Future of Machine Learning

September 27, 2016

Machine learning is a versatile field with a bright future. Engineers in the field are constantly innovating and creating new technologies that could one day be fully incorporated into people’s lives. Kitchens, labs and hospitals will soon be filled with machine learning technology.

June Intelligent Oven
Just in time for the holidays, a major advancement in home technology will be available for shipping all over the United States. June Intelligent Oven is the first breakthrough in kitchen appliances since the invention of the microwave in the 1970s, and it uses machine learning through image recognition.

This smart oven can identify 15 common foods, including cookie dough and bacon, with built-in HD cameras that can withstand temperatures up to 500 degrees and cutting edge image recognition technology. After its release, June will be continually updated to recognize a larger variety of foods.
After June identifies what food is about to be cooked, the food is weighed, and a cooking plan is recommended. Two core temperature probes ensure that foods like steak are cooked to the desired temperature.

Co-founder of June, Nikhil Bhogal, designed the camera software for the first five generations of iPhone, and members of the June team have previously worked on the Apple Watch, GoPro and FitBit. This qualified team utilized the same machine learning algorithms that Google Images uses.

Biotechnology and Cancer diagnosis
As scientists uncover more layers of complexity in the natural world, machine learning may be the only technology strong enough to comprehend the expanding field of biology. Cancer diagnosis and treatment, two of the most pertinent tasks in modern biology and medicine, will likely improve thanks to the abilities of artificial intelligence.

Sophia Genetics, a 5-year-old company paving the way for high-tech genomic research, uses machine learning algorithms to analyze thousands of different genomes to diagnose certain types of cancer. The software is also able to advise medical treatment for the cancer based on the genetic mutation that causes it.

According to Anna Domanska of “Industry Leaders Magazine,” this type of technology may soon be able to compare one individual’s cancer to that of a previous patient, give the survival rate of those with similar conditions and recommend the most effective treatment plan. In as soon as two years, machine learning may remodel the way we diagnose cancer.

Ellie the Robot Therapist
Machine learning isn’t just for the lab. At the Institute for Creative Technologies at USC, researchers have been developing a “robot psychologist” to surpass the duties of a human psychotherapist.

Named “Ellie,” this computer uses machine learning software to process information from the patient’s behavior and determine its own reaction. A webcam and microphone enable it to comprehend facial expressions and rate of speech, as well as the length of the pause the client takes before answering a question. This information is processed through a series of algorithms that tell it when to nod or ask a specific question.

As of now, Ellie is used only for research and not medical practice, but recent results prove it could be useful in the future because of its non-human makeup. According to a 2014 study by researcher Jonathan Gratch and his staff, patients who undergo “treatment” from Ellie are more likely to open up if they are aware that it is a computer — only a computer, with no human operator. Patients who are told they are talking to a human-controlled robot will be more closed off and focus more on what they say, whereas the distance of a guaranteed robot encourages more truthful results.

According to “The Economist,” this type of patient reaction could be useful for war veterans suffering from PTSD. Because many ex-soldiers are reluctant or opposed to seeking therapy for mental illness, Ellie may be a possible non-human emotional outlet that is capable of advising treatment plans.

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