Bloomberg’s corporate venturing unit listed 72 portfolio companies on its GitHub page in December, nearly half of which (35) have been “machine intelligence companies solving 35 meaningful problems in areas from security to recruiting to software development”, according to Shivon Zilis, partner at Bloomberg Beta responsible for seeking out many of them.
Zilis’s annual update – Current State of Machine Intelligence 3.0 – now in collaboration with partner James Cham, “has a third more companies than our first one did two years ago, and it feels even more futile to try to be comprehensive, since this just scratches the surface of all of the activity out there”, she added.
Having made her name as a smart investor a few years earlier, validated when network LinkedIn acquired her portfolio company Newsle for an undisclosed amount in July 2014 to form the cornerstone of its Connections In The News feature, Zilis has become influential in the burgeoning area of machine intelligence, including a guest comment in the Economist’s flagship World in 2017 review.
A look at 26 of Bloomberg Beta’s disclosed machine intelligence deals, the majority directed by Zilis, checked against data providers Crunchbase and Angelist, shows the fund is an investor in: Alation ($9m A round in March 2015), Arimo (formerly Adatao, $13m A round in August 2014), Aviso (founded 2011), Brightfunnel ($8.25m across seed and A rounds in October 2014 and December 2015), Context Relevant ($7m in A round in July 2013 and $34.5m across split B rounds in 2014), Deep Genomics ($3.7m seed round in November 2015), Diffbot ($500,000 seed round in June 2015), Digital Genius ($8.1m in convertible notes in 2015 and 2016), Domino Data Labs ($3m A round in August 2015), Drawbridge Networks ($1.7m seed round in December 2014), Gigster ($700,000 seed round in June 2015), Gradescope ($2.5m seed round in April 2016), Graphistry, Gridspace (2015 venture round), Howdy.ai ($1.5m seed round in October 2015), Kaggle, Kindred.ai, Mavrx ($10m A round in 2016), Motiva (seed round in March 2016), Orbital Insight ($28.7m from seed to B rounds 2014-16), PopUpArchive, Primer, Sapho (about $25m in seed and A rounds 2014-16), Shield.AI ($2m seed round in May 2016), Textio ($9.5m seed and A rounds in 2015), and Tule Technologies (seed round in May 2015).
Given that Bloomberg Beta closed its second fund at $75m only last summer, securing the funding by its sponsor and sole limited partner, media group Bloomberg, the fund could see further calls on its capital if it wanted to follow on with these early-stage deals and further exits.
The firm’s other exits include cloud computing company Nodejitsu through an acquisition by domain name issuer GoDaddy, data processor Concord Systems, acquired by Akami in September, and marketing platform Spiderbook, acquired by Demandbase in June. But interest in machine intelligence is growing and “anyone who has their wits about them is still going to be making initial build-and-buy decisions”, Zilis noted in her landscape of the sector.
She said deals in the space included Nervana by Intel, Magic Pony by Twitter, Turi by Apple, Metamind by Salesforce, Otto by Uber, Cruise by GM, SalesPredict by Ebay, and Viv by Samsung and “many of these happened fairly early in a company’s life and at quite a high price”. This reflected the changing maturity in the startups, Zilis said.
“For v1.0, we heard almost exclusively from founders and academics. Then came a healthy mix of investors, both private and public. Now overwhelmingly we have heard from existing companies trying to figure out how to transform their businesses using machine intelligence.
“For the first time, a one-stop shop of the machine intelligence stack is coming into view – even if it is a year or two off from being neatly formalised. The maturing of that stack might explain why more established companies are more focused on building legitimate machine intelligence capabilities.”
Such clarity of insight built of empirical data helps explain why Zilis has been rising in profile since Ozy described her as the “nerd-athlete investor”. Zilis won scholarships to the US from Canada for hockey and academia and, having taken the latter route, she majored in economics and philosophy at Yale.
And news provider Canadian Business’s profile of Zilis, who turned 30 last year, quoted the “proud Canadian” and self-described “data geek” as being “obsessed with technology back in school but wanted to be on the business side of technology”.
Canadian Business said she first went to work for tech company IBM’s global microfinance initiative, to enable loans to be made to small businesses in developing countries, before she moved to advise startups in the education and data services spaces for Bloomberg’s internal incubator.
From there it has been a short leap to learn how to invest successfully it seems.
