With faster processing power, training data can be larger and neural networks more complex. The rise of improved processing power and its availability through cloud services allows artificial intelligence to become more advanced.
Artificial intelligence needs large sets of data, called training data, to learn and become accurate. Depending on the level of complexity, these data sets may need millions or even billions of data points. With the rise of the internet, smartphones, and digitization, large scale user data is captured and now available to "train."
Datafication is a modern technological trend turning many previously analogue aspects of our lives into computerized, measurable data. Smartphones, laptops, tablets, and wearable devices capture previously undocumented data points to allow for more sophisticated predictive analytics. Such data points include heart rate, eye movements, tone of voice, location, facial expressions, speed, exercise habits, nutrition levels, and more. This holistic snapshot of users presents new opportunities for innovation.
The Opportunity To Revolutionize Education
90% of students learning through one-on-one instruction attain a level of achievement reached by only the highest 20% of students in the conventional 30-person classroom (Bloom, 1984). The educational experience should resemble the personalized engagement and achievement scores that one-to-one instruction brings. Classrooms, however, continue to be driven by the lecture method because one-to-one instruction has been too costly. What if the emerging trends in artificial intelligence could make individualized instruction now possible at scale? What if 90% of today's population could test in the top 20% of our existing conventional classroom structure?
Granting One-To-One Instruction To All
Ahura combines existing technologies, empirically-backed academic research, and its own intellectual property to provide personalized education that delivers performance equivalent to that of one-to-one instruction.