Posts Tagged ‘creativity’

Conversational AI: The Science behind the Alexa Prize

Conversational agents are exploding in popularity. However, much work remains in the area of social conversation as well as free-form conversation over a broad range of domains and topics. To advance the state of the art in conversational AI, Amazon launched the Alexa Prize, a 2.5-million-dollar university competition where sixteen selected university teams were challenged to build conversational agents, known as “socialbots”, to converse coherently and engagingly with humans on popular topics such as Sports, Politics, Entertainment, Fashion and Technology for 20 minutes.

The Alexa Prize offered the academic community a unique opportunity to perform research with a live system used by millions of users. The competition provided university teams with real user conversational data at scale, along with the user-provided ratings and feedback augmented with annotations by the Alexa team. This enabled teams to effectively iterate and make improvements throughout the competition while being evaluated in real-time through live user interactions.

To build their socialbots, university teams combined state-of-the-art techniques with novel strategies in the areas of Natural Language Understanding, Context Modeling, Dialog Management, Response Generation, and Knowledge Acquisition. To support the teams’ efforts, the Alexa Prize team made significant scientific and engineering investments to build and improve Conversational Speech Recognition, Topic Tracking, Dialog Evaluation, Voice User Experience, and tools for traffic management and scalability.

This paper outlines the advances created by the university teams as well as the Alexa Prize team to achieve the common goal of solving the problem of Conversational AI.

Conversational AI: The Science behind the Alexa Prize

by Ashwin Ram, Rohit Prasad, Chandra Khatri, Anu Venkatesh, Raefer Gabriel, Qing Liu, Jeff Nunn, Behnam Hedayatnia, Ming Cheng, Ashish Nagar, Eric King, Kate Bland, Amanda Wartick, Yi Pan, Han Song, Sk Jayadevan, Gene Hwang, Art Pettigrue

Proceedings of the 2017 Alexa Prize
Invited talk at NIPS-2017 Workshop on Conversational AI
Invited talk at re:Invent 2017 (with Spyros Matsoukas)

READ THE PAPER:

s3.amazonaws.com/alexaprize/2017/technical-article/alexaprize.pdf
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Announcing the 2017 Alexa Prize Finalists

We’ve hit another milestone in the Alexa Prize, a $2.5 million university competition to advance conversational AI. University teams from around the world have been hard at work to create a socialbot, an AI capable of conversing coherently and engagingly with humans on popular topics and news events for 20 minutes.

I am now excited to announce the university teams that will be competing in the finals! After hundreds of thousands of conversations, the two socialbots with the highest average customer ratings during the semifinal period are Alquist from the Czech Technical University in Prague and Sounding Board from the University of Washington in Seattle. The wildcard team is What’s Up Bot from Heriot-Watt University in Edinburgh, Scotland.

READ MORE:

developer.amazon.com/blogs/alexa/post/783df492-4770-4b11-81ac-59e009669d56/announcing-the-2017-alexa-prize-finalists

 

Join the Alexa Prize Journey and Test the Socialbots

On September 29, 2016, Amazon announced the Alexa Prize, a $2.5 million university competition to advance conversational AI through voice. In April, university teams from around the world assembled at the appropriately named Day 1 building in Seattle for the Alexa Prize Summit. The event was a base camp for teams to share learnings and make preparations for the most challenging leg of their journey: to build and scale an AI capable of conversing coherently and engagingly with humans for 20 minutes.

As they build their “socialbots,” they will encounter esoteric problems like context modeling and dialog planning as well as exoteric problems like user experience and conversational engagement. And they will need all the help they can get.

We invite you to join the students on their journey and help them along the way. You can interact with their socialbots simply by saying, “Alexa, let’s chat” on any device with Alexa.

READ MORE:
developer.amazon.com/blogs/alexa/post/e4cc64d1-f334-4d2d-8609-5627939f9bf7/join-the-alexa-prize-journey-and-test-the-socialbots

 

Making The Future Possible: Conversational AI in Amazon Alexa

No longer is AI solely a subject of science fiction. Advances in AI have resulted in enabling technologies for computer vision, planning, decision making, robotics, and most recently spoken language understanding. These technologies are driving business growth, and releasing workers to engage in more creative and valuable tasks.

I’ll talk about the moved from the age of the keyboard, to the age of touch, and are now entering the age of voice. Alexa is making this future possible. Amazon is committed to fostering a robust cloud-based voice service, and it is this voice service that the innovators of today, tomorrow, and beyond will be building. It is this voice service—and the ecosystem around it—that awaits the next generation of AI talent.

Keynote at Udacity Intersect Conference, Computer History Museum, Mountain View, CA, March 8, 2017.
 

