Abacus.AI raises another $22M and launches new AI modules

AI startup RealityEngines.AI changed its name to Abacus.AI in July. At the same time, it announced a $13 million Series A round. Today, only a few months later, it is not changing its name again, but it is announcing a $22 million Series B round, led by Coatue, with Decibel Ventures and Index Partners participating as well. With this, the company, which was co-founded by former AWS and Google exec Bindu Reddy, has now raised a total of $40.3 million.

Abacus co-founder Bindu Reddy, Arvind Sundararajan and Siddartha Naidu. Image Credits: Abacus.AI

In addition to the new funding, Abacus.AI is also launching a new product today, which it calls Abacus.AI Deconstructed. Originally, the idea behind RealityEngines/Abacus.AI was to provide its users with a platform that would simplify building AI models by using AI to automatically train and optimize them. That hasn’t changed, but as it turns out, a lot of (potential) customers had already invested into their own workflows for building and training deep learning models but were looking for help in putting them into production and managing them throughout their lifecycle.

“One of the big pain points [businesses] had was, ‘look, I have data scientists and I have my models that I’ve built in-house. My data scientists have built them on laptops, but I don’t know how to push them to production. I don’t know how to maintain and keep models in production.’ I think pretty much every startup now is thinking of that problem,” Reddy said.

Image Credits: Abacus.AI

Since Abacus.AI had already built those tools anyway, the company decided to now also break its service down into three parts that users can adapt without relying on the full platform. That means you can now bring your model to the service and have the company host and monitor the model for you, for example. The service will manage the model in production and, for example, monitor for model drift.

Another area Abacus.AI has long focused on is model explainability and de-biasing, so it’s making that available as a module as well, as well as its real-time machine learning feature store that helps organizations create, store and share their machine learning features and deploy them into production.

As for the funding, Reddy tells me the company didn’t really have to raise a new round at this point. After the company announced its first round earlier this year, there was quite a lot of interest from others to also invest. “So we decided that we may as well raise the next round because we were seeing adoption, we felt we were ready product-wise. But we didn’t have a large enough sales team. And raising a little early made sense to build up the sales team,” she said.

Reddy also stressed that unlike some of the company’s competitors, Abacus.AI is trying to build a full-stack self-service solution that can essentially compete with the offerings of the big cloud vendors. That — and the engineering talent to build it — doesn’t come cheap.

Image Credits: Abacus.AI

It’s no surprise then that Abacus.AI plans to use the new funding to increase its R&D team, but it will also increase its go-to-market team from two to ten in the coming months. While the company is betting on a self-service model — and is seeing good traction with small- and medium-sized companies — you still need a sales team to work with large enterprises.

Come January, the company also plans to launch support for more languages and more machine vision use cases.

“We are proud to be leading the Series B investment in Abacus.AI, because we think that Abacus.AI’s unique cloud service now makes state-of-the-art AI easily accessible for organizations of all sizes, including start-ups. Abacus.AI’s end-to-end autonomous AI service powered by their Neural Architecture Search invention helps organizations with no ML expertise easily deploy deep learning systems in production.”

 


By Frederic Lardinois

GO1, an enterprise learning platform, picks up $40M from Microsoft, Salesforce and more

With a large proportion of knowledge workers doing now doing their jobs from home, the need for tools to help them feel connected to their profession can be as important as tools to, more practically, keep them connected. Today, a company whose platform helps do precisely that is announcing a growth round of funding after seeing engagement on the platform triple in the last month.

GO1.com, an online learning platform focused specifically on professional training courses (both those to enhance a worker’s skills as well as those needed for company compliance training), is today announcing that it has raised $40 million in funding, a Series C that it plans to use to continue expanding its business, which started out in Brisbane, Australia and now has its operations also based out of San Francisco. (It was part of a Y Combinator cohort back in 2015.) Specifically, it wants to continue growth in North America, and to continue expanding its partner network.

