What we have seen lately, is that while systems can learn things they are
not explicitly told, this is mostly in virtue of having more data, not more
subtlety about the data. So, what seems to be AI, is really vast knowledge,
combined with a sophisticated UX.
What’s next? That’s easy. 2017 will be the year of artificial intelligence.
It is when every industry will ask how the latest old trend in computing
threatens to upend the existing order as they know it.
After a year of breakthroughs, experts believe they are on the brink of
revolutionising our daily lives through artificial intelligence – and Asia
can play a leading role in this brave new world.
The world’s biggest technology showcase kicks off in Las Vegas on 5 January
2017. Here’s everything we know about what will be happening at CES.
It is my suspicion though that this meta meta-model approach if pursued in
greater detail may the key in locking “Unsupervised learning” or
alternatively “Predictive learning” . Perhaps our puny human brains cannot
figure this out. However armed with meta-learning capabilities, it may be
possible for machines to continually self improve upon themselves. The
reason that this may not work however is that the vocabulary or language is
not available and furthermore somehow not derivable through this
bootstrapping method.
Anything can be automated. At least, that seems to be the industry
perspective. Humans are rash, impulsive and tainted by personal bias. So
why not just replace them with machines? Apparently, that’s what Facebook
thought when they fired their entire team of news editors for political
bias, replacing them instead with a new algorithm. That did not go well.
Online maths company has partnered with scientists to identify what makes
lessons successful – and to see if AI can be used to improve teaching.
Earlier this month, Apple made a splash when it told the artificial
intelligence research community that the secretive company would start
publishing AI papers of its own. Not even a month later, it’s already
starting to make good on that promise.
As AI evolves, the role of the computer scientist is changing. Sure, the
world still needs people who can code software. But increasingly, it also
needs people who can train neural networks, a very different skill that’s
more about coaxing a result from the data than building something on your
own. Companies like Google and Facebook are not only hiring a new kind of
talent, but also reeducating their existing employees for this new future –
a future where AI will come to define technology in the lives of just about
everyone.
Can machines really think? Here is a series of interviews with some of the
AI pioneers, Jerome Wiesner, Oliver Selfridge, and Claude Shannon. A view
of the future of computer intelligence from back then.
