| Constellation Research

Uber Q4 strong, eyes platform expansion

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. ...

Uber reported strong fourth quarter results as it capped a year focused on profitable growth and CEO Dara Khosrowshahi said the company in 2024 will "use our data advantage to drive more efficient pricing, matching, and incentive spend."

While Uber is best known for its mobility and delivery services, the company is really a data platform that is extensible into new businesses. For instance, Uber has 19 million Uber One subscribers globally and has an ad business that's on a $900 million annual revenue run rate.

Uber also has been leveraging artificial intelligence as well as machine learning alongside process mining and automation. Uber has been cited as a reference customer for Oracle Cloud Infrastructure, Databricks, Celonis and UIPath.

The company will outline more about its data strategy during an Investor Update call Feb. 14.

Uber reported fourth quarter earnings of $1.4 billion, or 66 cents a share, including a $1 billion gain due to revaluing of equity investments. Revenue for the quarter was $9.94 billion, ahead of $9.76 billion expected by analysts.

In the quarter, Uber saw gross booking surge 22% with mobility up 29% and delivery up 17%. For the first quarter, Uber projected gross bookings of $37 billion to $38.5 billion with adjusted EBITDA of $1.26 billion to $1.34 billion.

Khosrowshahi said:

“2023 was a year of sustainable, profitable growth for Uber as we executed against our strategy. We grew our business by improving marketplace health and scaling new products, bolstering our competitive position in key markets.

Turning to 2024, I want to highlight several key priorities. First, our goal is to make the Uber use case even more of an everyday reality. We’ll continue to enhance the power of our platform by expanding the number of consumers who use multiple Uber products, turbocharged by our Uber One membership program. Second, we will strategically reinvest into promising new growth vectors to deliver strong multi-year growth with healthy long-term unit economics. Lastly, we will maintain our industry-leading cost structure and use our data advantage to drive more efficient pricing, matching, and incentive spend."

By the numbers:

Uber had 150 monthly active platform consumers in the fourth quarter, up 15% from a year ago.
Trips in the quarter were up 24%.
Mobility revenue in the fourth quarter was $5.54 billion, up 34% from a year ago.
Delivery revenue was up 6% in the fourth quarter to $3.12 billion.
Freight revenue was $1.28 billion, down 17% from a year ago.
For 2023, Uber reported net income of $1.89 billion on revenue of $37.3 billion.

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Alibaba Cloud focuses on revenue quality, boosts Q3 profitability

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Alibaba's cloud unit in the fiscal third quarter delivered revenue growth of 3%, but improved its adjusted earnings before interest, taxes and amortization by 86%.

In its third quarter earnings results, Alibaba's cloud unit delivered third quarter EBITA of $333 million on revenue of $3.5 billion, up 3% from a year ago.

Alibaba had planned to spin off its cloud unit, but shelved plans citing uncertainty over trade restrictions. Alibaba reported third quarter revenue of $36.67 billion, up 5% from a year ago, with net income of $2.03 billion, and announced another $25 billion to its share repurchase program.

The company has improved its cloud economics by focusing on revenue quality. The company said: "We continue to improve revenue quality by reducing the revenue from low-margin project-based contracts. On the other hand, revenue from public cloud products and services grew healthily which contributed to profitability improvement."

Constellation ShortList™ Global IaaS for Next-Gen Applications | Constellation ShortList™ Artificial Intelligence and Machine Learning Cloud Platforms

Alibaba CEO Eddie Wu said:

"In cloud computing, we're committed to our strategy of prioritizing public cloud. We have proactively optimized our business structure, reduced revenue from project-based contracts and increased investment in public cloud products. These structural adjustments are showing results and Alibaba Cloud's overall profitability capability continues to improve.

We've also upgraded Alibaba Cloud's sales operations establishing different sales and service systems to serve different types and sizes of customers by improving our customer coverage and service capabilities, we will enhance our growth rate."

Alibaba's Cloud Intelligence Group delivered the company's second highest EBITA in the third quarter. The company added that it rolled out its new elastic compute instances aimed at AI inferencing and is gaining database workloads.

