Yesterday Twitter appointed Fei-Fei Li to their board of directors. Dr. Li is one of AI’s most brilliant minds and a leader in our field. Her engagement with Twitter is a clear indication that AI is strategically important for some of the world’s most well-known companies.
As it so happens, I had just finished writing and eBook (released today) that highlights one of her many contributions to the field - so the news made for a great start to my week. Nice move Twitter!
In our eBook - titled “Deep Learning For Data Security Professionals” - I write about a handful of watershed developments in AI and deep learning. Beginning in 2006, Dr. Li and her team were responsible for one of those developments. At the time, researchers tested new image recognition algorithms against a standard database so they could have a single benchmark to compare performance. As the state of the art improved, that database just wasn’t enough of a challenge. New algorithms all seemed to perform equally well and progress stalled. Dr. Li and her team started working on the problem, culminating in the ImageNet challenge in 2010. ImageNet revitalized algorithm research and catalyzed improvements all across the discipline. It’s certainly not Dr. Li’s only contribution to the field, but with the perspective of time it’s clear what a game changer it was.
Concentric is pioneering the use of natural language processing (a deep learning sub-discipline) in data security. As I’ve talked to customers and practitioners, I saw the need for a more thorough discussion of deep learning designed for IT professionals. In other words, this eBook is for technically-literate and intellectually curious readers. I hope you enjoy it.
Over the next few posts, I’m going to summarize some material from the eBook here in our blog. Here’s what you can expect:
- Deep learning - what, exactly, does the “deep” in deep learning mean?
- Representation learning - how do deep learning models categorize data?
- Natural language processing - what is it and how is it used?
- Deep learning versatility - how is deep learning capable of solving problems from autonomous driving to medical diagnostics to data security?
Can’t wait? Download our eBook here. And subscribe to our blog - we’ll let you know when we post our next installment!