Sam Altman testified Tuesday that Elon Musk abandoned OpenAI during a crucial period in the company’s development, rejecting Musk’s claims that OpenAI improperly transformed itself away from its nonprofit mission.

Speaking for roughly four hours in federal court in Oakland, California, Altman told jurors that Musk failed to follow through on commitments to support the company financially as OpenAI struggled to secure the computing resources needed to compete in artificial intelligence research.

“We were kind of left for dead,” Altman testified.

Musk sued OpenAI, Altman, and OpenAI President Greg Brockman in 2024, alleging the company violated its founding principles by shifting toward commercial operations and pursuing profits rather than operating solely for charitable purposes. Musk argues that the roughly $38 million he contributed to OpenAI was used for unauthorized commercial expansion.

Altman disputed that claim in court, saying he never promised Musk that OpenAI would permanently maintain a nonprofit-only structure.

Much of the trial has focused on internal negotiations in 2017 and 2018 involving Altman, Musk, Brockman, and co-founder Ilya Sutskever over how to finance increasingly expensive AI development. According to testimony, OpenAI leaders debated several possible corporate structures, including for-profit models, as they sought billions of dollars in computing and infrastructure funding.

Those discussions ultimately collapsed, and Musk left OpenAI’s board in February 2018.

Altman testified that Musk’s departure created uncertainty inside OpenAI, with employees worrying about how the organization would survive financially. He also said some researchers viewed Musk’s exit as a morale improvement due to dissatisfaction with his management style.

“I don’t think Mr. Musk understood how to run a good research lab,” Altman told the court.

Court filings and testimony also revealed that Musk continued corresponding with OpenAI leadership after leaving the board. In one 2018 email presented during testimony, Musk wrote that OpenAI had “0%” chance of competing with Google DeepMind without dramatically increasing resources and spending billions annually.

Altman said the message remained “burned into my memory.”

OpenAI’s Origins Face Unprecedented Scrutiny

The trial has become one of the most consequential legal disputes in the AI industry because it directly examines how OpenAI evolved from a nonprofit research lab into one of the world’s most valuable private technology companies.

Musk argues OpenAI abandoned its original public-interest mission in favor of commercial expansion tied closely to Microsoft and large-scale investor funding. OpenAI has countered that evolving its structure was necessary to finance advanced AI development and compete against heavily funded rivals.

Testimony from current and former executives has exposed years of internal disagreements over governance, funding, safety priorities, and control of increasingly powerful AI systems.

Earlier in the trial, Sutskever testified that he had previously gathered evidence alleging Altman showed a “consistent pattern of lying” before Altman’s temporary removal as CEO in 2023. The court also heard testimony about previously undisclosed discussions involving a potential merger between OpenAI and rival Anthropic after Altman’s brief ouster.

AI Governance and Corporate Control Move into Public View

Beyond the personal conflict between Musk and Altman, the case highlights broader tensions shaping the AI industry as companies balance nonprofit ideals, investor demands, infrastructure costs, and control over frontier AI systems.

The enormous computing requirements associated with advanced AI development have pushed leading labs toward increasingly commercial models and deep partnerships with cloud providers and investors. At the same time, regulators, policymakers, and courts are beginning to examine how these organizations govern technologies that could have major economic and national security implications.

The outcome of the trial could influence how future AI companies structure governance, investor oversight, and nonprofit commitments as the industry continues consolidating around a small group of heavily capitalized firms.

Anthropic has overtaken OpenAI in verified business customer adoption for the first time, according to new data from fintech platform Ramp.

Ramp’s latest AI Index, which analyzes expense data from more than 50,000 companies using its payment and finance platform, found that 34.4% of participating businesses are now paying for Anthropic services, compared with 32.3% for OpenAI. It marks the first time Anthropic has held the top position in the survey.

According to Ramp economist Ara Kharazian, Anthropic had already established a lead among highly technical industries including finance, technology, and professional services before expanding into broader enterprise categories.

The data also illustrates how rapidly Anthropic has grown over the past year. In May 2025, only 9% of surveyed businesses were paying for Anthropic products. That figure has since increased by 26 percentage points over a 12-month period. During the same timeframe, OpenAI’s business adoption share declined by roughly 1%, while overall enterprise adoption of AI products across the survey increased by 9%.

Kharazian said Anthropic’s strategy of initially focusing on technical customers and developer-oriented use cases helped establish stronger traction within enterprise environments before broader expansion through products such as Claude Cowork.

The findings align with broader market signals suggesting growing enterprise adoption of Claude models. OpenRouter usage rankings, which track another segment of AI users and developers, last showed OpenAI ahead of Anthropic in December 2025.

Ramp noted that the index is not a complete representation of the overall AI market because it only reflects companies using its platform. However, the dataset remains one of the largest publicly discussed indicators of verified commercial AI spending activity.

Enterprise AI Competition Shifts Toward Deployment And Reliability

The report highlights how competition between leading AI companies is increasingly being shaped by enterprise deployment rather than consumer visibility alone.

Anthropic has spent much of the past year expanding its presence in regulated industries and enterprise workflows, particularly in finance, cybersecurity, operations, and software development. Its Claude family of models has gained traction among businesses seeking longer context handling, coding assistance, and AI agents designed for workplace tasks.

