Israeli company Run:AI, provides a Deep Learning virtualization AI infrastructure platform, announced that it is partnering up with London Medical Imaging & Artificial Intelligence Centre for Value Based Healthcare to provide technology that will help them better manage their AI resources and provide elastic resource allocation, visibility and control.

Using AI in the fight against COVID-19

Deep learning is a technique that has produced major advances in AI but its demand for computation power in the form of GPUs (a specialized kind of computer chip) has increased exponentially in a very short time. Run:AI pools GPU to easily speed up AI innovations and harness ‘unlimited’ compute power.

The London Artificial Intelligence Centre for Value Based Healthcare is one of five Centres of Excellence, established as part of the UK Government’s Industrial Strategy Challenge Fund, delivered through UK Research and Innovation. The London-based AI Centre utilizes the NHS’ massive de-identified patient data bank, which includes medical images and clinical pathway data, in order to train and teach sophisticated AI Deep Learning algorithms. These algorithms are used to create new tools for faster diagnosis, personalized therapies, and more effective screening.

The COVID-19 pandemic outbreak forced the AI Centre to devote much of its resources to the fight against the novel coronavirus. By using the advanced AI tool, the Centre found that anosmia (loss of smell and taste) was a stronger and more data-backed predictor of the COVID-19 virus than fever, resulting in the British government changing its recommendations on the subject.

“Healthcare is one of the most important and impactful uses of advanced AI, especially now as it can help save lives during the Covid-19 pandemic. We’re proud to be working with the London AI Centre to help ensure their important research can get the best use out of their hardware, so they can run more experiments quickly and efficiently,” explained Omri Geller, CEO and co-founder of Run:AI.

Slash the time, but double the experiments

Run:AI ensures that the AI Centre’s data scientists can get the full use out of their hardware, guaranteeing that GPU (Graphics Processing Unit) resources are efficiently and elastically allocated to teams that need them. This enables the AI Centre to run more experiments and to speed up time to results while providing cross-team visibility into how their hardware is being used.

Since installing Run:AI, the AI Centre has slashed the time taken to complete its experiments. The current average is just a day and a half, whereas a simulation of the AI Centre’s exact infrastructure running without Run:AI showed an average of over 46 days per experiment - an improvement of 3000%. Over a 40-day period, the researchers ran more than 300 experiments after installing Run:AI compared to just 162 in a simulation of the same environment over the same time period. In addition, actual GPU utilization increased by 2x in the months since Run:AI’s platform has been in use.

“Our experiments can take days or minutes, using a trickle of computing power or a whole cluster,” said Dr. M. Jorge Cardoso, Associate Professor & Senior Lecturer in AI at King's College London and CTO of the AI Centre. “With Run:AI we’ve seen great improvements in speed of experimentation and GPU hardware utilization. Reducing time to results ensures we can ask and answer more critical questions about people’s health and lives.”

This may seem just like just a cool innovation, but the potential here is groundbreaking, we will witness this tech change our reality, as the age of AI is upon us. With this in mind, we asked Geller where he thinks the company is headed: “Data centers are being reassigned in order to support the new form of AI workloads, including new dedicated hardware processors, networking equipment and storage solutions. Our goal is to transform Run:AI’s AI orchestration platform into the de facto standard for IT organizations operating AI data centers.”

Israeli AI-tech company, Run:AI, was founded in 2018 by CEO Omri Geller and CTO Dr. Ronen Dar. The company has raised $13 million up-to-date.