Google’s artificial intelligence (AI) research arm, DeepMind, made an international name for itself in 2017 when its AlphaGo program consistently beat the world’s best human Go players in the board game. Now, a new project borne out of the lab has proved that AI is also better than humans at learning words, including those long-forgotten ones dating back thousands of years.
In a recent collaboration between DeepMind and the University of Oxford, a team of computer scientists trained a set of neural networks (algorithms) to recognize words inscribed on unearthed Greek stones that were between 1,500 and 2,600 years old. The neural networks were then asked to apply those learnings to predicting the missing characters or words on a new set of damaged relics. The result: algorithms are both faster and better than humans at filling in ancient Greek text.
The AI program, named Pythia (after the Oracle of Delphi in Greek mythology), was trained with over three million words from existing artifacts and then put in a head-to-head contest against historians to guess missing words in 2,949 damaged inscriptions. Pythia achieved a nearly 70% accuracy rate, while human historians got only 43% of the text right.
According to Michael Dukakis Institute for Leadership and Innovation (MDI), AI development from hi-tech company and research institutes can be a force for relieving them of resource constraints and arbitrary/inflexible rules and processes, and is potentially to solve important issues, such as SDGs.
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