural language user interface, a compressed local large language model, heterogeneous computing with CPU, GPU, NPU, privacy and security protection and our AI application ecosystem. We believe this trend will stimulate another industry refresh cycle, as the users require devices designed for more creativity and productivity."

Lores said HP is working with partners to make sure applications can leverage the new PC capabilities. Lores noted that HP has seen more stability in small business sales and education and AI PCs will drive gradual sales improvements over the next two years.

For HP and Lenovo, AI PCs will have to appeal to consumers and enterprises to move the needle. HP's PC sales in the first quarter skewed commercial. 

Dell is mostly focused on sales to corporate customers. The bulk of Dell's PC sales go to enterprises and the focus pays off as total revenue per unit is nearly twice as large as the competition.

Clarke said AI PCs will drive sales, but Dell's guidance doesn’t include them. Simply put, Dell isn't seeing the upside yet. Clarke's bet is that the Windows upgrade cycle is likely to drive corporate sales.

"Do I expect the PC market to be bigger in calendar 24 than 23? Yes. Do I think the PC market is likely bigger in the second half of 24 than it is in the first half? Absolutely. We believe the opportunity in PCs is second half driven. That is primarily a result of an aging install base. It has never been bigger or older than it is today. We have a version of Windows that is retiring.”

What can derail the AI PC dream? Inflation and constrained budgets for both consumers and enterprises. Consumers are stretching out used cars well beyond historical life spans and PCs aren't going to be much different. Enterprises have steadier refresh cycles, but will want to see productivity gains from AI PCs, which will cost more than regular PCs. Enterprises will also be looking to leverage those pandemic-era PCs as long as possible because IT budget priorities rest elsewhere.

Bottom line: There's hope that PC sales will improve in the second half of 2024, but it's telling that major players aren't including any uplift in their financial guidance. In the end, that approach makes sense. Hope isn't strategy.

Will generative AI make enterprise data centers cool again?

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

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This post first appeared in the Constellation Insight newsletter, which features bespoke content weekly and is brought to you by Hitachi Vantara.

The lowly enterprise data center may be making a comeback as companies look to leverage generative AI but keep corporate data secure.

This burgeoning trend may not come as a complete surprise. Constellation Research analyst Dion Hinchcliffe noted in a report last year that CIOs were scrutinizing public cloud workloads because they could get better total cost of ownership on-premises. What's emerged is a hybrid cloud approach where generative AI may tip the scales toward enterprise data centers.

On C3 AI's third quarter earnings call, CEO Tom Siebel talked generative AI workloads. He said: "The interesting trend we're seeing--and this is really counterintuitive--is we're going to see the return of in-house data centers where people have the GPUs inside. I'm hearing this in the marketplace and even my engineers have talked about it. Some are saying, 'it's going to be cost effective for us to build.'"

Siebel isn't the only one seeing generative AI making the data center cool again.

Nutanix CEO Rajiv Ramaswami said the company is "seeing more examples of people repatriating" workloads from the public cloud to data centers and private cloud arrangements. Enterprise concerns about generative AI are likely to equate to more data center buildouts than you'd think.

"I'm talking about enterprise workloads, because what has gone to the public cloud largely has been net new applications. So, for these workloads are still sitting in the enterprise environment, I think CIOs are being a lot more careful about how much of that do they take to the public cloud," said Ramaswami. "There's some repatriation happening from the public cloud back on-prem. But there's also a lot more scrutiny and forethought being applied to what should go into the public cloud."

Nutanix, which just reported earnings, is also seeing traction with its GPT-in-a-box offering, which accelerates generative AI across an enterprise while keeping data secure. Many of the industries interested in GPT-in-a-box cited by Ramaswami were noted by C3. Federal agencies, defense, pharmaceutical, and finance.

It's not surprising that defense, federal agencies and banking and finance are driving on-premises generative AI workloads. These companies are well-capitalized, have critical security needs and operate as technology companies in many ways.

Enterprises in these industries, along with nation-states, are the ones most likely to build their own data centers for AI workloads. Nvidia CEO Jensen Huang equates these next-gen data centers as AI factories.

