Upstream Security secures $9 million to advance cloud-based connected car security

Upstream Security has secured $ 9 million in series A funding to advance its cloud-based cybersecurity platform for connected cars and self-driving vehicles, after securing $ 2 million in a seed funding round in June.

According to the company, the fresh amount will be utilised for expanding its R&D programme, strengthening research teams in the engineering and security divisions and opening marketing and sales offices in the US and Europe.

The funding was led by CRV (Charles River Ventures) and included expanded investments from Glilot Capital Partners and Maniv Mobility.

Izhar Armony, general partner at CRV, said: “Connected and semi-autonomous cars are already a reality, so it’s a matter of ‘when’ not ‘if’ these self-driving technologies will be deployed at scale. Upstream’s engineers were the first to solve how to protect connected cars and autonomous vehicles using the cloud, crucial for near-term and future deployment of automotive cybersecurity at the fleet level.

"We believe in Upstream’s groundbreaking approach to secure connected and autonomous vehicles and in the abilities of cybersecurity veterans, Yoav Levy and Yonatan Appel, to build a rapidly growing business in this hot, emerging space.”

Talking about the increasing security threats in the connected car industry, Upstream CEO and cofounder Levy commented: “Security solutions for the car are undergoing rapid advances at an unprecedented rate. We’re using emerging technologies like AI and machine learning to carry out an evolutionary leap in cybersecurity for passenger and commercial vehicles.”

It’s not the only money going into this space of late. Earlier this month, Canada-based connected vehicle startup Mojio secured $ 30 million in Series B funding, which will be utilised by the company to expedite its connected-vehicle solution and for global expansion.

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Oracle gives its cloud-based business apps an AI boost

Oracle business apps get AI boost

Smart factories and connected warehouses are among the business functions set to benefit from new AI-powered Adaptive Intelligent Apps from Oracle.

Modern artificial intelligence (AI) shouldn’t just be capable of supporting “sophisticated decision science”, but also do it in a way that it is hidden from users and embedded in the software that they use to perform day-to-day work tasks.

That’s the view of Steve Miranda, executive vice president of applications development at tech giant Oracle. At the company’s Oracle Open World 2017 conference in San Francisco, the company has today announced new AI-based apps for employees in finance, human resources, supply chain, manufacturing, commerce, customer service, marketing and sales.

Read more: Oracle beefs up its IoT efforts in smart factories push

Adaptive Intelligent Apps

The new Oracle Adaptive Intelligent Apps are built into existing Oracle Cloud Applications, making it possible for “business users from across the organization to quickly and easily take advantage of the latest advancements in artificial intelligence,” said Miranda.

By embedding AI in existing apps, he explained, the company has eliminated the need for integrations in order to combine “first and third-party” data with advanced machine learning.

The announcement builds on the company’s first introduction of its ‘adaptive intelligence’ concept in its customer experience (CX) apps earlier this year. Now, it is expanding the reach of AI across a much wider swathe of its cloud-based enterprise applications.

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Smart manufacturing and logistics

In theory, any of the business functions set to benefit from these new apps is likely to have some kind of IoT data from connected devices that could potentially prove useful for fuelling AI-based decision-making – but it’s clear that supply chain and manufacturing professionals are particular targets.

In supply chain, for example, new AI capabilities in Oracle’s Supply Chain IoT applications will crunch through data from connected equipment in warehouses and logistics centres. “The applications use predictive analytics and machine learning techniques to detect and analyze key signals in device data and then to act on these insights through their associated business functions and connected processes,” said the company.

In manufacturing, similar thinking applies. New AI-powered capabilities will enable companies to more consistently meet their production goals, based in part on the intelligence that comes from plant floor machinery. According to Oracle: “The new capabilities drive factory and shop floor improvements by demonstrating how incident detection, root cause analysis and smart resolution are performed within minutes in a connected factory.”

Some of the data powering Adaptive Intelligent Apps, meanwhile, will come from the Oracle Data Cloud, which the company claims is the largest third-party data marketplace in the world, with a collection of more than 5 billion global consumer and business IDs and more than 7.5 trillion data points collected monthly.

Read more: Oracle broadens IoT cloud offering with four new solutions

Substantial opportunity in AI arms race

The market for AI and for AI-enabled applications is “substantial”, according to David Schubmehl, an analyst at market research company IDC. “We expect this to be a rapidly expanding area for both enterprise and commercial development as organizations race to embed predictive and prescriptive capabilities into their applications portfolio to deliver smarter software solutions to customers,” he said.

In other words, this could be a money-spinner for Oracle if its customers prove to get as hooked on AI-based decision-making as the company clearly hopes they will. But big competitors such as SAP, Infor and Microsoft are also working hard to embed AI into the software need to run smart factories and connected warehouses – so AI is fast becoming an arms race.

The quality of ingested data, however, looks likely to be an important differentiator, Schubmehl claims, as it will determine the resulting recommendation, action or output delivered. “Vendors with a strong foundation of first and third-party data to fuel machine learning have a clear and distinct advantage in the market, providing strong, targeted AI-enabled solutions for their customers.”

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