9 AI trends on our radar

[A version of this post appears on the O’Reilly Radar.]

How new developments in automation, machine deception, hardware, and more will shape AI.

Here are key AI trends business leaders and practitioners should watch in the months ahead.

We will start to see technologies enable partial automation of a variety of tasks.

Automation occurs in stages. While full automation might still be a ways off, there are many workflows and tasks that lend themselves to partial automation. In fact, McKinsey estimates that “fewer than 5% of occupations can be entirely automated using current technology. However, about 60% of occupations could have 30% or more of their constituent activities automated.”

We have already seen some interesting products and services that rely on computer vision and speech technologies, and we expect to see even more in 2019. Look for additional improvements in language models and robotics that will result in solutions that target text and physical tasks. Rather than waiting for a complete automation model, competition will drive organizations to implement partial automation solutions—and the success of those partial automation projects will spur further development.
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7 data trends on our radar

[A version of this post appears on the O’Reilly Radar.]

From infrastructure to tools to training, here’s what’s ahead for data.

Whether you’re a business leader or a practitioner, here are key data trends to watch and explore in the months ahead.

Increasing focus on building data culture, organization, and training

In a recent O’Reilly survey, we found that the skills gap remains one of the key challenges holding back the adoption of machine learning. The demand for data skills (“the sexiest job of the 21st century”) hasn’t dissipated. LinkedIn recently found that demand for data scientists in the US is “off the charts,” and our survey indicated that the demand for data scientists and data engineers is strong not just in the US but globally.

With the average shelf life of a skill today at less than five years and the cost to replace an employee estimated at between six and nine months of the position’s salary, there is increasing pressure on tech leaders to retain and upskill rather than replace their employees in order to keep data projects (such as machine learning implementations) on track. We are also seeing more training programs aimed at executives and decision makers, who need to understand how these new ML technologies can impact their current operations and products.
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In the age of AI, fundamental value resides in data

[A version of this post appears on the O’Reilly Radar.]

The O’Reilly Data Show Podcast: Haoyuan Li on accelerating analytic workloads, and innovation in data and AI in China.

In this episode of the Data Show, I spoke with Haoyuan Li, CEO and founder of Alluxio, a startup commercializing the open source project with the same name (full disclosure: I’m an advisor to Alluxio). Our discussion focuses on the state of Alluxio (the open source project that has roots in UC Berkeley’s AMPLab), specifically emerging use cases here and in China. Given the large-scale use in China, I also wanted to get Li’s take on the state of data and AI technologies in Beijing and other parts of China.

Here are some highlights from our conversation:
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Books I enjoyed in 2018

Here are nonfiction books I enjoyed reading in 2018 (more precisely, these are books I read during the second part of 2017 through 2018). Not all of these books were released this year, although most them are 2018 releases. I read many of these using Apple Books on my iPad but I’ve also gotten back to scouring thrift stores and used bookstores (where I’ve gotten some amazing bargains this year).


China
My wife and I have taken several trips to China over the last few years, and along the way I’ve enjoyed several books that I list below:

  • The China Questions: Critical Insights into a Rising Power – This highly readable collection of essays is truly an essential resource.
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