Andrew Watson is Vice President of AI and R & D at Healx. Prior to joining Healx he worked at the technology giant Dyson, where he was the founding member of the Machine Learning Research Department, leading the research and implementation of machine learning and artificial intelligence across a variety of global product categories. In his time as Director of Machine Learning at Dyson, Andrew also established a new research group, focused on the intersection between machine learning and cutting-edge biomedical research. Healx is an AI-powered, patient-inspired technology company, dedicated to helping rare disease patients around the world access life-improving therapies. There are 7,000 known rare diseases that affect 400 million people across the globe but only 5% of those conditions have approved treatments.

Today, Graphcore is proud to take the next step in our commitment to helping customers accelerate their innovation and harness the power of AI at scale. Together with Cirrascale Cloud Services, we have built something totally new for AI in the cloud, with the first publicly available Mk2 IPU-POD scale-out cluster, offering a simple way to add compute capacity on-demand, without the need to own and operate a datacentre. We recognise that the tremendous opportunity offered by AI brings with it a unique set of computing challenges; model size is growing rapidly, and the bar for accuracy is constantly being raised. If customers are to take full advantage of the latest innovations, they need a tightly integrated hardware and software system built specifically for artificial intelligence. Graphcloud is a secure and reliable IPU-POD family cloud service that allows customers to access the power of Graphcore's Intelligence Processing Unit (IPU), as they scale from experimentation, proof of concept and pilot projects to larger production systems.

Now too is the legislation proposing to regulate it. Earlier this year, the European Union outlined its proposed artificial intelligence legislation and gathered feedback from hundreds of companies and organizations. The European Commission closed the consultation period in August, and next comes further debate in the European Parliament. As well as banning some uses outright (facial recognition for identification in public spaces and social "scoring," for instance), its focus is on regulation and review, especially for AI systems deemed "high risk" -- those used in education or employment decisions, say. Any company with a software product deemed high risk will require a Conformité Européenne (CE) badge to enter the market.

We take a look into how artificial intelligence is aiding the fight against the coronavirus pandemic, how effective will AI prove to be? Artificial intelligence may have been hyped - but when it comes to medicine, it already has a proven track record. Oxford-based Exscientia, the first to put an AI-discovered drug into human trial, is trawling through 15,000 drugs held by the Scripps research institute, in California. And Healx, a Cambridge company set up by Viagra co-inventor Dr David Brown, has repurposed its AI system developed to find drugs for rare diseases. Drug discovery has traditionally been slow, but AI is providing much faster results. Healx hopes to turn that information into a list of drug candidates by May and is already in talks with labs to take those predictions into clinical trials.

It feels as if a superhuman effort is needed to help ease the global pandemic killing so many. Artificial intelligence may have been hyped - but when it comes to medicine, it already has a proven track record. There is no shortage of companies trying to solve the dilemma. Oxford-based Exscientia, the first to put an AI-discovered drug into human trial, is trawling through 15,000 drugs held by the Scripps research institute, in California. And Healx, a Cambridge company set up by Viagra co-inventor Dr David Brown, has repurposed its AI system developed to find drugs for rare diseases.

The recent outbreak of the coronavirus disease has caused a drop in sales and profit margin for most companies across the globe and tech companies are not exceptional. With this, it's very surprising to see how the coronavirus has affected the tech companies. But in the future, artificial intelligence could help researchers do a better job in driving away the coronavirus disease. Though it might be too late for the fledging technology to play a major role in the current epidemic -- but there is still hope for the next outbreaks. Artificial Intelligence is always good at combining through mounds of data to help find the connection that makes it easier to know the sort of treatments that could work.

Disease outbreaks like the coronavirus often unfold too quickly for scientists to find a cure. But in the future, artificial intelligence could help researchers do a better job. While it's probably too late for the fledgling technology to play a major role in the current epidemic, there's hope for the next outbreaks. AI is good at combing through mounds of data to find connections that make it easier to determine what kinds of treatments could work or which experiments to pursue next. The question is what Big Data will come up with when it only gets meager scraps of information on a newly emerged illness like Covid-19, which first emerged late last year in China and has sickened more than 75,000 people in about two months.

Disease outbreaks like the coronavirus often unfold too quickly for scientists to find a cure. But in the future, artificial intelligence could help researchers do a better job. While it's probably too late for the fledgling technology to play a major role in the current epidemic, there's hope for the next outbreaks. AI is good at combing through mounds of data to find connections that make it easier to determine what kinds of treatments could work or which experiments to pursue next. The question is what Big Data will come up with when it only gets meager scraps of information on a newly emerged illness like Covid-19, which first emerged late last year in China and has sickened more than 75,000 people in about two months.

Healx has raised $56 million (€51 million) to launch 40 rare disease programs while taking some of its existing assets into the clinic. The ambitious target is enabled by an AI drug discovery platform that Healx thinks gives it a scalability that has more in common with tech than biotech. David Brown, the former global head of drug discovery at Roche, and Tim Guilliams cofounded Healx in 2014 to use AI to find opportunities to repurpose existing molecules to treat rare diseases. After quietly working on the technology in its early years, Healx raised $10 million last year to build on its early success in identifying a potential treatment for Fragile X syndrome. That money was due to see Healx through to 2020 but Guilliams, who works as CEO, decided to pull the financing forward in light of the success rate of the company's predictions and translations.

Healx, a company using artificial intelligence (AI) to discover new drug treatments for rare diseases, has raised $56 million in a series B round of funding led by Atomico, with participation from Intel Capital, Balderton Capital, Global Brain, Btov Partners, Amadeus Capital Partners, and Cambridge Innovation Capital's Jonathan Milner. Founded out of Cambridge in 2014, Healx's core AI Platform -- Healnet -- applies a range of machine learning techniques to public and proprietary data sources, covering literature, clinical trials, patents, drug targets, chemical structures, symptoms, and more. Part of this process involves using natural language processing (NLP) to extract insights and knowledge from all the published sources around specific diseases. The culmination of all this data, Healx CEO and cofounder Dr. Tim Guilliams said, is a knowledge graph of rare diseases that could help pharmacologists or biologists unearth effective new treatments that would otherwise be much more difficult to spot. "We use a variety of machine learning algorithms to solve the many tasks necessary to predict drug treatments and translate them in the clinic effectively," Guilliams told VentureBeat.