May
20
2020
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Directly, which taps experts to train chatbots, raises $11M, closes out Series B at $51M

Directly, a startup whose mission is to help build better customer service chatbots by using experts in specific areas to train them, has raised more funding as it opens up a new front to grow its business: APIs and a partner ecosystem that can now also tap into its expert network. Today Directly is announcing that it has added $11 million to close out its Series B at $51 million (it raised $20 million back in January of this year, and another $20 million as part of the Series B back in 2018).

The funding is coming from Triangle Peak Partners and Toba Capital, while its previous investors in the round included strategic backers Samsung NEXT and Microsoft’s M12 Ventures (who are both customers, alongside companies like Airbnb), as well as Industry Ventures, True Ventures, Costanoa Ventures and Northgate. (As we reported when covering the initial close, Directly’s valuation at that time was at $110 million post-money, and so this would likely put it at $120 million or higher, given how the business has expanded.)

While chatbots have now been around for years, a key focus in the tech world has been how to help them work better, after initial efforts saw so many disappointing results that it was fair to ask whether they were even worth the trouble.

Directly’s premise is that the most important part of getting a chatbot to work well is to make sure that it’s trained correctly, and its approach to that is very practical: find experts both to troubleshoot questions and provide answers.

As we’ve described before, its platform helps businesses identify and reach out to “experts” in the business or product in question, collect knowledge from them, and then fold that into a company’s AI to help train it and answer questions more accurately. It also looks at data input and output into those AI systems to figure out what is working, and what is not, and how to fix that, too.

The information is typically collected by way of question-and-answer sessions. Directly compensates experts both for submitting information as well as to pay out royalties when their knowledge has been put to use, “just as you would in traditional copyright licensing in music,” its co-founder Antony Brydon explained to me earlier this year.

It can take as little as 100 experts, but potentially many more, to train a system, depending on how much the information needs to be updated over time. (Directly’s work for Xbox, for example, used 1,000 experts but has to date answered millions of questions.)

Directly’s pitch to customers is that building a better chatbot can help deflect more questions from actual live agents (and subsequently cut operational costs for a business). It claims that customer contacts can be reduced by up to 80%, with customer satisfaction by up to 20%, as a result.

What’s interesting is that now Directly sees an opportunity in expanding that expert ecosystem to a wider group of partners, some of which might have previously been seen as competitors. (Not unlike Amazon’s AI powering a multitude of other businesses, some of which might also be in the market of selling the same services that Amazon does).

The partner ecosystem, as Directly calls it, use APIs to link into Directly’s platform. Meya, Percept.ai, and SmartAction — which themselves provide a range of customer service automation tools — are three of the first users.

“The team at Directly have quickly proven to be trusted and invaluable partners,” said Erik Kalviainen, CEO at Meya, in a statement. “As a result of our collaboration, Meya is now able to take advantage of a whole new set of capabilities that will enable us to deliver automated solutions both faster and with higher resolution rates, without customers needing to deploy significant internal resources. That’s a powerful advantage at a time when scale and efficiency are key to any successful customer support operation.”

The prospect of a bigger business funnel beyond even what Directly was pulling in itself is likely what attracted the most recent investment.

“Directly has established itself as a true leader in helping customers thrive during these turbulent economic times,” said Tyler Peterson, Partner at Triangle Peak Partners, in a statement. “There is little doubt that automation will play a tremendous role in the future of customer support, but Directly is realizing that potential today. Their platform enables businesses to strike just the right balance between automation and human support, helping them adopt AI-powered solutions in a way that is practical, accessible, and demonstrably effective.”

In January, Mike de la Cruz, who took over as CEO at the time of the funding announcement, said the company was gearing up for a larger Series C in 2021. It’s not clear how and if that will be impacted by the current state of the world. But in the meantime, as more organizations are looking for ways to connect with customers outside of channels that might require people to physically visit stores, or for employees to sit in call centres, it presents a huge opportunity for companies like this one.

“At its core, our business is about helping customer support leaders resolve customer issues with the right mix of automation and human support,” said de la Cruz in a statement. “It’s one thing to deliver a great product today, but we’re committed to ensuring that our customers have the solutions they need over the long term. That means constantly investing in our platform and expanding our capabilities, so that we can keep up with the rapid pace of technological change and an unpredictable economic landscape. These new partnerships and this latest expansion of our recent funding round have positioned us to do just that. We’re excited to be collaborating with our new partners, and very thankful to all of our investors for their support.”

May
19
2020
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Microsoft launches Project Bonsai, its new machine teaching service for building autonomous systems

At its Build developer conference, Microsoft today announced that Project Bonsai, its new machine teaching service, is now in public preview.

If that name sounds familiar, it’s probably because you remember that Microsoft acquired Bonsai, a company that focuses on machine teaching, back in 2018. Bonsai combined simulation tools with different machine learning techniques to build a general-purpose deep reinforcement learning platform, with a focus on industrial control systems.

