TaskBot Challenge FAQs

Frequently asked questions about the challenge.
TaskBot
What is a TaskBot?
A TaskBot is a conversational agent that assists customers in completing DIY and Cooking tasks requiring multiple steps and decisions. It is the second conversational AI challenge to incorporate multimodal (voice and vision) customer experiences.
Can I choose to build any type of conversational bot?
No, you must build a TaskBot.
What will my TaskBot do?
A TaskBot helps customers complete tasks that require multiple steps and decisions in target domains such as hobbies and at-home activities such as Home Improvement and Cooking. For example, customers could ask a TaskBot to help them “bake a healthy birthday cake”. A successful TaskBot will be able to discuss different approaches to nutrition and understand individual customer’s preferences. It would then walk the customer through baking a cake step-by-step, while solving problems arising along the way, e.g., missing ingredients, and continue the conversation over multiple-days sessions.
How will I build my TaskBot?
You will use the Alexa Skills Kit (ASK) to build an Alexa skill, hosted on AWS Lambda that will create the end-to-end conversational experience for a user. Using the provided APIs, your skill will receive as input the text of the user’s utterance, and produce as output a text sentence that will be spoken to the user. You do not need to tackle ASR (automatic speech recognition) or TTS (text to speech). You will also be provided with the TaskBot Toolkit (a conversational bot toolkit), a software development kit that works with ASK and was built specifically for Alexa Prize teams to reduce the involved engineering in setting up a TaskBot and allow teams to focus on the science.


Your skill will need to determine an appropriate response at each turn of the conversation. You may use additional data sources or libraries if you wish, subject to the terms described in the Official Rules.
What is the Alexa Skills Kit (ASK)?
The Alexa Skills Kit (ASK) is a collection of free, self-service APIs, tools, documentation, and code samples that make it fast and easy for you to add skills to Alexa. Your team will use ASK to build, deploy, and test a TaskBot that is capable of conversing with millions of Alexa users.
What is TaskBot toolkit?
TaskBot, is a conversational bot toolkit in Python for natural language understanding and dialog management. The toolkit provides a set of tools, libraries and base models designed to help develop, train and deploy multimodal conversational experiences through the Alexa Skills Kit (ASK), and to provide uniform visual look for TaskBots on screened devices. The primary goal of the toolkit is to drive improved quality of conversational agents by providing a solution that is modular, extensible, and scalable, and provide abstractions for infrastructure and low-level tasks.
Competition details
How will winners be selected?
Through various phases of the competition, TaskBots will be evaluated based on feedback from Alexa users and assessment by Amazon.


Midway through the competition, all TaskBots that have been certified and published will be evaluated by Alexa users and Amazon. As defined in the Official Rules, TaskBots that meet the required criteria will advance to later phases of the competition and eventually the semifinals.



