OpenAI has launched ChatGPT integrations for Microsoft Excel and Google Sheets, bringing AI-powered spreadsheet generation, editing, and analysis directly into both platforms. The add-ins are available globally across consumer, education, and enterprise ChatGPT plans, including Free, Plus, Pro, Business, Enterprise, Edu, and K-12 tiers.

The integrations run as sidebar assistants inside spreadsheets and are designed to handle large, multi-tab workbooks containing formulas, references, assumptions, and linked calculations. Users can ask ChatGPT to build spreadsheets from scratch, explain unfamiliar models, update assumptions, clean formatting, remove duplicates, troubleshoot formulas, or generate scenario analyses using natural-language prompts.

OpenAI said the tools are particularly aimed at spreadsheet-heavy workflows such as budgeting, forecasting, KPI reporting, financial modeling, and operational planning. Example use cases include updating a model while preserving formatting, tracing broken formulas across sheets, generating sensitivity analyses, and summarizing changes after edits.

The company emphasized that ChatGPT for Excel and Google Sheets operates as a separate experience from standard ChatGPT conversations. Spreadsheet chats do not sync with regular chat history and currently do not have access to ChatGPT memory features. Advanced spreadsheet functionality such as VBA and macros may also have limited support.

The integrations additionally support Skills and connected apps. Skills act as reusable workflow templates that guide ChatGPT through structured spreadsheet tasks, while apps connect the assistant to external enterprise data sources. Users can invoke Skills directly within prompts or connect business systems for more context-aware spreadsheet operations.

For enterprise customers, OpenAI said the tools support compliance controls including role-based access permissions, data residency options where available, Enterprise Key Management, and integration with the Compliance API. Administrators can deploy the Excel integration internally through Microsoft 365 management tools if direct marketplace access is restricted.

OpenAI Pushes Deeper Into Productivity Software

The release expands OpenAI’s strategy of embedding ChatGPT directly into existing workplace software instead of requiring users to switch between standalone AI interfaces and productivity tools. Spreadsheets are one of the most widely used business applications, particularly in finance, operations, and analytics, making them a natural target for AI-assisted workflows.

Unlike traditional spreadsheet automation tools, the integrations focus on contextual understanding of entire workbooks rather than isolated formulas or macros. The assistant can interpret relationships between tabs, assumptions, and calculations while modifying spreadsheets through conversational instructions.

Spreadsheet AI Moves Toward Agentic Workflows

OpenAI’s description of usage-based “agentic limits” signals a broader move toward AI systems that perform multi-step operational tasks rather than simple question answering. Complex spreadsheet edits, model reviews, and workbook restructuring require persistent reasoning across large files and multiple operations.

At the same time, OpenAI included repeated warnings about reviewing outputs before relying on them, particularly for financial, legal, and tax-related work. The company acknowledged that formulas, calculations, and edits can still contain errors, reinforcing that spreadsheet AI remains assistive rather than fully autonomous for high-stakes workflows.

Panthalassa has raised $140 million in a Series B funding round led by Peter Thiel to expand its offshore AI computing and wave-energy platform. The company plans to use the funding to scale manufacturing, deploy larger ocean-based compute nodes, and move toward commercial operations beginning in 2027.

Panthalassa is developing autonomous offshore systems that generate electricity from ocean waves and use the energy directly to power onboard AI computing hardware. Instead of sending electricity back to terrestrial grids, the company runs AI workloads at sea and transmits data through low-Earth-orbit satellite networks.

The company says the model is designed to address several infrastructure constraints emerging from rapid AI growth, including grid congestion, water shortages for cooling, permitting delays, and rising opposition to large terrestrial data centers. Because the systems operate in the open ocean, surrounding seawater can also be used for passive cooling.

“The future demands more compute than we can imagine,” Thiel said. “Extra-terrestrial solutions are no longer science fiction. Panthalassa has opened the ocean frontier.”

Panthalassa has already deployed two prototypes, Ocean-1 in 2021 and Ocean-2 in 2024. The new funding will support a pilot manufacturing facility near Portland and accelerate deployment of the Ocean-3 series, scheduled for the northern Pacific Ocean in 2026.

“There are three sources of energy on the planet with tens of terawatts of new capacity potential: solar, nuclear, and the open ocean,” said Panthalassa CEO Garth Sheldon-Coulson. “We’ve built a technology platform that operates in the planet’s most energy-dense wave regions, far from shore, and turns that resource into reliable clean power.”

The financing round included investors such as John Doerr, Marc Benioff’s TIME Ventures, Max Levchin’s SciFi Ventures, Super Micro Computer, and returning backers including Founders Fund and Lowercarbon Capital.

Offshore Compute Targets AI Energy Constraints

Panthalassa’s approach differs from conventional renewable energy projects because the generated electricity is consumed directly where it is produced. By placing compute workloads offshore, the company avoids transmitting large amounts of power through already constrained electrical grids.

The strategy also targets one of the largest operational challenges in AI infrastructure: cooling. High-density GPU clusters consume enormous amounts of electricity and generate significant heat, forcing data center operators to secure large water supplies and specialized cooling systems. Panthalassa argues that open-ocean deployment removes much of that constraint.

John Doerr called the technology “a game changer in addressing global energy needs and clean power generation,” adding that it strengthens American technological leadership while creating new industrial infrastructure.

