HTS magnets are costly but important components in any magnetic confinement reactor, one of the two main ways startups are attempting to harness fusion power for commercial purposes. In magnetic confinement reactors, powerful magnetic fields contain and compress plasma, helping to heat the particles until the fuel can fuse and release large amounts of energy. Thea's reactor is based on a design known as a stellarator. Stellarators look like inner tubes that have been twisted and squeezed in ways that help it confine the plasma more effectively. Most stellarators use magnets that are built to mimic those twists and turns, which makes them expensive to manufacture. To minimize manufacturing costs, Thea uses fewer variants. The 12 large magnets that do the heavy lifting are made from four different templates, and the more than 300 smaller magnets used to fine tune the plasma are all identical. They're arrayed around the periphery of the reactor, similar to how pixels are distributed across a computer display....

Prentis, a new AI research lab focused on computer use models, co-founded by serial entrepreneur Ritankar Das and tech heavyweights Reid Hoffman and Mark Pincus, is in talks to raise $100 million at a $1 billion valuation, according to two people familiar with the discussions. Launched in April, Prentis is training models to learn how office workers navigate routine workflows across documents and systems, with the goal of building AI agents that can control computers to automate those tasks. Prentis will ostensibly develop agents tailored to these customers' needs, such as handling insurance claims and automating customs duty refund exceptions without needing a human to hunt down paperwork. The startup has already signed contracts worth up to $50 million with several customers, including healthcare management service organization, a manufacturer, and goods and clothing manufacturers, the two people familiar with the discussions tell TechCrunch. This echoes investor materials obtained by TechCrunch that predict an estimated $75 million annualized run rate by the third quarter of this year. (Prentis' pitch deck notes those figures reflect estimated annualized value based on a contracted fee equal to 20% of savings realized, not recognized revenue, and are 'performance-dependent and subject to final execution.')...

Dimitri Bertsekas PhD '71, the Jerry McAfee (1940) Emeritus Professor in Engineering in the Department of Electrical Engineering and Computer Science (EECS), a principal investigator in the Laboratory for Information and Decision Systems (LIDS), and the Fulton Professor of Computational Decision Making at Arizona State University, died on June 3 at his home in Belmont, Massachusetts. He was 83 years old. Over the course of his career, Bertsekas' research spanned, and had a definitive influence upon, several fields, including optimization, control, large-scale computation, reinforcement learning, and artificial intelligence. He served as a consultant to various private companies; an editor for several scientific journals; the founder of a publishing company, Athena Scientific; and chief scientific advisor of Bayforest Technologies, a London-based quantitative investment company. However, his most lasting impact may have come through his prolific authorship and co-authorship of over 20 highly influential books, monographs, and textbooks, and through his vast network of students, mentees, friends, and collaborators....

Daniel Docter, managing director at Dell Technologies Capital, began his career as a technologist. He holds degrees in electrical engineering and computer science, as well as a Ph.D., but early on found himself gravitating away from purely technical work toward translating technology into business and commercial use cases. His technical roots are reflective of Palo Alto, California-based Dell Technologies Capital's broader team. Its investors have degrees in fields including electrical engineering, computer engineering, computer science and data science, and many have worked at both large technology companies and startups. That experience shapes the firm's affinity for deeply technical founders and its approach to early-stage investing. When evaluating seed and Series A companies, the team focuses heavily on the potential impact of a technology: what problem it solves, what it could disrupt, and how well it works, often before traditional financial metrics become the central consideration....