AI and the Future of Machine-Learning


 How the dream of artificial intelligence is shaping the coming world


It all started as Science Fiction. The concept of artificial intelligence, or AI, began in the 50s and 60s, with dystopian depictions of hyper intelligent robots invading, enslaving humans and taking over the world. Movies like Star Wars, 2001: A Space Odyssey, and the Terminator franchise introduced us to sentient machines, capable of benevolence as well as evil. But for all the hype and expectation, actual advancement in this technology was pure fiction, up until recently. These days AI is at the precipice of a new frontier of technological capability, due to developments in its most practical branch - machine learning. 

Machine learning involves computer programs that autonomously learn from large swaths of data, to evolve their algorithms without being explicitly programmed. The first real breakthrough in machine learning occurred when IBM’s Deep Blue beat the world chess champion Garry Kasparov in 1997. Since then, AI and machine learning have come to the forefront of tech culture, so much so that the White House recently formed a subcommittee on machine learning and artificial intelligence, which monitors the benefits and privacy risks associated with this new technology.

The end goals of machine learning are to have computers execute tasks currently performed by humans, and eventually to surpass human intelligence altogether in problem solving. There are examples of machine learning programs currently in use all around us, from Google’s near-perfect spam filters, to Netflix’s individualized recommendations. As AI continues to develop at this exponential rate, the potential for practical applications is beginning to see the light of day. Here are some of the leading applications being developed, that offer us a glimpse into a bright and exciting future:

Autonomous Driving

Elon Musk has been described as an Einstein of the digital age. His companies have pioneered mass production of the electric car, produced affordable solar energy for homes and with SpaceX, revolutionized modern space travel. Musk’s current challenge is to create a fully autonomous vehicle, a self-driving car. His company Tesla uses machine learning algorithms, detailed mapping and valuable sensor data taken from other Teslas on the road. The brilliance of Musk’s software is that the Tesla fleet works in a great, interwoven network; when one car learns something, all the others learn it too. Elon Musk has announced that the fully-autonomous vehicle will be ready soon, and when it is, the practical applications will be revolutionary.

Just as the introduction of the machine took over for many unskilled farm and factory laborers during the Industrial Revolution, a self-driving vehicle would surely replace modern truck driving. Massive cargo being transported across the country every day, by error-prone humans, would likely be replaced with machines, capable of working continuously and without major risk.

Personalized Medicine

Personalized medicine is a practice that involves separating patients into specific groups, with products and treatments specially targeted to the needs of those individuals. The Machine Learning for Personalized Medicine organization, or MLPM, is leading the way towards spawning scientists who use machine learning to create individual medical treatment based on patients’ genetic properties. MLPM’s work begins with recording the health state of a patient down to the molecular level, with the goal being to optimize medical treatment for the specific patient.

The end goal in the coming years will be to see a comprehensive file on every single patient in a hospital, containing the genetic makeup, molecular profile and completely accurate predictable models of different treatment outcomes, based on multitudes of observational data. This would drastically limit misdiagnoses and waste both time and medical resources.

Language Translation

Skype, the video call application, utilized machine learning to create an automatic translate feature. A user speaking into a headset and the application then converts the words into text, translates those words, and transmits synthesized spoken words in the new language to the other person on the line. Skype is continuing to improve and develop this technology to create instant translation.

What this means for communication is unprecedented; people from different countries and cultures can speak and understand one another instantly. The possibilities of this technology are endless, people can and will be connected like they’ve never been before. The Skype translator is the result of machine learning algorithms based in speech recognition research.


AI and machine learning have given practical and achievable goals for data scientists everywhere. In the near future, machine learning and its resulting technology will be involved in every aspect of technology, improving our world like never before. So when you think of AI, you don’t need to think of hyper-intelligent evil robots attacking humanity and enslaving us all, it’s not going to happen. Well, probably not.


Interested in joining the discussion? Connect with Eccella CEO, Meitav Harpaz on LinkedIn. Connect on LinkedIn