SocialBot Grand Challenge FAQs

Frequently asked questions about the challenge.
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.

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As an Applied Scientist in the Alexa AI team, you will spearhead the advancement and deployment of state-of-the-art ML/RAG systems that revolutionize how millions of customers interact with Alexa. You'll leverage your expertise in machine learning, natural language processing, and large language models to create reliable, scalable, high-performance products that set new standards in operational excellence. Working at the intersection of research and production, you'll translate latest AI innovations into customer-facing features that delight users daily. Your work will span the full ML lifecycle: from analyzing customer behavior patterns and building novel metrics for personal digital assistants, to deploying automated training pipelines and conducting rigorous A/B testing across diverse devices and endpoints. Collaborating closely with business, engineering, and science teams across Amazon, you'll lead high-visibility programs that automate workflows and deliver measurable customer impact. This role offers the unique opportunity to publish at top-tier conferences while seeing your innovations scale to one of the world's most popular voice assistants, serving millions of customers globally. Key job responsibilities As an Applied Scientist in the Alexa AI team: You'll analyze and model customer behavior at scale, building novel metrics for personal digital assistants across diverse devices and endpoints. Your work will involve creating deep learning, policy-based learning, and machine learning algorithms that directly impact customer experiences, translating complex data patterns into actionable insights that drive product innovation. Your technical leadership will extend to building and deploying automated model training and evaluation pipelines, implementing complex machine learning and deep learning algorithms, and conducting rigorous model and data analysis through online A/B testing. You'll research and implement novel approaches that push the boundaries of what's possible in conversational AI. Beyond model development, you'll ensure operational excellence by taking ownership of production systems, including on-call responsibilities during peak and non-peak hours. Working alongside Software Development Engineers, you'll deploy fixes and handle high-severity issues, ensuring our ML systems maintain the reliability and performance that millions of Alexa customers depend on daily. A day in the life As an Applied Scientist in the Alexa AI team, your day will involve collaborating with talented engineers and scientists to build scalable solutions for our conversational assistant. You'll dive into data analysis, experiment with novel algorithms, and iterate on models based on real-time user feedback. Working in a fast-paced, ambiguous environment, you'll tackle complex technical challenges: from debugging production issues to presenting research findings to stakeholders. Your self-motivated approach will drive you to swiftly deliver impactful solutions while maintaining the high standards that define our mission to revolutionize user experiences for millions of customers. About the team The Alexa AI team develops the intelligence behind one of the world's most popular voice assistants, serving millions of customers globally. We're a diverse group of scientists, engineers, and researchers united by our mission to make Alexa more natural, helpful, and delightful. Our culture thrives on innovation, collaboration, and customer obsession. We tackle some of the most challenging problems in conversational AI; from natural language understanding to personalization at scale. Here, you'll work alongside world-class talent, publish at top-tier conferences, and see your innovations impact customers daily. We move fast, think big, and celebrate both successes and learnings.
JP, 13, Tokyo
This position is for an 8–12 week full-time, on-site internship to be conducted in Summer 2027 (June–September 2027). *Minimum 12 weeks internship is required for all international hires (who require JP visa support). *Target Candidates: Students graduating in 2029 Do you want to see your research directly impact how millions of customers discover, browse, and purchase products on Amazon — across Japan and the globe? Amazon's Japan Store Tech team owns the science and technology behind cross-border shopping — product discovery, search relevance, personalization, and content experiences spanning dozens of marketplaces. We tackle problems at massive scale: multi-language signals, multi-marketplace data, and region-specific customer behaviors, all served at low latency to millions of daily shoppers. We're looking for current Bachelor or Master students with a passion for applied science and machine learning to join us as an Applied Scientist Intern in Summer 2027 to shape the future of customer experiences at scale. For this position, our Japan Store Tech team is looking for students with a specialization in one or more of the following research areas: machine learning, deep learning, natural language processing (NLP), information retrieval, recommender systems, computer vision, large language models (LLMs), generative AI, causal inference, experimentation and A/B testing, optimization, and more! As an Applied Scientist Intern, you'll develop novel models and algorithms, design and run experiments on live traffic, and own meaningful science contributions end-to-end. You'll also leverage and contribute to GenAI/LLM systems that power both customer-facing experiences and internal development tools. If you want to kickstart your science career at global scale — solving real customer problems alongside talented scientists and engineers in a collaborative, international environment — this is the place to start. Key job responsibilities - Collaborate and communicate effectively with experienced cross-disciplinary Amazonians to design, develop, and deploy innovative machine learning models and scientific solutions that delight our customers, while participating in technical discussions to drive solutions forward. - Develop and implement scalable machine learning models and algorithms to improve product discovery, search relevance, personalization, or other customer-facing experiences. - Design and conduct experiments (offline and online) to validate hypotheses and measure the impact of proposed solutions. - Analyze large-scale datasets to identify patterns, generate insights, and inform model design decisions. - Leverage and contribute to the development of GenAI and LLM-powered tools to enhance customer experiences and development productivity while staying current with emerging technologies. - Write clean, maintainable, production-quality code following best practices. - Communicate research findings effectively through documentation, presentations, and technical papers. - Work in an agile environment and collaborate closely with software engineers to bring science solutions from prototype to production. A day in the life As an intern, you will be matched to a manager and a mentor and will have the opportunity to influence the evolution of Amazon's science and technology and lead critical projects early in your career. In addition to working on an impactful project, you will have the opportunity to engage with Amazonians for both personal and professional development, expand your network, and participate in activities with other interns throughout your internship. No matter the location of your internship, we give you the tools to own your project and learn in a real-world setting. Amazon internships are full-time positions, and interns should expect to work in office, Monday–Friday, up to 40 hours per week typically between 9am–6pm. Specific team norms around working hours will be communicated by your manager. Interns should not have other employment during the Amazon work-day.
