So far, though, attempts to build supercomputer brains have not even come close. A multi-billion-dollar European project that began in 2013 is now largely understood to have failed. That effort has shifted to look more like a similar but less ambitious project in the U.S., developing new software tools for researchers to study brain data, rather than simulating a brain.
Digital platforms, the websites and apps which compete for our precious screen time, have successfully invaded the traditional territory of many sectors of the “old economy”. They have become the preferred – expected, even – domains for many kinds of human behaviour, from banking and property buying, to dating and entertainment.
Data drives our global digital ecosystem, and AI technologies reveal patterns in data. Smartphones, smart homes, and smart cities influence how we live and interact, and AI systems are increasingly involved in recruitment decisions, medical diagnoses, and judicial verdicts. Whether this scenario is utopian or dystopian depends on your perspective.
Surely an AI won’t ever be able to compete? Well, it turns out they might. A paper recently published in Nature reports that an AI has now managed to predict future scientific discoveries by simply extracting meaningful data from research publications.
Science fiction is brimming with visions of the future and the many wondrous things the human race can achieve. But it is full of warnings too – and we should be careful to take heed of some of the big messages that are more relevant now than they ever were before.
Gmail will now go ahead and correct spelling errors and point out grammatical errors made while you’re typing.
In this week’s Light Start, the Channel is crossed, AI takes on knitting, we indulge in some Console Wars (later), and check out some Little Monsters.
Despite their names, artificial intelligence technologies and their component systems, such as artificial neural networks, don’t have much to do with real brain science. I’m a professor of bioengineering and neurosciences interested in understanding how the brain works as a system – and how we can use that knowledge to design and engineer new machine learning models.
These days all text is digital. From writing an email to publishing a new edition of War and Peace, text nearly…
As a cryptocurrency, there is no physical form that gives Bitcoin value, so it is impossible to perform traditional fundamental analysis of the currency. Consequently, many investors track the so-called technical trading indicators (geometric patterns constructed from historical prices and trading volumes) in order to understand and predict Bitcoin’s future movement.