Tech
Capitol Hill
(Demetrius Freeman/Getty Images)
CTRL-F

Here’s all the AI stuff in Trump’s tax bill

Over $2 billion is allocated to deploying AI for nuclear weapons programs, autonomous underwater drones, and sovereign AI models.

Jon Keegan

Yesterday the Senate passed President Trump’s massive tax bill, and today it heads to the House, where it faces an uncertain future.

The text of the bill is loooong — it spans 870 pages as a PDF and is full of allocations of federal dollars for Trump’s priorities, including over $2 billion for AI programs for defense, energy, and homeland security.

Top AI insiders might hold a lot of sway in this administration, but tech companies like Microsoft, Meta, Palantir, and OpenAI did suffer a major loss yesterday when a key provision to halt all state-level AI regulation for a decade was removed from the bill.

Things could change in the House, but let’s take a look at all the AI-related things that made it through the Senate.

Defense

💣 Resources for scaling low-cost weapons into production

 💻 Improving efficiency and cybersecurity

  • $200,000,000 for the deployment of automation and artificial intelligence to accelerate the audits of the financial statements of the Department of Defense

☢️ Enhancement of resources for nuclear forces

  • $115,000,000 for accelerating nuclear national security missions through artificial intelligence

⛴️ Enhancement of Department of Defense resources for shipbuilding

  • $188,360,000 for the development and testing of maritime robotic autonomous systems and enabling technologies

  • $174,000,000 for the development of a Test Resource Management Center robotic autonomous systems proving ground

  • $200,000,000 for the development, procurement, and integration of mass-producible autonomous underwater munitions

  • $500,000,000 to prevent delays in delivery of attritable autonomous military capabilities

  • $75,000,000 to contract the services of, acquire, or procure autonomous maritime systems

Energy

🤖 Transformational artificial AI models ($150 million)

  • “American science cloud”: a system of US government, academic, and private sector programs and infrastructures utilizing cloud computing technologies to facilitate and support scientific research, data sharing, and computational analysis across various disciplines while ensuring compliance with applicable legal, regulatory, and privacy standards

  • Mobilize National Laboratories to partner with industry sectors within the United States to curate the scientific data of the Department of Energy across the National Laboratory complex so that the data is structured, cleaned, and preprocessed in a way that makes it suitable for use in artificial intelligence and machine learning models

  • Initiate seed efforts for self-improving artificial intelligence models for science and engineering

Homeland Security

🚔 Border security, technology, and screening

  • $168,000,000 for procurement and integration of new nonintrusive inspection equipment and associated civil works, including artificial intelligence, machine learning, and other innovative technologies, as well as other mission support, to combat the entry or exit of illicit narcotics at ports of entry and along the southwest, northern, and maritime borders

Rural hospitals

🏥 Rural health transformation program ($50 billion)

  • Providing training and technical assistance for the development and adoption of technology-enabled solutions that improve care delivery in rural hospitals, including remote monitoring, robotics, artificial intelligence, and other advanced technologies

More Tech

See all Tech
tech
Jon Keegan

DeepSeek releases new V4 series models highlighting efficiency and long context

Chinese AI lab DeepSeek has released a major new version of its eponymous open-source AI models that are nipping at the heels of leading frontier models in some areas.

The most significant DeepSeek-V4 Pro and DeepSeek-V4 Flash both have a 1 million-token context — the amount of information the model can actively work with in a single session — which is a crucial feature for complex, long-running coding tasks.

DeepSeek rebuilt how the models process information under the hood, making them substantially more efficient — and that efficiency is what makes the large context window actually usable.

Also, the new models’ coding skills have closed the gap with the major frontier models from Anthropic, OpenAI, and Google.

The authors of the model acknowledge some of V4’s shortcomings, such as its lower scores on reasoning benchmarks, saying that V4 “trails state-of-the-art frontier models by approximately 3 to 6 months.”

As open-weight models, V4 can be run on any user’s own hardware, making the V4 models among the top-performing open-source models out there. V4’s large context and token efficiency are especially significant among open-source models.

But like with earlier DeepSeek models, don’t ask it about Tiananmen Square.

DeepSeek Unveils Flagship AI Model a Year After Breakthrough

DeepSeek Unveils Flagship AI Model a Year After Breakthrough

DeepSeek rebuilt how the models process information under the hood, making them substantially more efficient — and that efficiency is what makes the large context window actually usable.