Huang explained on Nvidia's most recent earnings call:

"You see us talking about industrial generative AI. Now our industries represent multi-billion-dollar businesses, auto, health, financial services. In total, our vertical industries are multi-billion-dollar businesses now. And of course, sovereign AI. The reason for sovereign AI has to do with the fact that the language, the knowledge, the history, the culture of each region are different, and they own their own data.

They would like to use their data, train it to create their own digital intelligence and provision it to harness that raw material themselves. It belongs to them, each one of the regions around the world. The data belongs to them. The data is most useful to their society. And so, they want to protect the data. They want to transform it themselves, value-added transformation, into AI and provision those services themselves."

The rest of us just want better TCO on AI workloads, but you get the idea. Dell Technologies appears to be capitalizing on AI-optimized servers along with SuperMicro. 

How AI workloads will reshape data center demand

Jeff Clarke, Vice Chairman and Chief Operating Officer at Dell Technologies, said orders for AI-optimized servers grew 40% sequentially and backlog doubled to $2.9 billion.

"83% of all data is on-prem. More data will be created outside of the data center going forward that inside the data center today, that's going to happen at the edge of the network, a smart factory and oil derrick. We believe AI will ultimately get deployed next to where the data is created driven by latency.

We sold to education customers, manufacturing customers, and governments. We've sold the financial services, business, engineering and consumer services. Companies are seeing vast deployments, proving out the technology. Customers quickly find that they want to run AI on-prem because they want to control their data. They want to secure their data. It's their IP and they want to run domain specific and process specific models to get the outcomes they're looking for."

Power problems

What could derail the march to in-house data centers? Today, it's procuring GPUs, but that'll work itself out. Power will be the big issue going forward. Siebel explained:

"The constraint today is you have to call up Jensen and beg for GPUs. Let's say we can figure out how to do that. Maybe we know somebody who knows Jensen. Okay, the hard part is we can't get power. You cannot get the power to build the data center in Silicon Valley. Power companies will not give you power for a data center. So, I think this GPU constraint is ephemeral and soon it's going to be power."

Pure Storage Charles Giancarlo cited power as a limiting factor for AI adoption on the company's fourth quarter earnings call. "The energy demands of AI are outstripping the availability of power in many data center environments," he said.

The power issue was also noted at Constellation Research's Ambient Experience conference this week. Rob Tarkoff, Executive Vice President & GM, CX Applications at Oracle, said sustainable and cost-effective power is of generative AI's big challenges.

"Where are we going to get the power cost effectively and environmentally sustainable power to be able to run all the models we want to run? How are we going to keep the cost at a level that companies can realistically invest in?" asked Tarkoff, who added that scaling data and compute isn't cheap. "All of this sounds really cool in production, but it's an expensive and energy consuming value proposition."

Constellation Research's take

This thread about enterprises potentially building out data centers for generative AI spurred a bit of debate internally. Here's what a few analysts had to say.

• Doug Henschen: "Data warehouse/lakehouse workloads are selectively remaining on or moving back on premises. Warehouse and lakehouse workloads are often data- and compute-intensive, and in many cases, organizations that have moved these workloads to the cloud have had sticker-shock experiences. Among those firms that have maintained on-premises systems and data center capacity, we've seen some instances where they've either delayed migration of data warehouse workloads to the cloud or even repatriated workloads to on-premises platforms. When workloads are stable and predictable and there's no need for cloud elasticity, it can be more cost effective to run these workloads on premises."
• Dion Hinchcliffe: "Here's the problem with public cloud and today's increasingly always-on, high performance computing workloads (basically, a lot of ML + AI, both training and ops): 1) The hyperscalers' profit margins, 2) R&D costs for I/PaaS, and 3) the massive build-out Capex to support high growth. All three numbers are high right now. Public cloud customers cover all three expenses as major cost components in their monthly bills. Many CIOs have now realized they can bring in a good percent of workloads back in, sweat their private DC assets to the last penny, and largely avoid paying these markups (that at the end of the day aren't really their problem.) So, the big question: Is the pendulum swinging back to private data centers? Not hardly, but as my CIO interviews and research on the topic last year showed, there is definitely an active rebalancing of workloads to where they run best. That means a good bit of AI, especially training, will go back in-house or to specialty partners that are highly optimized for this, that will also keep the private training data away from the hyperscalers."
• Chirag Mehta: "The reality doesn't quite add up. Even with AI, running GPU on-prem is Capex intensive and requires highly skilled people. Other than a few companies this is not a practical thing to do."
• Andy Thurai: "The repatriation/migration is happening on a selected workload basis. For AI workloads, especially the training, it is a bit complicated and requires a ton of MLOps and scaling tools that the private data centers don't have. The GPU shortage and scale needed for model training are also constraints. While it is easy to move ML workloads, AI workloads are still a challenge from what I hear."

