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Relativity Space raises $500 million as its sets sights on the industrialization of Mars

3D-printed rocket startup Relativity Space has closed $500 million in Series D funding (making official the earlier reported raise), the company announced today. This funding was led by Tiger Global Management, and included participation by a host of new investors including Fidelity Management & Research Company, Baillie Gifford, Iconiq Capital, General Catalist and more. This brings the company’s total raised so far to nearly $700 million, as the startup is poised to launch its first ever fully 3D-printed orbital rocket next year.

LA-based Relativity had a big 2020, completing work on a new 120,000 square-foot manufacturing facility in Long Beach. Its rocket construction technology, which is grounded in its development and use of the largest metal 3D printers in existence, suffered relatively few setbacks due to COVID-19-related shutdowns and work stoppages since it involves relatively few actual people on the factory floor managing the 3D printing process, which is handled in large part by autonomous robotic systems and software developed by the company.

Relativity also locked in a first official contract from the U.S. government this year, to launch a new experimental cryogenic fluid management system on behalf of client Lockheed Martin, as part of NASA’s suite of Tipping Point contracts to fund the development of new technologies for space exploration. It also put into service its third-generation Stargate 3D metal printers – the largest on Earth, as mentioned.

The company’s ambitions are big, so this new large funding round should provide it with fuel to grow even more aggressively in 2021. It’s got new planned initiatives underway, both terrestrial and space-related, but CEO and founder Tim Ellis specifically referred to Mars and sustainable operations on the red planet as one possible application of Relativity’s tech down the road.

In prior conversations, Ellis has alluded to the potential for Relativity’s printers when applied to other large-scale metal manufacturing – noting that the cost curve as it stands makes most sense for rocketry, but could apply to other industries easily as the technology matures. Whether on Mars or on Earth, large-scale 3D printing definitely has a promising future, and it looks like Relativity is well-positioned to take advantage.

We’ll be talking to Ellis at our forthcoming TC Sessions: Space event, so we’ll ask him more about this round and his company’s aspirations live there, too.

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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,” Yanda Erlich, a p artner at Coatue Ventures  told me. “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.”

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Provizio closes $6.2M seed round for its car safety platform using sensors and AI

Provizio, a combination hardware and software startup with technology to improve car safety, has closed a seed investment round of $6.2million. Investors include Bobby Hambrick (the founder of Autonomous Stuff); the founders of Movidius; the European Innovation Council (EIC); ACT Venture Capital.

The startup has a “five-dimensional” sensory platform that — it says — perceives, predicts and prevents car accidents in real time and beyond the line-of-sight. Its “Accident Prevention Technology Platform” combines proprietary vision sensors, machine learning and radar with ultra-long range and foresight capabilities to prevent collisions at high speed and in all weather conditions, says the company. The Provizio team is made up of experts in robotics, AI and vision and radar sensor development.

Barry Lunn, CEO of Provizio said: “One point three five road deaths to zero drives everything we do at Provizio. We have put together an incredible team that is growing daily. AI is the future of automotive accident prevention and Provizio 5D radars with AI on-the-edge are the first step towards that goal.”

Also involved in Provizio is Dr. Scott Thayer and Prof. Jeff Mishler, formally of Carnegie Mellon robotics, famous for developing early autonomous technologies for Google / Waymo, Argo, Aurora and Uber.

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