For the nine months ended, Dec. 31, 2023, Alibaba's cloud unit had revenue of $11.4 billion, up 3% compared to a year ago, with EBITA of $660 million.

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SAP's German speaking user group takes aim at cloud contracts, BTP and more

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

The German-speaking SAP User Group (DSAG) is holding its Technology Days conference in Hamburg with a series of demands to alleviate concerns about recent SAP policy changes.

DSAG, one of the more vocal user groups in enterprise technology, has previously had gripes with SAP's move to tether innovation to cloud operating models. At its Technology Days 2024, DSAG elaborated on customer concerns, which often revolve around SAP Business Technology Platform (BTP).

In a statement, DSAG said:

"The hype surrounding generative artificial intelligence (AI) systems is currently attracting the attention of many companies, which are increasingly looking for suitable areas of application. From DSAG's point of view, integrating AI into existing products to improve their functionality makes sense and can be helpful. However, there is still a world of difference between vision and reality or between sales and usable software."

The upshot here is that DSAG is arguing that what is good for SAP's business model isn't necessarily in customer interests. DSAG noted that customers are unsettled over SAP's plans to only make AI innovations available via RISE with SAP Premium since many customers have opted for S/4HANA Private Cloud or on-premises deployments. "Offering AI only in a single cloud contract and operating model is also technically untenable, as large-language models can be implemented independently of this at any time," said Sebastian Westphal, Board Member Technology of DSAG.

Constellation Research CEO Ray Wang said:

"SAP users continue to pay for upgrades, acquisitions, and technical platforms that should have been covered with their original maintenance dollars. This is why many customers are looking to independent maintenance options like Rimni Street and are waiting until 2030 to postpone their upgrade. All this financial engineering is not helping SAP make the case to customers that they should upgrade."

DSAG's demands come as SAP just outlined its 2024 and 2025 ambitions and strategy. In addition, enterprises are looking at more hybrid cloud models for generative AI and the reality is that a one-cloud-fits-all model will encounter pushback.

DSAG outlined the following demands:

The technical integration of AI models must be open and must not be made dependent on commercial contract models. "Transparent and proven billing models and metrics are needed. It must also be possible to prove that valid guidelines have been implemented and documented when AI makes process decisions," said DSAG.
Identity management requires a clear target solution from SAP with migration scenarios and services.
Uniform Harmonized Document Management across the entire SAP portfolio including Ariba and SuccessFactors and BTP.
Consistency across BTP services. DSAG noted that monitoring and logging of individual BTP services is not standardized. BTP needs a uniform strategy.
Comprehensive end-to-end business applications for SAP Datasphere and SAP Analytics Cloud as well as an extended license model for business users. "In addition to the live connection of the SAP Analytics Cloud to all SAP products, this is also needed for non-SAP sources. Appropriate migration scenarios that take existing solutions into account and a license model for occasional users have also been necessary for years," said Westphal.
Considerable progress in the areas of data fabric/data mesh and modern data warehouse architectures.
Security tools for Solution Manager beyond 2027. "Initial signals from SAP that these functionalities will be provided in the SAP Cloud ALM target platform in the future can only be the beginning," said DSAG.
Flexibly controllable cloud services to replace always-on scenarios and re-served instances.
Energy consumption must be taken into account for cloud services and the development of cloud-based infrastructures.
Green ledgers for sustainability requirements must not be provided at extra cost and only for RISE-with-SAP premium customers.

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Cisco rolls out AI infrastructure with Nvidia, aims to track generative AI deployments

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Cisco launched a series of artificial intelligence applications, infrastructure and services aimed at generative AI deployments and their data management, security and cost tracking issues.

Announced at Cisco Live Amsterdam, the company moved to address enterprises that will be deploying generative AI on-premises and in hybrid cloud models. Last week, Cisco announced a partnership with Hitachi Vantara.

Here's a breakdown of was announced.

