Tech News Today, October 29, 2026: Apple, Alphabet’s $9.1B Cash Burn, Google’s Gemini 4 Carbon, Microsoft’s AI Boom, & Samsung’s Record Profits

Daily Global Technology Digest | Thursday, October 29, 2026

It’s Thursday, October 29, 2026, and the AI boom is delivering record profits, burning through billions in cash, and exposing new fault lines across the tech industry. Microsoft and Google are reporting staggering cloud revenues, Samsung is riding an unprecedented memory-chip boom, and Apple is rewriting its laptop playbook with its first touchscreen MacBook Pro. Meanwhile, cybersecurity threats are growing more sophisticated, regulators are tightening their grip, and investors are asking a question that matters more than ever: Can the AI industry’s extraordinary growth justify the enormous cost of building it?

The global technology industry is waking up to a striking contrast in the artificial intelligence economy. Alphabet reported a $9.1 billion quarterly cash outflow despite doubling Google Cloud revenue to $30.7 billion, sending its shares sharply lower after hours. Microsoft delivered a different picture, reporting $92.3 billion in quarterly revenue as Azure grew 48% and its commercial contract backlog reached $677 billion. The results offer investors two competing perspectives on the cost of building the infrastructure behind AI.

Google is also advancing the technology itself. The company introduced Gemini 4 Carbon, a new frontier model designed for complex coding, cybersecurity research, and long-running autonomous tasks. Its initial rollout is limited to selected cybersecurity defenders as Google evaluates the risks of increasingly capable AI systems.

The semiconductor industry is producing extraordinary financial results. Samsung Electronics reported approximately $80 billion in quarterly operating profit, becoming the first technology company to surpass 100 trillion Korean won in operating earnings. Yet the same demand driving record semiconductor profits is increasing costs for smartphone manufacturers, electronics companies, and businesses purchasing computing infrastructure.

The financial pressure is forcing technology companies to reconsider how they operate. Oracle has outlined a plan to generate at least $30 billion in annual free cash flow by fiscal 2029 while limiting additional capital raises. German software giant SAP is replacing expensive AI models with cheaper alternatives when they can do the same work, showing that model efficiency is becoming a key business decision.

Cybersecurity and regulation remain equally consequential. Researchers have uncovered a covert hacking framework linked to China’s Volt Typhoon group that reportedly enabled attacks using previously unknown software vulnerabilities. New York has enacted legislation restricting how AI chatbots interact with children, while cybersecurity startup Upwind has raised $400 million at a $3.8 billion valuation.

Elsewhere, the physical AI economy is expanding. Serve Robotics and DoorDash have launched autonomous food deliveries in Australia, marking Serve’s first international deployment. Space technology startup Rendezvous Robotics has raised $20 million to develop spacecraft that assemble themselves in orbit.

On the consumer side, Apple has introduced its first touchscreen MacBook Pro, marking a major change in the company’s approach to laptop design. Meanwhile, eBay is expanding AI-powered listing tools as its online marketplace reports stronger merchandise sales.

The broader picture is becoming clearer. AI development continues to generate extraordinary demand for computing, software, and capital, but investors are increasingly distinguishing between businesses that can convert that demand into profits and those still dependent on large financial commitments.

From Google’s latest AI model and Alphabet’s spending shock to record semiconductor earnings, cybersecurity threats, robotics expansion, and new technology regulations, here are today’s 15 biggest technology news stories.

Alphabet Reports $9.1 Billion Cash Burn as Google Cloud Revenue Doubles to $30.7 Billion

Google parent Alphabet reported negative free cash flow of $9.07 billion in the third quarter as heavy spending on artificial intelligence infrastructure overshadowed strong cloud growth. The company announced Wednesday that quarterly revenue increased 25% to $127.6 billion, while operating income rose 30% to $40.6 billion. Google Cloud revenue surged 103% to $30.7 billion, exceeding analysts’ expectations and reflecting strong enterprise demand for AI computing infrastructure. However, Alphabet’s cash outflow was substantially larger than Wall Street had anticipated. Its shares fell about 10% in extended trading as investors weighed the company’s financial commitments against growth in its core search advertising business. Google Search revenue increased 12%, but some investors remain concerned about how AI-powered search experiences will affect long-term advertising economics.

