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White House AI Action Plan, Part II

When the White House unveiled its sweeping AI Action Plan earlier this year, it was presented as a blueprint for American leadership in artificial intelligence, outlining how to cut red tape, modernize infrastructure, and give the United States a competitive edge. Three months later, some of the plan’s ninety directives are beginning to move from policy statements to tangible execution. Others are running into the country’s fractured regulatory environment.

From Policy to Practice

Federal agencies have now entered the implementation phase. The Office of Management and Budget and the Office of Science and Technology Policy instructed each major department to appoint a Chief AI Officer and submit internal adoption frameworks by the end of the year. Agencies such as the Department of Energy and the Department of Health and Human Services are leading early efforts, using AI systems to analyze data, streamline permitting, detect anomalies in contracting, and identify inefficiencies in energy use.

The Department of Energy is putting the plan’s infrastructure focus into action. It has selected four federal sites; Idaho National Laboratory, Oak Ridge, Paducah, and Savannah River to host AI-integrated data centers designed to manage grid optimization and speed up clean energy projects. These pilots answer the Action Plan’s call for faster project approvals, reduced administrative friction, and better coordination between agencies.

Progress has been uneven. Agencies face difficulties recruiting qualified AI talent while competing with private companies, and coordination between departments varies widely. Some have already met their initial milestones, while others are still drafting frameworks or waiting for funding. As one White House adviser put it at a recent AI policy forum, “Execution is the bottleneck, not ambition.”

AI in Public Services

The Department of Transportation is beginning to put the White House AI Action Plan into motion through new pilot programs focused on traffic optimization. Along several major freight corridors, the agency is testing how real-time sensor data and machine learning can predict congestion, reroute shipments, and coordinate with state traffic systems.

Early findings show delivery times reduced by twelve percent and fuel use down seven percent during peak hours. The pilots reflect the Action Plan’s goal of using AI to modernize public infrastructure and improve efficiency within critical federal systems. If expanded nationwide, this approach could become a model for applying AI to other public services, including emergency response and energy management.

The Regulatory Fault Lines

While the White House pushes for national alignment on AI, the state response tells a different story. California’s legislature recently passed several AI-related bills targeting safety, misinformation, and youth protection. Many of these conflict with the federal plan’s deregulatory stance. One bill requires AI companies to test for harmful emergent behavior before releasing products, a standard that some federal officials have privately called unworkable.

Texas and Florida have taken the opposite approach, passing laws that align with the federal plan and encourage investment and research. The result is an uneven regulatory landscape that threatens the goal of a unified national AI strategy.

The White House approach, which discourages federal funding for states seen as burdensome to AI innovation, adds more tension. Legal analysts warn this could spark lawsuits over federal overreach, similar to earlier disputes in education and environmental policy. Local governments argue that Washington’s hands-off model leaves citizens exposed to algorithmic harm, while federal agencies say too much oversight would stall innovation.

The debate reflects a deeper divide: should AI be regulated as infrastructure or as speech? The federal government’s current stance prioritizes speed, efficiency, and competition. States like California focus on consumer protection and civil rights.

A Plan in Motion

Three months later, the AI Action Plan is no longer just a vision. Agencies are hiring, data centers are breaking ground, and pilot programs are under way. Yet the divide between federal ambition and state caution could shape what comes next. The United States is now racing not only against global rivals but against its own fragmented system of governance. The coming months will reveal whether America’s AI future can be coordinated or whether competing interests will pull it apart.

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Bay Area Startups Collectively Secured $3.54B this week

Bay Area startups closed on $3.54B in fundings this week, bringing the October total to just over $8B. 83% of the total came from seven megadeals, and the majority of that came from three AI infrastructure companies. Crusoe led with a $1.37 Series E, followed by two Series B megadeals for LangChain and fal AI. Special mention goes to Fal AI's $250M round with a $4B valuation - it comes less than three months after their $125M Series C at a $1.5B valuation. Their revenue growth, reportedly from $10M to $95M ARR in less than a year, reflects the rapid adoption of the  applications built on their infrastructure for multimodal AI.

IPO Watch: On the question of jump now or wait till 2026 with the start of holidays justa month away, three companies have decided to jump: BilliontoOne, Evommune, and Navan . All three priced this week and expect to complete their IPOs early in November.

For all startups raising capital (and service providers interested in who's getting capital): The Pulse of the Valley weekday newsletter keeps you current with the startups that are getting funded and who's investing in them – and not just the big, high profile deals. We surface the 50% of early stage fundings – and their investors - that close quietly and never hit the press. Details include investor and executive connections + contact information on 25+ years of fundings and business activity. Founders get the full $50/month package for just $7/month with our Entrepreneur membership, details and signup here.

Follow us on LinkedIn to stay on top of what's happening in 2025 in startup fundings, M&A and IPOs, VC fundraising plus new executive hires & investor moves.

Early Stage:

• Tempo Blockchain closed a $500M Series A, a purpose-built, layer 1 blockchain for payments, developed in partnership with leading fintechs and Fortune 500s.

• Seneca closed a $60M Series A, a resilience technology and infrastructure company building advanced firefighting technology for situations that were previously unsafe, inefficient, or impossible, using autonomous drones and AI-driven software.

• Keycard closed a $30M Series A, unlocking the power of AI agents by giving developers and enterprises the foundations they need to build and adopt trusted agentic applications at scale.

• Petal Surgical closed a $10M Seed, developing incisionless surgery.

• Tensormesh closed a $4.5M Seed, the AI infrastructure optimization company enabling up to 10x faster inference while keeping full control of data and deployment.

Growth Stage:

• Uniphore closed a $260M Series F, the Business AI Company that unlocks the agentic enterprise with a complete, composable AI platform spanning agents, models, knowledge, and data.

• fal closed a $250M Series B, the leading platform for generative media, offering cutting-edge inference solutions for AI-powered video, image, and audio applications.

• Sesame AI closed a $250M Series B, developing lightweight eyewear that is designed to be worn all day, giving you high-quality audio and convenient access to your companion who can observe the world alongside you.

• LangChain closed a $125M Series B, the platform for building reliable agents, providing hundreds of integrations and composable components, making it easy to connect with the latest models, tools, and databases — with minimal engineering overhead.

• Cala Health closed a $50M Series C, a bioelectronic medicine company transforming the standard of care for chronic disease using wearable neuromodulation therapies to deliver individualized peripheral nerve stimulation.

WOMEN x AI | Empowering Women to Lead in Artificial Intelligence

About WOMEN x AI

WOMEN x AI (WxAI) is a global community dedicated to amplifying women’s voices, leadership, and impact in artificial intelligence. Based in Silicon Valley, the organization connects founders, researchers, investors, and technologists shaping the future of AI — ensuring women are not just participants, but leaders in the industry.

What They Do

• Community & Networking: WxAI hosts both in-person Bay Area gatherings and global virtual events to help women connect, collaborate, and grow their AI expertise.

• Resources & Education: Through blogs, spotlights, and tool reviews, members gain access to insights on emerging AI trends, best practices, and opportunities.

• Podcast: The WOMEN x AI Podcast, hosted by Reut Lazo and Jenny Kay Pollock, features trailblazing women in tech who share real stories, strategies, and lessons for building meaningful careers in AI.

Why It Matters

With over 1,700+ attendees, 500+ global members, and 80+ women speakers, WOMEN x AI is cultivating a more inclusive and representative AI ecosystem — one where women have the tools, mentorship, and visibility to thrive.

📍 Join the Movement: womenxai.com
Follow WOMEN x AI on LinkedIn, Instagram, and YouTube.

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Head of Content // Team Ignite

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