Cisco said it will offer converged data center infrastructure for AI workloads via a partnership with Nvidia. While AI infrastructure buildouts have been focused on hyperscale cloud providers, enterprises are also looking to run workloads in their data centers for better security and lower costs in some cases.

Specifically, Cisco and Nvidia will offer integrated systems and add Tensor Core GPUs in Cisco's M7 generation of UCS servers, including Cisco UCS X-Series and UCS X-Series Direct. Nvidia AI Enterprise, which includes frameworks, pretrained models and tools will also be available.

Cisco and Nvidia said there will be a host of validated designs for AI deployments with converged and hyperconverged systems.

These AI optimized systems are seeing strong demand that's surfacing in Supermicro results. CXOs in the BT150 are looking at various generative AI use cases and exploring hybrid cloud models. Both Dell Technologies and HPE have signaled strong pipelines for generative AI systems.

Cisco also launched Motific, which was hatched in the company's incubation unit. Motific provides a central view of generative AI deployments allowing central IT and security teams to track risks, data privacy, responsible AI and costs.

According to Cisco, Motific can cut generative AI implementation times by automatically configuring APIs, data sources and foundational models with built in compliance tool, audit trails and analytics.

Cisco added new AI capabilities to its Security Cloud, including Identity Intelligence, which runs on top of customers' existing identity stores to provide visibility, analytics and tools to flag vulnerable accounts, manage privileges and thwart attacks.

Cisco Observability Platform will get a natural language interface for troubleshooting. Cisco AIOps will aim to automate IT processes.

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Palantir posts strong Q4, sees enterprise traction in US

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Palantir's commercial revenue in the US surged 70% as the company delivered in line fourth quarter earnings with revenue that was just ahead of expectations.

The data platform and AI company, which is best known for its government customers, has been working to build out its enterprise business and appears to be succeeding.

Palantir reported fourth-quarter net income of $93 million, or 4 cents a share, on revenue of $608 million, up 20% from a year ago. Adjusted earnings of 8 cents a share were in line with estimates.

In the fourth quarter, Palantir posted commercial revenue of $284 million, up 32% from a year ago. Government revenue was $324 million, up 11% from a year ago. In the US, commercial revenue was $131 million, up 70% from a year ago. Palantir ended the quarter with 221 commercial customers in the US.

Palantir's commercial business scales with help of AI boot camps | The Urgent Case for a Chief AI Officer

For 2023, Palantir reported net income of $210 million, or 9 cents a share, on revenue of $2.23 billion, up 17% from the year before.

As for the outlook, Palantir projected first quarter revenue between $612 million and $616 million. For 2024, Palantir is projecting revenue between $2.65 billion and $2.67 billion with net income each quarter of the year. US commercial revenue is expected to grow at least 40% in 2024.

In a shareholder letter, Palantir CEO Alex Karp said the company is hitting its stride.

"The demand for large language models from commercial institutions in the United States continues to be unrelenting. Every part of our organization is focused on the rollout of our Artificial Intelligence Platform (AIP), which has gone from a prototype to a product in months. And our momentum with AIP is now significantly contributing to new revenue and new customers."

Karp said that AIP significantly speeds up data integration and can get enterprise up and running quickly.

"The proliferation of and interest in large language models obscures the simple fact that the sophistication and power of such natural language processing systems mean little without an effective way of allowing those systems to interact with an organization’s underlying and proprietary data, which is often scattered across hundreds if not thousands of disparate repositories. AIP is connective tissue, and the organic and unconstrained demand for its capabilities is unlike anything we have seen in two decades."

Since launching AIP, Karp said Palantir has conducted more than 500 bootcamps and more than 130 commercial pilots.

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Hitachi Vantara, Cisco launch hybrid cloud suite

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Hitachi Vantara and Cisco launched a suite of hybrid cloud services, Hitachi EverFlex with Cisco Powered Hybrid Cloud, that aims to automate deployments and provide predictive analytics.

The two companies have been long-term partners. The combination aims to bring Hitachi Vantara's storage, managed services and hybrid cloud management and integrate them with Cisco's networking and computing stack. Hitachi Vantara and Cisco said customers will see a consistent experience across on-premises and cloud deployments.

