It’s part of a $27 million fund being managed by MIT and Harvard. Reid
Hoffman, the founder of LinkedIn, and the Omidyar Network, eBay founder
Pierre Omidyar’s nonprofit, have each committed $10 million to fund
academic research and development aimed at keeping artificial intelligence
systems ethical and prevent building AI that may harm society.
Flirting with a computer and even falling in love will be possible within
just 15 years, a futurist has predicted. The world depicted in the film
Her, where a man develops a relationship with an intelligent computer
operating system, is closer than we think, according to Google’s
engineering director, Ray Kurzweil.
Mapo — Predict mining prospects and mineral depositsIt’s time for the mining industry to use machine learning and artificial intelligence to solve it’s biggest question — where to explore and build mines?Mining Industry PredictionsAt Produvia, we predi…
Human intelligence is capable of irrational thought. Some algorithms do
better than humans. We make witty jokes. We catch footballs, while looking
into a mirror. All that is still very hard for AI. Emotional intelligence
will be very hard to conquer, if not impossible, due to our emotions being
related to our biology and functional structure.
Insurance firm Fukoku Mutual Life Insurance is making 34 employees
redundant and replacing them with IBM’s Watson Explorer AI.
“All known methods of algorithmic classification suffer from the problem of
overfit. Example: All training photos of a classroom have a blackboard, so
a room with a whiteboard can’t be a classroom. “
An intelligent computer algorithm runs in a well-managed virtual memory
space under the strict control of the programming. The algorithm is not
free to learn anything else. Human intelligence is programmed in many
ways, though it is ordinarily taught or trained by unwitting parents and
teachers.
If you want to transform data which can be logically and clearly defined
into some output which is equally well defined, algorithms will always win
hands down. If you want to transform potentially ambiguous, illogical and
unexpected data into somewhat desirable, adaptive but essentially
unpredictable and not entirely reliable output, you need a human as your
general purpose “machine”.
Our AI models are being constructed using the same outdated education
pattern. The neural networks are passive in their nature. They are “dumb”
and rigorous training has to be performed on them with huge data sets in
order for them to learn how to perform a certain task.
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.