Relevant Shortlists:

• Next-Generation Computing Platforms
• Artificial Intelligence and Machine Learning Best Of Breed Platforms
• Artificial Intelligence & Machine Learning Cloud Platforms
• Cloud-Based Data Science and Machine Learning Platforms
• Hybrid-Cloud and MultiCloud NoSQL Databases
• Hybrid-Cloud and Multicloud Analytical Data Platforms
• Infinite Connectivity Vendors
   

Zoho CEO Sridhar Vembu: Long-term thought leadership on innovation, technology, people

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

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Zoho CEO Sridhar Vembu has scaled a company with humility, a focus on giving back to smaller communities and playing the long game when it comes to technology, people and customer value.

Vembu's approach is refreshing and effective--not to mention a touch quirky compared to many CEOs we encounter.

At Zoho Day 2024, Constellation Research CEO Ray Wang caught up with Zoho CEO Sridhar Vembu (right) to talk about how to approach business and social good, innovation and focusing on customers. Here's are some of the takeaways from the conversation.

Transnational localism. "It's really about getting closer to the customers at one level, and just talking about business first. But beyond that, it's also putting back into communities that income needed from technology, create good jobs, in smaller communities, which people are not doing enough," said Vembu.

The approach to giving back to smaller communities is a bit part of Zoho's strategy. Zoho has offices in Chennai, India; McAllen, TX; and a bevy of other locations in UK, US, India, Egypt, Nigeria, Kenya to name a few.

"You can operate out of smaller towns and create high impact R&D. And that helps the customer from smaller places and creates opportunities for people who didn't have it before," said Vembu.  

McAllen, Texas. Zoho has built out its operations in McAllen, Texas. Vembu explained why McAllen was chosen.

"We looked around for communities that are small, but not too small and there are enough people that are similar to our value system, and the demographic where we can recruit and train people and there's a low cost of living and affordable housing. We want this for our employees because we want to keep them forever. If our employee can buy a home and build families, they're more contented. They're more likely to be satisfied employees, which will lead to more satisfied customers. McAllen checked all the boxes, and then we sent an email to the Mayor's office and got an instant response."

Taking a long-term view. Vembu said Zoho is running its own schools, which is about giving back but also building a talent base for the years ahead. "That requires us to take a long-term view that you cannot just go hire for today and then be productive two weeks later," said Vembu. "40% to 50% of hires don't actually work out. In an interview process, you really cannot tell culture fit and a lot of things that go into making someone successful at work. We believe that first we have to nurture the talent and that automatically brings in good people to us over time."

Jobs, automation and AI. Wang asked Vembu about the future of meaningful work, AI and automation and what a long-term view looks like. Vembu said there has to be a way to balance automation and human work as well as wealth.

"We have to balance this out if we want a sustainable society so there isn't a civil war. We have to balance things out. We cannot just create all the wealth in one place. Income as a percentage of GDP is at all-time lows or near all-time lows. Profit as a percentage of GDP is near all-time highs. This can't go on forever. This has run this for 20, 30, 40 years now, but the bills are coming due. We have to think differently. This is not a political statement. I actually believe that the solutions aren't in the political arena today. We have to try new experiments like a scientist trying new things."

Zoho's technology investments. Vembu said the company's strategy has been evolving rapidly from building individual products to complete platforms that appeal to large companies with more complex requirements. Zoho is also infusing artificial intelligence throughout the platform.

"We are particularly very happy with smaller domain specific models, which are also cheaper to run," explained Vembu. "We're getting good payoff from the approach where we have a mix of smaller models, not one chain model."