The results reveal a difficult financial trade-off facing the world’s largest technology companies. Alphabet generates substantial revenue from customers buying AI infrastructure and cloud services, yet expanding its computing capacity requires enormous upfront investment. The company says its proprietary Tensor Processing Units are contributing meaningfully to cloud revenue, while its Gemini application has reached one billion users. Google also reports that its first-party model APIs are processing nearly 32 billion tokens per minute, more than four times the volume recorded a year earlier. These figures demonstrate growing adoption, but they do not establish when infrastructure spending will produce sustained positive free cash flow. For investors, the challenge is determining whether Google’s rapid cloud expansion can eventually offset the costs of building and operating increasingly expensive AI systems.

Why It Matters: Alphabet’s results show that extraordinary AI revenue growth does not automatically translate into positive cash flow, increasing pressure on technology companies to demonstrate returns on infrastructure investments.

Source: Alphabet, Third Quarter 2026 Financial Results.

Microsoft Reports $92.3 Billion in Revenue as Azure Grows 48% and AI Contract Backlog Reaches $677 Billion

Microsoft reported record quarterly revenue of $92.3 billion, up 19% from a year earlier, as demand for Azure cloud services and enterprise AI products continued to strengthen. The company announced Wednesday that net income increased 32% to $36.6 billion, while operating income rose 21% to $45.9 billion. Microsoft Cloud revenue reached $63.9 billion, up 30% year over year. Azure was particularly strong, generating approximately $33.2 billion in revenue, a 48% increase from the previous year. Microsoft also disclosed that its commercial remaining performance obligations, a measure of contracted future revenue, increased 73% to $677 billion. The figure includes commitments across its commercial services and should not be interpreted entirely as revenue from AI companies. Microsoft’s results exceeded analyst expectations, with shares rising in after-hours trading.

The results provide a different perspective on AI infrastructure economics than Alphabet’s latest report. Microsoft is spending heavily on data centers and computing equipment, with quarterly capital expenditures exceeding $45 billion. However, its established enterprise software business continues generating substantial profits and recurring revenue. The company reported approximately $10 billion in revenue from OpenAI, underscoring the commercial importance of its relationship with the ChatGPT developer. Microsoft also maintains infrastructure relationships with other AI companies while expanding its own Copilot products. Its $677 billion commercial backlog provides visibility into future demand, although those commitments will be recognized as revenue over time and remain subject to contract terms. The company is also restructuring parts of its workforce, making the relationship between AI spending, productivity, and employment an increasingly important question.

Why It Matters: Microsoft’s record results demonstrate how enterprise cloud demand is translating into substantial revenue and profits, offering investors evidence that some large AI infrastructure investments are already producing commercial returns.

Source: Microsoft, Fiscal First Quarter 2027 Results — October 28, 2026

Google Launches Gemini 4 Carbon, a Frontier AI Model Built for Cybersecurity and Autonomous Coding

Google introduced Gemini 4 Carbon on Wednesday, expanding its frontier AI model family with a system designed for advanced cybersecurity research, software development, and complex autonomous tasks. The company says Carbon ranks first on version 5.0 of the Artificial Analysis Intelligence Index, achieving a score of 59. Google also reported strong performance across specialized security benchmarks, including 88.2% on SEC-bench Pro for vulnerability detection, 54.8% on ExploitGym for exploit development, and 71% on CWE-bench for software vulnerability repair. These results come from evaluations reported by Google and should not be interpreted as guarantees of equivalent performance in production environments. Carbon follows Gemini 4 Argon, introduced two weeks earlier, and is designed to handle engineering tasks that can require sustained work over multiple days.

Google is taking a restricted approach to the initial release because advanced cybersecurity capabilities can be used for legitimate defense or malicious attacks. Carbon will first become available to selected cybersecurity organizations, with access gradually expanding through Google’s Fairwind Program. The company says it is also participating in voluntary government testing before broader deployment. Its introductory API pricing will match Gemini 4 Argon at $2 per million input tokens and $10 per million output tokens. Google reports improvements in generating secure code and reducing unsupported claims, although independent evaluations will be needed to establish performance across different applications. The release intensifies competition with OpenAI and Anthropic, especially as enterprises adopt agents that can modify software, investigate vulnerabilities, and operate computer systems with limited supervision.

