Social

SocialBot Grand Challenge FAQs

Frequently asked questions about the challenge.
General
General
What is a SocialBot?
In the context of Alexa Prize, a SocialBot is an Alexa skill that can engage customers in a conversation about popular topics such as entertainment, sports, politics, technology, and fashion.
Can I choose to build any kind of conversational bot?
No, this competition focuses solely on SocialBots. Your SocialBot will need to converse about a wide range of popular societal topics and current events, and not only topics of your choosing. You will develop your own technologies relevant to your approach, such as natural language understanding, dialog management, knowledge acquisition, commonsense reasoning, conversational planning, machine learning, natural language generation, etc. Far-field automatic speech recognition (ASR) and text-to-speech (TTS) will be provided by Amazon, along with additional data, models, and tools.
What will my SocialBot do?
Your SocialBot will be an Alexa skill that can converse coherently and engagingly with humans on popular topics and current events. If your SocialBot advances to the pertinent stage of the competition, Alexa users in the U.S. may ask to converse with your SocialBot about topics of interest to them, such as baseball playoffs, celebrity gossip, or scientific breakthroughs. For example:
  • User: Let’s chat about the Mars Mission.
  • SocialBot: There are multiple Mars missions, some public and some private.
  • User: Who do you think will succeed?
  • SocialBot: I think more than one will succeed. The first one to get to Mars will open the doors for others.
  • User: I’d love to go to Mars.
  • SocialBot: Me too. Luckily I can hitch a ride on any computer.
  • User: That’s very funny.
  • SocialBot: The biggest challenge isn’t technology, it’s funding. It will cost $500 billion to send humans to Mars.
Your SocialBot will continue turn-by-turn interaction, starting with a topic the user asked for, until the user chooses to stop. Like an everyday human conversation, the interaction may shift naturally to related topics, as in the above example, but the conversation should remain coherent, relevant, and engaging. Your SocialBot may suggest topics to keep the conversation flowing. The goal is to keep the conversation from deteriorating to the point where the user loses interest.
How will I build my SocialBot?
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 CoBot 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 SocialBot and allow teams to focus on the science.


Your skill will need to determine an appropriate response at each turn of the conversation. It will also need to keep up with current news and events using the provided data sources. 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 SocialBot that is capable of conversing with millions of Alexa users.
Competition details
What is the goal of the challenge?
The goal of the SocialBot Grand challenge 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. The grand challenge objective is to create a SocialBot that converses coherently and engagingly with humans on popular topics for 20 minutes while achieving a user rating of at least 4.0/5.0.
How will winners be selected?
Through various phases of the competition, SocialBots will be evaluated based on feedback from Alexa users and assessment by Amazon.


Following the initial feedback period, SocialBots that have been certified and published will be evaluated on criteria such as the average interaction rating, uptime requirements, and ability to filter offensive content in order to advance to the Semifinals Interaction Period.



During the semifinals interaction period, Alexa customers will evaluate the semifinalist SocialBots. The two SocialBots with the highest Semifinals Interaction Rating Average and up to three more SocialBots selected by Amazon will advance to the finals.



Teams that advance to and complete the Semifinals Interaction Period, regardless of whether they advanced to the Finals Event, will be eligible to compete for Scientific Invention and Innovation Prizes based on the level of scientific invention and innovation demonstrated by each Entrant Team throughout the Competition.



The Teams whose SocialBots attain the three highest Composite Scores during the finals event will be the winners of the Overall Performance Prizes.
Will this competition be judged like a Turing Test?
No. The goal of the Alexa Prize is to create SocialBots that engage in interesting, human-like conversations, not to make them indistinguishable from a human when compared side-by-side. While the SocialBots 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, SocialBots may have ready access to much more information than a human. Asking the SocialBots to act like a human could diminish the customer experience and hinder the efforts of the participants to build the best SocialBot to further conversational AI.
When and where is the finals event?
The finals event will be held in July 2023 at a location to be determined, with a science invention and innovation presentation review to follow. The competition results will be announced in August 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.
Will Alexa customers be able to engage with our SocialBot?
Your team will be required to submit its SocialBot 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 SocialBot and provide feedback. After the Internal Amazon Beta Period, we will allow Alexa users to try your SocialBot and provide feedback to you. Amazon may impose requirements that the SocialBots must meet before they will be made available to Alexa users. Such requirements 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 SocialBots, and what languages must they support?
SocialBots 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 SocialBot 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 SocialBot 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 SocialBot. 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 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 four to six 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 Official Rules for details.
Can we discuss our SocialBot with faculty or students who aren’t on our team?
Only team members may work on their SocialBots. 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?
Begin the application via 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. 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?
Overall Performance Prize: For the three teams that build the SocialBot with the highest overall performance, the first-place team will win $250,000, the second-place team will win $50,000, and the third-place team will win $25,000. These prizes will be paid directly to the students on each winning team.


