Digital Catapult MiGarage programme: a spotlight on the first six months
In January 2018, Digital Catapult launched its Machine Intelligence Garage programme and was set to supercharge the development of machine intelligence startups in the UK. The programme is designed to accelerate the growth of early stage AI and machine learning businesses by providing access to computation power and expertise. It also enables companies of all sizes to get to grips with systems for machine intelligence through a host of activities including workshops and experimentation days.
Putting a spotlight on startup success stories:
At Digital Catapult we’re delighted to have already supported nineteen great startups on our programme, many of which have continued to develop and grow their business. We put a spotlight on just some of the companies here:
Bloomsbury AI deploy machine learning, in particular cutting-edge natural language processing, to extract information from text documents and develop a question-answering system. The tool Cape is available to use through an online demo here. As part of its involvement in the Machine Intelligence Garage programme, Bloomsbury AI had dedicated access to an NVIDIA DGX-1 deep learning computer. Using this technology Bloomsbury AI could train algorithms much faster than before whilst creating a better model for text understanding.
Guillaume Bouchard, CEO Bloomsbury AI reported: “Machine Intelligence Garage as a programme is more focused on what resources the startups need. The system made a huge change to the team’s productivity and throughput of our solutions.”
Bloomsbury AI has recently been acquired by Facebook to further natural language processing research and applications, as covered in TechCrunch.
Skin Analytics is developing an AI based melanoma screening service, which when used in primary care promises to improve patient outcomes and significantly reduce the number of referrals and cost of identifying melanoma. Its solution will enable dermatologist-quality screening at primary care, within the current appointment times and without the need for expensive equipment.
This will have two benefits:
- More accurate identification of melanoma, leading to potentially better health outcomes and reduced treatment cost; and
- Fewer onward referrals to secondary care, reducing burden on rapid access pigmented lesion clinics and lowering the cost of identifying melanoma.
Skin Analytics joined Machine Intelligence Garage to access computation resources that enable them to more efficiently train and refine their cutting-edge models to detect and monitor melanoma. Through Machine Intelligence Garage, the company has benefited from the AWS Activate for Startups programme allowing it to use the most appropriate hardware for this task.
Skin Analytics has recently announced a successful round of funding to allow it to launch its product to market, including £1.2m seed round funding.
GTN Ltd is transforming drug discovery through interdisciplinary innovation. Bringing a single new drug to the market costs $2.9bn and can take up to 15 years, with a high chance of failure. GTN combine machine learning and quantum physics and use its unique patented technology, Generative Tensorial Networks, to discover innovative new drug-like molecules. This will create substantial efficiencies in the whole drug development cycle.
The Machine Intelligence Garage programme provided the necessary computational power to develop and train GTN’s model, as well as expertise and networking opportunities. GTN have recently secured £2.1m in seed funding led by Octopus Ventures and Pentech, with follow on funding from Entrepreneur First. The company has since been able to grow from two to ten staff and develop the technology to allow for the discovery of innovative new drug-like molecules which have the potential to create huge benefits in the drug discovery process.
Further to all this GTN recently received the One to Watch Award in the Best Investment in DisruptiveTech category at the UKBAA Awards and the CogX UK Rising Star award for Outstanding Achievement in Machine Learning.
Intellisense.io uses artificial intelligence and industrial IoT technologies to develop optimisation software for the mining industry. The out of the box applications have proven to drastically reduce operating costs and improve efficiencies across the extraction, processing and utility systems in world leading mining companies. This is achieved with zero capital expenditure and minimal disruption to mines.
The first flagship company to have signed up to IntelliSense.Lab is the Kazakhstan Gold Mining company, Altynalmas, who are deploying the Grinding Optimisation application to increase overall ore throughput. The joint venture will see IntelliSense.io move into four new industrial sectors, provide the platform to develop a local ecosystem of application developers who would develop new applications on its brains.app platform that can be distributed to local and international companies through an “app store” model. Besides Mining and Metals, the IntelliSense.io platform (brains.app) will be targeting Oil & Gas, Energy & Utilities, Shipping & Logistics, and Manufacturing.
The story continues…
The story however does not end there, you can find all of the details from the full cohort of companies involved in the programme on the Machine Intelligence Garage website.
The programme runs regular Open Calls for startups to get involved and access programme agnostic computation power and expertise. To be part of the next cohort join and apply here, The current call for applications closes 14th October. For enquiries about how your startup could benefit from the programme, please contact firstname.lastname@example.org.
To create Machine Intelligence Garage, Digital Catapult is collaborating with hardware providers, cloud computing providers, high performance computing facilities and academics. These include Amazon Web Services (AWS), Google Cloud Platform, NVIDIA, Graphcore, STFC Hartree Centre, EPCC, Newcastle University, Spinnaker, Cray and the Alan Turing Institute. The programme’s initial funders are Innovate UK and ERDF via the CAP-AI project.