December 24, 2019

133 words 1 min read

The state of AI adoption

The state of AI adoption

Program chairs Ben Lorica and Roger Chen kick off the O'Reilly AI Conference in San Francisco with an overview of the current trends they have observed in the industry.
Talk Title The state of AI adoption
Speakers Ben Lorica (O’Reilly), Roger Chen (Computable)
Conference Artificial Intelligence Conference
Conf Tag Put AI to Work
Location San Francisco, California
Date September 18-20, 2017
URL Talk Page
Slides
Video Talk Video

Enterprises are finding more use cases for artificial intelligence, driving a wave of algorithmic innovation, but the ripples from this impact are also influencing how data and computing technology stacks should be built for AI workloads. Program chairs Ben Lorica and Roger Chen kick off the O’Reilly AI Conference in San Francisco with an overview of the current trends they have observed in the industry.

intelligence intel conference algorithm cisco ai use case artificial intelligence
comments powered by Disqus
Humans in the loop: Jupyter notebooks as a frontend for AI pipelines at scale

Humans in the loop: Jupyter notebooks as a frontend for AI pipelines at scale

December 22, 2019

Paco Nathan reviews use cases where Jupyter provides a frontend to AI as the means for keeping humans in the loop. This process enhances the feedback loop between people and machines, and the end result is that a smaller group of people can handle a wider range of responsibilities for building and maintaining a complex system of automation.
Artificial intelligence in the software engineering workflow

Artificial intelligence in the software engineering workflow

December 20, 2019

Artificial intelligence is playing an increasingly important role in new software products, but the workflow of an AI researcher is quite different from the workflow of the software developer. Peter Norvig explains how the two can come together.
Benchmarking deep learning inference

Benchmarking deep learning inference

December 20, 2019

Artificial intelligence has had a tremendous impact on various applications at Baidu, including speech recognition and autonomous driving, although the performance requirements for all of these applications are very different. Sharan Narang outlines the challenges in inference for deep learning models and different workloads and performance requirements for various applications.
Fighting financial fraud at Danske Bank with artificial intelligence

Fighting financial fraud at Danske Bank with artificial intelligence

December 19, 2019

Fraud in banking is an arms race with criminals using machine learning to improve their attack effectiveness. Ron Bodkin and Nadeem Gulzar explore how Danske Bank uses deep learning for better fraud detection, covering model effectiveness, TensorFlow versus boosted decision trees, operational considerations in training and deploying models, and lessons learned along the way.
How Amy, an artificial intelligence capable of scheduling meetings, understands human intents

How Amy, an artificial intelligence capable of scheduling meetings, understands human intents

December 18, 2019

Rakesh Chada introduces x.ai's Amy, an AI assistant that schedules meetings via email. Rakesh discusses Amy's architecture and the various challenges the team faced during its design and shares several machine learning approaches for intent classification. Rakesh concludes by exploring a novel method for error optimization in a conversational agent that exploits customer error tolerance.
Is the body the missing link for true AI?

Is the body the missing link for true AI?

December 18, 2019

Ben Medlock explores the future of AI, explaining why the potential it holds is not at all frightening. Ben argues that the key to achieving elusive human-like AI lies in a central piece of the puzzle: embodiment.