Vembu said Zoho has long-run experiments on raising developer productivity with smaller models that ensure the correctness of code that will build future products.

Giving customers choice. Vembu said that software as a service should be about freedom of choice and simple payment plans. He said:

"We actually believe in two cardinal virtues as a company to keep ourselves grounded. One is humility. The customer always comes first. Their needs take precedence over immediate revenue. The second is contentment. We have to stay contented because there are times where you end up chasing growth for its own sake. And companies get in trouble when they do that. These two principles we practice which is why we say that if you don't need all of this just buy the stuff you need."

Zoho offers a monthly plan but doesn't force customers to pay annually. In other words, Zoho has reached hit scale with $50 a month as other vendors have gone from that sum to $500 today and priced companies out.

Enterprise class software for SMBs. "SMB software is relegated to a niche where it is not as powerful and doesn't scale," said Vembu. "We deliver so you can go from two employees to 200 to 20,000 to 200,000. We will scale with you."

Wang noted that one large services firm asked whether Zoho could scale to a 500,000 to 1 million user organization. Vembu said Zoho has won a deal that size but hasn't announced it yet. "We will show you if you give us the opportunity," he said. "We will not say give us the money. Give us the opportunity. We'll show you."

Perils of the hard sell. Vembu said Zoho isn't into the hard sell and pushing limits for sales. "We let the customer slowly figure us out and understand us. I want to sleep at night. I don't want to piss off customers by pushing hard. A lot of people do that and the result of it is employee burnout," said Vembu. "Not a lot of CEOs can't do this job for a long period. I've done this for nearly 27 years now. I'm still going strong. I say okay, we can win this customer next year. Let's not push this hard if you're not ready."

More on Zoho:

• Truly Confusing? Truly Different. Truly Zoho.
• Zoho outlines generative AI plans, large enterprise and solopreneur products
• Zoho Analytics: A New Value Leader Emerges in Business Intelligence
• Constellation ShortList™ B2C Marketing Automation for Small to Midsize Business
• Constellation ShortList™ Product and Innovation Roadmapping
• Constellation ShortList™ B2B Marketing Automation for Small and Midsize Business
   

Dell Technologies AI optimized server backlog swells to $2.9 billion exiting Q4

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

Read more

Dell Technologies reported a better-than-expected fourth quarter as the company saw strong demand for AI-optimized servers.

Jeff Clarke, vice chairman and chief operating officer, Dell Technologies, said orders for AI-optimized servers grew 40% sequentially and backlog doubled to $2.9 billion. "We've just started to touch the AI opportunities ahead of us, and we believe Dell is uniquely positioned with our broad portfolio to help customers build GenAI solutions that meet performance, cost and security requirements," said Clarke. 

Dell shipped $800 million of AI optimized servers in the quarter. "We are also seeing strong interest and orders for AI optimized servers equipped with the next generation of AI GPUs, including the H200 and MI300X," said Clarke, referring to Nvidia and AMD GPUs, respectively. HPE's quarter was mixed and executives cited GPU deals as a reason for weaker sales. 

During the quarter, Dell Technologies managed through revenue declines compared to a year ago. The company reported fourth-quarter revenue of $22.32 billion, down 11% from a year ago, with net income of $1.16 billion, or $1.59 a share. Non-GAAP earnings for the quarter were $2.20 a share. Dell also unveiled a 20% hike to its annual dividend to $1.78 per share.

Wall Street was expecting Dell Technologies to report fourth quarter earnings of $1.72 per share on revenue of $22.17 billion.

For fiscal 2024, Dell reported net income of $3.2 billion, or $4.36 a share, on revenue of $88.42 billion, down 14% from a year ago. The company said it expects to return to growth in fiscal 2025.

By unit, Dell's Infrastructure Solutions Group had revenue of $9.3 billion, down 6% from a year ago. Operating income was $1.4 billion. Clarke said there's the obvious buildout in the public cloud for AI workloads, but enterprises are increasingly buying AI-optimized servers too. Dell can sell more richly configured GPU servers and attach services to them as enterprises build out. 

