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SimBot Challenge FAQs

Frequently asked questions about the challenge.
General
General
What is the Alexa Prize?
Alexa is Amazon’s cloud-based voice service available on over 100 million devices from Amazon and third-party device manufacturers. With Alexa, you can build natural voice experiences that offer customers a more intuitive way to interact with the technology they use every day. Our collection of tools, APIs, reference solutions, and documentation makes it easy for anyone to build with Alexa.
Why did Amazon create the Alexa Prize?
The Alexa Prize, an annual university competition dedicated to accelerating the field of conversational artificial intelligence (AI), was created to recognize students from around the globe who are changing the way we interact with technology. The goal is to advance several areas of conversational AI including natural language understanding (NLU), context modeling, dialog management, commonsense reasoning, natural language generation (NLG), and knowledge acquisition.
How does the Alexa Prize support research?
The Alexa Prize is a research testbed for university students to experiment with and advance conversational AI at scale.

Research teams own the intellectual property (IP) in their systems and are encouraged to publish scientific articles on their work. As described in the Official Rules, participating teams grant Amazon a non-exclusive license to any technology or software they develop in connection with the competition.
What new datasets will I have access to as part of the Alexa Prize?
The TEACh dataset as well as a training dataset proprietary to the live interaction portion of the SimBot Challenge will be available to competitors in each phase.
SimBot
What is the SimBot Challenge?
SimBot, a competition focused on helping advance development of next-generation virtual assistants that will assist humans in completing real-world tasks by continuously learning, and gaining the ability to perform commonsense reasoning.

The SimBot Challenge will have two phases: A public benchmark phase, and a live interactions phase. Participants in both phases will build machine-learning models for natural language understanding, human-robot interaction, and robotic task completion. Artificial intelligence challenges addressed in the competition relate to reasoning on language and scene understanding, learning from demonstration, self-learning, and task completion utilizing natural language.

Unlike previous Alexa Prize competitions, the public benchmark challenge phase will be open to university teams, as well as individuals in academia and industry interested in advancing the science of AI and engaging top researchers from around the globe. The SimBot Challenge public benchmark phase is like existing visual language navigation competitions.
What is the difference between the Public Benchmark Challenge and the Live Interaction Challenge?
The Public Benchmark Challenge is open to any individual or team, academic or industry, who wants to complete and submit a model for evaluation and rating during the evaluation period. It is based on the TEACh dataset offered to the research community in October, 2021. The Live Interaction Period’s participation is limited solely to the university-based teams selected for the SimBot Challenge in November 2021 and June, 2022. These teams will each receive Amazon sponsorship to build a SimBot that will compete in a challenge from July, 2022 to September 2022 where they will receive real time ratings and feedback from Alexa Users.
Why is the SimBot - Live Interaction Challenge only limited to university teams?
The SimBot Challenge - live interaction phase is part of the Alexa Prize which is currently limited to universities and university students in Amazon initiatives to advance AI. However, the Public Benchmarking Challenge is open to both academic and university-based teams.
What will my SimBot do?
SimBot will navigate in a virtual environment to complete challenges guided by Alexa users. SimBot will interact with objects in the environment including but not limited to those common to offices and homes. There will be obstacles and hazards introduced to make game play fun and challenging.
How will I build my SimBot?
SimBots will use images from the game and instructions from Alexa users to navigate in a virtual world. Teams will build AI models which recognize objects and scenes as well as understand natural language commands from users. We plan to provide baseline data and a baseline model as a reference but we expect teams to develop new and novel approaches as well as augment the provided data to improve performance.
Eligibility: Public Benchmark Challenge
Phase 1, SimBot challenge
Who is eligible to participate in the public benchmark challenge?
Any individual or team, academic or industry-based.
How do I sign up to participate in the public benchmark challenge?
A registration form will open on November 15, 2021 at alexaprize.com.
Is funding available to university teams competing in the public benchmark challenge?
No, funding is only available to university teams selected to participate in the SimBot Challenge. In addition to the teams selected in 2021 up to four new, high-performing teams from the public benchmark challenge will be invited to apply for the SimBot challenge, live interaction phase for which funding is available. Learn more here.
Who can apply to participate?
Any individual or team can register and participate in the public benchmark phase with exception of parties from Cuba, Iran, North Korea, Sudan, Syria, and the region of Crimea.

