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Artificial Intelligence in Boston – An Overview of Startups, Funding, and Trends

excitement in full swing, Boston is buzzing as always with it’s own batch of startups, accelerators, and VCs, and I decided to do a deep dive into the local artificial intelligence ecosystem.

After my speech at the AI Applications Summit (based on our recent research on Machine Learning in Healthcare) in Boston on December 2017, I decided to stay for another entire week, doing my best to interview as many professionals in the AI community (investors, founders, researchers, non-profits) as possible, in-person.

My goal was to create the most in-depth assessment conducted to date on where AI in Boston is headed, and what it means for researchers, startup founders, and existing enterprises who might be considering Boston to be their home.

Today, BU, UMass, MIT, Harvard, and others have thriving artificial intelligence programs for both grad students and undergrads, and many Boston locals believe that this strong academic base (Boston has about 35 colleges in the area) –

Like any other major tech city, Boston has seen the hype wave of artificial intelligence building over the last 3 years, and (not surprisingly, given Boston’s academic talent pool) they’ve spun out their own ecosystem of AI-focused startups, AI-focused VCs, and AI-focused consulting firms.

Thought over a dozen interviews I found some pretty consistent patterns about how the AI spotlight has impacted founders and businesspeople, and it’s a trend that was somewhat similar to what we say in our Montreal AI ecosystem feature.

The same eagerness and curiosity that grew Emerj’s traffic by 10x in 2017 (mostly from a huge increase in organic search volume, for basic terms like “what is machine learning”

In addition, prospects often come to the conversation with a tertiary understanding of the technology to start with, and seem to require less hand-holding understanding on the basics of neural nets and AI in general.

Her sentiments were shared by almost all of the companies I spoke with, and the trend is probably even more obvious from the perspective of investors. Brendan Kohler is co-founder and CTO Sentenai and also co-founder at Hyperplane Venture Capital: “Over the past 3 years as part of a machine intelligence focused venture fund we’ve seen a lot of companies mention AI….

The uptick in customer interest (read: more demand) has come higher prices of AI-related talent (read: limited supply). Most of the Boston firms I spoke with mentioned that talent has gotten more expensive.

While some companies (including Sentenai) mentioned that they had grabbed ML researchers from firms in California (with a little help from Boston’s better cost of living, and an interesting project to work on), it’s likely to suppose that Massachusetts in general loses more talent than it would like to big West Coast firms who can pay astronomic salaries and come along with more cache, cash, and clout than most any newborn Boston startup can offer.

Some of our interviewees doubt whether thousands of founders riding the AI hype-wave (by faking the use of AI, or using the term merely as a marketing term), and the same may be the case in academia –

When pressed about the pros and cons of the hype around machine learning, he went immediately to the impact on research: “The downside is that suppose I read an academic paper and spend a couple of months implementing that algorithm, but it doesn’t work since the paper has not considered some relevant factor,and has not been peer-reviewed;

Brendan Kohler himself mentioned both drug discovery and robotics again: “As an ecosystem Boston is really unique in that there has always been lot if talent in AI because the systems around robotic and drug manufacture have existed for a long time.

The good news about Boston creating lots of scientists (and not so many jobs) is that talent is more accessible. Mike Lacobucci is CEO of Interactions: “In Boston, and to an extent in New Jersey and New York, we have a concentration of some of the most well known data scientists in this field, some of whom were part of inventing this technology which made hiring a lot of talent in one place easier.” This may have to do with a difference in culture, which we’ll get into in greater depth in the “Boston vs San Francisco”

The fresh infusions of young, bright, ambitious young people to Boston schools is a massive advantage to the Boston ecosystem, and more or less every single person I spoke with echoed the same.

With a little poking and prying my interviewees, I coaxed out what I think is the differentiator from Boston and other college-heavy areas (Chicago, Philadelphia, etc) is the following: These obviously aren’t claims against other metro areas, they’re simple the stated “differentiators”

As for college “proximity”, I did a bit of homework: Apparently Los Angeles isn’t so far behind in terms of total university students in the greater metro area.

That being said, the Boston Metro Area spans a rather large stretch of land, down near Providence, RI and deep into New Hampshire: The founders I spoke with were likely talking about that little tight circle, where indeed there are a great many elite universities.

Nischal told me: “When [Boston] AI companies get to the point where they need to access more talent at bigger scale, that’s when they will have to make the decision of whether to move [to the Bay area] or to open an office;

Though it may be reeking havoc on the SF housing market, it seems to encourage an attitude that nonetheless is probably a plus when it comes time to grow something big: The ability to stomach risk.

Byron Galbraith, Chief Scientist at Talla put it well: “I find that Boston is incredibly conservative in terms of business and they tend to be very big serious businesses like biotechnology or hardware, things that have lots of capital expense, things that need a lot of people…

you can’t get a couple of grad students and start a business, these companies tend to go to San Francisco” In this statement Byron touches on the conservatism of Boston (sticking to what they know well), but he also touches on the “hard problems”

in terms of the tech scene I like Boston better, but access to capital and enthusiasm around new technologies is higher out there [Bay Area] in the general population.” Byron and I jested about how far this “enthusiasm”

For all it’s focus on academia, Cortex’s Brennan White sees Boston as somewhat more isolated in terms of its academic focus, Boston founders and talent might not cross-pollinate as much as other ecosystems do: “Having traveled to Toronto and San Francisco, there are three centers Stanford, MIT and University of Toronto, not necessarily in that order but Boston is a little bit more insular than the other cities, they seem to collaborate a lot more;

Two or three years ago I first started chatting with the team at BootstrapLabs here in SF (including covering and speaking at their annual Applied AI Conference), as the first had shifted their focus entirely to focus on artificial intelligence.