It’s not disclosing its valuation but we are asking. It’s worth pointing out that not only has GO1 seen engagement triple in the last month as people turn to online learning as one way of keeping users connected to their professional lives as they work among children and house pets, noisy neighbours, dirty laundry, sourdough starters, and the rest — and that’s before you count the harrowing news we are hit with on a regular basis. But even beyond that, longer term GO1 has shown some strong signs that speak of its traction.

It counts the likes of the University of Oxford, Suzuki, Asahi and Thrifty among its 3,000+ customers, with more than 1.5 million users overall able to access over 170,000 courses and other resources provided by some 100 vetted content partners. Overall usage has grown five-fold over the last 12 months. (GO1 works both with in-house learning management systems or provides its own.)

“GO1’s growth over the last couple of months has been unprecedented and the use of online tools for training is now undergoing a structural shift,” said Andrew Barnes, CEO of GO1, in a statement. “It is gratifying to fill an important void right now as workers embrace online solutions. We are inspired about the future that we are building as we expand our platform with new mediums that reach millions of people every day with the content they need.”

The funding is coming from a very strong list of backers: it’s being co-led by Madrona and SEEK — the online recruitment and course directory company that has backed a number of edtech startups, including FutureLearn and Coursera — with participation also from Microsoft’s venture arm M12; new backer Salesforce Ventures, the investing arm of the CRM giant; and Our Innovation Fund.

Microsoft is a strategic backer: GO1 integrated with Teams, so now users can access GO1 content directly via Microsoft’s enterprise-facing video and messaging platform.

“GO1 has been critical for business continuity as organizations navigate the remote realities of COVID-19,” said Nagraj Kashyap, Microsoft Corporate Vice President and Global Head of M12, in a statement. “The GO1 integration with Microsoft Teams offers a seamless learning experience at a time when 75 million people are using the application daily. We’re proud to invest in a solution helping keep employees learning and businesses growing through this time.”

Similarly, Salesforce is also coming in as a strategic, integrating this into its own online personal development products and initiatives.

“We are excited about partnering with GO1 as it looks to scale its online content hub globally. While the majority of corporate learning is done in person today, we believe the new digital imperative will see an acceleration in the shift to online learning tools. We believe GO1 fits well into the Trailhead ecosystem and our vision of creating the life-long learner journey,” said Rob Keith, Head of Australia, Salesforce Ventures, in a statement.

Working remotely has raised a whole new set of challenges for organizations, especially those whos employees typically have not worked for days, weeks and months outside of the office. Some of these have been challenges of a more basic IT nature: getting secure access to systems on the right kinds of machines and making sure people can communicate in the ways that they need to to get work done.

But others are more nuanced and long-term: making sure people remain focused and motivated and in a healthy state of mind about work. Education is one way of getting them focused in the latter way: professional development is not only useful for the person to do her or his job better, but it’s a way to motivate them and focus their minds, and rest from routine, in a way that still remains relevant to work.

GO1 is absolutely not the only company pursuing this opportunity. Others include Udemy and Coursera, which have both come to enterprise after initially focusing more on traditional education plays. And LinkedIn Learning (which used to be known as Lynda, before LinkedIn acquired it and shifted the branding) was a trailblazer in this space.

For these, enterprise training sits in a different strategic place to GO1, which started out with compliance training and onboarding of employees before gravitating into a much wider set of topics that range from photography and design, through to Java, accounting, and even yoga and mindfulness training and everything in between.

It’s perhaps the directional approach, alongside its success, that have set GO1 apart from the competition and that has attracted the investment, which seems to have come ahead even of the current boost in usage.

“We met GO1 many months before COVID-19 was on the tip of everyone’s tongue and were impressed then with the growth of the platform and the ability of the team to expand their corporate training offering significantly in North America and Europe,” commented S. Somasegar, managing director, Madrona Venture Group, in a statement. “The global pandemic has only increased the need to both provide training and retraining – and also to do it remotely. GO1 is an important link in the chain of recovery.” As part of the funding Somasegar will join the GO1 board of directors.