Hitachi Vantara Exchange New York: 10 takeaways on generative AI, transformation, data management

Here are the moving parts of the Hitachi Vantara and Cisco combined offering:

Hitachi Infrastructure Orchestration as a Service (HIOaaS) and Cisco Intersight will be integrated to offer an observability layer across hybrid cloud environments along with analytics and automation.
A flexible managed services operating model for provisioning, implementation and transitions.
An elastic consumption model across hybrid cloud and on-premises deployments via Hitachi EverFlex.
Automation of routine tasks.
A full set of security and compliance tools.

Here's a look at the stack and combination of Hitachi Vantara and Cisco and deployment options.

As noted at Hitachi Vantara's recent Exchange event in New York, enterprises are prepping data management infrastructure for generative AI and other emerging technologies.

Mark Katz, CTO of Financial Services at Hitachi Vantara, said the explosion of data, most of it unstructured, means that businesses have to be able to manage data, protect personal identifiable information with segmentation and track lineage. "It's not enough to simply store the data and retrieve it," said Katz. "You need a set of data management tools across enormously complex cloud and hybrid cloud environments."

Learn more:

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General Motors needs to fix its software issues quickly

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

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

General Motors has software development problems, and the company is facing a brand risk unless it can get its code, user experience and delivery right.

Yes, GM is an automaker and a profitable one, but its future model depends on software prowess. For the fourth quarter, GM reported net income of $2.1 billion on revenue of $43 billion, roughly flat with a year ago. That profit came amid a strike and a reset for its electric vehicle plans.

However, GM CEO Mary Barra spent a good chunk of the company's software woes. First, GM had to stop selling its Blazer EV due to software glitches. Edmunds review of the 2024 Blazer EV was brutal with 23 fault codes that didn't turn up on the dashboard. GM plans a software update to fix the issues.

In addition, GM's Cruise autonomous vehicle investment is at risk. GM owns 80% of Cruise. In October, Cruise had to pause driverless operations to "examine our processes, systems, and tools and improve how we operate." In October, Cruise vehicles were involved in two accidents. Cruise issued a voluntary software recall and issued an update that should fix issues.

After two high-profile software failures, Barra had to address the software issues in her shareholder letter and earnings conference call. This won't be the first time an automaker has to talk about software issues. Ford recently recalled F-150 Lightning EV trucks over software issues.

Regarding GM's Blaze software issue, Barra said:

"We disappointed these customers, and we know it. We are determined to get the software right and we will. We have made several organizational and process improvements that will help us deliver the best possible customer experience going forward. Among several important organizational realignments, we established a software quality division within the software and services team that has been performing a retrospective on the Blazer EV and has improved the current software development and test processes across the enterprise. Outcomes of this activity are getting applied to all programs going forward and they include improved standardization of the software development and release process, increased focus on test automation at the vehicle level, and additional quality gates and metrics for software at the vehicle level."

On the Cruise incidents, Barra said the 2024 investment plan revolves around being more deliberate and slowing the cash burn rate as it stabilizes its software efforts.

Barra said:

"We've already begun to implement significant changes to build a better Cruise. We are committed to earning back trust with our regulators and the public through our actions. Our plan for 2024 investment in Cruise reflects our more deliberate and cadence go-to-market strategy and we are developing new financial targets and a new roadmap. Spending will be down considerably this year, but we will continue to invest in the people who are advancing the software, specialized hardware, and AI capabilities. This reflects our commitment to our vision, which is to deliver the safety benefits of self-driving technology and a scalable, profitable business."

Simply put, GM seems to understand that it needs to hone its software game if it's going to transition its business model. As a result, GM will push its investor day until later in the year. "This will give our software team the time to focus on software for our upcoming launches, and we will be able to share more tangible proof points on all four pillars of our strategy, ICE, EV, AV, and software," said Barra. "When we do get together, we will show you what we've done, not just tell you what we're going to do. In the meantime, we've already provided a roadmap for EV profitability in 2025, and we'll share updates on Cruise as we finalize the technology and relaunch plans."

