All posts in “Private Equity”

Andrew Ng is raising a $150M AI Fund


We knew that Andrew Ng had more than just a series of deep learning courses up his sleeve when he announced the first phase of his deeplearning.ai last week. It’s clear now that the turn of Ng’s three part act is a $150 million venture capital fund, first noted by PEHub, targeting AI investments.

Ng, who formerly founded Google’s Brain Team and served as chief scientist at Baidu has long evangelized the benefits AI could bring to the world. During an earlier conversation, Ng told me that his personal goal is to help bring about an AI-powered society. It would follow that education via his deep learning classes is one step of that and providing capital and other resources is another.

2017 has been a particularly active year for starting AI-focused venture capital funds. In the last few months we have seen Google roll out Gradient Ventures, Basis Set Ventures hall in $136 million, Element.AI raise $102 million, Microsoft Ventures start its own AI fund and Toyota corral $100 million for AI investment.

It’s unclear at this point how Ng’s AI Fund will differentiate from the pack. Many of these funds are putting time and resources into securing data sets, technical mentors and advanced simulation tools to support the unique needs of AI startups. Of course Ng’s name recognition and network should help ensure solid deal flow and enable Ng to poach and train talent for startups in need of scarce deep learning engineers.

I’ve sent a note to Andrew and we will update this post if and when we get more details.

Featured Image: Dawn Endico/Flickr UNDER A CC BY-SA 2.0 LICENSE

A running list of every company backed by the $93B SoftBank Vision Fund

When SoftBank announced the first close of its $93 billion Vision Fund back in May, it was hard to understand how the company would even manage to deploy so much capital in an already saturated ecosystem. Two months have passed and we’re starting to get a taste of the strategy of the fund — bet big and bet often and you just might be able to influence who wins and loses in the technology industry.

It’s far too early to evaluate the viability of such a fund. This is the first time such a fund has been raised and there is zero precedent for the manner in which the capital is being deployed. But, for starters, it seemed like a good idea to keep a running list of all Vision Fund investments for reference. We will update this list on a regular basis as more deals are made public.

Reach Robotics closes $7.5M Series A for its augmented reality bots


After years of research and development, Reach Robotics has closed a $7.5 million Series A, co-led by Korea Investment Partners (KiP) and IGlobe, to bring its augmented reality bots to market in a big way. The Bristol-based startup is looking to expand into the U.S., and the team is exploring opportunities for growth into other European and Asian markets.

Reach Robotics’ first product, MekaMon, launched last fall. Today’s round comes after the company produced and sold an initial run of 500 of its four-legged, crab-like, bots. MekaMon fits into an emerging category of smartphone-enabled augmented reality toys like Anki.

Silas Adekunle, CEO of Reach Robotics, tells me the influx of capital will be used to make some strategic hires and increase brand recognition through marketing. This is the first time the startup has announced a funding round. Adekunle tells me his experience raising capital wasn’t easy; as they say, hardware is hard.

“It was hard to pitch in our early days because people didn’t believe,” explained Adekunle.

MekaMon sits somewhere between toy and full-fledged robot. Unlike the radio-controlled RadioShack robots of yesteryear, MekaMon costs a hefty $329. At first glance this can be hard to swallow, but Adekunle remains adamant that he is building a platform and not a line of toys — think PS4 instead of an expensive, single-use robot collecting dust on a shelf.

Outside of retail sales, another avenue for the company to make money is through partnerships within the entertainment industry. Adekunle says that Reach would never go out of its way to deliver a specific product for a client, but he always keeps an eye out for overlap where a partnership could occur with minimal operational changes.

“People are taken aback that something could be this realistic,” asserts Adekunle. “If you strip back the product and lose that, then you don’t have an innovative company.”

Because Reach is selling software-enabled hardware, it has the opportunity to collect all sorts of interesting data that it can use to fine-tune its products. The startup is able to track retention in aggregate and look at how people actually use their robots. Moreover, if MekaMon suffers leg failure, Reach can analyze indicators like temperature readings and torque.

Adekunle insists on keeping the Reach Robotics team interdisciplinary — one employee helped shape the way robots move in the Transformers movie series. This same team is focused on empowering the next group of developers who will build on the MekaMon platform and create new use cases, beyond the company’s initial vision for the product.

Here are the winners of the Google Cloud machine learning pitch-off


Back in March at Google’s Cloud Next conference, the company announced plans to run its own machine learning startup competition side-by-side with Data Collective and Emergence Capital. Four months later, 10 startups, pulled from a pool of 350+ applicants, presented onstage at Google’s Launchpad Space in San Francisco.