Why It Matters: Gemini 4 Carbon advances the market for AI-assisted cybersecurity while raising important questions about how companies should release models that can discover and exploit software vulnerabilities.

Source: Google DeepMind

Samsung Reports Record $80 Billion Quarterly Profit as AI Memory Boom Reshapes Global Semiconductor Industry

Samsung Electronics reported record third-quarter operating profit of 107.4 trillion won, approximately $80 billion, becoming the first technology company to surpass 100 trillion won in quarterly operating earnings. The South Korean electronics giant announced Thursday that revenue reached 195.3 trillion won, approximately $146 billion, up 14% from the previous quarter. Its semiconductor division generated 147.1 trillion won in revenue and 106.5 trillion won in operating profit, accounting for nearly all of the company’s earnings. Samsung attributed the results to strong demand for high-bandwidth memory, advanced server DRAM, and storage products used in AI data centers. The company also reported a substantial increase in sales of its newer HBM4 memory products as customers expanded computing infrastructure. Samsung expects AI-related semiconductor demand to remain strong through 2027, with industry supply continuing to face constraints.

The results demonstrate how AI investment is changing the economics of semiconductor manufacturing. Demand for specialized memory has increased prices and strengthened profit margins for major suppliers. However, the same pricing environment is creating difficulties for Samsung’s consumer electronics businesses. Its Device eXperience division, which includes smartphones and other consumer products, reported an operating loss of 0.8 trillion won despite higher revenue. The contrast illustrates how higher component costs can benefit semiconductor manufacturers while reducing profitability elsewhere in the electronics supply chain. Samsung plans to increase production of advanced memory products, including high-bandwidth memory and server storage. However, manufacturing expansion requires substantial capital, and investors remain concerned that the semiconductor industry could experience another downturn if AI infrastructure spending eventually slows.

Why It Matters: Samsung’s record profits demonstrate the financial importance of AI memory chips while revealing how semiconductor shortages and rising prices can hurt consumer electronics manufacturers.

Source: Samsung Electronics

Oracle Targets $225 Billion in Annual Revenue by 2030 and Promises to Limit Additional AI Financing to $20 Billion

Oracle has outlined an ambitious financial plan projecting annual revenue above $225 billion by fiscal 2030 while limiting additional capital-market financing to $20 billion. The company presented the outlook Wednesday during its investor day in Las Vegas. Oracle expects revenue to grow at a compound annual rate exceeding 35% from fiscal 2026 through fiscal 2030. Management also projected adjusted operating margins of at least 40% and adjusted earnings of more than $21 per share by fiscal 2030. More immediately, Oracle expects free cash flow to turn positive during the second half of fiscal 2028 and reach at least $30 billion in fiscal 2029. The company plans to limit additional fundraising through fiscal 2030 to approximately $10 billion in equity and $10 billion in debt, excluding refinancing of existing obligations. These figures are management forecasts, not guaranteed financial outcomes.

The announcement is significant because Oracle has become one of the largest infrastructure providers supporting the expansion of frontier AI companies. Building new computing facilities requires substantial spending on processors, power systems, networking equipment, and construction. Oracle has relied on a combination of debt, equity financing, customer commitments, and partnerships to support that expansion. Its revised financial plan is intended to address investor concerns about whether those commitments can eventually generate enough cash to finance continued growth. Management expects capital spending to peak during fiscal 2027 and 2028 before declining. However, achieving the forecast will depend on delivering planned data-center capacity, obtaining sufficient electricity, meeting construction schedules, and maintaining customer demand. Oracle’s financial outlook will test whether the current AI infrastructure boom can become self-sustaining.

Why It Matters: Oracle’s financial targets show how AI infrastructure companies are responding to investor concerns by emphasizing cash flow, financing discipline, and long-term profitability.

Source: Oracle Corporation

SAP Replaces Expensive AI Models With Cheaper Alternatives as Enterprise Software Giant Targets €2 Billion in Efficiency Gains

German enterprise software company SAP is increasingly replacing expensive artificial intelligence models with lower-cost alternatives when they can perform the same tasks effectively. Chief Financial Officer Dominik Asam told Reuters on Wednesday that SAP selects models based on the requirements and economics of individual applications rather than automatically using the most capable available system. The company currently works with more than 70 models from providers including OpenAI, Anthropic, and Google. SAP expects AI-related operational improvements to generate more than €2 billion in efficiency gains, although those savings are not attributable exclusively to switching models. The company also expects overall AI spending to increase as customer adoption expands. Its objective is to improve the economics of delivering AI services while maintaining healthy margins.