It remains to be seen if GM can fix its software issues before 2024 ends. A few thoughts:

Automakers are at risk of losing customer experience to Apple and Google with CarPlay and Android Auto, respectively.
A transition to EVs will mean autos are basically data centers on wheels. Software will be the primary technology driving customer experience.
However, automakers lack the consumer-facing application development experience. There's a reason a company like Tesla can deliver a better software experience than incumbents and even the EV giant can struggle.
User expectations for vehicle systems are higher.
And finally, GM will have to change its culture to improve its application development. It has moved to simplify its offerings, but large companies like GM don't turn on a dime. The pressure is on GM to improve software before the risk to its brand grows.

From our underwriter

Commercial generative AI use cases are promising, but CXOs at the Hitachi Vantara Exchange in New York note there's a lot of work ahead--data management, privacy and training models--to scale. Here's a look at the key takeaways on the use cases that can drive transformation from Hitachi Vantara Exchange in New York.

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Meta's Zuckerberg lays out AI vision with heavy dose of open source

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Meta Platforms 2023 of efficiency concluded with blowout fourth quarter earnings, a dividend and strong usage across the company's platform. But Meta CEO Mark Zuckerberg's AI ambitions may be the thing to watch in the long run.

Now it's easy to overlook Zuckerberg's ode to AI and open source. Meta’s fourth quarter revenue was $40.1 billion, up 25% from a year ago, and net income was $14.02 billion, up 200% from a year ago. The outlook was strong, and Meta will pay out its first-ever dividend. I could even find something nice to say about Meta's Reality Labs unit in that it had revenue of $1 billion in the fourth quarter (still lost $4.65 billion in the quarter).

Nevertheless, Meta's AI ambitions are clear and on par with Microsoft, Google and Amazon. Meta said 2024 capital expenditures will be $30 billion to $37 billion with a big chunk of that driven by AI-related spending. Here's a look at the AI strategy.

Meta plans to give consumers a copilot. The copilot craze has mostly been an enterprise effort, led by Microsoft, but Zuckerberg's vision was broader. He said:

"We'll be building the most popular and most advanced AI products and services. And if we succeed, everyone who uses our services will have a world-class AI assistant to help get things done, every creator will have an AI that their community can engage with, every business will have an AI that their customers can interact with to buy goods and get support, and every developer will have a state-of-the-art open-source model to build with."

You could call Meta's strategy a copilot for all play.

AI-centric devices won't be today's devices. Naturally, Zuckerberg will talk up smart glasses and Oculus, but the idea is broader. "Everyone will want a new category of computing devices that let you frictionlessly interact with AIs that can see what you see and hear what you hear, like smart glasses. And one thing that became clear to me in the last year is that this next generation of services requires building full general intelligence," he said.

AI models will have to be broad. Zuckerberg pushed back on use case specific AI products because they only do a subset of activities. Life doesn't operate in silos. "We're going to need our models to be able to reason, plan, code, remember and many other cognitive abilities in order to provide the best versions of the services that we envision. We've been working on general intelligence research and FAIR for more than a decade. But now general intelligence will be the theme of our product work as well," he said.

This AI strategy will need hyperscale infrastructure and Meta has it. "By the end of this year, we'll have about 350,000 (Nvidia) H100s, and including other GPUs, that will be around 600,000 H100 equivalents of compute. We're well positioned now because of the lessons that we learned from Reels. We initially underbuilt our GPU clusters for Reels. And when we were going through that, I decided that we should build enough capacity to support both Reels and another Reels-sized AI service that we expected to emerge so we wouldn't be in that situation again," said Zuckerberg.

Infrastructure will be critical since training and operating models are going to be more compute-intensive than today. Zuckerberg added he wasn't sure how much compute will be needed but state-of-the-art large language models have been trained on 10x the compute each year.

Zuckerberg said Meta is looking at novel data center designs as well as its own custom silicon for its workloads.

