At Google Cloud Next this week, the tech giant announced a bevy of new updates to Workspace, its subscription-based productivity suite aimed at professionals. As you might expect, the updates are heavy on AI, integrating new automation tools into various workflows — everything from drafting emails to organizing Google Sheets. Overall, the changes are clearly designed to give office workers a leg up in their pursuit of less busy work.

Here’s some of what is new:

Workspace Intelligence. Workspace Intelligence, a new AI system built into Google’s office suite, is designed to automate assistance across various tasks. The system draws on a user’s Workspace data, including their Gmail, Calendar, Chat, and Drive (Docs, Slides, and Sheets). Google has given users administrative control over what the AI system can see and access. Users can disable Workspace Intelligence’s access to particular data sources at any time. The tradeoff: The more data the system has access to, the more it’s able to assist in those particular areas.

Build and fill out Google Sheets with Gemini. A number of new features allow users to both build and fill out Google Sheets, the company’s spreadsheet tool. Users can construct sheets by prompting Gemini to construct them. Prompts can include things like formatting and data retrieval, allowing Google’s AI system to do much of the work a human would’ve previously needed to do. At the same time, Gemini also helps with data entry, automatically filling out Sheets with “prompt-based” filling. Google claims that its new feature allows users to populate the spreadsheets “9x faster” than manual entry, because the system is designed to infer what you’re going to enter. Another new Sheets feature allows users to convert unstructured data into organized tables.

AI writing capabilities. Google has also brought new new AI writing tools to Google Docs. Users can now use Gemini to “generate, write, and refine” documents. The feature is powered by the company’s Workspace Intelligence system, which draws on data from a user’s Drive, Chat, and Gmail archives, as well as the internet, to assist with editorial tasks. Users merely prompt Gemini to help them write or edit their documents. Users can prompt Gemini to “help me write” or ask it to “match” their writing style so that it can effectively mimic their voice.

Realizing that enterprise customers are where the money is, tech companies are racing to deploy the most convenient and efficient office tools — applications that can make the average worker’s life a matter of degrees easier. Google has a certain advantage; its office products are already deeply embedded in workplaces worldwide, giving it a built-in audience for these AI upgrades. But Microsoft, Apple, and a growing field of startups are all competing for the same turf.

Tesla CEO Elon Musk kicked off the company’s first-quarter earnings call with a monetary heads-up — or depending on the mindset of the investor, a warning. Tesla’s capital expenditures will skyrocket to $25 billion in 2026, far outpacing its previous annual spend as it races to stay ahead of the competition and transitions to an AI and robotics company, according to its first-quarter earnings report.

That figure, which covers what Tesla plans to spend on physical assets outside of its day-to-day operating expenditures, is three times higher than its annual capex budget in previous years. For comparison, Tesla’s annual capital expenditures were $8.5 billion in 2025, $11.3 billion in 2024, and $8.9 billion in 2023.

Tesla had announced in January that it expected capital expenditures to be in excess of $20 billion in 2026, already a substantial increase meant to cover its AI initiatives, including investments in compute infrastructure and data centers, and the expansion and ramp of its manufacturing and R&D production lines, among other items.

This $5 billion uptick suggests these initiatives will require more money than previously planned. But so far, its quarterly capital expenditure, which was $2.5 billion, was in line with previous quarters, the report shows.

Of course, Musk views this as a positive, a sentiment many other shareholders will likely also share since it positions Tesla as a company investing in its future, namely AI and robotics.

“With 2026 we’re going to be substantially increasing our investments in the future,” Musk said in the earnings call Wednesday. “So you should expect to see significant, a very significant increase in capital expenditures, but I think well justified for a substantially increased future revenue stream.”

Musk was quick to note that Tesla isn’t the only company raising its capital expenditure budget. Amazon, for instance, has projected $200 billion in capital expenditures in 2026, across “AI, chips, robotics, and low earth orbit satellites.” Google is slated to spend between $175 billion and $185 billion in capital expenditures in 2026, up from $91.4 billion the previous year.