During the semifinals round, Alexa users will evaluate the semifinalist TaskBots. Two TaskBots selected by Alexa users and up to three TaskBots selected by the Amazon panel will advance to the finals. During the finals in September 2023, the finalist teams will compete head-to-head in front of judges. The judges will score the TaskBots on their ability to successfully complete the task requested.
Will this competition be judged like a Turing Test?
No. The goal of the Alexa Prize is to create TaskBots that fluently and effectively assist the user, not to make them indistinguishable from a human when compared side-by-side. While the TaskBots built for the Alexa Prize will be human-like in some respects, they will be very different in others, and could easily reveal themselves in a Turing Test. For example, TaskBots may have ready access to much more information than a human. Asking the TaskBots to act like a human could diminish the customer experience and hinder the efforts of the participants to build the best TaskBot to further conversational AI.
When and where is the finals event?
The finals event will be held in September 2023 at a location to be determined, with the results will be announced in September 2023.
Can we use other funding to help us participate in this challenge?
Yes, you may use other funding to support your team, subject to the terms described in the Official Rules. External funding must be disclosed to Amazon.
Can we use technology other than AWS to host our TaskBot?
Your team may build its TaskBot in any framework of your choosing, but the TaskBot must be hosted on AWS to leverage Alexa’s TaskBot toolkit.
Will Alexa customers be able to engage with our TaskBot?
Your team will be required to submit its TaskBot for certification and publication by the Amazon Alexa team. After certification, you will enter the Internal Amazon Beta Period, where Amazon employees will test your TaskBot and provide feedback. After the Internal Amazon Beta Period, we will allow Alexa users to try your TaskBot and provide feedback to you. Amazon may impose requirements that the TaskBots must meet before they will be made available to Alexa users. Such requirements, specified in the Official Rules, may include, among other things, a minimum average customer rating, uptime requirements, or the ability to consistently filter offensive content.
Which Alexa users will be able to interact with the TaskBots, and what languages must they support?
TaskBots will be made available to Alexa users in the United States or who select the United States as their preferred marketplace. Your team must build its TaskBot using U.S. English.
Will we publish our research from the Alexa Prize?
Yes. Publishing research papers as an outcome of your work on Alexa Prize is required for all teams participating in the competition, although teams may not publish Amazon confidential information, as described in the Official Rules. The Alexa Prize requires all teams to submit a technical paper for the Alexa Prize proceedings. Your TaskBot will not be selected for the finals if your team does not submit a technical paper for Alexa Prize proceedings. Papers will be published online at the end of the competition and made publicly available.


Teams may also publish research papers in third-party publications and conferences, as long as all papers are provided to Amazon for review at least two weeks before the submission deadlines and no research papers are published before the Alexa Prize proceedings are published, unless Amazon approves otherwise in writing.
Who will own the intellectual property rights in my submission?
You will retain ownership over your TaskBot. Amazon will have a non-exclusive license to any technology or software you develop in connection with the competition. See the Official Rules for details.
Eligibility
Who can apply to participate?
The Alexa Prize is open to full-time students enrolled in an accredited university, with the exception of universities in Cuba, Iran, Syria, North Korea, Sudan, the region of Crimea, and where prohibited by law (see Official Rules). Proof of enrollment will be required to participate.
Can I participate if I don’t attend a university?
No. The Alexa Prize is open only to full-time enrolled university students.
Do I need to be enrolled in a university program throughout my participation in the competition?