Long-term AI R&D. "While we're working on today's products and models, we're also working on the research that we need to advance for Llama 5, 6 and 7 in the coming years and beyond to develop full general intelligence," said Zuckerberg. "It's important to have a portfolio of multiyear investments in research projects, but it's also important to have clear launch vehicles like future Llama models that help focus our work."

Why Llama 2, open-source models change the LLM game

Open source is a big part of Meta's long-term AI strategy. Meta open sources its Llama models and tools like PyTorch as well as hardware designs. "Open sourcing improves our models. And because there's still significant work to turn our models into products because there will be other open-source models available anyway, we find that there are mostly advantages to being the open-source leader," said Zuckerberg.

He added that strategic benefits of open-source AI approaches include:

Security.
Compute efficiency.
Ongoing feedback and scrutiny.
Standardized approaches to hardware and software.
Developer popularity and the ability to hire talent.

Training data and feedback loops will reinforce models and general intelligence AI. Zuckerberg said:

"When people think about data, they typically think about the corpus that you might use to train a model upfront. And on Facebook and Instagram, there are hundreds of billions of publicly shared images and tens of billions of public videos, which we estimate is greater than the common crawl data set. And people share large numbers of public text posts and comments across our services as well.

But even more important in the upfront training corpus is the ability to establish the right feedback loops with hundreds of millions of people interacting with AI services across our products. And this feedback is a big part of how we've improved our AI systems so quickly with Reels and Ads, especially over the last couple of years when we had to re-architect it around new rules."

Add it up and Meta plans to infuse AI into its platform for new services. Zuckerberg said the company will even put multiple teams on the same project to test versions.

To end the AI strategy talk, Zuckerberg also noted the metaverse investment. Rest assured that the bet is that AI and the metaverse will converge at some point. "I think that people are going to want new categories of devices that seamlessly engage with AIs frequently throughout the AI without having to take out your phone and press a button and point it at what you want to see," said Zuckerberg. "I think that smart glasses are going to be a compelling form factor for this, and it's a good example of how our AI and metaverse visions are connected."

Also see: How Generative AI Has Supercharged the Future of Work | Generative AI articles | Why you need a Chief AI Officer | Software development becomes generative AI's flagship use case | Enterprises seeing savings, productivity gains from generative AI | Work in a generative AI world will need critical, creative thinking

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Apple Q1 better than expected, services strong as product lines mixed

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Apple reported better-than-expected first quarter results with revenue growth of 2%.

The company reported first quarter earnings of $2.18 a share on revenue of $119.6 billion. Wall Street was expecting Apple to report earnings of $2.10 a share on revenue of $117.9 billion.

Apple CEO Tim Cook said the company saw record services revenue in the quarter powered by iPhone sales. Cook added that "our installed base of active devices has now surpassed 2.2 billion, reaching an all-time high across all products and geographic segments."

The company will launch its Apple Vision Pro Feb. 2.

On a conference call with analysts, Cook talked up the Apple Vision Pro launch and said Apple will continue to invest in new technologies. He said:

"We're so focused on pushing technology to its limits as we work to enrich the lives of our users. As we look ahead, we will continue to invest in these and other technologies that will shape the future. That includes artificial intelligence, where we continue to spend a tremendous amount of time and effort and we're excited to share the details of our ongoing work in that space later this year."

Here's the breakdown by product line:

iPhone sales in the first quarter were $69.7 billion, up from $65.77 billion a year ago.
Mac sales were $7.78 billion, roughly flat from a year ago.
iPad sales were $7 billion, well below $9.4 billion a year ago.
Wearable revenue was $11.95 billion, down from $13.5 billion a year ago.
Servies revenue was $23.1 billion, up from $20.77 billion a year ago.

Other than the iPhone, Apple's product lines were on par with expectations or below the mark. Apple did have 13 weeks in the first quarter of fiscal 2024 compared to 14 weeks a year ago.

By geography, Apple's China sales were $20.82 billion, down from $23.9 bilion a year ago. Other geographies showed revenue gains.

