Did you sign off on those expenses in Concur? Ever feel too busy at work to get any actual work done? Well, apparently you are right. According to a new report from Microsoft, our workplaces have a serious productivity problem. The study – which surveyed nearly 31,000 full-time employed or self-employed workers across 31 markets between 1 February 2023 and 14 March 2023 – found that 64% say they struggle with having the time and energy to do their job.

The UK has experienced a "lost decade" for productivity, with no increase in production efficiency between 2007 and 2017. Beware those who tell you they know the answer to our longstanding productivity woes. It is a highly complex question and there is no consensus on the precise causes, or what we should prioritise to solve the problem. Yet the bald facts are indisputable. In 2015, this country's output was just 76% of the level in the US, and well behind that of most of our other major competitors in the global marketplace.

Deep learning is fueling breakthroughs in everything from consumer mobile apps to image recognition. Yet running deep learning-based AI models poses many challenges. One of the most difficult roadblocks is the time it takes to train the models. The need to crunch lots of data and the computational complexity of building deep learning-based AI models also slows down the progress in accuracy and the practicality of deploying deep learning at scale. It's the training times -- often measured in days, sometimes weeks -- that slow down implementation.

We cannot increase people's living standards, or expect America to lead the world, unless we rapidly increase productivity. But productivity growth over the last decade has been the slowest since the government started measuring it in 1947. This is why the economy has been mired in sluggish growth. Productivity is the measure of how much we produce in our work days; the economy expands as each worker produces more. The recent slowdown has given fodder to a cottage industry of economic pessimists who tell us we better get used to it. Former Treasury Secretary Larry Summers argues we are in an age of structural stagnation.

Since the rise of modern medicine, the pharmaceuticals industry has relied on the brainpower of chemists and biologists to discover and develop new drugs. Their painstaking work has brought about dramatic advances in human health yet the slow pace of progress has prompted a search for new approaches. As in so many areas, some of the most promising ideas are coming from Silicon Valley. In the era of big data and artificial intelligence, could computer algorithms provide a short-cut to the next generation of medical breakthroughs? Among the pioneers of computer-based drug discovery is a Californian company called Verseon.