PETER HUBSHMAN

Co-Founder, Finance Advisor, MuKn Studio Business Operator

Peter is a finance and operations expert focusing on early round startups.  With origins in private equity, fund management and leveraged buyouts, in the early 2000’s he operated Internet Real Estate Group, a Web 2.0 studio in Boston which successfully developed businesses including Creditcards.com; Phone.com; Luggage.com; Jeans.com and a dozen other early primary domain businesses. There, his pioneering team of engineers created some of the earliest successful affiliate marketing and advertising platforms on the Internet, and were early experts in search engine optimization. 

In 2009 Peter became CFO of Digiport Data Centers in Miami FL until its sale in 2013.  There he developed business plans and economic models for all of Digiport’s spinout startups, including:The collaborative consumption platform, Boatsetter.com (Air BnB for yachts, captains included); SaaS startup, Itopia.com (early cloud-ware for small-midsized professional offices and now, .edu); and artworld upstart, Blackdove.com (a digital arts platform for digital artists, restaurants, residential, and corporate).  In 2018 Peter was Management Consultant to, and Interim CFO at TheDroneRacingLeague.com (e-sports, media, and drone technology).  There he helped prepare the management team and crew for a successful C round led by a prestigious investment bank in 2019. Later in 2019, he became Interim CFO of Gemic.com (Brand Strategy for Fortune 100’s).  There he led the financial team supporting their successful A round with Bocap, a private equity firm in Finland.

Peter joined MuKn in Q1 2022 as CFO, Co- Founder and a Board Member.  He remains a Member of the Board, and is currently Finance Advisor while on assignment as CXO to a new MuKn studio spinout, FormalFoundry.ai (Dedicated to ensuring the correctness of AI models at scale).  Peter studied economics at Tufts University and has a Masters in Public and Private Management from the Yale University School of Management.

If you thought there was any probability that a technology could work to help save humanity, would you pass up supporting a clearly defined, low-cost test, on a scientifically promising route to effective control of the issue?  What if you could build a set of tools and then spread their use to avoid such a disaster? Please join us as we work within the AI community to ensure AI safety through correctness at scale.