UK start-up Babylon raises $60m for AI-based doctor app

UK start-up Babylon, which specializes in remote health applications, has doubled its valuation in its latest funding round, raising $ 60 million.

The funding brings the company’s valuation to more than $ 200 million since its previous funding round, which took place in January 2016.

Babylon will use the money to build its artificial intelligence (AI) healthcare platform, which aims to help patients to diagnose their ailments via a smartphone.

The company’s Series A funding round, led by Swedish investment group, AB Kinnevik, raised $ 25 million. The founders of DeepMind, the AI group acquired by Google in 2014, Demis Hassabis and Mustafa Suleyman, were also involved in that round.

According to the Financial Times, this round of funding includes backing from Egyptian billionaire business family, the Sawiris. The family’s Orascom conglomerate spans telecommunications, construction, tourism and technology.

Currently, Babylon’s app enables patients to type their symptoms into a chat box, much like texting. From there, the AI will perform triage for urgent but non-life-threatening conditions. Patients with urgent needs are directed to a human doctor.

As well as performing triage, the app includes a paid-for video consultation function costing roughly $ 6.15 a month.

Beyond triage

The app is currently used by 800,000 people worldwide and is being trialled by the UK’s National Health Service, with a test group involving 1.2 million people in London. Babylon claims that 10 percent of the adult population of Rwanda (total population around 12 million) registered with the company in its first six months of operating in that country, where it has signed a deal with the government.

Now, the company wishes to improve upon the speed and sophistication of the apps medical diagnoses with this round of funding.

“We already have a machine that can diagnose the majority of primary clinical conditions, so the next step is to get clinically certified by the UK’s Medicines and Healthcare Products Regulatory Agency, and the US Food and Drug Administration,” said Ali Parsa, chief executive of Babylon. “We will also invest heavily into predicting disease ahead of time.”

Read more: Data scientists developing doctor chatbots for ‘self-treatable’ conditions

To achieve this, Babylon says it has curated the largest knowledge graphs of medical content, and made advances in various applications of deep learning techniques adapted specifically for healthcare.

In a press release, Parsa added “Cutting-edge artificial intelligence, together with ever-increasing advances in medicine, means that the promise of global good health is nearer than most people realize.

“Babylon scientists predict that we will shortly be able to diagnose and foresee personal health issues better than doctors, but this is about machines and medics cooperating, not competing.

“Doctors do a lot more than diagnosis: artificial intelligence will be a tool that will allow doctors and health care professionals to become more accessible and affordable for everyone on earth. It will allow them to focus on the things that humans will be best at for a long time to come.”

The post UK start-up Babylon raises $ 60m for AI-based doctor app appeared first on Internet of Business.

Internet of Business

Mythic, an AI-based Microchip closes $8.8M Series A

Mythic, the Austin-based startup raised $ 9M Series A at an unknown valuation on March 22, 2017. It is an AI-based chip that performs hybrid digital/analog calculation inside flash arrays enabling computer vision and voice control on smart devices.

Five backers participated in the round with Lux Capital and Draper Fisher Jurvetson (DFJ) as lead investors. Previously, the company raised $ 500k seed in May, 2016. The startup plans to use the funds to grow a team of 20 by this summer and consolidate market position.

Led by Mike Henry (founder & CEO) and Dave Fick as Founder-CTO, the recent funding round brings Shahin Farshchi, partner at Lux Capital and Steve Jurvetson, Managing Director at Draper Fisher Jurvetson (DFJ) as board members and advisers of Mythic.

Traditionally, “artificial neural networks needed big server racks powered by graphics processing units (GPUs)”, writes Berenice Magistretti of Venture Beat. For instance, Amazon’s Alexa and Apple’s Siri run on the cloud which creates a time lapse in their response. High latency is a major problem in existing solutions. Mythic is approaching the problem differently by running the processes on a single microchip. It lets them bypass the traditional approach of dependence on memory, processors, cloud and network connections.

The new approach used by AI-startup performs the inference step of deep neural networks inside the memory array which stores the processing weight long term. This eliminates the need to have memory and processors by doing computations inside the memory.


Postscapes: Tracking the Internet of Things

$5.3M raised by AI-based pattern recognition software

The Industrial-IoT pattern recognition company, Falkonry, based at Santa Calara, CA raised $ 5.3M in equity funding. Polaris Partners, Start Smart Labs and Zetta Venture partners participated in the venture round. The company announced the successful round of investment on Feb 23 2017.

Falkonry UI

In addition to the venture capital, Mark Gorenberg founding partner of Zetta Venture Partners will join Falkonry’s board of directors. Zetta is the first fund focused on intelligent enterprise software and has $ 160 million under management.

“Zetta has the reputation of being a top intelligent enterprise venture partner and we are excited to leverage their grasp of early business models and growth strategy. We are also delighted to have Mark join our board”, said Falkonry’s CEO Nikunj Mehta.

Until now industrial units have been using traditional methods to improve yield, quality, efficiency, and uptime. Falkonry addresses these issues by productizing solutions to costly, complex industrial business problems.

Falkonry’s AI model detects the earliest indication of degradation in a client’s machinery/equipment by examining time series data. Unknown pattern of machine behavior is monitored in real-time. Any indication of degradation is returned to Splunk server from which notifications are generated. This helps Falkonry’s industrial clients to leverage predictive and prescriptive analytics, and avert costly failures and minimize production/operational downtime.


Postscapes: Tracking the Internet of Things