Startup investors this week demonstrated continued willingness to write big checks for promising companies in sought-after areas. Leading the pack was Saviynt, an AI identity security platform that picked up a fresh $700 million. 1. Saviynt, $700M, AI identity security: Saviynt, a provider of AI-optimized identity security tools, announced that it secured $700 million in Series B financing. KKR led the round, which set a $3 billion valuation for the 15-year-old, El Segundo, California-based company. 2. Unconventional AI, $475M, AI energy efficiency: Unconventional AI, a startup designing a computer to optimize energy efficiency for AI, raised $475 million in seed funding. Andreessen Horowitz and Lightspeed Venture Partners led the financing for the San Francisco Bay Area company. 3. Fervo Energy, $462M, geothermal energy: Houston-based Fervo Energy, a developer and operator of geothermal energy projects with a focus on technologies to scale this power source, picked up $462 million in Series E funding led by B Capital. The funding will go toward a geothermal project in Western Utah as well as other projects in its pipeline....

The only real consistency about the asset class is it's reliably volatile. Sectors in vogue one year are out a few quarters later. Angel syndicates must increasingly compete with venture big shots. And founders who secure the biggest rounds can't assume more capital is en route. For 2025, the seed investment environment exhibited its typical quirkiness, with a few trends standing out. In particular, it was a huge year for huge rounds. Predictably, it was also a banner period for AI dealmaking. And in geographic trends, we saw the U.S. pull in a bigger-than-usual share of total investment. The concept of a seed round being very small is rather retro. Today, both eight- and nine-figure rounds are reasonably common, especially for a startup with highly regarded founders, expertise in a hot sector, and an early technological advantage. However, keep in mind: most of the rise was due to a single round. This was the $2 billion seed financing for Thinking Machines Lab, the AI startup co-founded by former OpenAI CTO Mira Murati. This month, another giant deal also boosted the totals, a $475 million financing for Unconventional AI, which is designing a computer to optimize energy efficiency for AI....

Artificial intelligence can enhance decision-making and enable action with reduced risk and greater precision, making it a critical tool for national security. A new program offered jointly by the MIT departments of Mechanical Engineering (Course 2, MechE) and Electrical Engineering and Computer Science (Course 6, EECS) will provide breadth and depth in technical studies for naval officers, as well as a path for non-naval officers studying at MIT, to grow in their understanding of applied AI for naval and military applications. 'The potential for artificial intelligence is just starting to be fully realized. It's a tool that dramatically improves speed, efficiency, and decision-making with countless applications,' says Commander Christopher MacLean, MIT associate professor of the practice in mechanical engineering, naval construction, and engineering. 'AI is a force multiplier that can be used for data processing, decision support, unmanned and autonomous systems, cyber defense, logistics and supply chains, energy management, and many other fields.'...

Donald Trump launched his political career by insisting that free-trade deals had sacrificed the national interest in the pursuit of corporate profits. One wonders what that version of Trump would make of his most recently announced trade policy. On Monday, he declared on Truth Social that the United States would lift restrictions on selling highly advanced semiconductors to China. In doing so, the president has effectively chosen to cede the upper hand in developing a technology that could determine the outcome of the military and economic contest between the U.S. and its biggest geopolitical rival. The U.S. is currently ahead in the AI race, and it owes that fact to one thing: its monopoly on advanced computer chips. Several experts told me that Chinese companies are even with or slightly ahead of their American counterparts when it comes to crucial AI inputs, including engineering talent, training data, and energy supply. But training a cutting-edge AI model requires an unfathomable number of calculations at incredible speed, a feat that only a few highly specialized chips can handle. Only one company, the U.S.-based Nvidia, is capable of producing them at scale....