The artificial intelligence investment frenzy is increasingly shifting away from the companies building large language models and toward the firms supplying the infrastructure that allows those models to operate at scale.

That trend was underscored this week when California-based AI startup Baseten announced a $1.5 billion funding round that values the company at $13 billion, one of the largest private funding deals in the AI infrastructure sector this year.

The round was led by Sands Capital and Wellington Management, while Australian venture capital giant Blackbird VC participated with what it described as the largest investment in its history. Although Blackbird did not disclose the amount invested, the firm said the deal represents its biggest financial commitment to date.

The financing highlights the enormous investor appetite for companies positioned in the less glamorous but increasingly critical layer of the AI ecosystem: inference infrastructure. While firms such as OpenAI, Anthropic, and Google have attracted attention for developing advanced AI models, a growing number of investors are focusing on the infrastructure providers that help enterprises deploy, customize, and run those models efficiently.

Baseten sells software and computing infrastructure that enables companies to build and deploy customized AI applications. Rather than creating foundational models itself, the company provides the tools that allow businesses to operationalize AI systems, often at lower costs than relying directly on major model providers.

That positioning appears to be resonating strongly with customers.

Baseten said revenue has increased 20-fold over the past year, driven largely by surging demand for inference services. Inference refers to the stage where trained AI models are put into real-world use, generating responses, recommendations, images, code, or other outputs for customers.

The distinction is becoming increasingly important across the AI industry. Training frontier AI models requires enormous computing resources and billions of dollars in investment. However, many analysts believe inference could ultimately become the larger market because every AI interaction, query, and application depends on inference infrastructure after a model has been trained.

As enterprises increasingly embed AI into products, workflows, and customer services, demand for efficient inference platforms is expected to rise sharply.

Baseten’s latest fundraising is its fourth capital raise in just 18 months, reflecting how rapidly investors are pouring money into infrastructure providers that support the commercialization of generative AI.

“It’s a signal of conviction,” Blackbird partner Michael Tolo said, explaining the firm’s decision to deepen its investment.

Tolo argued that the economics of AI deployment are beginning to change in ways that favor infrastructure specialists.

“For companies building AI into their tech systems, Baseten competes with companies like OpenAI and Anthropic at a lower price, and this is the biggest shift that we’ve seen in both unit economics and competitive leverage within the AI market so far,” he said.

However, enterprises are becoming increasingly sensitive to costs associated with running AI workloads as competition intensifies. While foundation model providers have spent heavily building cutting-edge systems, a parallel race has emerged among infrastructure companies seeking to reduce deployment costs and improve performance.

Investors now see that layer of the market as potentially more durable and profitable than model development itself.

The funding round also bolsters a wider investment narrative that has dominated technology markets over the past two years. Much of the capital flowing into AI has focused on the infrastructure stack rather than end-user applications. Chipmakers, cloud providers, data center operators, networking companies, and inference platforms have attracted massive valuations as investors bet they will benefit regardless of which AI models ultimately dominate the market.

The strategy mirrors previous technology cycles where infrastructure providers often emerged as some of the biggest winners. During the internet boom, for example, companies supplying networking equipment, cloud infrastructure, and software platforms frequently generated more sustainable returns than many consumer-facing startups.

Baseten now joins a growing list of AI infrastructure firms attracting multibillion-dollar valuations as investors take positions for what many believe will be years of rising enterprise AI adoption. The company said it plans to use the new capital to expand computing capacity, enhance its software platform, and hire additional staff.

The fundraising also highlights Australia’s growing footprint in the global AI ecosystem. Baseten was co-founded by Australians, while Blackbird’s participation demonstrates how local venture capital firms are increasingly gaining exposure to some of Silicon Valley’s most valuable private technology companies.

Oracle has reduced its workforce by about 21,000 employees over the past year, underscoring how artificial intelligence and an aggressive push into cloud infrastructure are reshaping one of the world’s largest enterprise software companies.