All participating team members must remain full-time students in good standing at their university while participating in the competition.
Do I need to be a certain age?
Participants must be at or above the age of majority in the country, state, province or jurisdiction of residence at the time of entry.
Can I enroll if a family member is an Amazon employee?
Immediate family members and household members of Amazon employees, directors, and contractors are not eligible to participate. See Official Rules for additional restrictions.
Teams
How many teams will be selected to participate?
All applications will be reviewed and evaluated by Amazon. Up to ten teams will be selected and sponsored by Amazon. All teams will receive a $250,000 grant intended to support two full-time students and a month of faculty time, free Alexa devices, and free AWS hosting including access to CPU and GPU based machines, SQL and NoSQL databases, and object storage. See the Official Rules for details.
How many team members can our team have?
There is no minimum or maximum number of team members. All team members must be enrolled in their university throughout their participation. All teams will receive a $250,000 grant regardless of how many members are on the team. We recommend a team with 4-6 students with diverse fields of study or areas of expertise.
Can students from different universities be on the same team?
No. Teams must be comprised of students attending the same university.
Can one university have more than one team?
Yes, universities may have more than one team. Multiple teams cannot have the same faculty advisor.
Can I participate on two separate teams?
No. You can only be a part of one team for the duration of the competition.
Can undergraduate and graduate students work together?
Yes, teams may be comprised of undergraduate and graduate students.
Do I need a faculty advisor?
All teams must nominate a faculty advisor and include the faculty advisor’s consent in the applications.
What is the role of the faculty advisor?
Faculty advisors will advise students on technical directions and be a sounding board for new ideas, similar to a graduate school advisor. They will also act as the official representative from the university for this competition.
Can we add or remove team members during the competition?
During the competition, there will be a period of time during which faculty advisors may request to remove or add members to the team, subject to approval by Amazon. See the Official Rules for details.
Can we discuss our TaskBot with faculty or students who aren’t on our team?
Only team members may work on their TaskBots. However, the faculty advisor and other students and faculty members at your university may provide support and advice to your team and may co-author technical publications and research papers.
Application process
How do we apply?
Please fill in the Taskbot Challenge 2 application hosted on YouNoodle.
What do we need to apply?
Once you have selected your team members, team leader, and faculty sponsor, you are ready to begin the application process.
Do all team members have to apply?
Each team must have a team lead, who should submit only one application on behalf of the whole team. Your application must include all of your team members’ information.
Is there an application fee?
There is no application fee.
How will teams be selected to participate?
All applications will be reviewed by Amazon. Teams will be selected by Amazon based on the following criteria: (1) the potential scientific contribution to the field; (2) the technical merit of the approach; (3) the novelty of the idea; and (4) an assessment of the team’s ability to execute against their plan. Please be sure to provide enough detail in your application to enable evaluation of your proposal.
Prizes
What are the prizes for winning the competition?
A prize of $500,000 will be awarded to team that creates the best TaskBot. The second-place and third-place finalist teams will receive a $100,000 and a $50,000 prize, respectively. See the Official Rules for details.
Do we get a stipend and devices to participate in the Alexa Prize?
Up to ten teams will be sponsored to participate in the competition. Each sponsored team’s university will receive a $250,000 research grant to help fund the team’s participation.