Brendan Kohler “The biggest gap here is that the funding ecosystem has moved out West, but that’s VC forms like Glasswing and Hyperplane are starting to turn the tide, so we are seeing a lot more companies stay here.”

don’t have any data on the number of Boston companies leaving for West Coast funding and whether than number has increased or decreased in the last 5 years, so I’m unable to back up that perspective.

Brendan has some interesting insight as to why Boston is behind SF in overall VC presence: “If you look at it from an ecosystem perspective, most of the long standing Boston venture funds made all their money in the 70s and 80s in the mini-computer revolution, they did not adapt to the consumer internet.

Because of that, fewer people became angel investors, and so there was never a virtuous cycle in the 90s like there was in SF where people who made money invested it back in the ecosystem.” Maybe Rana was right in stating that the consumer internet wasn’t a cultural fit for Boston in the first place, and Boston is better off focusing its VC funds on the B2B domains where it’s deepest strengths lie.

Over and over again, I heard companies say that their decision to stay in Boston was because they primarily sold to businesses, not consumers. Tomás Ratia García-Oliveros of expressed that this focus extends to investment capital as well: “Boston actual has some pretty robust venture capital, the volume maybe one third of SF, but there are VCs focused on AI here now, so if you have a market fit, there is really no shortage of funding.

Instead of re-hashing what’s been said before, I’ll address the classic points often brought up in the Boston vs SF debate, and then I’ll add a series of factors that might be specifically relevant for business leaders working on AI.

From the perspective of technical employees, it’s simple: When $50MM dollars is getting raised here, $100MM is being raised there, and the hottest companies from all over the world at moving to your city or opening offices there, you have options.

Jeremy Achin, founder and CEO of DataRobot (a firm with over 300 employees now, almost all of whom are in Boston), mentions the same sentiment, with a positive spin: “I think the silicon valley is not even a realistic place to have a company because of the competition in terms of costs, the amount of recruiting needed (high attrition), people don’t seem to be as hard working because there are so many options.

I’m sure this tendency has in some ways encouraged big companies to be birthed in the Bay Area, but it’s also a kind of risk that isn’t something all companies want to (or need to) endure in order to grow and prosper.

But if you have a mobile app or a B2C application, San Francisco is the place to be in mainly from a talent diversity point of view.” Abhi told me that SF is an important place to hire for specific kinds of technical talent.

(Fun fact: I lived in Mountain View for nearly a year, and it’s indeed common to see people with six figure salaries being crammed into small $3,500/mo apartments to save costs.) The following cost-of-living calculator at puts some of the broad cost comparisons in full view: Consumer prices, groceries, and (most importantly) rent is clearly higher.

in SF were brought up somewhat often: These factors by no means take away from the myriad benefits of the Bay Area, but they are factors to consider for early-stage companies looking to pick their HQ location.

The physical chill can be heart-warming for some, as snow brings with it: “Announced by all the trumpets of the sky, Arrives the snow, and, driving o’er the fields, Seems nowhere to alight: the whited air Hides hills and woods, the river, and the heaven, And veils the farm-house at the garden’s end.

The sled and traveller stopped, the courier’s feet Delayed, all friends shut out, the housemates sit Around the radiant fireplace, enclosed In a tumultuous privacy of storm.”

Romantic coziness aside, the bottom line for business is that Boston weather is bad, and in the dead of winter one could almost forgive the egregious relative cost of living in SF for the fact that you can wear sandals and bike to work year-round.

of that same hype: In Marie-Therese’s words: “We use the hype just to start getting people aware of what this [AI] is, in terms of who has the right to talk about it and how should it be talked about, I think that it is multidisciplinary, engineers are good at getting things to work well, but might not be thinking about how things might affect human behavior.” Esam Goodarzy brought up a point about the potential downside of adding a lot of enthusiasm atop a complex and challenging subject: “It’s natural when something gets popular the conversation gets oversaturated with information;

what I’m worried about the hype is that there’s so many topics that everything gets leveled out and in terms of what’s the most important aspects to be focusing our efforts on from an altruistic perspective.” Admittedly, it’s challenging to know whether privacy, racial bias, or superintelligence are the most important on a utilitarian scale.

Edmond Awad is a postdoctoral associate at MIT Media Lab, and he runs a project called Moral Machine, aggregating human ethical sentiments around AI moral dilemmas (such as self-driving cars having to choose between crashing, or hitting pedestrians).

The recent AI collaboration between IBM and MIT (establishing the new MIT–IBM Watson AI Lab, thanks to a 10-year plan for IBM to invest $240MM in the lab) began with a call for papers, including papers about “advancing shared prosperity through AI”, a topic we might not have suspected to see just a few years ago.


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