Notably, GO1 is currently making all COVID-19 related learning resources available for free “to help teams continue to perform and feel supported during this time of disruption and change,” the company said.


By Ingrid Lunden

RealityEngines.AI raises $5.25M seed round to make ML easier for enterprises

RealityEngines.AI, a research startup that wants to help enterprises make better use of AI, even when they only have incomplete data, today announced that it has raised a $5.25 million seed funding round. The round was led by former Google CEO and Chairman Eric Schmidt and Google founding board member Ram Shriram. Khosla Ventures, Paul Buchheit, Deepchand Nishar, Elad Gil, Keval Desai, Don Burnette and others also participated in this round.

The fact that the service was able to raise from this rather prominent group of investors clearly shows that its overall thesis resonates. The company, which doesn’t have a product yet, tells me that it specifically wants to help enterprises make better use of the smaller and noisier datasets they have and provide them with state-of-the-art machine learning and AI systems that they can quickly take into production. It also aims to provide its customers with systems that can explain their predictions and are free of various forms of bias, something that’s hard to do when the system is essentially a black box.

As RealityEngines CEO Bindu Reddy, who was previously the head of products for Google Apps, told me the company plans to use the funding to build out its research and development team. The company, after all, is tackling some of the most fundamental and hardest problems in machine learning right now — and that costs money. Some, like working with smaller datasets, already have some available solutions like generative adversarial networks that can augment existing datasets and that RealityEngines expects to innovate on.

Reddy is also betting on reinforcement learning as one of the core machine learning techniques for the platform.

Once it has its product in place, the plan is to make it available as a pay-as-you-go managed service that will make machine learning more accessible to large enterprise, but also to small and medium businesses, which also increasingly need access to these tools to remain competitive.


By Frederic Lardinois

Microsoft launches a drag-and-drop machine learning tool

Microsoft today announced three new services that all aim to simplify the process of machine learning. These range from a new interface for a tool that completely automates the process of creating models, to a new no-code visual interface for building, training and deploying models, all the way to hosted Jupyter-style notebooks for advanced users.

Getting started with machine learning is hard. Even to run the most basic of experiments take a good amount of expertise. All of these new tools great simplify this process by hiding away the code or giving those who want to write their own code a pre-configured platform for doing so.

The new interface for Azure’s automated machine learning tool makes creating a model as easy importing a data set and then telling the service which value to predict. Users don’t need to write a single line of code, while in the backend, this updated version now supports a number of new algorithms and optimizations that should result in more accurate models. While most of this is automated, Microsoft stresses that the service provides “complete transparency into algorithms, so developers and data scientists can manually override and control the process.”

For those who want a bit more control from the get-go, Microsoft also today launched a visual interface for its Azure Machine Learning service into preview that will allow developers to build, train and deploy machine learning models without having to touch any code.

This tool, the Azure Machine Learning visual interface looks suspiciously like the existing Azure ML Studio, Microsoft’s first stab at building a visual machine learning tool. Indeed, the two services look identical. The company never really pushed this service, though, and almost seemed to have forgotten about it despite that fact that it always seemed like a really useful tool for getting started with machine learning.

Microsoft says that this new version combines the best of Azure ML Studio with the Azure Machine Learning service. In practice, this means that while the interface is almost identical, the Azure Machine Learning visual interface extends what was possible with ML Studio by running on top of the Azure Machine Learning service and adding that services’ security, deployment and lifecycle management capabilities.

The service provides an easy interface for cleaning up your data, training models with the help of different algorithms, evaluating them and, finally, putting them into production.

While these first two services clearly target novices, the new hosted notebooks in Azure Machine Learning are clearly geared toward the more experiences machine learning practitioner. The notebooks come pre-packaged with support for the Azure Machine Learning Python SDK and run in what the company describes as a “secure, enterprise-ready environment.” While using these notebooks isn’t trivial either, this new feature allows developers to quickly get started without the hassle of setting up a new development environment with all the necessary cloud resources.


By Frederic Lardinois