Scientific Invention and Innovation Prize: For the three teams that demonstrate the most scientific invention and innovation throughout the competition, the first-place team will win $250,000, the second-place team will win $50,000, and the third-place team will win $25,000. These prizes will be paid directly to the students on each winning team.



Grand Prize: If and only if the SocialBot of the team that wins the first-place Overall Performance Prize also achieves the grand challenge of conversing coherently and engagingly with humans for 20 minutes in at least two-thirds of its conversations at the finals event and achieves a 4.0 or higher composite score, that team’s university will be awarded a $1 million research grant.



See 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 SocialBot, and support from the Alexa Prize team.
How can the grant be spent?
The grant is 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.
How will the prizes be distributed among a team?
Each Overall Performance Prize and the Scientific Invention and Innovation Prize will be distributed equally among the members of each winning team.
Timeline
What are the key milestones of the competition?
Teams must submit their applications by October 5, 2022. Teams selected to participate in the competition will be notified in October of November 2022. The competition will run from about November 2022 through August 2023. See Official Rules for details.

Latest news

The latest updates, stories, and more about Alexa Prize.
  • knowledge-graph.png._CB453975899_.png
    Innovations from the 2018 Alexa Prize
    Behnam Hedayatnia
    March 5, 2019
    The 2018 Alexa Prize featured eight student teams from four countries, each of which adopted distinctive approaches to some of the central technical questions in conversational AI. We survey those approaches in a paper we released late last year, and the teams themselves go into even greater detail in the papers they submitted to the latest Alexa Prize Proceedings. Here, we touch on just a few of the teams’ innovations.
    Conversational AI
  • CoBot_architecture.jpg._CB453492855_.jpg
    AI tools let Alexa Prize participants focus on science
    Anushree Venkatesh
    February 27, 2019
    To ensure that Alexa Prize contestants can concentrate on dialogue systems — the core technology of socialbots — Amazon scientists and engineers built a set of machine learning modules that handle fundamental conversational tasks and a development environment that lets contestants easily mix and match existing modules with those of their own design.
    Conversational AI

