Pharmaceutical companies generate huge amounts of data. Their staff are intensive users of computing power. Yet the companies do not enjoy the full fruits of the research and knowledge that they produce. Datasets sit in silos so that users in one department of a company are unable to access relevant information held elsewhere.
Nine years ago, I wrote in Scientific Computing World about using weightless neural networks from ITS to speed the sorting of decorated potsherds from an archaeological dig. It seemed pretty impressive at the time; nowadays, such is the march of progress, it seems laughable. Things move fast in information technology these days, even if implementation can’t always keep up with research and development. Within that statement of the obvious, computerised pattern recognition is an explosive growth area, with implications of which it is impossible to keep track.
Interoperability is a crucial component these days
The nature of laboratory instruments has changed dramatically. A few decades ago scientists bought equipment to perform a particular task and would then simply read the output on a screen or collect print-outs. Any software that came with that equipment was usually proprietary and simply there to manage the data acquisition.
It has been known for some time that the traditional silicon chip technology will run out of steam. The Moore’s Law increase in power versus decrease in feature size will bring us to a point where quantum effects will make traditional circuit design impossible. There is still headroom, but most people regard the silicon chip as being closer to its limit than to its origin.