READ MORE:

blog.udacity.com/2017/02/dr-ashwin-ram-intersect-2017-speaker.html

VIEW THE TALK:

linkedin.com/feed/update/urn:li:activity:6286681682187812864

 

Announcing the Sponsored Teams for the 2016-2017 Alexa Prize

On September 29, 2016, Amazon announced the Alexa Prize, a $2.5 million university competition to advance conversational AI through voice. We received applications from leading universities across 22 countries. Each application was carefully reviewed by senior Amazon personnel against a rigorous set of criteria covering scientific contribution, technical merit, novelty, and ability to execute. Teams of scientists, engineers, user experience designers, and product managers read, evaluated, discussed, argued, and finally selected the ten teams who would be invited to participate in the competition. Wait, make that twelve; we received so many good applications from graduate and undergraduate students that we decided to sponsor two additional teams.

Today, we’re excited to announce the 12 teams selected to compete with an Amazon sponsorship.

READ MORE:

developer.amazon.com/blogs/post/Tx1UXVV4VJTPYTL/announcing-the-sponsored-teams-for-the-2016-2017-alexa-prize

The Alexa Prize: $2.5M to Advance Conversational AI

Artificial intelligence (AI) is becoming ubiquitous. With advances in technology, algorithms, and sheer compute power, it is now becoming practical to utilize AI techniques in many everyday applications including transportation, healthcare, gaming, productivity, and media. Yet one seemingly intuitive task for humans still eludes computers: natural conversation. Simple and natural for humans, voice communication in everyday language continues to be one of the ultimate challenges for AI.

Today, we are pleased to announce the Alexa Prize, a $2.5 million university competition to advance conversational AI through voice. Teams of university students around the world are invited to participate in the Alexa Prize (see contest rules for details). The challenge is to create a socialbot, an Alexa skill that converses coherently and engagingly with humans on popular topics for 20 minutes. We challenge teams to invent an Alexa socialbot smart enough to engage in a fun, high quality conversation on popular topics for 20 minutes.

Are you up to the challenge?

READ MORE:

developer.amazon.com/public/community/post/Tx221UQAWNUXON3/Are-you-up-to-the-Challenge-Announcing-the-Alexa-Prize-2-5-Million-to-Advance-Co

Construction and Adaptation of AI Behaviors in Computer Games

Computer games are an increasingly popular application for Artificial Intelligence (AI) research, and conversely AI is an increasingly popular selling point for commercial digital games. AI for non playing characters (NPC) in computer games tends to come from people with computing skills well beyond the average user. The prime reason behind the lack of involvement of novice users in creating AI behaviors for NPC’s in computer games is that construction of high quality AI behaviors is a hard problem.

There are two reasons for it. First, creating a set of AI behavior requires specialized skills in design and programming. The nature of the process restricts it to certain individuals who have a certain expertise in this area. There is little understanding of how the behavior authoring process can be simplified with easy-to-use authoring environments so that novice users (without programming and design experience) can carry out the behavior authoring task. Second, the constructed AI behaviors have problems and bugs in them which cause a break in player expe- rience when the problematic behaviors repeatedly fail. It is harder for novice users to identify, modify and correct problems with the authored behavior sets as they do not have the necessary debugging and design experience.

The two issues give rise to a couple of interesting questions that need to be investigated: a) How can the AI behavior construction process be simplified so that a novice user (without program- ming and design experience) can easily conduct the authoring activity and b) How can the novice users be supported to help them identify and correct problems with the authored behavior sets? In this thesis, I explore the issues related to the problems highlighted and propose a solution to them within an application domain, named Second Mind(SM). In SM novice users who do not have expertise in computer programming employ an authoring interface to design behaviors for intelligent virtual characters performing a service in a virtual world. These services range from shopkeepers to museum hosts. The constructed behaviors are further repaired using an AI based approach.

To evaluate the construction and repair approach, we conduct experiments with human subjects. Based on developing and evaluating the solution, I claim that a design solution with behavior timeline based interaction design approach for behavior construction supported by an understandable vocabulary and reduced feature representation formalism enables novice users to author AI behaviors in an easy and understandable manner for NPCs performing a service in a virtual world. I further claim that an introspective reasoning approach based on comparison of successful and unsuccessful execution traces can be used as a means to successfully identify breaks in player experience and modify the failures to improve the experience of the player interacting with NPCs performing a service in a virtual world.

The work contributes in the following three ways by providing: 1) a novel introspective reasoning approach for successfully detecting and repairing failures in AI behaviors for NPCs performing a service in a virtual world.; 2) a novice user understandable authoring environment to help them create AI behaviors for NPCs performing a service in a virtual world in an easy and understandable manner; and 3) Design, debugging and testing scaffolding to help novice users modify their authored AI behaviors and achieve higher quality modified AI behaviors compared to their original unmodified behaviors.

Read the dissertation:

Construction and Adaptation of AI Behaviors in Computer Games

by Manish Mehta

PhD dissertation, College of Computing, Georgia Institute of Technology, August 2011.

smartech.gatech.edu/handle/1853/42724