The startups vied for three prizes — a choice each from DCVC and Emergence, as well as a Built with Google award for the top startup utilizing Google’s Cloud Platform. Additionally, Google provided $200k in GCP credits to all finalists. In advance of the competition, both VC firms committed to providing seed capital to their selections and both were involved from the beginning in diligencing applicants.

The event is in many ways the physical manifestation of GCP’s strategy to cozy up with machine intelligence startups. Google Cloud still lags behind Amazon and Microsoft in usage and the company is trying to position itself as “friendly” to a class of startups that will surely generate immense amounts of data at scale that needs to be stored somewhere. Founders participating in the competition pointed to both Kubernetes and TensorFlow as selling points for GCP — and of course, the free cloud credits don’t hurt.

We’ve briefly profiled the winners of each prize below and included a description of their reward.

DCVC’s Choice – BrainSpec

Alex Zimmerman, CEO of BrainSpec

$500K investment

BrainSpec is building its own platform that helps doctors measure brain metabolites using standard MRI equipment. Metabolites are the chemical result of cellular processes and often hold the key to understanding brain injuries, Alzheimer’s and other brain disorders.

Doctors can use Magnetic Resonance Spectroscopy, a traditionally complex process, to perform chemical analysis of tissue to detect key indicators of these neurological diseases. BrainSpec is simplifying this technique with a web interface and cloud-based statistical analysis.

Matt Ocko, a partner at DCVC, explained his investment by speaking to the sheer market size of the problem BrainSpec is looking to address. The startup brings strong domain expertise to a product with a clear path to productization and regulatory approval.

Emergence Capital’s Choice – LiftIgniter

Adam Spector, co-founder of LiftIgniter

$500K investment 

LiftIgniter, a former TC Disrupt Battlefield competitor, wants to help businesses personalize the content they deliver to users. Today, big players like Amazon and Spotify have their own advanced recommendation systems that drive engagement, but many other businesses struggle to deliver the same demanding technology.

The team, which had experience building YouTube’s machine learning recommendation system, is productizing its service around an API. The company says it has never lost an A/B test and is seeing strong traction with 1.8 million in ARR and 22 percent month-over-month growth.

The team also won an extra $500K in GCP credits as the runner-up for the Built with Google Award.

Built with Google Award – PicnicHealth

Noga Leviner, CEO of PicnicHealth

$1M in GCP credits

PicnicHealth is layering machine learning on top of its centralized digital medical record system to produce outcomes data for pharmaceutical companies and research groups.

The startup combines automated extraction with a team of human nurses to annotate anonymized records. Pharmaceutical companies in particular are willing to pay serious money for data to the extent that PicnicHealth is seeing $5,000 gross margins.

Patients using the consumer side of the platform retain control of their data and are in charge of entering their care providers. From there, Picnic automates record collection, analysis and releases.

Datatron raises $2.7M to help companies query real-time and historical data


Fresh out of 500 startups, Datatron has raised $2.7 million in seed financing for its data-savvy assistant, Emma. But under the somewhat trite coating of an assistant, Datatron is making it easier for employees to gather insights from the complex web of historical and real-time data.

Businesses generate hordes of data on uneven timelines. Some data is updated less frequently, like the number of Uber drivers registered in a given city. Other data is updated to the minute, like the number of active Uber drivers on standby for pickup. Combine this with the myriad other types of data and business logic and you create an intricate mesh of data that’s difficult to derive conclusions from.

Founded by Harish Doddi and Jerry Xu, Datatron helps businesses apply this data to specific use cases within traditional verticals like sales, marketing and finance. From a simplified dashboard, users can query key indicators derived from predictive models held within the platform.

Datatron originated as a platform solution for enterprises — performing real-time feature extraction and data cleansing to speed up the process by which insights can be derived from data. In recent months, the company added the aforementioned means of top-level interaction to open up the power of the platform to a wider audience.

One of the system’s early optimizations is for sales — helping teams quickly evaluate leads and determine where to spend their precious time and resources. Datatron ships with key integrations for platforms like Zuora, Salesforce, Marketo and Zendesk.

The company has raised capital from Start X, Credence Partners, Authentic Ventures, Enspire Partners, Plug and Play and 500 Startups, and says it’s already working with a number of early customers.

Featured Image: John Lund/Getty Images