This is part 3 in a series. Part 1 is here and Part 2 is here.To announce Google’s AutoML, Google CEO Sundar Pichai wrote, “Today, designing neural nets is extremely time intensive, and requires an expertise that limits its use to a smaller community of scientists and engineers. That’s why we’ve created an approach called AutoML, showing that it’s possible for neural nets … [Read more...] about Google’s AutoML: Cutting Through The Hype
NLP
An Opinionated Introduction To AutoML And Neural Architecture Search
This is part 2 in a series. Check out part 1 here and part 3 here.Researchers from CMU and DeepMind recently released an interesting new paper, called Differentiable Architecture Search (DARTS), offering an alternative approach to neural architecture search, a very hot area of machine learning right now. Neural architecture search has been heavily hyped in the last year, … [Read more...] about An Opinionated Introduction To AutoML And Neural Architecture Search
4 Approaches To Natural Language Processing & Understanding
In 1971, Terry Winograd wrote the SHRDLU program while completing his PhD at MIT. SHRDLU features a world of toy blocks where the computer translates human commands into physical actions, such as “move the red pyramid next to the blue cube.” To succeed in such tasks, the computer must build up semantic knowledge iteratively, a process Winograd discovered was brittle and … [Read more...] about 4 Approaches To Natural Language Processing & Understanding
What Salesforce Einstein Teaches Us About Enterprise AI
Every business has customers. Every customer needs care. That’s why CRM is so critical to enterprises, but between incomplete data and clunky workflows, sales and marketing operations at most companies are less-than-optimal.At the same time, companies who aren’t Google or Facebook don’t have the billion dollar R&D budgets to build out A.I. teams to take away our … [Read more...] about What Salesforce Einstein Teaches Us About Enterprise AI