"83% of all data is on-prem. More data will be created outside of the data center going forward that inside the data center today, that's going to happen at the edge of the network, a smart factory and oil derrick. We believe AI will ultimately get deployed next to where the data is created driven by latency.

We sold to education customers, manufacturing customers, governments. We've sold the financial services, business, engineering and consumer services. Companies are seeing vast deployments, proving out the technology. Customers quickly find that they want to run AI on-prem because they want to control their data. They want to secure their data. It's their IP and they want to run domain specific and process specific models to get the outcomes they're looking for."

The PC business had fourth quarter revenue of $11.7 billion, down 12$ from a year ago. Commercial PC revenue was $9.6 billion of that total. Operating income was $726 million.

In prepared remarks, Clarke said:

"FY 24 was one of those years that didn’t go as planned, but I really like how we navigated it.  We showed our grit and determination by quickly adapting to a dynamic market, focusing on what we can control, and extending our model into a high growth AI opportunity."

Clarke added that AI-optimized PowerEdge XE9680 server sales were ramping quickly. He added that Dell's storage business should also fair well due to projected growth in unstructured data.  

• Dell Technologies delivers mixed Q3, but strong demand for AI-optimized servers
• Dell Technologies to exit commercial agreement with VMware
• How AI workloads will reshape data center demand
• Dell Technologies, Hugging Face aim to make on-premises generative AI deployments easier

HPE Q1 server revenue falls 23% in mixed quarter

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

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Hewlett Packard Enterprise posted a mixed first quarter where sales fell short of expectations due to what CFO Marie Myers said were "challenges brought by the softening of the networking market and GPU deal timing."

The company reported first quarter non-GAAP earnings of 48 cents per share, GAAP earnings of 29 cents a share and revenue of $6.8 billion, down 14% from a year ago. Wall Street was expecting HPE to report adjusted earnings of 45 cents per share on revenue of $7.1 billion. HPE is planning to buy Juniper Networks in a deal valued at $14 billion.

By unit, HPE said server revenue fell 23% in the first quarter to $3.4 billion. Intelligent edge revenue was $1.2 billion, up 3% from a year ago. Hybrid cloud revenue was $1.2 billion in the first quarter, down 10% from a year ago.

CEO Antonio Neri said HPE had operational discipline to manage through the quarter and remained confident in the strategy. Myers added that "we are controlling what we can control, and we are optimistic about delivering strong shareholder returns over the remainder of the fiscal year.”

As for the second quarter, HPE said revenue will be between $6.6 billion to $7 billion with non-GAAP earnings of 36 cents per share to 41 cents per share. For fiscal 2024, revenue growth will be flat to up 2% from a year ago. HPE non-GAAP earnings per share will be between $1.82 and $1.92.

• HPE to acquire Juniper Networks for $14B: What it means
• HPE Enters the Next-Generation Computing Market
• HPE sees Q4 strength in AI, edge, high performance computing
• HPE bets AI, edge, supercomputing workloads will drive growth

On a conference call with analysts Neri said HPE lacked GPU supply and customers were digesting Aruba networking orders. The networking comments have been echoed by Cisco, who said something similar in its most recent earnings call. Regarding AI-optimized servers, Neri said "several large GPU acceptances shifted" and the company "did not have the GPU side."

Here's a look at the key points from the conference call via Neri:

• "We saw campus networking weaken and the decline late in the quarter was greater than expected. There was a large headwind relative to our expectations. Customers are taking longer to digest prior orders than we had anticipated."
• "We expect weakness in the networking market to persist and impact reveneu through fiscal year 2024."
• "Server demand remains very strong evidenced by our growing cumulative order book. However, GPU availability remains tight and our delivery timing has also been affected by the increase in length of time. Customers required to set up the data center space power and cooling requirements needed to run these systems. As a result of our AI server orders conversion was below our expectations."
• "We have already a lot of GPUs that we already built that the customers will take time to assemble systems. But the reality is that we need more supply against the backlog that we announced today, which was $3 billion at the end of the q1."
• "Our pipeline is large and growing across the entire AI lifecycle from training to tune into inferencing. We are starting to see a demand pull through for other solutions, including storage. We expect our server and hybrid cloud segments to grow sequentially through the fiscal year."
• "Given the softening network in market GPU deal timing and to some extent GPU availability. We're focused on execution as we navigate the fluctuations in demand we see in certain areas of the market."
• "This quarter is a moment in time and does not at all dampen our confidence in the future ahead of us."