Also, the new models’ coding skills have closed the gap with the major frontier models from Anthropic, OpenAI, and Google.

The authors of the model acknowledge some of V4’s shortcomings, such as its lower scores on reasoning benchmarks, saying that V4 “trails state-of-the-art frontier models by approximately 3 to 6 months.”

As open-weight models, V4 can be run on any user’s own hardware, making the V4 models among the top-performing open-source models out there. V4’s large context and token efficiency are especially significant among open-source models.

But like with earlier DeepSeek models, don’t ask it about Tiananmen Square.

$28.5T
Rani Molla

SpaceX thinks its total addressable market (TAM) is a whopping $28.5 trillion for its businesses, according to an S-1 filing for its upcoming IPO reviewed by Reuters. And most of that market isn’t rockets. The company says roughly 90% could come from AI — largely selling artificial intelligence tools to businesses.

“We believe that our enterprise strategy, which is focused on serving the digital needs of the world’s largest industries with Al solutions, positions us competitively to pursue this rapidly ⁠growing opportunity,” ​SpaceX said in the filing. “We believe we have identified the largest actionable total addressable market in human ​history.”

TAM, of course, assumes capturing every possible customer. But even a small slice of a $28.5 trillion market would be enormous.

tech
Rani Molla

Tesla Cybercab production has begun

On Tesla’s earnings call earlier this week, CEO Elon Musk said production of the company’s steering-wheel-less Cybercab had begun. Since then, Musk and Tesla have posted videos showing the gold two-seater rolling off the line at its Texas Gigafactory and onto the road.

The Cybercab — meant both for consumers and Tesla’s Robotaxi network — is widely seen as central to the company’s future. “The future of the company is fundamentally based on large-scale autonomous cars and large scale and large volume, vast numbers of autonomous humanoid robots,” Musk said last year.

Whether these cars actually make it to consumers is another question. For now, regulations generally require steering wheels, and Tesla still has to prove the vehicles can reliably drive themselves.

On the earnings call, Musk said production would be “very slow” but would ramp up and go “kind of exponential towards the end of the year and certainly next year.”

tech
Rani Molla

Meta signs deal to use Amazon Graviton chips

Meta said it will deploy “tens of millions” of Amazon Web Services Graviton CPU cores to power so-called “agentic” AI systems — tools that can reason, plan, and act on their own. The move makes Meta one of the largest customers of Amazon’s in-house chips.

The deal also underscores a broader shift in AI infrastructure, as companies move beyond Nvidia GPUs and use different chips for different tasks.

Meta, which is working on its own custom inference chips, also has chip deals with Advanced Micro Devices and Nvidia.

Meta Partners With AWS on Graviton Chips to Power Agentic AI

Meta Partners With AWS on Graviton Chips to Power Agentic AI

The deal also underscores a broader shift in AI infrastructure, as companies move beyond Nvidia GPUs and use different chips for different tasks.

Meta, which is working on its own custom inference chips, also has chip deals with Advanced Micro Devices and Nvidia.

tech
Rani Molla

Oracle rises after Wedbush’s Dan Ives calls the stock a buy with 25% upside

Oracle extended its premarket gains Friday after Wedbush Securities’ Dan Ives initiated coverage with an “outperform” rating and a $225 price target — about 25% upside to its pre-initiation level — calling the enterprise software and cloud infrastructure company a “foundational infrastructure provider for the AI revolution.”

Ives argues investors are misreading Oracle’s heavy capital spending and negative free cash flow as risky, despite being backed by a massive $553 billion backlog of contracted demand. He says the company’s “secret sauce” is a two-part strategy: building high-performance cloud infrastructure for AI workloads while connecting those models directly to companies’ own data.

“We believe Oracle is in the early innings of a significant repositioning as it executes on this generational opportunity,” Ives wrote.

Latest Stories

Sherwood Media, LLC produces fresh and unique perspectives on topical financial news and is a fully owned subsidiary of Robinhood Markets, Inc., and any views expressed here do not necessarily reflect the views of any other Robinhood affiliate, including Robinhood Markets, Inc., Robinhood Financial LLC, Robinhood Securities, LLC, Robinhood Crypto, LLC, Robinhood Derivatives, LLC, or Robinhood Money, LLC. Futures and event contracts are offered through Robinhood Derivatives, LLC.
©2026 Sherwood Media, LLC