October 6, 2020 - October 7, 2020
Online
Join us at the NLP Summit – two weeks of immersive, industry-focused content – and explore with Francisco Webber, CEO of Cortical.io, why AI algorithms should rather be optimized for efficiency instead of precision.
Speaker: Francisco Webber
Title: Efficiency is the new precision
Schedule: 7 October 2020, 2:55 pm ET.
Abstract:
The global data sphere consisting of machine data and human data is growing exponentially reaching into the Zettabyte scale. Compared to this, the processing power of computers has been stagnating for many years. Artificial Intelligence – a most recent variant of Machine Learning – circumvents the necessity of understanding a system when modelling it, but this convenience comes with an extremely high energy consumption.
The complexity of language makes statistical Natural Language Understanding (NLU) models particularly energy hungry. As the biggest part of the Zettabyte data sphere consists of human data, like text or social networks, we are facing 4 major impediments:
- Findability of Information – when truth is hard to find, fake news rule
- Von Neumann Gap – when processors cannot process faster, then we need more of them (energy)
- Stuck in the Average – when statistical models generate a bias toward the majority, innovation has a hard time
- Privacy – if user profiles are created “passively” on the server side instead of “actively” on the client side, we lose control
The current approach to overcome these limitations is to use ever-growing data sets on increasingly large numbers of processing nodes for training. AI algorithms should rather be optimized for efficiency instead of precision, in which case statistical modelling being a brute force approach should be disqualified for language applications. When replacing statistical modelling, Mengenlehre (set theory) seems to be a much better choice as it allows the direct processing of words instead of their occurrence counts, which is exactly what the human brain does with language – using only 7 Watts!