It’s maybe no surprise then that Project Bonsai, too, has a similar focus on helping businesses teach and manage their autonomous machines. “With Project Bonsai, subject-matter experts can add state-of-the-art intelligence to their most dynamic physical systems and processes without needing a background in AI,” the company notes in its press materials.

“The public preview of Project Bonsai builds on top of the Bonsai acquisition and the autonomous systems private preview announcements made at Build and Ignite of last year,” a Microsoft spokesperson told me.

Interestingly, Microsoft notes that project Bonsai is only the first block of a larger vision to help its customers build these autonomous systems. The company also stresses the advantages of machine teaching over other machine learning approach, especially the fact that it’s less of a black box approach than other methods, which makes it easier for developers and engineers to debug systems that don’t work as expected.

In addition to Bonsai, Microsoft also today announced Project Moab, an open-source balancing robot that is meant to help engineers and developers learn the basics of how to build a real-world control system. The idea here is to teach the robot to keep a ball balanced on top of a platform that is held by three arms.

Potential users will be able to either 3D print the robot themselves or buy one when it goes on sale later this year. There is also a simulation, developed by MathWorks, that developers can try out immediately.

“You can very quickly take it into areas where doing it in traditional ways would not be easy, such as balancing an egg instead,” said Mark Hammond, Microsoft General Manager
for Autonomous Systems. “The point of the Project Moab system is to provide that
playground where engineers tackling various problems can learn how to use the tooling and simulation models. Once they understand the concepts, they can apply it to their novel use case.”

May
18
2020
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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 that helps do precisely that is announcing a growth round of funding after seeing engagement on its 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. The startup was founded in Brisbane, Australia and now has operations also based out of San Francisco — it was part of a Y Combinator cohort back in 2015 — and more specifically, it wants to continue growth in North America, and to continue expanding its partner network.

GO1 not disclosing its valuation but we are asking. It’s worth pointing out that not only has it seen engagement triple in the last month as companies turn to online learning to keep users connected to their professional lives even 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 health 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 Venture Group 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 another previous backer, 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 whose employees typically have never before 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 but actually just as important, such as making sure people remain in a healthy state of mind about work. Education is one way of getting them on the right track: professional development is not only useful for the person to do her or his job better, but it’s a way to motivate people, to focus their minds, and take a rest from their routines, but 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.

May
14
2019
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Algorithmia raises $25M Series B for its AI automation platform

Algorithmia, a Seattle-based startup that offers a cloud-agnostic AI automation platform for enterprises, today announced a $25 million Series B funding round led by Norwest Partners. Madrona, Gradient Ventures, Work-Bench, Osage University Partners and Rakuten Ventures also participated in this round.

While the company started out five years ago as a marketplace for algorithms, it now mostly focuses on machine learning and helping enterprises take their models into production.

“It’s actually really hard to productionize machine learning models,” Algorithmia CEO Diego Oppenheimer told me. “It’s hard to help data scientists to not deal with data infrastructure but really being able to build out their machine learning and AI muscle.”

To help them, Algorithmia essentially built out a machine learning DevOps platform that allows data scientists to train their models on the platform and with the framework of their choice, bring it to Algorithmia — a platform that has already been blessed by their IT departments — and take it into production.

“Every Fortune 500 CIO has an AI initiative but they are bogged down by the difficulty of managing and deploying ML models,” said Rama Sekhar, a partner at Norwest Venture Partners, who has now joined the company’s board. “Algorithmia is the clear leader in building the tools to manage the complete machine learning life cycle and helping customers unlock value from their R&D investments.”

With the new funding, the company will double down on this focus by investing in product development to solve these issues, but also by building out its team, with a plan to double its headcount over the next year. A year from now, Oppenheimer told me, he hopes that Algorithmia will be a household name for data scientists and, maybe more importantly, their platform of choice for putting their models into production.

“How does Algorithmia succeed? Algorithmia succeeds when our customers are able to deploy AI and ML applications,” Oppenheimer said. “And although there is a ton of excitement around doing this, the fact is that it’s really difficult for companies to do so.”

The company previously raised a $10.5 million Series A round led by Google’s AI fund. It’s customers now include the United Nations, a number of U.S. intelligence agencies and Fortune 500 companies. In total, more than 90,000 engineers and data scientists are now on the platform.

May
13
2019
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Market map: the 200+ innovative startups transforming affordable housing

In this section of my exploration into innovation in inclusive housing, I am digging into the 200+ companies impacting the key phases of developing and managing housing.

Innovations have reduced costs in the most expensive phases of the housing development and management process. I explore innovations in each of these phases, including construction, land, regulatory, financing, and operational costs.

Reducing Construction Costs

This is one of the top three challenges developers face, exacerbated by rising building material costs and labor shortages.

May
02
2019
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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.

Mar
28
2019
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Microsoft gives 500 patents to startups

Microsoft today announced a major expansion of its Azure IP Advantage program, which provides its Azure users with protection against patent trolls. This program now also provides customers who are building IoT solutions that connect to Azure with access to 10,000 patents to defend themselves against intellectual property lawsuits.

