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AI start-ups win in Merc innovation challenge

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Three artificial intelligence start-ups were the winners of the Mercedes-Benz South Africa Innovation Challenge.

Nine finalists presented their innovative ideas at a final selection event in the MBSA East London plant – the culmination of a unique partnership between MBSA, the LaunchLab and STARTUP AUTOBAHN that kicked off at the end of August this year.

The two winners in the manufacturing category were DataProphet, a group of machine learning specialists which provides A.I./ML development through corporate partnerships with the aim of delivering bleeding-edge machine solutions, and Vizbility Insight, an artificial Intelligence company specialising in globally scaleable predictive and prescriptive risk management software.

The winner in the sales and marketing category was NumberBoost, a startup that builds machine learning and artificial intelligence applications.

DataProphet was the overall winner.

These category winners each receive R300 000 to pilot their idea for future use within MBSA. DataProphet will also travel to Europe next year to pitch the innovative idea in front of hundreds of automotive decision makers at a big STARTUP AUTOBAHN event in Germany.

“I am highly impressed with the innovative solutions that were displayed at the MBSA Innovation Challenge,” said Markus Schäfer, Member of the Divisional Board Mercedes-Benz Cars, Manufacturing and Supply Chain for Daimler AG, MBSA’s parent company. “South Africa has some serious talent. The presentations were absolutely awesome and provided real solutions to the tasks that we face as a company. I congratulate all start-ups that presented at this event.”

The Mercedes-Benz South Africa Innovation Challenge targeted two streams. It asked interested students and professionals (as a first stream) and existing startups (as a second stream) to pitch innovative ideas to revolutionise the automotive manufacturing and marketing and sales environment.

“From an MBSA perspective, this challenge is crucial in that it will assist us in increasing agility while developing internal capability that changes organisational culture and the way we work,” said Andreas Engling MBSA CEO and executive director for manufacturing. “Most importantly, these innovative ideas will allow us to respond to changes and adapt to new market challenges quicker. In this process, we can increase our productivity.”

Innovation has always been a key to success for the automotive sector. In a world where disruption reigns and new opportunities need to be seized, innovation will be even more important in future.

Anne Knierim, senior manager for technology management and research policy and head of STARTUP AUTOBAHN, Daimler AG, said: “STARTUP AUTOBAHN globally scouts startups and matches them to the right colleagues within Daimler. I am impressed about the passion and capabilities of the South African startups in the challenge and I am really excited about the results we will see during the next months.”

The challenge also aims to provide a gateway for existing startups to grow and sustain their businesses.

MBSA will extend the opportunity for the student stream into 2018, to determine who will get the opportunity to be enrolled by the LaunchLab in its Lift-Off Programme for an initial three-month period. The Lift-Off Programme will be facilitated from the Nedbank Stellenbosch University LaunchLab, in Stellenbosch.

“This is what the LaunchLab is all about: facilitating valuable connections for startups and corporates for their mutual benefit,” said Philip Marais, CEO of the LaunchLab. “Through this Innovation Challenge, South African startups can have a global impact. Financial support from MBSA and support from high-profile representatives from Daimler and MBSA has really raised the profile of this event and helped to make it a great success. Well done to the winners.”

Ends.

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Project Bloodhound saved

The British project to break the world landspeed record at a site in the Northern Cape has been saved by a new backer, after it went into bankruptcy proceedings in October.

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Two weeks ago,  and two months after entering voluntary administration, the Bloodhound Programme Limited announced it was shutting down. This week it announced that its assets, including the Bloodhound Supersonic Car (SSC), had been acquired by an enthusiastic – and wealthy – supporter.

“We are absolutely delighted that on Monday 17th December, the business and assets were bought, allowing the Project to continue,” the team said in a statement.

“The acquisition was made by Yorkshire-based entrepreneur Ian Warhurst. Ian is a mechanical engineer by training, with a strong background in managing a highly successful business in the automotive engineering sector, so he will bring a lot of expertise to the Project.”

Warhurst and his family, says the team, have been enthusiastic Bloodhound supporters for many years, and this inspired his new involvement with the Project.

“I am delighted to have been able to safeguard the business and assets preventing the project breakup,” he said. “I know how important it is to inspire young people about science, technology, engineering and maths, and I want to ensure Bloodhound can continue doing that into the future.

“It’s clear how much this unique British project means to people and I have been overwhelmed by the messages of thanks I have received in the last few days.”