The increase in Tesla’s capital expenditures is linked to Musk’s desire and ambition to evolve the company beyond building and selling EVs, solar, and energy storage.

Some of the capex spend will go toward Tesla’s core technologies such as its battery and AI software, according to Musk. The company plans to invest in AI training, chip design, and “laying the groundwork” for increasing manufacturing production, as well as invest in its robotaxi operations and its new semiconductor research fab in Austin.

The Fremont, California, factory will likely suck up some of that capital as the company ends production of the Tesla Model S and Model X and begins building its Optimus humanoid robot at scale. The company said Wednesday it has also cleared ground outside its Austin factory for a dedicated Optimus manufacturing facility.

Tesla plans to increase its internal production of Optimus for testing and then “probably” make Optimus “useful outside of Tesla sometime next year,” he said.

Tesla is also putting money toward strengthening its supply chain “across the board,” Musk said, adding that this covers batteries, energy, and AI silicon.

All of this spending, which CFO Vaibhav Taneja said will last a couple of years, comes with a literal cost. The company — which enjoyed a brief 4% share price bump due, in part, to an unexpected $1.4 billion in free cash flow — will head into negative territory later this year, Taneja said.

Tesla shares erased their gains in after-hours trading as Musk and Taneja laid out these plans to investors. Still, Tesla is sitting on loads of cash. At the end of the first quarter, Tesla reported $44.7 billion in cash, cash equivalents, and short-term investments.

“While this may seem like a lot, and we will have the impact of negative free cash flow for the rest of the year, we believe this is the right strategy to position the company for the next era,” Taneja said.

Former OpenAI executive Mira Murati’s startup, Thinking Machines Lab, has signed a new multi-billion-dollar agreement to expand its use of Google Cloud’s AI infrastructure, including systems powered by Nvidia’s latest GPUs, TechCrunch has exclusively learned.

The deal is valued in the single-digit billions, according to a source familiar with the matter, and includes access to Google’s latest AI systems built atop Nvidia’s new GB300 chips, alongside infrastructure services to support model training and deployment.

Google has been actively striking a number of cloud deals with AI developers as it aims to wrap together its AI computing offerings with other cloud services like storage, a Kubernetes engine, and Spanner, its database product. Earlier this month, Anthropic signed an agreement with Google and Broadcom for multiple gigawatts of tensor processing unit (TPUs) capacity (these are Google’s custom-designed AI chips for machine learning workloads). 

But the competition is fierce. Just this week, Anthropic also signed a new agreement with Amazon to secure up to 5 gigawatts of capacity for training and deploying Claude. 

Earlier this year, Thinking Machines partnered with Nvidia in a deal that included an investment from the chipmaker. But this is the first time the lab has struck a deal with a cloud services provider. The deal is not exclusive, so Thinking Machines may use multiple cloud providers over time, but it’s still a sign that Google is looking to lock in fast-growing frontier labs early. 

Murati left her job as OpenAI’s chief technologist and founded Thinking Machines in February 2025. The company, which soon afterwards raised a $2 billion seed round at a $12 billion valuation, has remained highly secretive, but launched its first product in October. Dubbed Tinker, it’s a tool that automates the creation of custom frontier AI models. 

Wednesday’s deal provided some insight into what Thinking Machines is developing. In a press release, Google noted that it can support the startup’s reinforcement learning workloads, which Tinker’s architecture relies on. Reinforcement learning is a training approach that has underpinned recent breakthroughs at labs, including DeepMind and OpenAI, and the scale of the Google Cloud deal reflects how computationally expensive that work can get. 

Thinking Machines is among the first Google Cloud customers to access its GB300-powered systems, which offer a 2X improvement in training and serving speed compared to prior-generation GPUs, per Google. 

“Google Cloud got us running at record speed with the reliability we demand,” Myle Ott, a founding researcher at Thinking Machines, said in a statement.