The approach illustrates an important change in the enterprise AI market. Businesses deploying thousands or millions of automated tasks must consider cost per completed task alongside model accuracy, speed, security, and reliability. A smaller or cheaper model may suffice for routine activities such as document classification, information extraction, or responding to straightforward business requests. More demanding tasks may still require expensive frontier systems. SAP’s commercial model makes those distinctions particularly important because customers increasingly pay for completed business activities rather than the underlying computing resources. The company is also encountering growing interest from European governments and regulated industries in locally governed AI services. For startups developing specialized models, the shift creates opportunities to compete with larger providers on cost and performance within narrowly defined applications.

Why It Matters: SAP’s strategy demonstrates that enterprise AI competition is increasingly shifting from model capability alone to the cost, reliability, and efficiency of completing business tasks.

Source: Reuters

Marvell Reportedly in Advanced Talks to Acquire $83 Billion Optical Networking Company Lumentum

Semiconductor company Marvell Technology is reportedly in advanced discussions to acquire Lumentum Holdings, a major supplier of optical components used in data centers and communications networks. Bloomberg first reported the discussions Wednesday, and Reuters later confirmed details through a source familiar with the matter. Lumentum had a market capitalization of approximately $83 billion when the talks became public, suggesting that a transaction could rank among the largest acquisitions in semiconductor industry history. Neither company has announced an agreement, and discussions could end without a transaction. After the reports, Lumentum shares rose about 9% in extended trading, while Marvell shares fell more than 8%. Investors appeared concerned about the financial requirements and potential integration risks associated with a purchase of that scale.

The reported acquisition reflects the growing importance of optical networking in AI infrastructure. Advanced computing systems need to move enormous amounts of information between processors, servers, and data centers. Optical technologies use light to transmit data and can support faster communications over longer distances than conventional electrical connections. Lumentum develops optical components used in those systems, while Marvell supplies networking semiconductors and custom AI processors. Combining their capabilities could give Marvell greater control over important parts of the AI computing supply chain. However, financing such a large acquisition would be challenging, particularly given Lumentum’s valuation. Marvell previously announced a $3.25 billion acquisition of photonics company Celestial AI, demonstrating its interest in optical computing technology. Recent discussions suggest that competition in AI hardware is expanding beyond processors into the networking infrastructure that connects them.

Why It Matters: A potential Marvell-Lumentum combination could reshape the optical networking market as AI data centers demand faster, more efficient connections between computing systems.

Source: Bloomberg

Apple Unveils First Touchscreen MacBook Pro With PROLED XDR Display, Starting at $2,899

Apple introduced its first touchscreen MacBook Pro on Wednesday, reversing a longstanding approach that kept touch interactions largely separate from its Mac laptop lineup. The redesigned computer features a tandem OLED display marketed as PROLED XDR, with up to 2,000 nits of peak brightness, a 120Hz variable refresh rate, and a claimed contrast ratio of 10,000,000:1. The new design also brings Dynamic Island to the Mac, along with support for touch gestures, improved color accuracy, and up to 24 hours of battery life under Apple’s testing conditions. Prices begin at $2,899 for the 14-inch model and $3,399 for the 16-inch version. Preorders opened October 28, with availability scheduled for November 6.

The announcement marks a notable shift in Apple’s hardware strategy. For years, the company argued that laptops and tablets served different purposes, favoring the Mac’s keyboard and trackpad while developing touch-first interfaces for the iPad. The new MacBook Pro combines traditional desktop controls with direct screen interaction, potentially changing how developers design professional applications. Apple says existing software can interpret touches as clicks, while updated system interfaces will allow developers to build more specialized touch experiences. Applications involving graphic design, video editing, music production, and 3D modeling could benefit from direct manipulation. However, the premium pricing means the devices will initially target professional users rather than the broader laptop market. Competing Windows manufacturers already offer touchscreen notebooks across multiple price categories, making Apple’s software integration and display technology important differentiators.

