The beginning of the year has been incredibly busy here at BenevolentAI - I am sure over the coming weeks and months you'll be hearing more on this - it is an incredibly exciting time. Despite the frenetic activity I try to make the effort to read around new and interesting publications in the digital healthcare space.
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.
Professor Jackie Hunter, CEO of BenevolentBio, writes for The Huffington Post on diversity in the AI industry and how it has the chance to embrace it or risk going the same way as many other industries.
Jackie Hunter explains why we need to encourage diversity in AI in a co-ordinated effort across the home, at school, at university and into the workplace.
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.
In an age where you could soon be legally (and safely) asleep at the wheel thanks to driverless cars will morality in AI go the same way – is the principle of ethics in AI asleep at the wheel?
10 years ago I attended a symposium looking at the future of pharmacology and healthcare.
These are truly exciting times for artificial intelligence (“AI”) and bioscience. This month, together with The Crick and Turing Institutes and the Wellcome Trust, we co-hosted the first of what we anticipate will be an annual symposium on ‘Artificial Intelligence in Bioscience’.