The company has also aggressively expanded enterprise infrastructure and partnerships in recent months, including new deployment initiatives, financial services AI agents, cybersecurity tools, and large-scale compute agreements aimed at supporting business demand.

Meanwhile, OpenAI continues to maintain a dominant consumer footprint through ChatGPT while simultaneously pushing deeper into enterprise deployments through consulting partnerships, deployment services, and productivity integrations.

Amazon has introduced Alexa for Shopping, a new AI-powered shopping assistant designed to combine conversational AI, product expertise, and customer shopping history into a unified retail experience across Amazon’s app, website, and Echo Show devices.

The launch merges capabilities from Alexa+ and Amazon’s Rufus shopping assistant, which the company said helped more than 300 million customers research and compare products in 2025. Alexa for Shopping is now integrated directly into Amazon’s main search bar, allowing users to ask conversational questions, compare products, track orders, generate shopping guides, and automate purchases using natural language.

Amazon said the assistant continuously personalizes recommendations using browsing activity, purchase history, preferences, and conversations across Alexa-enabled devices. The company described the system as a persistent shopping layer that carries context between devices and sessions instead of resetting interactions each time a customer searches.

The assistant can create AI-generated category overviews, compare products side-by-side from search results, surface one-year price history charts, and automatically monitor products for price drops. Customers can also create “Scheduled Actions” that automate recurring shopping tasks such as replenishing household items, tracking book releases, or adding products to carts when prices reach specific targets.

Amazon is also expanding agentic shopping capabilities through Shop Direct and its “Buy for Me” feature. The system can discover products from external retailers and, for eligible items, complete purchases automatically using stored payment and shipping information.

The company said Alexa for Shopping can also generate personalized shopping guides for complex purchases such as laptops, TVs, or appliances by summarizing reviews, features, pricing differences, and category insights across Amazon and the broader web.

In addition to mobile and desktop support, Amazon is bringing the full Amazon storefront experience to Echo Show devices for the first time. Customers can browse and purchase products using voice commands, touch controls, or a combination of both.

Alexa for Shopping is rolling out to all U.S. customers this week and does not require a Prime membership, Alexa app subscription, or Echo device.

Amazon Pushes AI Deeper Into Commerce Automation

The launch marks one of Amazon’s most aggressive attempts yet to transform e-commerce from search-based navigation into AI-assisted decision making and task automation.

Rather than relying on keyword searches and static filters, Alexa for Shopping is designed to function as a persistent shopping assistant that remembers preferences, previous conversations, recurring purchases, family information, and shopping behavior across Amazon’s ecosystem.

Features such as automated cart-building, conversational product research, and price-triggered purchases move Amazon closer to agentic commerce systems where AI actively manages portions of the shopping process on behalf of users.

The integration of Rufus product intelligence with Alexa+ personalization also gives Amazon a broader contextual data advantage across retail, smart home devices, and media services.

Google is reportedly in talks with SpaceX over a potential rocket launch agreement tied to the company’s efforts to develop orbital data centers, according to a Wall Street Journal report citing people familiar with the discussions.

The report said Google is also holding conversations with other rocket-launch providers as it evaluates infrastructure options for deploying computing systems in space. The initiative is connected to Google’s previously disclosed Project Suncatcher program, which aims to research space-based data center technology and launch two prototype satellites by early 2027.

Project Suncatcher was first revealed in November as part of Google’s long-term exploration of alternative AI infrastructure systems. The project focuses on whether orbital computing platforms could eventually help address growing energy, cooling, and land constraints associated with terrestrial AI data centers.

A partnership with SpaceX would mark another instance of Elon Musk cooperating commercially with AI rivals he has publicly criticized in the past. Musk has repeatedly attacked Google’s AI strategy while simultaneously expanding his own AI infrastructure ambitions through xAI and SpaceX.

Space-Based Computing Gains Attention In AI Industry

The idea of orbital data centers has shifted from theoretical research toward early-stage infrastructure planning as AI companies search for ways to overcome physical limitations facing existing compute expansion.

Space-based infrastructure offers several potential advantages, including access to uninterrupted solar energy, reduced land and cooling constraints, and theoretically massive long-term compute scalability if launch costs continue declining.

However, major technical challenges remain, including radiation exposure, hardware reliability, maintenance logistics, latency management, and the economics of deploying large-scale compute systems into orbit.

AI Infrastructure Race Expands Beyond Earth

Competition in artificial intelligence is expanding into infrastructure ownership and compute deployment strategy rather than focusing solely on model development.

Last week, Anthropic signed an agreement to access the full compute capacity of SpaceXAI’s Colossus 1 supercomputer facility in Memphis, adding more than 220,000 NVIDIA GPUs to support Claude training and inference workloads. The partnership also included discussions around developing multiple gigawatts of orbital compute infrastructure.

The move followed Musk’s decision to merge xAI directly into SpaceX under a new SpaceXAI structure combining AI models, compute infrastructure, and aerospace operations into a single organization. Analysts said the consolidation could give SpaceXAI a unique advantage if orbital AI infrastructure becomes commercially feasible in the coming years.