Why It Matters: Apple’s first touchscreen MacBook Pro signals a major change in laptop design strategy and could encourage developers to create more touch-enabled professional software.

Source: TechStartups via Apple Newsroom

New York Enacts AI Chatbot Safety Law Restricting Emotional Relationships and Harmful Content for Children

New York Governor Kathy Hochul signed legislation Wednesday restricting how artificial intelligence chatbots interact with users under 18. The law prohibits covered chatbots from presenting themselves as real people with human emotions or relationships and restricts behavior that could encourage self-harm, secrecy, unhealthy dependency, or other potentially dangerous interactions. Developers must verify users’ ages through approved methods, including an option that does not depend exclusively on government identification. The New York attorney general will have authority to investigate violations and seek penalties of up to $25,000 per violation, alongside additional remedies. The state also enacted separate security requirements for internet-connected baby monitors. Supporters argue that the chatbot restrictions address growing concerns about emotionally persuasive AI systems used by children.

The legislation represents a shift in how governments approach AI safety. Earlier rules often emphasized disclosure requirements, encouraging companies to remind users that they were interacting with software. New York is moving further by restricting specific chatbot behaviors and product features. Child safety organizations have welcomed the decision, arguing that conversational AI systems can create risks when they simulate intimate relationships or provide inappropriate responses to vulnerable users. Technology industry representatives, including Tech:NYC, have raised concerns about the law’s broad language and potential constitutional implications. Developers may also struggle to determine when ordinary conversational behavior crosses a prohibited boundary. The law arrives as states introduce different AI requirements in the absence of comprehensive federal legislation. For startups developing consumer chatbots, compliance could increasingly depend on the jurisdictions where they offer products.

Why It Matters: New York’s legislation could establish an influential precedent for regulating AI chatbot behavior, particularly when products are used by children and teenagers.

Source: Associated Press.

Researchers Link China’s Volt Typhoon Hackers to Four Zero-Day Campaigns Using Covert Silent Train Network

Cybersecurity researchers at Lumen Technologies have uncovered a covert infrastructure system used by the China-linked hacking group Volt Typhoon to conceal attacks against high-value organizations. The system, called Silent Train, uses rapidly changing chains of compromised routers, networking equipment, and other connected devices to hide the origin of malicious activity. Lumen’s Black Lotus Labs reported Wednesday that it had tracked the framework for approximately three years and identified at least four confirmed campaigns involving previously unknown software vulnerabilities. The activity targeted centralized management platforms used by telecommunications companies, government organizations, defense contractors, and other critical infrastructure operators. Researchers also identified a fifth campaign involving a suspected zero-day vulnerability. The findings are based on Lumen’s security observations, and the company has not publicly identified every affected organization.

Silent Train is particularly concerning because it targets systems with broad administrative access. Compromising a network management platform could give attackers control over connected devices and access to downstream customers. According to Black Lotus Labs, the attackers assembled temporary chains of compromised infrastructure, conducted operations, and removed evidence before moving to new systems. Some sessions lasted only a few hours, limiting opportunities for conventional monitoring systems to detect the activity. The researchers say the framework helped Volt Typhoon maintain access while avoiding established methods for identifying malicious infrastructure. Organizations are being advised to restrict public access to administrative interfaces, update vulnerable software, monitor unusual authentication activity, and preserve security logs. The findings reinforce concerns about attacks against communications and infrastructure systems that could become strategically important during international crises.

Why It Matters: The Silent Train investigation reveals how sophisticated attackers can exploit centralized network management systems while using compromised devices to conceal their operations.

Source: Lumen Technologies, Black Lotus Labs.

Cybersecurity Startup Upwind Raises $400 Million at $3.8 Billion Valuation as Demand for AI Security Surges

Cloud cybersecurity startup Upwind has raised $400 million in Series C funding at a $3.8 billion valuation, becoming one of the latest security companies to attract substantial investment amid growing enterprise AI adoption. Bessemer Venture Partners led the financing, with participation from Canapi Ventures and existing investors including Greylock Partners, Cyberstarts, Craft Ventures, Salesforce Ventures, and TCV. Upwind announced Wednesday that its revenue had quadrupled during 2026, although the company did not disclose audited financial results or a complete revenue breakdown. The new valuation represents a substantial increase from the $1.5 billion figure attached to its Series B financing in January. Founded in 2022, Upwind develops software that monitors cloud infrastructure, applications, APIs, and AI agents to identify security weaknesses and suspicious activity.