Registration for the public benchmark challenge will open November 15, 2021. The challenge will begin on January 10, 2022.
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 registration.
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.
Eligibility: SimBot Challenge
Includes sponsored teams for both Public Benchmark and Live Interaction phases
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, North Korea, Sudan, Syria, and the region of Crimea (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 the duration of 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.
If my team fails to apply for the SimBot Challenge now, will there be any future opportunities to compete in the Live Interaction challenge?
Yes, the initial application period run from October 4-31, 2021. In addition to the teams selected in 2021 up to four new, high-performing university teams from the public benchmark challenge will be invited to apply for the SimBot challenge, live interaction phase for which funding is available. Learn more here.
Will university teams selected post-Public Benchmark Challenge be eligible for funding and for what amount?
Teams selected for the SimBot Challenge in June, 2022 will be eligible for funding.
If my team was not selected during the first application period are we eligible to re-apply in may if we qualify?
Yes. University-based teams that participate in the public benchmark phase are eligible to re-apply for the SimBot challenge between May 9 - 23, 2022. Four new, high-performing university teams from the public benchmark challenge will be invited to apply for the SimBot challenge, live interaction phase for which funding is available. Learn more here.
My team is not completely comprised of university students but we perform well in the public benchmark challenge? Is there an opportunity for us to continue in the competition?
Yes, we plan to continue the public benchmark competition through the end of 2022.
My company does collaborative work with several universities, are we eligible to compete in the live interaction challenge alongside them?
No, only full-time students are eligible to participate in the SimBot challenge, which includes the live interaction period.
My university and another frequently collaborate on projects - is there any exception to the students all enrolled in one university rule?
Applications are limited to students all from the same, single, university.
Teams
How many teams will be selected to participate?
All applications will be reviewed and evaluated by a panel of Amazon experts. Up to ten teams will be selected and sponsored by Amazon. All teams selected in November, 2021 will receive a $250,000 grant while those selected in June, 2022 will receive a $200,000 grant intended to support two full-time students, 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 are no minimum or maximum team member requirements. All team members must be enrolled in their university throughout the duration of the competition. All teams will receive a $250,000 grant if selected in November 2021 or a $200,000 grant if selected in June, 2022 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?
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.
Can I participate on two separate teams?
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, faculty advisors may request to remove or add members to the team, subject to approval by Amazon.
Can we discuss our SimBot with faculty or students who aren’t on our team?
Only team members may work on their SimBot. 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?
Check the SimBot page for the latest update on applications.
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 apply 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 a panel of Amazon employees. Teams will be selected 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 our experts to evaluate your proposal.
Competition details
What is the goal of the challenge?
To develop AI models which advance the state of the art and allow users to naturally interact with a robotic assistant in a virtual world to successfully complete a range of challenges.
How will winners be selected?
Winners will be determined based on the final standings at the completion of the finals period.
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 will need to be disclosed by January 1, 2023.
Will Alexa customers be able to engage with our SimBot?
Your team will be required to submit its SimBot 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 SimBot and provide feedback. After the Internal Amazon Beta Period, we will allow Amazon Alexa customers to try your SimBot and provide feedback to you. Amazon may impose Availability Criteria, or requirements the SimBot must meet before it will be made available to Alexa users. Availability Criteria may include criteria such as a minimum average customer rating, uptime requirements, and an ability to consistently filter offensive content.
Amazon launched the Echo in the UK, Germany, India, Japan, and other countries. Will localized languages be supported?
Your team must build its SimBot using U.S. English. Your SimBot will be available to Alexa customers in the U.S. Customers in other countries may also access it by setting their Amazon PFM (Preferred Marketplace) to U.S.
Will we publish our research from the Alexa Prize?
Yes. Publishing research papers as an outcome of your work on the Alexa Prize is required for all teams participating in the competition, although teams should 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 SimBot will not be selected for the finals if your team does not submit a technical paper for Alexa Prize proceedings. Papers will be published at the end of the competition in an online Proceedings of the Alexa Prize, which will be 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 without Amazon’s prior approval.
Who will own the intellectual property rights in my submission?
You will retain ownership over your SimBot. 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.
Prizes
What are the prizes for winning the competition?
A prize of $500,000 will be awarded to the team that creates the best SimBot. The second-place and third-place finalist teams will receive a $100,000 and a $50,000 prize, respectively. See the contest 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 Alexa Prize in November, 2021. These teams’ universities will receive a $250,000 research grant to fund the team members’ work over the year. Additional teams selected to participate in the SimBot Live Interaction challenge in June, 2022 will receive a $200,000 research grant to fund the team members’ work over the year.

