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Meta Platforms has been spending too aggressively on artificial intelligence (AI) infrastructure and that will affect the tech giant’s profitability, according to a new investor note from Wall Street analyst firm MoffettNathanson. The note, published on Tuesday, points out that Metas stock price (Nasdaq: META) has fallen almost 20% over the past month or so, exacerbated by its most recent earnings results, which were released on October 29. MoffettNathanson has been a staunch defender of the Facebook and Instagram parent company, even when its shares have dipped in the past. But on Tuesday, analysts at the firm wrote, we were obviously too complacent in our investment advice.” Why is Meta spending so much on AI? Meta along with fellow Big Tech firms including Amazon, Microsoft, and Google parent company Alphabet are in a high-stakes race to build out infrastructure and invest in the talent they see as necessary to compete in a world being transformed by generative AI. However, investors and many experts have expressed concerns that we may be in an AI bubble similar to the one seen during the dotcom era. So the question is whether these investments will pay off in the long run. To be crystal clear, we feel that this time is different and that defending the stock even at this level is harder because of the ramping of the massive incremental bet that Meta, without a cloud business or pre-existing enterprise assets, has been making in building out a Meta Superintelligence business, the note says. Given the outlook, the issue from here is that even with strong top-line expectations, Q4 and 2026 margins will likely compress. In other words, MoffettNathansons team feels that Meta is overspending on AI, and it could come back to bite investors. Despite the relatively harsh words, the firm still rates Meta’s stock as a buy, though it has adjusted its price target, dropping it from $875 to $750. window.addEventListener("message",function(a){if(void 0!==a.data["datawrapper-height"]){var e=document.querySelectorAll("iframe");for(var t in a.data["datawrapper-height"])for(var r,i=0;r=e[i];i++)if(r.contentWindow===a.source){var d=a.data["datawrapper-height"][t]+"px";r.style.height=d}}}); Meta, and much of tech overall, has significantly increased its capital expenditures in the wake of the AI revolution. But according to the note, Meta is “trying to punch above its weight” when compared to its peers. Although the company is spending a similar amount on AI infrastructure, it does not have a cloud platform like Microsoft, Alphabet, and Amazon, the analysts point out. MoffettNathanson projects that Meta’s capex-to-revenue ratio will hit 47% next year. By comparison, Microsofts is 29%, Alphabets is 26%, and Amazons is 16%, MoffettNathanson estimates. Meta lacks a comparable coherent pathway for monetizing GenAI directly, the firm says. Shares of Meta are trending downward this week along with the tech-heavy Nasdaq Composite as investors await tomorrow’s highly anticipated earnings report from AI chip giant Nvidia. Meta shares are down roughly 2% year to date.
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E-Commerce
At Microsofts Ignite conference on November 18, the company unveiled new AI-powered software features designed to make coders lives easierincluding a tool to automatically fix security issues as new vulnerabilities are discovered. Over this past year, the nature of being a software engineer has really started to change, says Amanda Silver, corporate vice president and head of product for apps and agents at Microsoft. And our focus has been on tackling the most miserable, soul-draining parts of the job and really transforming them, so that developers can kind of bring joy back to their day-to-day lives. One result of that effort is an AI offering, now in public preview, that combines the runtime application protection of Microsoft Defender for Cloud with GitHub Advanced Securitys protection for source code to spot and help fix a variety of security vulnerabilities. When Microsoft Defender for Cloud detects that an app on the Microsoft Azure cloud system has a security issue, perhaps based on information from a published vulnerability report, that knowledge can be channeled into Microsoft-owned GitHub, to help set up what’s called a security campaign. Thats a GitHub feature designed for a coordinated effort to tackle security holes. Once its set up, GitHubs AI Copilot Autofix tool can automatically suggest code changes to address the issue. The developer doesn’t have to write the code to respond to the issue, Silver says. Rather, GitHub Copilot actually issues the pull request, and the developer just has to review and accept it. Even when the problem is caused by a security flaw in third-party code, like an open-source library, Copilot can help in upgrading to a later edition of the library without the bug and help with code changes required for compatibility with the new version. The announcement follows the May debut of Azure SRE Agent, another AI tool designed to spot and help analyze certain security issues and other problems, assisting engineers in quickly finding and fixing the causes of incidents affecting cloud systems. Its one of a number of AI tools recently released by various companies that can flag problems and help engineers comb through the often-voluminous log files generated by applications, operating systems, and other software to understand the root cause, ideally before an issue becomes urgent. Nobody joined the industry because they want to be woken up in the middle of the night because they’re on a live site incident call, says Silver. And for developers building software designed to itself integrate with artificial intelligence to process data or answer user questions, deciding which AI model is best suited for a particular task can be a complex question, particularly when considering factors like speed and cost as well as accuracy. To help address that challenge, Microsoft also on November 18 unveiled what it calls the Model Router in Azure AI Foundry, which automatically dispatches particular AI prompts to an appropriate model in real time as an app runs. Smaller (and cheaper) models can be used when theyll likely do the trick, while bigger and more costly models can be used for more complex scenarios, with reasoning models invoked for tasks requiring their skills. Microsoft has also been working on ways to help businesses upgrade aging code and move older applications to the cloud. Its another notoriously tedious task that AI programming assistants like GitHub Copilot can help automate. Internally, Microsoft reports, units including the Xbox team have used GitHub Copilot to help modernize code, at times dramatically cutting the developer effort required. And a new offering also unveiled November 18, called Managed Instance on Azure App Service, makes it easier for developers to move code to the cloud with fewer tweaks in the first place, by providing closer compatibility with older Microsoft software. That, along with AI help in ultimately making further upgrades, should help stave off burnout as developers dodge the tedious tasks of getting aging code to run on todays cloud systems, Silver says. No engineer really joined the industry to get assigned a months-long refactoring job of doing thankless migration work, Silver says. That’s the kind of developer toil that really quietly drains morale, and it burns out great teams and great engineers.
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E-Commerce
Growth in U.S. markets helped Swedish fintech firm Klarna to achieve a 26% jump in third-quarter revenue, beating expectations in its first report as a public company and forecasting revenue above $1 billion in the current quarter, the company said on Tuesday. The buy now, pay later lender, which went public in September in New York, reported revenue of $903 million, beating analysts’ expectations of $882 million, according to data compiled by LSEG. “To a large degree, AI is accelerating our ability to ship new features and products,” CEO Sebastian Siemiatkowski told Reuters. Klarna had been an early adopter of AI and used the technology to help customers and merchants cut jobs, create marketing campaigns, and improve products. However, Siemiatkowski expressed some nervousness about the huge spending on building data centres. While there will be an uptick in demand for AI in both the consumer space and enterprises, there will be more compression of data in businesses, hitting future compute demand, he said. Tech companies have announced massive spending plans this year for building data centres as they expect AI to fuel demand. Klarna’s gross merchandise volume (GMV), a commonly used e-commerce metric for measuring sales, rose 23% to $32.7 billion in the quarter. In the U.S., Klarnas largest market, GMV grew 43% and revenue rose 51%. Active customers rose 32% to 114 million from a year ago. The company, however, reported a net loss of $95 million, compared with a profit of $12 million in the year-ago period, which it said was partly due to a shift to U.S. accounting principles following its New York listing. In the current quarter, the company expects revenue of $1.07 billion, compared with expectations of $1.06 billion. Supantha Mukherjee, Reuters
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E-Commerce
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