Ocean Infrastructure Moves From Prototype To Scale

The company’s next challenge will be proving that offshore compute systems can operate reliably at commercial scale in difficult ocean conditions. That includes maintaining stable power generation, satellite connectivity, and hardware performance over long periods at sea.

The Ocean-3 deployment planned for 2026 is expected to serve as Panthalassa’s first large-scale operational test before broader commercial rollout in 2027. If successful, the company could become part of a wider push to decentralize AI infrastructure away from land-constrained data center hubs.

Anthropic has announced a compute partnership with SpaceX that gives the company access to the full capacity of the Colossus 1 AI data center. The agreement adds more than 300 megawatts of compute power and over 220,000 NVIDIA GPUs, significantly expanding the infrastructure available for Claude models.

The additional capacity is already affecting Anthropic’s products. The company said it is doubling Claude Code’s five-hour rate limits for Pro, Max, Team, and enterprise seat-based plans. It is also removing peak-hour usage reductions for Pro and Max subscribers and substantially increasing API rate limits for Claude Opus models.

According to Anthropic, the SpaceX agreement is part of a broader infrastructure expansion strategy aimed at addressing rising demand for Claude services. The company said the added GPU capacity will directly improve availability for Claude Pro and Claude Max users, who have faced tighter usage restrictions as demand for coding and reasoning workloads increased.

The Colossus 1 facility includes dense deployments of NVIDIA H100, H200, and GB200 accelerators. Anthropic said the compute cluster will support both model training and inference workloads, including Claude Code and API services.

The SpaceX agreement follows several other large-scale infrastructure deals announced by Anthropic this year. These include an agreement with Amazon for up to 5 gigawatts of AI infrastructure, including nearly 1 gigawatt expected online by the end of 2026; a 5 gigawatt partnership with Google and Broadcom beginning in 2027; a strategic infrastructure partnership involving Microsoft and NVIDIA worth up to $30 billion in Azure capacity; and a $50 billion AI infrastructure investment initiative with Fluidstack.

Usage Limits Increase As Demand Surges

The immediate product changes show how tightly compute availability is tied to user experience in large AI systems. Claude Code, which allows developers to use Claude for software engineering workflows, has become one of Anthropic’s most compute-intensive products because coding tasks often require long reasoning chains and repeated iterations.

By raising rate limits and removing peak-hour reductions, Anthropic is effectively signaling that infrastructure constraints had become a bottleneck for paid users. The increase in API capacity also matters for enterprise customers building applications on Claude Opus, Anthropic’s most capable model.

The company’s reliance on multiple hardware platforms, including AWS Trainium chips, Google TPUs, and NVIDIA GPUs, reflects a broader strategy to diversify compute supply instead of depending on a single cloud or chip provider.

AI Infrastructure Expands Beyond The US

Anthropic also said future infrastructure expansion will increasingly happen internationally, particularly for enterprise customers in regulated industries such as healthcare, government, and financial services. Many of these customers require local hosting to meet data residency and compliance rules.

The company said some of its new inference capacity through Amazon will be deployed in Asia and Europe. Anthropic also emphasized that future expansion will prioritize countries with stable legal frameworks and secure supply chains for networking, hardware, and data center infrastructure.

The announcement additionally included continued discussions with SpaceX around orbital AI compute systems. While still experimental, the idea reflects growing concern inside the AI industry that future model development could outgrow the practical limits of terrestrial power, cooling, and land availability.

OpenAI could move into the smartphone market sooner than expected, according to analyst Ming-Chi Kuo, who says the company’s AI-focused handset may enter mass production in the first half of 2027. Earlier reports had pointed to a 2028 timeline, but Kuo now suggests the schedule has accelerated amid rising competition in AI-powered mobile devices and the possibility of an OpenAI public offering.

The device is reportedly being developed around AI-agent functionality rather than traditional smartphone features alone. According to Kuo, MediaTek is expected to become the exclusive supplier of the phone’s system-on-chip. The handset would reportedly use a customized Dimensity 9600 processor built on TSMC’s N2P process technology, which is expected to enter production later this year.

Kuo said the smartphone will place significant emphasis on imaging and real-world visual sensing. The image signal processor is expected to feature an upgraded HDR pipeline designed to improve how the device interprets and processes visual information. The phone is also rumored to include a dual neural processing unit architecture for handling AI workloads directly on the device.

Additional reported specifications include LPDDR6 memory, UFS 5.0 storage, and security technologies such as protected kernel-based virtualization and inline hashing. These features suggest the device is being designed to support more advanced local AI processing while strengthening system-level security.

If development proceeds on schedule, Kuo estimates that cumulative shipments across 2027 and 2028 could reach 30 million units, potentially positioning the device as one of the first large-scale AI-native smartphones from a major AI company.

AI Companies Push Beyond Software Platforms

The reported smartphone project reflects how AI companies are increasingly exploring dedicated hardware to support next-generation AI experiences. Rather than relying entirely on existing mobile ecosystems, firms are looking at ways to integrate AI agents more deeply into operating systems, sensors, and on-device computing infrastructure.

For OpenAI, entering hardware could expand its ecosystem beyond software subscriptions and enterprise services. The company has already been increasing its presence across productivity tools, APIs, and personalized AI assistants, making a dedicated device a logical extension of its platform ambitions.