The workforce reduction, disclosed in Oracle’s latest annual report, comes as the company embarks on one of the most ambitious expansion plans in its history, pouring tens of billions of dollars into AI-related infrastructure while simultaneously restructuring operations to improve efficiency and competitiveness.

The filing shows Oracle employed 141,000 people as of May 31, 2026, down from roughly 162,000 a year earlier, representing a 13% decline in headcount. The reduction follows reports earlier this year that the company was cutting thousands of positions across multiple business units.

The scale of the restructuring is reflected in Oracle’s spending. The company incurred $1.84 billion in severance payments and other exit-related costs during fiscal 2026, nearly five times the $374 million spent in the previous fiscal year.

According to the filing, the workforce adjustments were driven by a combination of factors, including management changes, product realignments, performance-related decisions, acquisitions, and broader strategic shifts. While Oracle did not explicitly attribute the job reductions solely to artificial intelligence, the restructuring coincides with growing adoption of AI tools across the technology sector, where companies are increasingly automating functions previously handled by employees.

The cuts also come at a time when concerns about AI-driven displacement are intensifying. Data from Layoffs.fyi shows that 196 technology companies have eliminated more than 119,800 jobs so far this year, highlighting a broader industry trend toward leaner operations as businesses invest heavily in artificial intelligence.

Oracle’s workforce reduction comes off a paradox unfolding across the technology industry. Companies are spending unprecedented sums on AI infrastructure while simultaneously seeking efficiencies that often result in smaller workforces.

The transformation thus marks a dramatic evolution from its traditional identity as a database and enterprise software provider. For years, Oracle lagged behind larger cloud rivals such as Amazon and Microsoft in the race for cloud computing dominance. The AI boom, however, has created an opportunity for Oracle to reposition itself as a critical supplier of computing infrastructure.

Over the past several months, Oracle has secured major data-center agreements with OpenAI and Meta, deals that have elevated the company’s standing in the AI ecosystem and generated optimism about future growth. The challenge is that Oracle lacks the financial flexibility enjoyed by some of its larger competitors. Unlike Microsoft and Amazon, which can fund massive infrastructure projects through enormous operating cash flows, Oracle has increasingly relied on debt issuance and external financing to support its expansion strategy.

That financing challenge is becoming more pronounced as spending accelerates.

Earlier this month, Oracle revealed plans to invest approximately $70 billion in net capital expenditures during its current fiscal year, one of the largest spending programs in corporate America. The investment is primarily aimed at expanding data-center capacity and supporting growing demand for AI workloads. To finance that spending, Oracle said it plans to raise an additional $40 billion through debt and equity markets, including a previously announced $20 billion stock offering.

The scale of those commitments is increasingly reshaping the technology industry. Success now depends much on the ability to build massive data centers filled with expensive chips and networking equipment, creating enormous capital requirements even for established technology firms.

Investors have responded cautiously. Oracle shares have fallen about 10% this year as markets weigh the company’s long-term AI opportunity against the risks associated with its aggressive spending and rising debt burden.

The workforce reduction can therefore be viewed not simply as a cost-cutting exercise but as part of a broader effort to redirect resources toward AI infrastructure and cloud growth.

In many respects, Oracle’s strategy mirrors a wider shift occurring throughout Silicon Valley. Technology companies are reallocating capital away from traditional business functions and toward AI development, data centers, and computing capacity. That transition is generating demand for engineers, data-center specialists, and AI researchers while reducing demand in other areas.

The development also adds to a growing debate about whether AI will ultimately create more jobs than it eliminates. While technology executives frequently argue that artificial intelligence will unlock new industries and employment opportunities, current trends suggest the transition may involve significant workforce disruption before those benefits materialize.

For Oracle, the restructuring represents a high-stakes bet on the future of AI infrastructure. The company is attempting to transform itself from a legacy software giant into a major player in the artificial intelligence era. But the workforce cuts indicate that Oracle is willing to make difficult adjustments to pursue that goal. They also provide another signal that the AI revolution is no longer just changing technology products—it is fundamentally reshaping how technology companies are structured, financed, and staffed.