Conversational AI / Natural-language processing

Alexa & Friends features Gokhan Tur, senior principal scientist at Amazon Alexa AI

Hear Tur discuss his experience from his work on DARPA programs, how he’s seen the field of conversational AI evolve, and more.

By Staff writer
September 28, 2020
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Amazon recently unveiled a host of new devices and AI services, including the ability for Alexa customers to directly teach Alexa. Among other things, this service helps Alexa "learn new concepts on the fly" by having her ask questions to fill gaps in her understanding—similar to what we do as humans.

On October 1, Jeff Blankenburg and Gokhan Tur met for a live interview to discuss Tur’s experience from his early days working on DARPA programs, how he’s seen the field of conversational AI evolve, and more about the machine learning technologies that provide teachable moments for Alexa.

Q&A with Gokhan Tur, Alexa AI senior principal scientist | Amazon Science

Tur has spent the past 20 years within the industry exploring the field of human/machine conversational language understanding systems. He has helped research and develop some of today’s leading voice technology systems across a diverse set of companies, and today leads research efforts related to helping Alexa become more conversational, natural, context-aware, knowledgeable, and self-learning.

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View from space of a connected network around planet Earth representing the Internet of Things.
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Applied Scientist
US, WA, Seattle
An information-rich and accurate product catalog is a strategic asset for Amazon. It powers unrivaled product discovery, informs customer buying decisions, offers a large selection, and positions Amazon as the first stop for shopping online. We use data analysis and statistical and machine learning techniques to proactively identify and fix item-item relationships within the Amazon product catalog. This problem is challenging due to sheer scale (billions of products in the catalog), diversity (products ranging from electronics to groceries to instant video across multiple languages) and multitude of input sources (millions of sellers contributing product data with different quality).Amazon’s Item Authority group is looking for an innovative and customer-focused applied scientist to help us make the world’s best product catalog even better. We believe that failure and innovation are inseparable twins. In this role, you will partner with technology and business leaders to build new state-of-the-art algorithms, models, and services to infer product-to-product relationships that matter to our customers. You will work in a collaborative environment where you can experiment with massive data from the world’s largest product catalog, work on challenging problems, quickly implement and deploy your algorithmic ideas at scale, understand whether they succeed via statistically relevant experiments across millions of customers.
Data Scientist
US, WA, Seattle
What is the most relevant business data for AWS leadership? What are the most important insights in this data? Are we investing enough in our infrastructure, or too much? How much new workloads do our new products drive into AWS? Which initiatives help our customers utilize AWS the most? How do our customers react to changes in prices, purchase options or products?The Central AWS Econ team is dedicated to answering these questions using quantitative, economic and statistical methods. We develop cutting edge data pipelines, build accurate predictive models, and provide insights to executive leaders throughout the company. We are looking for a talented, driven, and analytical researcher to help us answer these (and many more) questions.This Data Scientist role will develop models and datasets to support projects led by our senior researchers. The successful candidate will be a versatile problem solver who enjoys diving into data. This role is ideal for a data scientist who has strong coding skills. The role requires moving algorithms from prototype to application, optimizing and evaluating alternative technical approaches to the problem. The work will require collaborating with Data Scientists, BIEs and Data Engineers across AWS.Key Responsibilities:· Develop ML models for customer level predictions· Implement new algorithms to improve existing models· Collaborate with data engineers to integrate new data sources into the econ pipeline
View from space of a connected network around planet Earth representing the Internet of Things.
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