The financing highlights growing investor interest in cybersecurity platforms that can monitor increasingly complicated cloud environments. Traditional security tools often identify vulnerabilities through periodic scans, generating alerts that require engineers to determine whether a particular weakness can actually be exploited. Upwind adds context by monitoring active systems and examining how applications, data, and automated agents interact. The company also offers AI-assisted tools to investigate threats and recommend corrective actions. Customers named by Upwind include Siemens, Roku, Carvana, Nubank, and other enterprises operating substantial cloud infrastructure. The startup says its software supports major cloud platforms including AWS, Azure, Google Cloud, and Oracle Cloud Infrastructure. The new funding will support engineering and commercial expansion. However, Upwind must still demonstrate that its growth can support its valuation while competing with established security vendors and other heavily funded startups.

Why It Matters: Upwind’s financing demonstrates how the growth of autonomous AI and cloud infrastructure is creating demand for cybersecurity platforms that can monitor live systems and prioritize meaningful threats.

Source: TechStartups via Upwind Security

Serve Robotics and DoorDash Launch Autonomous Food Delivery in Australia, Marking First International Expansion

Serve Robotics has launched its autonomous sidewalk delivery service in Australia through a partnership with DoorDash, marking the company’s first commercial expansion outside the United States. The companies announced the rollout Wednesday, with operations beginning in Queensland’s Gold Coast Health and Knowledge Precinct. Customers ordering through DoorDash can choose robot delivery when participating restaurants offer the option. The initial deployment includes a limited number of restaurant partners, with additional businesses expected to join during the coming weeks. Serve plans to invest approximately $500,000 in the region over the next year. The company has established an operations depot at Griffith University for charging, maintenance, and robot dispatch. The Australian launch builds on Serve’s existing American operations, where it reports deploying more than 2,000 delivery robots across over 40 cities.

The expansion tests whether autonomous delivery systems can operate successfully across different countries and regulatory environments. Sidewalk robots must navigate pedestrians, crossings, changing weather conditions, and local accessibility requirements. Serve’s machines travel at walking speed and can receive assistance from remote supervisors when necessary. Unlike traditional courier services, robot delivery depends on relatively short routes and neighborhoods with suitable pedestrian infrastructure. That limits potential deployment areas but could make the technology economically attractive for certain types of restaurant orders. DoorDash and Serve will also need to demonstrate that the robots can operate reliably while providing a convenient customer experience. The partnership reflects growing competition to automate last-mile delivery, an expensive part of logistics operations where labor, transportation, and customer expectations can significantly affect profitability.

Why It Matters: Serve’s Australian expansion provides an international test of autonomous delivery economics and demonstrates how robotics companies are moving beyond domestic pilot programs.

Source: Reuters.

Space Startup Rendezvous Robotics Raises $20 Million to Build Spacecraft That Assemble Themselves in Orbit

Colorado-based space technology startup Rendezvous Robotics has raised $20 million in seed funding to develop modular spacecraft that can autonomously assemble and reconfigure themselves after reaching orbit. MaC Venture Capital and Toyota Ventures led the financing, with participation from the University of Michigan Endowment, Astera, Industrious Ventures, and other investors. The company announced Wednesday that it is preparing a 2028 demonstration mission involving seven independent spacecraft modules. Under the proposed mission, the modules will maneuver into position, connect to form a larger spacecraft, separate, and assemble again in a different configuration. The technology builds on earlier research involving TESSERAE, a modular spacecraft assembly concept developed at MIT and advanced through the Aurelia Institute. Previous experimental versions have flown on Blue Origin’s New Shepard vehicle and missions involving the International Space Station.