The sponsorship includes one Alexa-enabled device per team member for up to a total of three devices per team and one Alexa-enabled device per faculty advisor, free AWS services to support the development of their SimBot, and support from the Alexa team.
How can the grant be spent?
The grants will be awarded with the intention that they will 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 grants 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. The official list of registered team members must be confirmed by January 30, 2023.
Timeline
What are the key milestones of the competition?
Teams must submit their applications between October 1, 2021 and October 31, 2021. Between November 1 and November 10, 2021, we will announce teams selected to participate. In the summer of 2022 following the public benchmark phase and the second application period teams will be invited to an Alexa Prize Bootcamp at Amazon where they will receive training on the resources made available to all competing teams. The finals will be scheduled between January 30 and March 27, 2023 and will determine the winning teams in the first annual SimBot Challenge.
If selected, when will we receive the stipend, devices, access to the Alexa Prize SimBot toolkit, our AWS account, and be introduced to our point of contact?
We will reach out to all teams no later than November 10, 2021 with instructions on next steps. Up to ten teams will be selected to receive a $250,000 stipend, Alexa-enabled devices, free AWS services to support their development efforts, and support from the Alexa team.
More information
See the full competition rules or submit your questions. Need assistance? Email: alexaprizesupport@amazon.com

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This role combines expertise in LLM reasoning and agentic AI with applied impact in life sciences. You will work on how large language models reason plan and act in complex scientific domains while applying domain knowledge to ensure models produce scientifically valid outputs. The problems span multiple fronts: • How do you build LLM-based agentic systems that correctly reason over clinical protocols regulatory standards and complex multi-step operational workflows? • How do you evaluate agent reliability and faithfulness rigorously enough to trust in high-stakes clinical settings? • How do you develop model customization methods (fine-tuning retrieval augmentation domain adaptation) that let customers get strong results from foundation models on their own data? You will focus on clinical trial operations (agentic automation structured reasoning evaluation domain adaptation) with opportunities to contribute across drug discovery (protein engineering antibody design) as the portfolio grows. You will own end-to-end scientific solutions from research through production and your work will directly shape the tools that scientists use daily. Key job responsibilities • Design train fine-tune and evaluate LLM-based agentic systems that reason over clinical protocols regulatory standards and operational workflows • Build rigorous evaluation harnesses and benchmarks to measure agent reliability faithfulness and failure modes in high-stakes domains • Develop model customization methods (fine-tuning RLHF retrieval augmentation domain adaptation) that help customers get better outputs on their own data with less effort • Contribute to graph-based and causal modeling approaches for clinical trial operations • Partner with Life Sciences domain experts product and engineering to translate scientific challenges into shipped capabilities • Own experiments end to end: problem framing implementation evaluation iteration and hand-off to production • Publish at top-tier venues where the work supports it • Contribute to drug discovery efforts (protein engineering antibody design) as opportunities arise A day in the life • Design and run an experiment to validate a new agentic reasoning or fine-tuning method then ship it as a capability customers can use • Diagnose why a model is failing on a new class of inputs and implement a fix to unblock a delivery milestone • Build or extend an evaluation benchmark to measure how faithfully an agent reasons over clinical logic • Meet with domain experts to scope what the next model release needs to do • Review results with a senior scientist sharpen the approach and get it over the finish line • Prototype a new idea that could become the next capability in the product About the team Amazon values diverse experiences. Even if you do not meet all of the preferred 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. 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. We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud. 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 and AmazeCon conferences, inspire us to never stop embracing our uniqueness. 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.
Data Scientist III, Amazon 1P Credito, Payments
BR, SP, Sao Paulo
Do you feel the challenge and the adrenaline kick when a huge data-set stares you in the face and you know that somewhere inside are hidden very important business insights that can fundamentally alter the way top business leaders think and act? Do you enjoy presenting strong data backed insights to business leaders; insights that can topple their long held beliefs and compel them to change their direction completely? If yes, then you are the one we are looking for. We are looking to invite passionate leaders, with expertise in generate power business insights from very large datasets, on a journey where the primary aim would be to enable needle moving business impacts through statistical analysis. We are looking for leaders who can envision the design and development of analytical infrastructure which can support strategic and tactical decision-making. Those who join this high visibility team would have to navigate through significant ambiguity in defining business problems and converting them to analytical problems. This role requires additional exposure and experience to Machine Learning. Key job responsibilities Use machine learning and analytical techniques to create scalable solutions for business problems • Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes • Design, development, evaluate and deploy innovative and highly scalable ml