The concept of the “technological singularity” is the idea that humans will one day be overtaken by machines with A.I.. The date for this to happen is getting closer and closer. But will robots eventually take over?
We don’t yet know if robots will be able to supplant us, but Ray Kurzweil (Google’s director of engineering) predicted that by 2029 robots will be smarter than humans. This concept, which arose in science fiction, is currently in full debate among A.I. experts, while Google has created the Singularity University to investigate it.
What timetable does Kurzweil foresee for the future?
– In 2023, a computer will equal the processing power of a human.
– In 2030, we would reach the Singularity and an out-of-control A.I. could emerge, capable of creating even better A.I.s exponentially.
– By 2050, one computer will be able to process as much as the sum of all human brains combined.
What key points does Kurzweil highlight?
1º. A.I. will drive a revolution in knowledge that will affect culture, science and engineering.
2º. Getting computers to understand natural language, to reach the same level of understanding as a human.
3º. In the future, the capacity of intelligent computers will merge with people, with chips integrated into our own body or brain, making us healthier and smarter.
Will robots take over?
Science fiction has promoted the idea that one day intelligent robots will make autonomous decisions and come to confront and subdue people.
In the scientific world, there are many who reject this idea. A.I. will improve us but not supplant us, however, it is also a double-edged sword that leads us to “play with fire”, it warms us and helps us to cook, but we can also get burned.
Are there more risks associated with A.I.?
As intelligent systems become embedded in society, we may be left in the hands of machines that decisively influence our health or work. The possibility of achieving singularity raises many unknowns for the future, if machines – with unprecedented intellectual capacity – become self-aware and are able to design even better machines, the debate is on. Technological advances in A.I. must go hand in hand with both legal and ethical consensus, determining the red lines that must never be crossed (as in genetics, for example).
Nubeprint developed the first engine with A.I. for MPS in 2013, improved a year later for management optimization and implemented to this day, always complying with the strictest security and data protection regulations. With its MPS-specific Machine Learning, machine learning algorithms use historical data as input to predict new values, based on the A.I.
SOURCE: bbc.com / actionsdata.com / lateralia.es / Nubeprint.com