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US, NY, New York
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Applied Scientist, Fauna
US, CA, Sunnyvale
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Senior Applied Scientist, Fauna
US, CA, Sunnyvale
We are seeking a Senior Applied Scientist to focus on Robotics Spatial Intelligence and Semantic Understanding. In this role, you'll research and build advanced semantic and world understanding algorithms that enable robots to observe, understand, and reason about complex and dynamic home environments. You'll work across a broad spectrum of 3D perception, contextual understanding, and world modeling approaches to build robust solutions that support autonomous decision making, task planning, navigation, and manipulation. Key job responsibilities - Develop and implement robust World Understanding and Modeling algorithms for a domestic robot. - Build simulation-based and on-robot evaluation frameworks with comprehensive benchmarks and metrics for systematic evaluation of Our Spatial Intelligence stack. - Conduct sim-to-real transfer experiments, analyzing performance gaps and developing techniques to ensure reliable real-world performance. - Collaborate with navigation, manipulation, and other teams to ensure seamless integration of World Understanding capabilities. - Stay current with the latest advances in World Modeling, Spatial Reasoning, and related fields and apply relevant findings to improve system performance About the team Fauna Robotics, an Amazon company, is building capable, safe, and genuinely delightful robots for everyday life. Our goal is simple: make robots people actually want to live and interact with in everyday human spaces. We believe that future won’t arrive until building for robotics becomes far more accessible. Today, too much effort is spent reinventing the fundamentals. We’re changing that by developing tightly integrated hardware and software systems that make it faster, safer, and more intuitive to create real-world robotic products. Our work spans the full stack: mechanical design, control systems, dynamic modeling, and intelligent software. The focus is not just functionality, but experience. We’re building robots that feel responsive, expressive, and genuinely useful. At Fauna, you’ll work at the frontier of this space, helping define how robots move, manipulate, and interact with people in natural environments. It’s an opportunity to solve hard problems across hardware and software with a team focused on making robotics accessible and joyful to build. If you care about making robotics real for everyone and building systems that are as delightful as they are capable, we’re interested in hearing from you.
Senior Data Scientist, IES CFX & Prime
IN, KA, Bengaluru
Are you passionate about applying machine learning and advanced statistical techniques to protect one of the world's largest online marketplaces? Do you want to be at the forefront of developing innovative solutions that improve Amazon's customers experience? Do you thrive in a collaborative environment where diverse perspectives drive breakthrough solutions? If yes, we invite you to join the Amazon Customer Fulfillment & Prime analytics team. We're seeking an exceptional scientist who can revolutionize how we delight our customers. As a key member of our team, you'll develop and deploy machine learning systems that analyze millions of customer interactions daily, ensuring state of art experience for customers across 10 countries. Your work will directly impact the shopping experience for hundreds of millions of customers worldwide. Key job responsibilities • Ability to work independently across the end-to-end ML lifecycle: feature engineering, modeling, and MLOps to productionize models. • Strong foundation in machine learning and statistical modeling. • Experience deploying ML solutions into a production environment. • Apply machine learning and statistical techniques to create scalable abuse-detection solutions that identify fraudulent customer behavior, rings of accounts, identity change, holistic customer risk, and marketplace manipulation schemes. • Innovate with the latest GenAI technology to build highly automated solutions for efficient customer promotions. • Collaborate with cross-functional teams to develop comprehensive ML/statistical models that scale to millions of customers across 10+ countries. • Willing to travel to Mexico (MX) and Brazil (BR). • Comfortable working CET hours to maintain overlap with Mexico and Brazil business teams. About the team You'll be working closely with business partners, science and engineering teams to create end-to-end scalable machine learning solutions that address real-world problems. You will build scalable, efficient, and automated processes for large-scale data analyses, model development, model validation, and model implementation. You will also be providing clear and compelling reports for your solutions and contributing to the ongoing innovation and knowledge-sharing that are central to the team's success.
Data Scientist II, Data Scientist, IES CFX & Prime
IN, KA, Bengaluru
Are you passionate about applying machine learning and advanced statistical techniques to protect one of the world's largest online marketplaces? Do you want to be at the forefront of developing innovative solutions that improve Amazon's customers experience? Do you thrive in a collaborative environment where diverse perspectives drive breakthrough solutions? If yes, we invite you to join the Amazon Customer Fulfillment & Prime analytics team. We're seeking an exceptional scientist who can revolutionize how we delight our customers. As a key member of our team, you'll develop and deploy machine learning systems that analyze millions of customer interactions daily, ensuring state of art experience for customers across 10 countries. Your work will directly impact the shopping experience for hundreds of millions of customers worldwide. Key job responsibilities • Ability to work independently across the end-to-end ML lifecycle: feature engineering, modeling, and MLOps to productionize models. • Strong foundation in machine learning and statistical modeling. • Experience deploying ML solutions into a production environment. • Apply machine learning and statistical techniques to create scalable abuse-detection solutions that identify fraudulent customer behavior, rings of accounts, identity change, holistic customer risk, and marketplace manipulation schemes. • Innovate with the latest GenAI technology to build highly automated solutions for efficient customer promotions. • Collaborate with cross-functional teams to develop comprehensive ML/statistical models that scale to millions of customers across 10+ countries. • Willing to travel to Mexico (MX) and Brazil (BR). • Comfortable working CET hours to maintain overlap with Mexico and Brazil business teams. About the team You'll be working closely with business partners, science and engineering teams to create end-to-end scalable machine learning solutions that address real-world problems. You will build scalable, efficient, and automated processes for large-scale data analyses, model development, model validation, and model implementation. You will also be providing clear and compelling reports for your solutions and contributing to the ongoing innovation and knowledge-sharing that are central to the team's success.
Data Scientist, Experience Analytics
US, WA, Seattle
AWS is seeking a Data Scientist to join our Consumer Experience team. We're looking for someone who is curious about large-scale data challenges and motivated to apply ML/AI and advanced analytics to solve real customer problems. Reporting to the Science Lead, this role supports the analytical capabilities of AWS by applying emerging technologies, contributing to data science best practices, and partnering with stakeholders to deepen understanding of the AWS customer experience. The ideal candidate has experience working in complex data and analytics environments, with hands-on skills in Machine Learning and advanced analytics techniques — preferably within cloud computing. You should be comfortable building models and equally comfortable explaining what they mean to a non-technical audience. Key job responsibilities - Apply statistical analysis, ML, and complex data mining techniques to deliver insights that shape the AWS customer experience. - Build production-ready analytics solutions that support effective business decisions. - Partner with product, engineering, and design teams to develop and launch data products. - Contribute to the adoption of Gen AI and ML-based approaches across the data science practice, including building proof-of-concept AI-driven customer use cases. - Communicate technical findings clearly to both technical and non-technical stakeholders. - Bring new ideas — share approaches, tools, and methods that raise the bar for the team.
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