Are you scared of Artificial Intelligence (AI)?
Do you believe the warnings from folks like Prof. Stephen Hawking, Elon Musk and others?
Is AI the greatest tool humanity will ever create, or are we “summoning the demon”?
To quote the head of AI at Singularity University, Neil Jacobstein, “It’s not artificial intelligence I’m worried about, it’s human stupidity.”
Read this introductory list of contemporary machine learning algorithms of importance that every engineer should understand.
By James Le, New Story Charity.
It is no doubt that the sub-field of machine learning / artificial intelligence has increasingly gained more popularity in the past couple of years. As Big Data is the hottest trend in the tech industry at the moment, machine learning is incredibly powerful to make predictions or calculated suggestions based on large amounts of data. Some of the most common examples of machine learning are Netflix’s algorithms to make movie suggestions based on movies you have watched in the past or Amazon’s algorithms that recommend books based on books you have bought before.
MIT researchers and their colleagues have developed a new computational model of the human brain’s face-recognition mechanism that seems to capture aspects of human neurology that previous models have missed.
The researchers designed a machine-learning system that implemented their model, and they trained it to recognize particular faces by feeding it a battery of sample images. They found that the trained system included an intermediate processing step that represented a face’s degree of rotation — say, 45 degrees from center — but not the direction — left or right.
This property wasn’t built into the system; it emerged spontaneously from the training process. But it duplicates an experimentally observed feature of the primate face-processing mechanism. The researchers consider this an indication that their system and the brain are doing something similar.
I know this is 2 days old; however, glad I came across it. As Gene Circuitry & Living systems in general are truly advancing more quickly in the recent year than I have seen over the past decade.
The real question is with AI, 3D/ 4D synbio printing, Gene/ Cell Circuitry; which areas of medicine will continue to existing in the next 15 years?
A Brock University research team has created a tool that can potentially be used in a future computer that will be made out of DNA.
Chemist Feng Li and graduate student Xiaolong Yang, formal postdoctoral fellow Yanan Tang and undergraduate student Sarah Traynor have devised a strategy that “helps simplify the design of DNA circuits that may eventually be used in a DNA computer,” says Li.
The team’s research was recently featured in the Journal of the American Chemical Society.
Driven by a declining population, a trend for developing robotic babies has emerged in Japan as a means of encouraging couples to become “parents”. The approaches taken vary widely and are driven by different philosophical approaches that also beg a number of questions, not least whether these robo-tots will achieve the aim of their creators.
To understand all of this it is worth exploring the reasons behind the need to promote population growth in Japan. The issue stems from the disproportionate number of older people. Predictions from the UN suggest that by 2050 there will be about double the number of people living in Japan in the 70-plus age range compared to those aged 15–30. This is blamed on a number of factors including so-called “parasite singles”, more unmarried women and a lack of immigration.
So, what are the different design approaches that are being taken to encourage more people to become parents? These have ranged from robots that mimic or represent the behavior of a baby to robots that look much more lifelike. Engineers at Toyota recently launched Kirobo Mini, for example, as a means of promoting an emotional response in humans. The robot does not look like a baby, but instead models “vulnerable” baby-like behaviors including recognising and responding to people in a high-pitched tone and being unstable in its movements.
Artificial intelligence and increasing automation is going to decimate middle class jobs, worsening inequality and risking significant political upheaval, Stephen Hawking has warned.
In a column in The Guardian, the world-famous physicist wrote that “the automation of factories has already decimated jobs in traditional manufacturing, and the rise of artificial intelligence is likely to extend this job destruction deep into the middle classes, with only the most caring, creative or supervisory roles remaining.”
He adds his voice to a growing chorus of experts concerned about the effects that technology will have on workforce in the coming years and decades. The fear is that while artificial intelligence will bring radical increases in efficiency in industry, for ordinary people this will translate into unemployment and uncertainty, as their human jobs are replaced by machines.
