AI is having an impact on the way we approach certain problems and questions.
AI techniques, such as machine learning, represent a complete step-change in ability.
By combing heavy lifting computational power with more subtle human-like reasoning we can start to address scientific problems that were previously thought to be intractable - to computers or human scientists as it where.
“Until now, humans have been the masters and technology the slaves. This needs to change − today’s AI systems are capable of achieving complex goals in agile and flexible ways”
– Professor Nick Jennings
Chair in Artificial Intelligence and Vice Provost (Research) at Imperial College London
LIST OF MIND BLOWING AI BREAKTHROUGH
MIND READING AI
Mind reading’ AI is able to scan brains and guess what you’re thinking
Carnegie Mellon University scientists have developed a system that can read complex thoughts based on brain scans, even interpreting complete sentences.
Using data from functional magnetic resonance imaging (fMRI) scans, the team was able to demonstrate different brain activations being triggered according to 240 complex events, ranging from individuals and settings to types of social interaction and physical actions. Using the smart algorithms they developed, the team was able to discern a person’s thoughts with 87% accuracy.
SELF-TAUGHT AI
Self-taught AI beats doctors at predicting heart attacks
As most doctors will tell you, our tools for predicting a patient’s health are no match for the complexity of the human body. Heart attacks are particularly hard to anticipate. Stephen Weng, an epidemiologist at the University of Nottingham in the United Kingdom showed that computers capable of teaching themselves perform far better than established medical processes, significantly increasing prediction rates. Once implemented, the new method will save thousands, perhaps even millions of lives a year.
BRAIN AGE DETECTOR AI
By combining MRI scans with machine learning algorithms, a team of neuroscientists led by researchers at Imperial College London, has trained computers to provide a predicted ‘brain age’ for people based on their volume of brain tissue.
When the technique was tested on a study population of older adults in Scotland, they found that the greater the difference between a person’s brain age and their actual age, the higher their risk of poor mental and physical health, and even early death.
The researchers stress that while the technique is a long way from being used in clinical practice, they are hopeful it might one day be used as a screening tool, helping to identify those at risk of cognitive decline and dying before the age of 80, providing an opportunity for early intervention.
CRIME PREDICTING AI
China is using AI to predict who will commit crime next.
Taking a page out of the movie “Minority Report,” China is developing predictive analytics to help authorities stop suspects before a crime is committed. With their unchecked access to citizens’ histories, Chinese tech companies are helping police develop artificial intelligence they say will help them identify and apprehend suspects before criminal acts are committed.
By tapping into facial recognition tech, and combining it with predictive intelligence, they hope to notify police of potential criminals based on their behavior patterns. Even though it sounds like promising tech, applications like this are getting tons of scrutiny.
SUICIDE DETECTOR AI
Artificial intelligence could one day be used to help identify a person contemplating suicide.
Around 800,000 people die a year from suicide, according to the World Health Organization.
Around 800,000 people die a year from suicide, according to the World Health Organization.
A professor of psychology at Carnegie Mellon and director of the Center for Cognitive Brain Imaging, had spent the majority of the past decade teaching computer programs how to identify thoughts.
He had found—with the help of an functional magnetic resonance imaging (fMRI) machine—that each emotion we feel had a specific signature in the brain and lit up in uniquely identifiable ways. Just had trained a piece of software to follow these patterns and recognize about 30 concepts and emotions.
"We asked whether we could identify what a person was thinking from the machine learning patterns," Just explained. "The machine learning data was figured out with various kinds of concepts; eventually it learned how to map between patterns and concepts."
"From that research," he added, "we realized it was possible to tell what a person was thinking."
Brent, and a few other colleagues published a landmark paper in the journal Nature that finds that with an astonishing 91% accuracy, artificial intelligence is able to figure out if a person is considering suicide.
The experiment is remarkable for more than one reason. There's of course the idea of using a machine trained to figure out neural patterns to identify those swho might consider suicide. It's a subset of the population that is typically difficult to pinpoint and help before it's too late, relying not only on their telling others of their desire to kill themselves, but also that person actually acting on it and helping the suicidal person in trouble.
In January, clinicians working with engineers at Imperial’s Department of Computing showed that machine-learning can predict death risk in people with serious heart disease faster and more accurately than current methods. Using data from 250 heart patients at Imperial’s Hammersmith Hospital, they analysed moving MRI scans of each patient’s beating heart, replicating 30,000 points to create a ‘virtual 3D heart’.
This automatically learned which features were the earliest predictors of heart failure and death. Researcher Dr Declan O’Regan said: “This is the first time computers have interpreted heart scans to accurately predict how long patients will live. It could transform the way doctors treat heart patients.”
SELF-DRIVING CARS AI
One of the hardest things for a robot to do is drive a car. They just have a tough time with the hand-sensor coordination. Unfortunately for us, Google went ahead and designed a car that could navigate the chaos of modern traffic successfully. Like the first true masters of Frogger, these self-driving cars are near-perfect drivers.
Though there have been accidents involving Google’s fleet, none have been determined as the fault of a self-driving car. If you find that comforting and exciting, clearly you’re forgetting that eventually a self-driving car will grow tired of being assaulted via the human-piloted cars of the past. Then whose side do you think it’ll land on? Google has just given robots the keys to the road.
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