The approach challenges a longstanding constraint in spacecraft engineering: satellites must be designed to fit inside the available space of a launch vehicle. That limitation affects antenna size, solar power capacity, thermal systems, and how much computing equipment can be installed. Rendezvous Robotics wants to launch smaller modules that connect after deployment, potentially allowing spacecraft to expand or adapt to new missions. The technology could eventually support larger communications platforms, scientific instruments, and other orbital infrastructure. However, autonomous assembly in space presents significant technical challenges involving navigation, precise alignment, mechanical connections, and long-term reliability. The company has not yet demonstrated its planned commercial architecture in orbit. The new capital will support spacecraft development, flight testing, and engineering expansion ahead of its targeted 2028 mission.

Why It Matters: Rendezvous Robotics’ financing highlights growing investment in technologies that could make spacecraft more adaptable and reduce constraints imposed by conventional launch vehicle designs.

Source: Rendezvous Robotics

ServiceNow Raises AI Contract Revenue Target to $1.7 Billion Despite 18% Stock Selloff

Enterprise software company ServiceNow raised its 2026 AI annual contract value target to $1.7 billion after reporting stronger third-quarter subscription revenue, even as investors reacted negatively to its earnings outlook. The company announced Wednesday that total revenue reached $4.106 billion, up 20.5% year over year. Subscription revenue increased 21% to $3.988 billion, while current remaining performance obligations reached $13.65 billion, also growing more than 20%. ServiceNow increased its full-year AI contract target from $1.5 billion, citing stronger customer demand for automated workflows and AI-assisted enterprise applications. However, adjusted earnings of $1 per share fell short of analysts’ expectations of approximately $1.02. The company’s shares fell about 18% in extended trading as investors weighed its outlook for future subscription growth.

The results demonstrate the complicated economics of enterprise AI adoption. ServiceNow is benefiting from businesses seeking tools that automate customer service, IT operations, employee workflows, and other administrative functions. Its software increasingly incorporates AI agents that can coordinate tasks across business applications. However, strong demand for AI products does not necessarily guarantee that overall subscription growth will accelerate at the same pace. Investors are also weighing the costs of acquisitions and product expansion. ServiceNow’s recent transactions have included security and AI software businesses intended to broaden its enterprise platform. Management says internal AI adoption is generating substantial productivity benefits, but those figures remain company estimates. For enterprise software startups, the results suggest that customers are willing to pay for AI applications tied to practical workflows, while investors are becoming more demanding about revenue growth and profitability.

Why It Matters: ServiceNow’s results show that enterprise AI demand is growing, but software companies still face pressure to demonstrate consistent revenue growth and attractive financial returns.

Source: ServiceNow, Third Quarter 2026 Financial Results — October 28, 2026

eBay Reports $23.2 Billion in Quarterly Merchandise Sales as AI-Powered Listing Tools Expand Across Six Countries

Online marketplace eBay reported stronger third-quarter results Wednesday as merchandise sales increased and the company expanded AI-powered tools designed to simplify selling. Revenue rose 14% to approximately $3.2 billion, while gross merchandise volume increased 15% to $23.2 billion. The company reported GAAP earnings of $1.11 per diluted share and adjusted earnings of $1.51. eBay also expanded its Magical Listing technology to new and returning sellers in six countries: the United States, United Kingdom, Germany, Australia, France, and Italy. The feature uses AI to help sellers create product listings with less manual effort. Meanwhile, eBay Live continued expanding as the company developed additional tools for interactive shopping, including AI-assisted moderation of video, audio, and chat activity.

The results illustrate how established e-commerce platforms are using AI to improve specific parts of the buying and selling experience. Creating product listings can be time-consuming, especially for individuals selling used goods or operating small businesses without dedicated merchandising teams. Automated tools can help generate descriptions, organize product information, and simplify listing workflows. However, listing accuracy remains important because incorrect descriptions can create disputes, returns, and customer dissatisfaction. eBay is also investing in recommerce, the market for used and refurbished products, as consumers look for alternatives to buying new merchandise. The company expects gross merchandise volume to grow between 12% and 14% in the fourth quarter. For smaller e-commerce startups, eBay’s expansion demonstrates how AI capabilities are becoming part of established marketplace infrastructure, increasing pressure to compete through specialized services, stronger customer relationships, and differentiated shopping experiences.

Why It Matters: eBay’s results demonstrate how AI is becoming an operational tool for online commerce, helping marketplaces reduce friction for sellers while supporting broader merchandise growth.

Source: eBay, Third Quarter 2026 Financial Results