Oracle adds generative AI features to Autonomous Database

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

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Oracle continued to build out its generative AI tools for its Autonomous Database with conversational AI, a broad set of large language models, new analytics for knowledge graphs, spatial learning and no-code modeling.

By bringing generative AI models to its database portfolio, Oracle is looking to make models more dynamic by connecting them to real-time data. The general theme behind Autonomous Database Select AI is to enable insights in natural language without the user needing to know where and how data is stored.

Here's a breakdown of new additions to Oracle Autonomous Database:

• Select AI, which uses LLMs to generate SQL queries based on natural language conversations. Select AI enables apps to integrate private data with generative AI and supports multiple models.
• Spatial machine learning, an addition to Oracle Machine Learning. Spatial machine learning uses location data to improve model performance and supports spatial algorithms.
• Model monitoring user interface, which is a no-code UI in Oracle Machine Learning. Model monitoring UI is designed to make it easier to monitor models and detect concept and quality drift.
• Operational graph views on knowledge graphs, a new no-code UI that facilitates graph analytics on knowledge graphs without duplicating data and examines connections.

Oracle executives said Select AI is available today in Oracle Autonomous Database and can be used in any database application. The Select AI rollout comes a few weeks after Oracle announced general availability of its Oracle Cloud Infrastructure Generative AI service and plans to integrate generative AI across its stack and applications.

Previously:

• Oracle adds vector search to Oracle Database 23c, melds generative AI, transactional data
• Oracle, Microsoft launch Oracle services within Azure data centers
• Oracle's Q2 mixed as revenue falls short, cloud sales sequentially flat

What VMware customers are doing through the lens of Nutanix

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

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If you want to know what VMware customers are plotting in the wake of Broadcom's acquisition it's worth checking out Nutanix's results, which are getting a gradual boost.

Not surprisingly, Nutanix's second quarter earnings conference call featured a heavy dose of VMware questions from Wall Street analysts. CEO Rajiv Ramaswami initially just mentioned VMware as an unnamed competitor, but analysts went right to the VMware between-the-lines benefit to Nutanix.

Ramaswami said VMware customers are rethinking overall strategies and looking toward other more automated options. "(VMware customers) were happy with the vendor prior, and now they don't feel happy. So, they got to look at an alternative. And we are a very solid infrastructure alternative," he said.

• VMware mansplains to customers about model changes, subscription pricing, account upheaval
• KKR buys VMware's EUC division from Broadcom for $4 billion
• Dell Technologies to exit commercial agreement with VMware
• Will VMware customers balk as Broadcom transitions them to subscriptions?
• BT150 CXO zeitgeist: AI trust, AI pilots to projects, VMware angst, projects ahead

First, the numbers.

Nutanix's second quarter earnings handily topped estimates with non-GAAP earnings of 46 cents a share on revenue of $565.2 million, up 16% from a year ago. Nutanix reported second-quarter net income of $32.8 million, or 13 cents a share.

The company said annual contract value (ACV) billings were up 23% from a year ago in the second quarter with annual recurring revenue up 26%.

As for the outlook, Nutanix projected third quarter revenue of $510 million to $520 million and fiscal 2024 revenue of $2.12 billion to $2.15 billion.

Ramaswami noted a few wins and how Nutanix is landing larger deals. "A good example is a seven-figure win with a global EMEA based provider of automotive technology solutions. This new customer had an existing three tier footprint in need of a refresh but was frustrated by the recent price increases of their incumbent vendor and was also looking to have the flexibility to potentially move some of their footprint to the public cloud in future. They chose our Nutanix Cloud Platform, including our AHP hypervisor, as well as Nutanix Cloud Management, based on its superior TCO, built-in automation for infrastructure as a service," he said.

