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Ten university teams selected for Alexa Prize TaskBot Challenge 2

Second iteration features five new teams.

By Alexa Prize team
February 15, 2023
5 min read
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Amazon today announced that ten teams from around the globe have been selected to participate in the Alexa Prize TaskBot Challenge year 2, a university challenge focused on developing multimodal (voice and vision) conversational agents that assist customers in completing tasks requiring multiple steps and decisions.

Alexa Prize is a flagship industry-academic collaboration dedicated to accelerating the science of conversational artificial intelligence (AI) and multimodal human-AI interactions.

“Prize competitions provide an agile science experimentation framework for researchers and students encouraging them to explore transformational ideas at the boundaries of what is achievable,” said Reza Ghanadan, senior principal scientist with Alexa AI and head of Alexa Prize. “We have developed the CoBot platform and tools to lower the barriers to AI innovation for both the academic research community and students interested in conversational AI assistants. These tools allow students to quickly deploy their solutions at scale in the real world with Alexa, then observe, evaluate, and enhance their research results using feedback from Alexa customers.”

Photo of Participants in the Alexa Prize TaskBot Challenge Bootcamp
The Alexa Prize TaskBot Bootcamp was held in Seattle, Washington, with representatives from all ten university teams.

The teams selected for the challenge, which began in January, feature five returning entrants — including the top three finishers in the most recent challenge — and five new universities.

Team

University

Faculty advisor

Returning

TWIZ

NOVA School of Science and Technology

João Magalhães

EvoquerBOT

Penn State University

Rui Zhang

Taco 2.0

The Ohio State University

Huan Sun

GRILL

University of Glasgow

Jeff Dalton

Maruna

University of Massachusetts Amherst

Hamed Zamani

New

BoilerBot

Purdue University

Julia Rayz

DiWBot

Rutgers University

Matthew Stone

Sage

University of California, Santa Cruz

Xin (Eric) Wang

ISABEL

University of Pittsburgh

Malihe Alikhani

PLAN-Bot

Virginia Tech

Ismini Lourentzou

The prizes for overall performance in the competition will be $500,000 for the first-place team, $100,000 for second, and $50,000 for third. Those prizes will be paid out to the students on the teams with the best overall performance.

“I am delighted to see that new teams are joining the second year of the competition together with returning teams, who, by competing again, are signaling to us that they found value in the TaskBot challenge, said Yoelle Maarek, vice president research and science for Amazon Shopping.  

“We expect these talented graduate students to continue surprising us, as well as Amazon customers, this year. Connecting academia, Amazonians, and actual customers experimenting with taskbots, is a winning combination to keep pushing the boundaries of science in conversational AI for Alexa to delight and ease the lives of millions of customers.”

The Alexa Prize is a competition for university students dedicated to advancing the field of conversational AI. Launched in 2016, the program was created to recognize students from around the globe who are changing the way we interact with technology.

TaskBot Challenge 2 teams are working to address one of the hardest problems in conversational AI — creating next-generation conversational AI experiences that delight customers by addressing their changing needs as they complete complex tasks. This challenge builds upon the Alexa Prize’s foundation of providing universities a unique opportunity to test cutting-edge machine learning models with actual customers at scale.

