In late November the U.S. Federal Drug Administration approved Benevolent AI's recommended arthritis drug Baricitnib as a COVID-19 treatment, just nine-months after the hypothesis was developed. The correlation between the properties of this existing Eli Lilly drug and a potential treatment for seriously ill COVID-19 patients, was made with the help of knowledge graphs, which represent data in context, in a manner that humans and machines can readily understand. Knowledge graphs apply semantics to give context and relationships to data, providing a framework for data integration, unification, analytics and sharing. Think of them as a flexible means of discovering facts and relationships between people, processes, applications and data, in ways that give companies new insights into their businesses, create new services and improve R&D research. Benevolent AI, a six-year-old London-based company which has developed a platform of computational and experimental technologies and processes that can draw on vast quantities of biomedical data to advance drug development, built-in the use of knowledge graphs from day one.

In late January, scientists at DeepMind, Google's London-based AI unit, gathered to discuss whether there was anything they could do to help fight the brewing coronavirus pandemic. At the time, the spread of Covid-19 was still largely confined to the city of Wuhan, but as case numbers continued to grow exponentially, machine learning experts from London to San Francisco were gearing up to try and harness the power of AI to fight the Sars-CoV-2 virus. "Our first reaction was to think how we might be able to help," says Demis Hassabis, CEO and co-founder of DeepMind. "Front of mind was our system, AlphaFold, which we had shown could predict the 3D structure of proteins with unprecedented accuracy compared to other computational methods." At the start of March, DeepMind released predictions generated by AlphaFold for the structures of various proteins associated with SARS-CoV-2, to try and accelerate the process of understanding how the virus functions.

In mathematics, there is this age-old question of whether new math is discovered or invented. It makes sense to ask the same sort of question about modern drug discovery. When using artificial intelligence to identify drug candidates, are these new drug candidates being developed, or simply exposed through a process of narrowing down the possibilities using mathematics and science? Are these new drug candidates discovered or designed? A flurry of progress in the race to identify a COVID-19 vaccine has produced new automated techniques for drug discovery using artificial intelligence.

BEGIN ARTICLE PREVIEW: What is discovery? In mathematics, there is this age-old question of whether new math is discovered or invented. It makes sense to ask the same sort of question about modern drug discovery. When using artificial intelligence to identify drug candidates, are these new drug candidates being developed, or simply exposed through a process of narrowing down the possibilities using mathematics and science? Are these new drug candidates discovered or designed? Or maybe it’s a distinction without a difference. Biotechnology company Moderna protocol files for COVID-19 vaccinations are kept at the Research … [+] Centers of America in Hollywood, Florida, on August 13, 2020. (Photo by CHANDAN KHANNA / AFP) (Photo by CHANDAN KHANN

In mathematics, there is this age-old question of whether new math is discovered or invented. It makes sense to ask the same sort of question about modern drug discovery. When using artificial intelligence to identify drug candidates, are these new drug candidates being developed, or simply exposed through a process of narrowing down the possibilities using mathematics and science? Are these new drug candidates discovered or designed? Biotechnology company Moderna protocol files for COVID-19 vaccinations are kept at the Research ... [ ] Centers of America in Hollywood, Florida, on August 13, 2020.

On Thursday, the World Health Organization announced it would host a global research and innovation forum on February 11 and 12. The invite list will include public health officials, research funders, and scientists who are working on coronavirus 2019 vaccines, diagnostics, therapeutics, and other relevant innovations. The goal is to chart out a global research agenda targeting the new coronavirus. To date, roughly 31,000 people around the world have been infected with the coronavirus. Some 600 have died, according to CBS News.

Fascination with AI shows no sign of abating in Europe. While established companies may still be slow to pick the technology up, new start-ups in the sector continue to grow – in France by as much as 38% this year already. There is also no shortage of investment, with $4bn pumped into the sector globally in Q3 compared to $2.8bn in the same period last year, while the UK continues to set the research and development standard in Europe with 623 AI-related patents. It's often said numbers like this are not intended to discourage entrepreneurs, but to motivate them to work smarter and harder. Unfortunately, it's more than just hard work that sets a company up for success – and for those who are looking to scale up their AI venture, the best lessons to be learned can be drawn from those who've been in the same position – and thrived.

AI startup Adarga has sealed a £5 million Series A fundraising by Allectus Capital. But this news cloaks the point that it has been developing a source of steam since its founding in 2016. Building up what they say is a £30 million-plus sales pipeline through meaningful collaborations with several global industrial associates and slowly creating its management team. The profits will be used to maintain the increase of Adarga's data science and software engineering teams and will roll out globally. Adarga, which originates from the word for an old Moorish guard, is a London and Bristol-based startup.

AI startup Adarga has closed a £5 million Series A fundraising by Allectus Capital. But this news rather cloaks the fact that it has been building up a head of steam since its founding in 2016, building up what they say is a £30 million-plus sales pipeline through strategic collaborations with a number of global industrial partners and gradually building its management team. The proceeds will be used to continue the expansion of Adarga's data science and software engineering teams and to roll out internationally. Adarga, which comes from the word for an old Moorish shield, is a London and Bristol-based startup. It uses AI to change the way financial institutions, intelligence agencies and defence companies tackle problems, helping crunch vast amounts of data to identify possible threats even before they occur.

Artificial intelligence is one of the technologies with the most transformative potential in business. According to research by McKinsey, 70 per cent of companies are likely to have adopted at least one form of AI by 2030. This will contribute to an additional $13tr of global economic activity. Machine learning – a subset of artificial intelligence – enables machines to get better at executing tasks without human intervention, by finding patterns in data, and learning from their experience. It's no surprise, therefore, that there has been an explosion in the number of machine learning companies worldwide.