This is a keynote highlight from the O'Reilly Artificial Intelligence Conference in Beijing 2019. You can also see other highlights from the event. Get a free trial today and find answers on the fly, or master something new and useful. Receive weekly insight from industry insiders--plus exclusive content, offers, and more on the topic of AI. Receive weekly insight from industry insiders--plus exclusive content, offers, and more on the topic of AI.

This is a keynote from the O'Reilly Artificial Intelligence Conference in New York 2019. See other highlights from the event. This keynote was sponsored by Dell Technologies. Get a free trial today and find answers on the fly, or master something new and useful. Receive weekly insight from industry insiders--plus exclusive content, offers, and more on the topic of AI.

We see the AI space poised for an acceleration in adoption, driven by more sophisticated AI models being put in production, specialized hardware that increases AI's capacity to provide quicker results based on larger datasets, simplified tools that democratize access to the entire AI stack, small tools that enables AI on nearly any device, and cloud access to AI tools that allow access to AI resources from anywhere. Integrating data from many sources, complex business and logic challenges, and competitive incentives to make data more useful all combine to elevate AI and automation technologies from optional to required. And AI processes have unique capabilities that can address an increasingly diverse array of automation tasks, tasks that defy what traditional procedural logic and programming can handle--for example: image recognition, summarization, labeling, complex monitoring, and response. Get a free trial today and find answers on the fly, or master something new and useful. In fact, in our 2019 surveys, more than half of the respondents said AI (deep learning, specifically) will be part of their future projects and products--and a majority of companies are starting to adopt machine learning.

Get a free trial today and find answers on the fly, or master something new and useful. Jonas argues that "AI is a lie"--meaning that our expectations far outsize the reality of what's currently possible. One of the issues arising from that disconnect is a level of corporate investment in the research process that hasn't been seen before. He argues this has led to "a lot questions about whether robots are going to take our jobs, and these sorts of things, which are all quite premature." Questions of ethics and what role it should play are increasingly arising in machine learning and AI research, especially in the area of science applications.

Check out the Strata Data and Artificial Intelligence conference series, which cover the topics and key issues discussed in this post. Here are key AI trends business leaders and practitioners should watch in the months ahead. 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."

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Subscribe to the O'Reilly Data Show Podcast to explore the opportunities and techniques driving big data, data science, and AI. Find us on Stitcher, TuneIn, iTunes, SoundCloud, RSS. In this episode of the Data Show, I speak with Alex Ratner, project lead for Stanford's Snorkel open source project; Ratner also recently garnered a faculty position at the University of Washington and is currently working on a company supporting and extending the Snorkel project. Snorkel is a framework for building and managing training data. Based on our survey from earlier this year, labeled data remains a key bottleneck for organizations building machine learning applications and services.

This is a keynote from the O'Reilly Artificial Intelligence Conference in London 2019. See additional keynotes and sessions from this event on the O'Reilly online learning platform. You can also check out more highlights from AI London '19. Get a free trial today and find answers on the fly, or master something new and useful. Receive weekly insight from industry insiders--plus exclusive content, offers, and more on the topic of AI.

People from across the TensorFlow community came together in Santa Clara, California for TensorFlow World. Below you'll find links to highlights from the event. Jeff Dean explains why Google open-sourced TensorFlow and discusses its progress. Get a free trial today and find answers on the fly, or master something new and useful. Theodore Summe offers a glimpse into how Twitter employs machine learning throughout its product.

Looking to make the most of current AI technologies and solutions in your business? Register now for the O'Reilly AI Conference in San Jose, September 9–12, 2019, and learn how to leverage AI in your work today. What can artificial intelligence (AI) and machine learning (ML) do to improve customer experience? AI and ML already have been intimately involved in online shopping since, well, the beginning of online shopping. You can't use Amazon or any other shopping service without getting recommendations, which are often personalized based on the vendor's understanding of your traits: your purchase history, your browsing history, and possibly much more.