State of AI Report 2019
State of AI Report 2019This year's "State of AI Report" has been released. Read it to find out about the latest in AI research, talent, industry, and politics form the past 12 months.
This year's State of AI Report is out.
The report is an attempt to "capture a snapshot of the exponential progress in AI with a focus on developments in the past 12 months," and is put together by Nathan Benaich — founder of Air Street Capital, a VC partnership of industry specialists investing in intelligent systems, founder of the Research and Applied AI Summit and the RAAIS Foundation to advance progress in AI — and Ian Hogarth — an angel investor in 50+ startups with a focus on applied machine learning and a Visiting Professor at UCL.
From the report's website:
Consider this report as a compilation of the most interesting things we’ve seen that seeks to trigger an informed conversation about the state of AI and its implication for the future. This edition builds on the inaugural State of AI Report 2018, which can be found here.
We consider the following key dimensions in our report:
- Research: Technology breakthroughs and their capabilities.
- Talent: Supply, demand and concentration of talent working in the field.
- Industry: Large platforms, financings and areas of application for AI-driven innovation today and tomorrow.
- China: With two distinct internets, we review AI in China as its own category.
- Politics: Public opinion of AI, economic implications and the emerging geopolitics of AI.
The report delves into specific topics such as reinforcement learning, the auto industry, robotics, advancements in NLP, professional employment trends, and much more.
In an effort to promote honesty and accountability, Benaich and Hogarth review and score their predictions from last year's report as well.
View the easily-digestible report on SlideShare or download a PDF, but definitely take a look at it in some form and make sure you haven't missed anything that has happened in AI over the past 12 months.
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- Seven Key Dimensions to Help You Understand Artificial Intelligence Environments
- NLP vs. NLU: from Understanding a Language to Its Processing