models such as risk scorecards, income models, fraud models for predictive learning in credit risk applications • Research and implement novel machine learning and statistical approaches • Work closely with software engineering teams to drive real-time model implementations and new feature creations • Work closely with business owners and operations staff to optimize various business operations • Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation • Mentor other scientists and engineers in the use of ML techniques • Innovate with the latest GenAI technology to build highly automated solutions for efficient customer promotions • Design, develop and deploy end-to-end machine learning solutions in the Amazon production environment to delight Amazon customers • Collaborate with cross-functional teams to develop comprehensive ML/statistical models that can scale to millions of customers to multiple countries Understand the credit risk data and evaluate the best ml model/ solution for dynamic business problems. About the team Brazil Payments is part of the International Emerging Stores Payments team and focuses on supporting the launch of new payment and financial products to our customers in Brazil.
Data Scientist II, Amazon 1P Credito, Payments
BR, SP, Sao Paulo
Do you feel the challenge and the adrenaline kick when a huge data-set stares you in the face and you know that somewhere inside are hidden very important business insights that can fundamentally alter the way top business leaders think and act? Do you enjoy presenting strong data backed insights to business leaders; insights that can topple their long held beliefs and compel them to change their direction completely? If yes, then you are the one we are looking for. We are looking to invite passionate leaders, with expertise in generate power business insights from very large datasets, on a journey where the primary aim would be to enable needle moving business impacts through statistical analysis. We are looking for leaders who can envision the design and development of analytical infrastructure which can support strategic and tactical decision-making. Those who join this high visibility team would have to navigate through significant ambiguity in defining business problems and converting them to analytical problems. This role requires additional exposure and experience to Machine Learning. Key job responsibilities • Use machine learning and analytical techniques to create scalable solutions for business problems • Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes • Design, development, evaluate and deploy innovative and highly scalable models for predictive learning • Research and implement novel machine learning and statistical approaches • Work closely with software engineering teams to drive real-time model implementations and new feature creations • Work closely with business owners and operations staff to optimize various business operations • Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation • Mentor other scientists and engineers in the use of ML techniques • Innovate with the latest GenAI technology to build highly automated solutions for efficient customer promotions • Design, develop and deploy end-to-end machine learning solutions in the Amazon production environment to delight Amazon customers • Collaborate with cross-functional teams to develop comprehensive ML/statistical models that can scale to millions of customers to multiple countries About the team Brazil Payments is part of the International Emerging Stores Payments team and focuses on supporting the launch of new payment and financial products to our customers in Brazil.
Data Scientist III, Amazon 1P Credito, Payments
BR, SP, Sao Paulo
Do you feel the challenge and the adrenaline kick when a huge data-set stares you in the face and you know that somewhere inside are hidden very important business insights that can fundamentally alter the way top business leaders think and act? Do you enjoy presenting strong data backed insights to business leaders; insights that can topple their long held beliefs and compel them to change their direction completely? If yes, then you are the one we are looking for. We are looking to invite passionate leaders, with expertise in generate power business insights from very large datasets, on a journey where the primary aim would be to enable needle moving business impacts through statistical analysis. We are looking for leaders who can envision the design and development of analytical infrastructure which can support strategic and tactical decision-making. Those who join this high visibility team would have to navigate through significant ambiguity in defining business problems and converting them to analytical problems. This role requires additional exposure and experience to Machine Learning. Key job responsibilities Use machine learning and analytical techniques to create scalable solutions for business problems • Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes • Design, development, evaluate and deploy innovative and highly scalable ml models such as risk scorecards, income models, fraud models for predictive learning in credit risk applications • Research and implement novel machine learning and statistical approaches • Work closely with software engineering teams to drive real-time model implementations and new feature creations • Work closely with business owners and operations staff to optimize various business operations • Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation • Mentor other scientists and engineers in the use of ML techniques • Innovate with the latest GenAI technology to build highly automated solutions for efficient customer promotions • Design, develop and deploy end-to-end machine learning solutions in the Amazon production environment to delight Amazon customers • Collaborate with cross-functional teams to develop comprehensive ML/statistical models that can scale to millions of customers to multiple countries Understand the credit risk data and evaluate the best ml model/ solution for dynamic business problems. About the team Brazil Payments is part of the International Emerging Stores Payments team and focuses on supporting the launch of new payment and financial products to our customers in Brazil.
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