Constellation ShortList™ Next-Generation Computing Platforms

It doesn't take Sherlock Holmes to figure out that competitor given the multiple reports of VMware disgruntlement. Ramaswami also said a converged infrastructure partnership with Cisco was showing promise even though it's early. Nutanix CFO Rukmini Sivaraman said the company is "seeing a higher mix of larger deals in our pipeline" as well as new and expansion opportunities in an uncertain environment.

So, what are VMware customers thinking? Here's a distilled version of the lessons from Nutanix's second quarter conference call.

VMware customer migrations are likely to be a multi-year events. Ramaswami said the timing and magnitude of landing VMware's customers is unpredictable, but the "pipeline is quite substantial and growing." Ramaswami said:

"We expect contribution for the opportunity to build gradually, and here are the reasons. First is that many customers signed multi-year ELAs enterprise agreements with VMware prior to the deal closing for three to five years. That buys them some time to make decisions. The second is converting from VMware 3-tier accounts or legacy storage accounts, which is a good chunk of VMware footprint, in many cases requires a refresh of their storage and our servers. That could also impact the timing of the potential software purchases that they would make with us."

Larger customers have a lot of work to do to migrate away from VMware, but inertia isn't much of an option. Customization is also a factor since that can slow migration work.

Ramaswami said:

“One of the reasons we're seeing these large deals is because of course for a while we've been working on a portfolio, that product portfolio, which we think is ready for large scale enterprise deployments. And so, we have segmented our focus a bit further up the market in terms of our own sales for segmentation, and then on top of that, we've got the industry disruption with VMware where many large customers, of course, who are not necessarily engaged with us before are now engaging with us. So that's the reason why we're seeing more of these large deals in our pipeline."

The catch? Those large deals have a lot of variability on timing even as the pipeline builds. "It's a sea of engagement, when you have these types of deals between both companies, we are investing resources, customers investing a lot of resources as well, because there's a lot of testing certifications, go into contract negotiations, security audits, a whole bunch of things that get through this process," he said.

VMware Cloud Foundation is the target. Broadcom has focused VMware on its VMware Cloud Foundation business. That platform happens to be the one that lines up with what Nutanix offers. Ramaswami said:

"If you compare the full stack that Broadcom was offering with VMware Cloud Foundation, that, -- and our Nutanix cloud platform pretty much goes head-to-head against that, and we've got all the capabilities. That's a full stack that includes the hypervisor, a software defined storage, networking and management. So, we compare very well with that full stack and we're able to go to a very comparable offering."

VMware customers on lower-tier offerings, VMware Virtual Foundation (formerly vSphere) attached to legacy storage, will look at Nutanix as a broader transformation move. Ramaswami said:

"Customers are actually making a shift from a legacy architecture that say hypervisor plus external storage to a modern HCI (hyperconverged infrastructure) architecture that includes our hypervisor, but also the rest of our stack."

As a side note, this is where Dell's decision to terminate a commercial agreement with VMware may affect HCI decisions.

Broadcom's VMware purchase may be speeding up moves to HCI. Nutanix has put incentives in place for partners, advertising more to highlight its platform and helping customers with migrations.

Cisco is going to be Nutanix's BFF and help with migrations. It's early in the Cisco-Nutanix partnership, but Cisco's scale and market position can only help Nutanix. "There's a lot of cooperation happening between our sellers, and Cisco sellers in the field. So, all good, good omens at this point in time, but still very early," said Ramaswami.

Snowflake's Slootman steps down as CEO, technologist Ramaswamy takes over

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

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Snowflake has a new CEO. The company said Sridhar Ramaswamy will become CEO immediately as Frank Slootman stepped down but remains Chairman of the board.

Ramaswamy (right) had been SVP of AI at Snowflake. Slootman said "there is no better person than Sridhar to lead Snowflake into this next phase of growth and deliver on the opportunity ahead in AI and machine learning."

Previously, Ramaswamy led all of Google's Advertising products, which included search, display and video advertising, analytics, shopping, payments, and travel.

Slootman explained the succession strategy on Snowflake's earnings conference call:

"The Board has run a succession process that wasn't based on arbitrary timeline, but instead, looked for an opportunity to advance the company's mission, well into the future. The arrival of Sridhar Ramaswamy through the acquisition of Neeva last year represented that opportunity.