The sponsorship includes Alexa-enabled devices, free AWS services to support the development of the team’s TaskBot, and support from the Alexa team.
How can the grant be spent?
The grants are intended to support two full-time students for the duration of the Competition and one month of the Faculty Advisor’s salary. No more than 35% of the research grant may be allocated to administrative fees. If your team would like to use the funds in another manner, your faculty advisor must receive approval from Amazon before doing so.
What happens if we are selected and receive a stipend but can no longer participate?
Stipends will be awarded in installments payable to the university. If your team withdraws before any of the installments, remaining funds will not be transferred to the university.
How will the prizes be distributed among a team?
The first, second, and third place prizes will be distributed equally among all registered team members.
Timeline
What are the key milestones of the competition?
Teams must submit their applications by early November, 2022. Teams selected to participate in the competition will be notified by early January, 2023. The competition will run from about January 2023 through September 2023. See the Official Rules for details.
More information
See the Official Rules or submit your questions. Need assistance? Email: alexaprizesupport@amazon.com

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The Amazon Search Mission Understanding (SMU) team is at the forefront of revolutionizing the online shopping experience through the Amazon search page. Our ambition extends beyond facilitating a seamless shopping journey; we are committed to creating the next generation of intelligent shopping assistants. Leveraging cutting-edge Large Language Models (LLMs), we aim to redefine navigation and decision-making in e-commerce by deeply understanding our users' shopping missions, preferences, and goals. By developing responsive and scalable solutions, we not only accomplish the shopping mission but also foster unparalleled trust among our customers. Through our advanced technology, we generate valuable insights, providing a guided navigation system into various search missions, ensuring a comprehensive and holistic shopping experience. Our dedication to continuous improvement through constant measurement and enhancement of the shopper experience is crucial, as we strategically navigate the balance between immediate results and long-term business growth. We are seeking an Applied Scientist who is not just adept in the theoretical aspects of Machine Learning (ML), Artificial Intelligence (AI), and Large Language Models (LLMs) but also possesses a pragmatic, hands-on approach to navigating the complexities of innovation. The ideal candidate will have a profound expertise in developing, deploying, and contributing to the next-generation shopping search engine, including but not limited to Retrieval-Augmented Generation (RAG) models, specifically tailored towards enhancing the Rufus application—an integral part of our mission to revolutionize shopping assistance. You will take the lead in conceptualizing, building, and launching groundbreaking models that significantly improve our understanding of and capabilities in enhancing the search experience. A successful applicant will display a comprehensive skill set across machine learning model development, implementation, and optimization. This includes a strong foundation in data management, software engineering best practices, and a keen awareness of the latest developments in distributed systems technology. We are looking for individuals who are determined, analytically rigorous, passionate about applied sciences, creative, and possess strong logical reasoning abilities. Join the Search Mission Understanding team, a group of pioneering ML scientists and engineers dedicated to building core ML models and developing the infrastructure for model innovation. As part of Amazon Search, you will experience the dynamic, innovative culture of a startup, backed by the extensive resources of Amazon.com (AMZN), a global leader in internet services. Our collaborative, customer-centric work environment spans across our offices in Palo Alto, CA, and Seattle, WA, offering a unique blend of opportunities for professional growth and innovation. Key job responsibilities Collaborate with cross-functional teams to identify requirements for ML model development, focusing on enhancing mission understanding through innovative AI techniques, including retrieval-Augmented Generation or LLM in general. Design and implement scalable ML models capable of processing and analyzing large datasets to improve search and shopping experiences. Must have a strong background in machine learning, AI, or computational sciences. Lead the management and experiments of ML models at scale, applying advanced ML techniques to optimize science solution. Serve as a technical lead and liaison for ML projects, facilitating collaboration across teams and addressing technical challenges. Requires strong leadership and communication skills, with a PhD in Computer Science, Machine Learning, or a related field. We are open to hiring candidates to work out of one of the following locations: Palo Alto, CA, USA | Seattle, WA, USA
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The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Applied Science Manager with a strong deep learning background, to lead the development of industry-leading technology with multimodal systems. Key job responsibilities As an Applied Science Manager with the AGI team, you will lead the development of novel algorithms and modeling techniques to advance the state of the art with multimodal systems. Your work will directly impact our customers in the form of products and services that make use of vision and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate development with multimodal Large Language Models (LLMs) and Generative Artificial Intelligence (GenAI) in Computer Vision. About the team The AGI team has a mission to push the envelope with multimodal LLMs and GenAI in Computer Vision, in order to provide the best-possible experience for our customers. We are open to hiring candidates to work out of one of the following locations: Bellevue, WA, USA | Seattle, WA, USA | Sunnyvale, CA, USA
US, WA, Seattle
Amazon is looking for a passionate, talented, and inventive Senior Applied Scientist with a strong machine learning background to help build industry-leading language technology. Our mission is to provide a delightful experience to Amazon’s customers by pushing the envelope in Natural Language Processing (NLP), Generative AI, Large Language Model (LLM), Natural Language Understanding (NLU), Machine Learning (ML), Retrieval-Augmented Generation, Responsible AI, Agent, Evaluation, and Model Adaptation. As part of our AI team in Amazon AWS, you will work alongside internationally recognized experts to develop novel algorithms and modeling techniques to advance the state-of-the-art in human language technology. Your work will directly impact millions of our customers in the form of products and services, as well as contributing to the wider research community. You will gain hands on experience with Amazon’s heterogeneous text and structured data sources, and large-scale computing resources to accelerate advances in language understanding. The Science team at AWS Bedrock builds science foundations of Bedrock, which is a fully managed service that makes high-performing foundation models available for use through a unified API. We are adamant about continuously learning state-of-the-art NLP/ML/LLM technology and exploring creative ways to delight our customers. In our daily job we are exposed to large scale NLP needs and we apply rigorous research methods to respond to them with efficient and scalable innovative solutions. At AWS Bedrock, you’ll experience the benefits of working in a dynamic, entrepreneurial environment, while leveraging AWS resources, one of the world’s leading cloud companies and you’ll be able to publish your work in top tier conferences and journals. We are building a brand new team to help develop a new NLP service for AWS. You will have the opportunity to conduct novel research and influence the science roadmap and direction of the team. Come join this greenfield opportunity! Amazon Bedrock team is part of Utility Computing (UC) About the team AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services. Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Hybrid Work We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices. We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA