As the UK’s leading AI and machine learning technology company, BenevolentAI wants to use this blog to share its thoughts, insight and predictions.
Every year, the World Economic Forum welcomes leading early-stage technology companies from around the world into its Technology Pioneer’s community. In its own words, these companies are “poised to have a significant impact on business and society”. Today we are delighted and humbled to be named as one such Technology Pioneer.
Joanna Shields gives the opening speech at CogX 2018 event about "Why AI matters to us all"
Clinicaltrials.gov is the world’s largest primary registry of clinical studies. For almost two decades now it has been helping physicians, patients, and regulators identify relevant trials and collect evidence.
Today marks my first official day as Group CEO at BenevolentAI. For me, it is the next step of a journey, one that has encompassed amazing experiences building some of the biggest technology brands on the planet. Yet none of them had the same potential to transform our lives for the better as we have here at BenevolentAI.
Ian Churcher, VP Drug Discovery recently published a paper in Nature to highlight how organic synthesis could represent an opportunity for the pharmaceuticals industries to improve drug development. He presents the current challenges that the industry needs overcome and explains how new technologies and industry-academia collaborations are essential to progress.
There is an increasing number of varieties of drug agents in clinical use ranging from antibodies and proteins to nucleic acids and, increasingly, cellular and genetic therapies but the majority of drugs on the market and in development today are still small, synthetic molecules made in a chemistry laboratory.
Marwin Segler, senior machine learning researcher at BenevolentAI, shows in his Nature paper how AI can transform the success rate of planning the synthesis of organic molecules – so-called retrosynthesis.
The design of small molecules with bespoke properties is of central importance to drug discovery. However significant challenges yet remain for computational methods, despite recent advances such as deep recurrent networks and reinforcement learning strategies for sequence generation, and it can be difficult to compare results across different works.
A new view brings a new perspective… …its late February and I am sitting in our new Cambridge office looking at an unusually snowy scene of lawns and woodland.
Most scientific breakthroughs are made by analysing data, but we live in a world where the exponential growth of scientific research data makes the discovery of new drugs and treatments for disease very difficult.
As we all work busily in our own corners of drug discovery, be it in Pharma, biotech or academia, ask yourself the question – are you just pushing that horse a little more or are you genuinely imagining and creating the model T of the 21st century?
Initiated after the first Artificial Intelligence (AI) in Bioscience Symposium in 2016, the special interest group on AI in Biomedicine aims at stimulating debate and encouraging collaboration between experts in life science and AI.
Recently we welcomed the news that we have officially selected a study name for BenevolentAI's first clinical trial.