The record attempt was due to be made late next year at Hakskeen Pan in the Kalahari Desert, where retired pilot Andy Green planned to beat the 1228km/h land-speed record he set in the United States in 1997. The target is for Bloodhound to become the first car to reach 1000mph (1610km/h). A track 19km long and 500 metres wide has been prepared, with members of the local community hired to clear 16 000 tons of rock and stone to smooth the surface.

The team said in its announcement this week: “Although it has been a frustrating few months for Bloodhound, we are thrilled that Ian has saved Bloodhound SSC from closure for the country and the many supporters around the world who have been inspired by the Project. We now have a lot of planning to do for 2019 and beyond.”

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Motor Racing meets Machine Learning

The futuristic car technology of tomorrow is being built today in both racing cars and
toys, writes ARTHUR GOLDSTUCK

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The car of tomorrow, most of us imagine, is being built by the great automobile manufacturers of the world. More and more, however, we are seeing information technology companies joining the race to power the autonomous vehicle future.

Last year, chip-maker Intel paid $15.3-billion to acquire Israeli company Mobileye, a leader in computer vision for autonomous driving technology. Google’s autonomous taxi division, Waymo, has been valued at $45-billion.

Now there’s a new name to add to the roster of technology giants driving the future.

DeepRacer on the inside

Amazon Web Services, the world’s biggest cloud computing service and a subsidiary of Amazon.com,  last month unveiled a scale model autonomous racing car for developers to build new artificial intelligence applications. Almost in the same breath, at its annual re:Invent conference in Las Vegas, it showcased the work being done with machine learning in Formula 1 racing.

AWS DeepRacer is a 1/18th scale fully autonomous race car, designed to incorporate the features and behaviour of a full-sized vehicle. It boasts all-wheel drive, monster truck tires, an HD video camera, and on-board computing power. In short, everything a kid would want of a self-driving toy car.

But then, it also adds everything a developer would need to make the car autonomous in ways that, for now, can only be imagined. It uses a new form of machine learning (ML), the technology that allows computer systems to improve their functions progressively as they receive feedback from their activities. ML is at the heart of artificial intelligence (AI), and will be core to autonomous, self-driving vehicles.

AWS has taken ML a step further, with an approach called reinforcement learning. This allows for quicker development of ML models and applications, and DeepRacer is designed to allow developers to experiment with and hone their skill in this area. It is built on top of another AWS platform, called Amazon SageMaker, which enables developers and data scientists to build, train, and deploy machine learning quickly and easily.

Along with DeepRacer, AWS also announced the DeepRacer League, the world’s first global autonomous racing league, open to anyone who orders the scale model from AWS.

DeepRacer on the outside

As if to prove that DeepRacer is not just a quirky entry into the world of motor racing, AWS also showcased the work it is doing with the Formula One Group. Ross Brawn, Formula 1’s managing director of Motor Sports, joined AWS CEO Andy Jassy during the keynote address at the re:Invent conference, to demonstrate how motor racing meets machine learning.

“More than a million data points a second are transmitted between car and team during a Formula 1 race,” he said. “From this data, we can make predictions about what we expect to happen in a wheel-to-wheel situation, overtaking advantage, and pit stop advantage. ML can help us apply a proper analysis of a situation, and also bring it to fans.

“Formula 1 is a complete team contest. If you look at a video of tyre-changing in a pit stop – it takes 1.6 seconds to change four wheels and tyres – blink and you will miss it. Imagine the training that goes into it? It’s also a contest of innovative minds.”

AWS CEO Andy Jassy unveils DeepRacer

Formula 1 racing has more than 500 million global fans and generated $1.8 billion in revenue in 2017. As a result, there are massive demands on performance, analysis and information. 

During a race, up to 120 sensors on each car generate up to 3GB of data and 1 500 data points – every second. It is impossible to analyse this data on the fly without an ML platform like Amazon SageMaker. It has a further advantage: the data scientists are able to incorporate 65 years of historical race data to compare performance, make predictions, and provide insights into the teams’ and drivers’ split-second decisions and strategies.

This means Formula 1 can pinpoint how a driver is performing and whether or not drivers have pushed themselves over the limit.

“By leveraging Amazon SageMaker and AWS’s machine-learning services, we are able to deliver these powerful insights and predictions to fans in real time,” said Pete Samara, director of innovation and digital technology at Formula 1.

  • Arthur Goldstuck is founder of World Wide Worx and editor-in-chief of Gadget.co.za. Follow him on Twitter on @art2gee and on YouTube

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