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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