With the onslaught of generative AI, Snowflake needs a hard-driving technologist to navigate the challenges the new world represents. Sridhar's vision for the future and his proven ability to execute at scale made it clear to us as a Board, he is the right executive at the right time to lead Snowflake."

Ramaswamy added:

"To deliver on the opportunity ahead, we must have clear focus and move even faster to bring innovation on the Snowflake platform to our customers and partners. This will be my focus."

The news overshadowed a strong quarter from Snowflake. Snowflake reported fourth quarter revenue of $774.7 million, up 33% from a year ago, with a net loss of $169.35 million, or 51 cents a share. The non-GAAP fourth quarter earnings per share were 35 cents per share.

Wall Street was expecting Snowflake to report fourth quarter earnings of 18 cents per share on revenue of $760.22 million.

Constellation Research analyst Doug Henschen said Snowflake could be entering a newer slower growth phase.  

For the first quarter, Snowflake said product revenue will be $745 million to $750 million, up 26% to 27% from a year ago. For fiscal 2025, Snowflake projected revenue $3.25 billion, up 22% from a year ago.

Henschen said:

"Frank Slootman joined Snowflake in May 2019 and quickly and spectacularly achieved what he was brought there to do: take the company public. Snowflake's September 2020 IPO raised an impressive $3.4 billion and still stands as the biggest software IPO in history. Now that market conditions have changed, there's a sense that Snowflake's fastest growth years may be behind it and it will require even harder work to maintain what's likely to be moderating growth. I wouldn't be surprised to see Slootman come out of retirement at some future date to take another company public."

CFO Mike Scarpelli said the fourth quarter was more normalized after a challenging year. 

"Holidays make it difficult to discern meaningful consumption trends. In the quarter, younger customers led revenue growth. These accounts are adding new workloads in migrating from legacy vendors. Financial Services and retail were our largest revenue contributors, and we are seeing emerging momentum from the EMEA region and technology vertical.

Customer optimizations returned to a normal level, with eight of our top 10 accounts growing sequentially. We proactively engaged with customers to help them optimize their Snowflake usage and we'll continue to do so. History has shown that optimizations expand our long-term opportunity. We now have 83 customers with trailing 12-month product revenue greater than $5 million, up from 75 in Q3."

Scarpelli noted that Snowflake's outlook accounts for a few moving parts related to storage pricing and product efficiency. 

"We are forecasting increased revenue headwinds associated with product efficiency gains, tiered storage pricing and the expectation that some of our customers will leverage Iceberg Tables for their storage. We are not including potential revenue benefits from these initiatives in our forecast. These changes in our assumption impact our long-term guidance. Internally, we continue to march towards $10 billion in product revenue. Externally, we will not manage expectations to our previous targets until we have more data. We are focused in executing in FY '24 to ensure long-term durable growth."

Scarpelli said that Snowflake is assuming an additional $50 million of GPU related costs in fiscal 2025 and $10 million should flow to product revenue. Snowflake's guidance isn't assuming that product revenue. 

Constellation Research analyst Holger Mueller noted that Snowflake's expenses have been rising. 

"Snowflake had a great year on the top line, but all costs went up – from cost of revenue all the way to operating expenses that topped $3 billion for the first time. The change in the CEO position – not telegraphed before – may or may not have to do with this, but certainly a slightly increased loss per share was not what investors wanted to see. Slootman is now out and with Ramaswamy a more technology focused executive is in charge. Like all data centric vendors, Snowfllake needs address the generative AI trend, and that is something Ramaswamy is probably in a better position to deliver on. Future will tell – starting with Q2."

Ramaswamy said he is focused on executing on Snowflake's current roadmap.

"I've had over 100 conversations with customers over the past year about generative AI in particular. And the product announcements that we've already made, things in private preview, including Snowflake Cortex, which is our managed AI and search layer combined with applications like Document AI for extracting structured data or our Copilot. These have been very well received. Document AI, for example, has hundreds of customers waiting for it to hit GA that are on our waitlist. So, I would say it is a matter of executing to the roadmap that we have already laid out. Cortex will hit public preview soon. Getting this in the hands of our customers, and having them realize value is the top priority. I don't think of this as needing a new strategy."