Future of Work apple Chief Information Officer

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AWS Q4 revenue growth 13% as Amazon's results shine

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Amazon Web Services' fourth quarter revenue was $24.2 billion, up 13% from a year ago, and below the 30% and 26% growth rates put up by Microsoft Azure and Google Cloud, respectively.

AWS revenue was in line with expectations and fourth quarter operating income of $7.2 billion was well ahead of the $5.2 billion a year ago. AWS's operating income also outpaced the $6.5 billion for Amazon's North America e-commerce business. Amazon's AWS report comes days after both Microsoft and Google reported fourth quarter earnings.

For the fourth quarter, Amazon reported net income of $10.6 billion, or $1 a share, on revenue of $170 billion, up 14% from a year ago. Wall Street was expecting fourth quarter earnings of 80 cents a share on revenue of $166.2 billion.

Amazon reported 2023 net income of $30.4 billion, or $2.90 a share, on revenue of $574.8 billion.

In a statement, Amazon CEO Andy Jassy said:

"The regionalization of our U.S. fulfillment network led to our fastest-ever delivery speeds for Prime members while also lowering our cost to serve; AWS’s continued long-term focus on customers and feature delivery, coupled with new genAI capabilities like Bedrock, Q, and Trainium have resonated with customers and are starting to be reflected in our overall results; our Advertising services continue to improve and drive positive results; our newer businesses are progressing nicely."

For the first quarter, Amazon projected revenue of $138 billion and $143.5 billion, or 8% to 13% growth from a year ago. Operating income will be between $8 billion and $12 billion.

Jassy said AWS is also seeing indicators of strong demand ahead. Jassy said AWS is seeing more migration as enterprises start spending on cloud again. He said:

"The lion's share of cost optimization has happened. It's not that there won't be any more that we don't see any more but it just attenuated very significantly. Migrations have started to pick up again.

If you go to the generic GenAI revenue in absolute numbers, it's a pretty big number, but in the scheme of $100 billion annual revenue run rate it's still relatively small. We really believe we're going to drive 10s of billions of dollars of revenue over the next several years (with GenAI). It's encouraging how fast it's growing and our offerings really resonate with customers."

Speaking on a conference call, Jassy made the following points:

North America profit margins have approved because Amazon has retooled its network to bring goods closer to customers. This move has lowered costs to serve. "We reduced our cost to serve on a per unit basis globally. In the US cost to serve was down by more than 45 cents per unit compared to the prior year," said Jassy. "Lowering cost to serve allows us not only to invest in speed improvements, but also afford adding more selection at lower average selling prices or ASP and profitably. We have a saying it's not hard to lower prices. It's hard to be able to afford lower prices."
Advertising revenue was up 26% largely due to sponsored ads across the Amazon network.
AWS added more than $1.1 billion in incremental sequential revenue. "Our customer pipeline remains strong as existing customers are renewing it larger commitments over longer periods and migrations are growing," said Jassy.
AWS' generative AI strategy revolves around options and choices for enterprises. "We've launched Bedrock, which is off to a very strong start with many 1,000s of customers using the service after just a few months," said Jassy. "what customers have learned at this early stage of GenAI is that there's meaningful iteration required. Customers don't want only one model. They want different models for different types of applications and different size models for different applications. Customers want a service that makes this experimenting and iterating simple."
"We're building dozens of Gen AI apps across Amazon's businesses, several of which have launched and others of which are in development," he said. "GenAI is and will continue to be an area of pervasive focus and investment across Amazon primarily because there are few initiatives if any, that give us the chance to reinvent so many of our customer experiences and processes. We believe it'll ultimately drive 10s of billions of dollars of revenue for Amazon over the next several years."

AWS' quarter in review:

Data to Decisions Tech Optimization amazon SaaS PaaS IaaS Cloud Digital Transformation Disruptive Technology Enterprise IT Enterprise Acceleration Enterprise Software Next Gen Apps IoT Blockchain CRM ERP CCaaS UCaaS Collaboration Enterprise Service Chief Information Officer Chief Technology Officer Chief Information Security Officer Chief Data Officer Chief Executive Officer

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AWS Q4 revenue growth 13% as Amazon's results shine