The Alexa Prize TaskBot challenge provides a realistic scenario with real-user multimodal interactions, making this the perfect setting to observe and measure human-bot conversations and AI algorithms in a groundbreaking setting.
rafael_ferreira_twiz.jpg
Rafael Ferreira, NOVA School of Science and Technology, Team TWIZ
Our vision of EvoquerBOT combines improving task completion rates and elevating user satisfaction. To this end, we deliver innovative solutions to fundamental NLP challenges.
haoran_zhang.jpeg
Haoran Zhang, Penn State University, Team EvoquerBOT
We are especially interested in developing innovative ways to achieve successful coordination of multiple modalities, such as visual and verbal elements, and create a more engaging and intuitive user experience.
Lingbo_Mo.JPG
Lingbo Mo, The Ohio State University, Team Taco 2.0
The GRILL team is excited to continue bringing cutting-edge AI research to improve people’s lives. Our research team works on new capabilities of foundation models that understand text, images, and the surrounding world.
Sophie_portrait.jpg
Sophie Fischer, University of Glasgow, Team GRILL
The competition lets us create interfaces for the general public in a production environment – it’s a unique opportunity to connect our research with our career goals.
Baber (Rutgers).jpeg
Baber Khalid, Rutgers University, Team DiWBot
We are very excited to be part of the community and look forward to working with the Alexa team and other teams.
Anthony_Sicilia.jpg
Anthony Sicilia, University of Pittsburgh, Team ISABEL
The Alexa Prize TaskBot Challenge combines a vast range of tasks over multiple domains with multimodal outputs. This is the ultimate test for any moonshot concept, and we can't wait to see what the real world has in store for us.
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Rey (Alex) Gonzalez, Purdue University, Team BoilerBot
Participating in this competition is an incredible opportunity that will allow us to do applied research and ship it to real users.
ChrisSamarinas_DSC02670.jpg
Chris Samarinas, University of Massachusetts Amherst, Team Maruna
Although artificial intelligence has experienced explosive development in the past decade, there is still a gap between research and real-world application. The TaskBot Challenge provides us with a unique opportunity to explore multimodal AI in practical situations.
UCSC Kaishi TB2.png
Kaizhi Zheng Univerisity of California, Santa Cruz-Amherst, Team Sage
Our bot will make adaptable conversation a reality by allowing customers to follow personalized decisions through the completion of multiple, sequential sub-tasks and adapt to the tools, materials, or ingredients available to the user by proposing appropriate substitutes and alternatives.
Afrina Tabassum
Afrina Tabassum

TaskBot is the first conversational AI challenge to incorporate multimodal customer experiences, so in addition to receiving verbal instructions, customers with Echo Show or Fire TV devices, can also be presented with step-by-step instructions, images, or diagrams that enhance task guidance.

This year’s challenge has been expanded to include more hobbies and at-home activities. Participating teams were asked to propose interesting ways to incorporate visual aids into every conversation turn when a screen is available. Innovative ideas on improving the presentation of visual aids, as well as the coordination of visual and verbal modalities, were part of the team selection criteria.

Each university selected for the challenge receives a $250,000 research grant, Alexa-enabled devices, free Amazon Web Services (AWS) cloud computing services to support their research and development efforts, access to Amazon scientists, the CoBot (conversational bot) toolkit and other tools such as automated speech recognition through Alexa, neural detection and generation models, conversational data sets, and design guidance and development support from the Alexa Prize team.

"Alexa, let's work together"

The university teams’ taskbots will be available for Alexa customers to engage with in May 2023 with a finals event being held in September, and winners announced later that month.

As with the previous challenge, Alexa customers can engage in conversation with teams’ taskbots when they become available in May by saying, “Alexa, let’s work together.” Until then, “Alexa, let’s work together” will direct you to conversations with the previous challenge winners of 2022 and the Alexa Prize TaskBot.

After initiating the interaction, Alexa customers then receive a brief message informing them that they are interacting with an Alexa Prize university taskbot before being randomly connected to one of the participating taskbots.

After exiting the conversation with the taskbot, which customers can do at any time, the customer is prompted for a verbal rating, followed by an option to provide additional feedback. The interactions, ratings, and feedback are shared with the teams to help them improve their taskbots. Customer ratings are also used to determine which university teams will move on to the semifinals and finals.

Our goal is to contribute to the multimodal conversational AI field and move it closer to the way humans perceive, reason, and communicate through multimodal information.
joao_magalhaes_twiz.jpg
João Magalhães, associate professor, NOVA School of Science and Technology, Team TWIZ
We look forward to the Challenge because it is the perfect platform to create multimodal, tasked-oriented dialogue systems that elevate user experience and engagement.
rui_zhang.jpeg
Rui Zhang, assistant professor, Penn State University, Team EvoquerBOT
Through this TaskBot Challenge, we hope our work can expand the horizon of conversational AI along dimensions like dialogue depth, multi-modal coordination, commonsense reasoning, and learning from use.
Huan_Sun.png
Huan Sun, associate professor, The Ohio State University, Team Taco 2.0
The GRILL team is creating the next generation of open assistants that understand and use knowledge about the world and can communicate effectively to inform and educate.
jeff.jpeg
Jeff Dalton, associate professor, University of Glasgow, Team GRILL
Our TaskBot will help people get things done through personalized, adaptive, and context-aware conversational interaction by combining our research results with the state-of-the-art capabilities of Alexa devices.
Matthew Stone (Rutgers).jpg
Matthew Stone, professor, Rutgers University, Team DiWBot
We work towards making conversational AI technology more inclusive and collaborative. Inclusive Alexa can collaborate with users from diverse cultures and with different communication capabilities and preferences.
Malihe_Alikhani.jpg
Malihe Alikhani, assistant professor, University of Pittsburgh, Team ISABEL
We hope to develop a task-oriented system that can interact with users based on their level of knowledge, experience, and communication preference.
purdue 1.jpg
Julia Rayz, professor, Purdue University, Team BoilerBot

