*This is an excerpt from Matthew Hugh’s original article posted on TheNextWeb
Language is tricky. It’s full of nuance and layers, and regional and dialectal variations that complicate things even further.
For example, if I was to describe something as “sick”, do I mean that it’s disgusting, impressive, or quite literally unwell? Again, there’s the word “cool”. Is it a positive adjective, or a statement of temperature?
Computers really struggle to understand this.
Sure, you can train an AI to identify spelling mistakes and grammatical errors. It’s relatively trivial to build a bot whose job is solely to identify the use of passive voice. But when it comes to actually understanding the language used, and making suggestions based on it, they tend to fall down.
At the core, you’ve got an artificial neural network that’s been painstakingly built to understand 23 distinct measures of language and structure. This artificial neural network is continuously growing, and as it consumes more data, it becomes more precise.
It boasts over three million articles in its database. This is growing constantly, and is analyzed on a regular basis.
“While a human being has an understanding of communication and language, computers do not,” explained Bradley Silver, co-founder of Atomic Reach.
“The biggest challenge for us has been for teach Atomic AI how to read, and continue to grow and adapt. Especially when inputs become more sophisticated, and language is a growing and dynamic thing.”
Silver explained that Atomic AI has been developed with the ability to identify the context and intended use of each word.