What’s maybe most interesting here, though, is that Microsoft is also donating 500 patents to startups in the LOT Network. This organization, which counts companies like Amazon, Facebook, Google, Microsoft, Netflix, SAP, Epic Games, Ford, GM, Lyft and Uber among its close to 400 members, is designed to protect companies against patent trolls by giving them access to a wide library of patents from its member companies and other sources.

“The LOT Network is really committed to helping address the proliferation of intellectual property lawsuits, especially ones that are brought by non-practicing entities, or so-called trolls,” Microsoft  CVP and Deputy General Counsel Erich Andersen told me. 

This new program goes well beyond basic protection from patent trolls, though. Qualified startups who join the LOT Network can acquire Microsoft patents as part of their free membership and as Andersen stressed, the startups will own them outright. The LOT network will be able to provide its startup members with up to three patents from this collection.

There’s one additional requirement here, though: To qualify for getting the patents, these startups also have to meet a $1,000 per month Azure spend. As Andersen told me, though, they don’t have to make any kind of forward pledge. The company will simply look at a startup’s last three monthly Azure bills.

“We want to help the LOT Network grow its network of startups,” Andersen said. “To provide an incentive, we are going to provide these patents to them.” He noted that startups are obviously interested in getting access to patents as a foundation of their companies, but also to raise capital and to defend themselves against trolls.

The patents we’re talking about here cover a wide range of technologies as well as geographies. Andersen noted that we’re talking about U.S. patents as well as European and Chinese patents, for example.

“The idea is that these startups come from a diverse set of industry sectors,” he said. “The hope we have is that when they approach LOT, they’ll find patents among those 500 that are going to be interesting to basically almost any company that might want a foundational set of patents for their business.”

As for the extended Azure IP Advantage program, it’s worth noting that every Azure customer who spends more than $1,000 per month over the past three months and hasn’t filed a patent infringement lawsuit against another Azure customer in the last two years can automatically pick one of the patents in the program’s portfolio to protect itself against frivolous patent lawsuits from trolls (and that’s a different library of patents from the one Microsoft is donating to the LOT Network as part of the startup program).

As Andersen noted, the team looked at how it could enhance the IP program by focusing on a number of specific areas. Microsoft is obviously investing a lot into IoT, so extending the program to this area makes sense. “What we’re basically saying is that if the customer is using IoT technology — regardless of whether it’s Microsoft technology or not — and it’s connected to Azure, then we’re going to provide this patent pick right to help customers defend themselves against patent suits,” Andersen said.

In addition, for those who do choose to use Microsoft IoT technology across the board, Microsoft will provide indemnification, too.

Patent trolls have lately started acquiring IoT patents, so chances are they are getting ready to make use of them and that we’ll see quite a bit of patent litigation in this space in the future. “The early signs we’re seeing indicate that this is something that customers are going to care about in the future,” said Andersen.

Feb
14
2019
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Peltarion raises $20M for its AI platform

Peltarion, a Swedish startup founded by former execs from companies like Spotify, Skype, King, TrueCaller and Google, today announced that it has raised a $20 million Series A funding round led by Euclidean Capital, the family office for hedge fund billionaire James Simons. Previous investors FAM and EQT Ventures also participated, and this round brings the company’s total funding to $35 million.

There is obviously no dearth of AI platforms these days. Peltarion focus on what it calls “operational AI.” The service offers an end-to-end platform that lets you do everything from pre-processing your data to building models and putting them into production. All of this runs in the cloud and developers get access to a graphical user interface for building and testing their models. All of this, the company stresses, ensures that Peltarion’s users don’t have to deal with any of the low-level hardware or software and can instead focus on building their models.

“The speed at which AI systems can be built and deployed on the operational platform is orders of magnitude faster compared to the industry standard tools such as TensorFlow and require far fewer people and decreases the level of technical expertise needed,” Luka Crnkovic-Friis, of Peltarion’s CEO and co-founder, tells me. “All this results in more organizations being able to operationalize AI and focusing on solving problems and creating change.”

In a world where businesses have a plethora of choices, though, why use Peltarion over more established players? “Almost all of our clients are worried about lock-in to any single cloud provider,” Crnkovic-Friis said. “They tend to be fine using storage and compute as they are relatively similar across all the providers and moving to another cloud provider is possible. Equally, they are very wary of the higher-level services that AWS, GCP, Azure, and others provide as it means a complete lock-in.”

Peltarion, of course, argues that its platform doesn’t lock in its users and that other platforms take far more AI expertise to produce commercially viable AI services. The company rightly notes that, outside of the tech giants, most companies still struggle with how to use AI at scale. “They are stuck on the starting blocks, held back by two primary barriers to progress: immature patchwork technology and skills shortage,” said Crnkovic-Friis.

The company will use the new funding to expand its development team and its teams working with its community and partners. It’ll also use the new funding for growth initiatives in the U.S. and other markets.

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