Success in the previous TaskBot Challenge required teams to address many difficult AI obstacles. The challenge required the fusion of multiple AI techniques including knowledge representation and inference, commonsense and causal reasoning, and language understanding and generation.

The “GRILLBot” team from University of Glasgow won the TaskBot 1 Challenge, earning a $500,000 prize for its performance. Teams from NOVA School of Science and Technology (Portgual) and The Ohio State University earned second- and third-place prizes, respectively.

Research papers from Amazon’s Alexa Prize team, and each of the competing teams, can be viewed and downloaded here.

Alexa Prize Taskbot Challenge Finals | Amazon Science

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Applied Scientist I, Tablet Product Software
US, WA, Seattle
Are you excited to play a strategic role in defining the customer experience on Tablets? Come join a dynamic, customer-obsessed, world-class science team to completely reshape the customer experience on our tablets. Key job responsibilities Using Amazon’s large-scale computing resources, you will design and deploy state-of-the-art recommendation models. You will ask research questions about customer behavior, design state-of-the-art models that help customers discover content, and deploy these models to production alongside other engineers. You will participate in the Amazon ML community and mentor other engineers with a strong interest in and knowledge of ML and generative AI. Your work will directly benefit customers! A day in the life We are looking for a passionate, hard-working, and talented Applied Scientist who has experience developing state-of-the-art models and deploying them to production. You will have an opportunity to make an enormous impact on the design, architecture, and implementation of products used everyday by real customers! About the team The Alexa Tablet team is a world-class team that delivers high-quality, innovative products that are loved by our customers. Our team focuses on spinning many of Amazon’s flywheels with bar-raising mobile experiences on our tablets. Over the last 12 years, we have built 4.0+ star rated products, and we continue to look for ways to scale our business. Join us as we continue our ambitious journey which will give you the opportunity to deliver disruptive products with global impact.
Applied Scientist II, Detail Page
IN, KA, Bengaluru
Amazon.com’s Product Detail Page team is looking for talented, motivated and passionate applied scientist to be part of the design and development of a highly scalable multi-tiered shopping application to provide the best possible online shopping experience for Amazon customers world-wide. Our team is comprised of talented applied scientists, developers, testers, program managers, designers and product managers tasked with the singular goal to create THE world's best buying experience. Scientists on this team develop the next-generation technologies and experiences that change how millions interact and shop online. To provide the best possible online shopping at the scale of the web requires ideas from every area of computer science, including distributed computing, large-scale system design, machine learning, natural language processing, data compression and user interface design; the list goes on and is growing every day. We need our scientists to be versatile and always eager to tackle new problems as we continue to push technology forward. Our team leverages sophisticated econometric, machine learning, and big data technologies to help customers to discover the right products at the right prices from millions of trusted sellers billions of times a day. If you are looking for a career-defining opportunity on one of the most customer centric and business impacting teams within Amazon, we’d love to hear from you. We are looking for an Applied Scientist to help build the next generation of Detail Page optimization algorithms. These new set of algorithms will incorporate the continually changing preferences of our customers and continue to scale with numerous new programs that Amazon is introducing for our customers. You will work with multiple Amazon businesses and programs to identify big business opportunities and propose new business features and technical systems to improve customer experience on Amazon Detail Page, Search Page and many other widgets throughout the website. You will be responsible for the quality of algorithm design and will get the opportunity to present your ideas and share results of your deliverables with Amazon executives on a frequent basis. You will get an opportunity to work with senior scientists to define and enforce broad, company-wide technical standards in optimization techniques, statistical modeling and simulation techniques, and/or data analytics.
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