CN, 31, Shanghai
上海职位 - 如果希望在上海工作,请投递本职位。 毕业时间:2026年10月 - 2027年9月之间毕业的应届毕业生 · 投递须知: 1 填写简历申请时,请把必填和非必填项都填写完整。提交简历之后就无法修改了哦! 2 学校的英文全称请准确填写。中英文对应表,请点击链接查看 https://docs.qq.com/sheet/DVmdaa1BCV0RBbnlR?tab=BB08J2 3 简历不限中英文。 如果您正在攻读自然语言处理(NLP)、信息检索(IR)、机器学习、生成式人工智能或相关方向的硕士或博士学位,并希望将前沿科学研究转化为服务真实客户的产品,我们诚挚邀请您加入亚马逊 International Technology 搜索团队。 我们的目标是帮助亚马逊客户更准确地找到所需商品,并发现符合其需求和兴趣的新商品。您每天的工作都将直接影响全球数百万客户的购物体验。团队使用 TB 级商品、查询和客户行为数据,持续推进搜索、推荐、自然语言理解以及生成式 AI 技术的发展。 在这个岗位中,您将研究并应用 NLP、IR、深度学习、大语言模型(LLM)和基础模型等前沿技术,解决搜索理解、相关性排序、语义匹配、个性化和对话式购物等问题。您将有机会探索预训练、监督微调(SFT)、参数高效微调、检索增强生成(RAG)、提示优化和智能体(Agent)等技术,并针对业务场景建立可靠的离线与在线评估方法。 您将与应用科学家、软件工程师和产品经理密切合作,完成从问题定义、数据分析、算法设计和实验验证,到模型部署、在线测试和持续迭代的完整闭环。您需要根据客户价值和业务目标选择合适的技术方案,并在模型质量、可靠性、安全性、推理延迟和计算成本之间做出合理权衡。 Key job responsibilities Key job responsibilities · 针对 Amazon 搜索和购物体验中的实际问题,提出可验证的科学假设,设计并实现机器学习、NLP、IR 或 LLM 解决方案。 · 使用大规模商品、查询和客户行为数据训练、微调和评估模型,建立可重复的实验与评估流程。 · 探索基础模型在搜索、推荐和对话式购物中的应用,包括 RAG、模型微调、提示优化和 Agent 等方向。 · 设计覆盖相关性、事实性、鲁棒性、安全性、延迟和成本的评估指标,并通过离线实验、A/B 测试和客户反馈验证效果。 · 与工程和产品团队合作,将原型转化为可扩展、可维护的生产系统,并持续分析和改进线上表现。 · 跟踪学术界和工业界的最新进展,形成技术文档,并在适当情况下向内部或外部科学社区分享研究成果。 基本要求 · 正在攻读或已获得计算机科学、计算机工程、机器学习、人工智能、运筹学、统计学或相关领域的硕士或博士学位。 · 具备机器学习或深度学习的基础知识,以及实验设计、统计分析和模型评估经验。 · 具备使用代码和工具实现、训练和评估算法的经验。 · 至少熟练使用一种编程语言,例如 Python、Java 或 C++。 · 了解 NLP、IR、推荐系统或生成式 AI 中至少一个方向的基本方法。 优先条件 · 在 NLP、IR、机器学习、数据挖掘或生成式 AI 相关顶级会议或期刊发表过论文,或有高质量研究项目经历。 · 熟悉 Transformer、LLM 或基础模型,并具有预训练、监督微调(SFT)、参数高效微调、偏好优化或推理优化中的一种或多种实践经验。 · 具有 RAG、向量检索、Embedding、语义匹配、Agent 或工具调用系统的研究或开发经验。 · 熟悉 PyTorch、TensorFlow 等深度学习框架,以及 Hugging Face Transformers 等常用 LLM 工具链。 · 具有搜索引擎或推荐系统经验,尤其是在索引、召回、排序、查询理解、个性化或在线实验方面。 · 具有 LLM 评估经验,能够从相关性、事实性、幻觉、鲁棒性、安全性、延迟和成本等维度衡量系统质量。 · 具有大规模数据处理、分布式训练、模型压缩或高效推理经验。 · 具备良好的批判性思维和技术沟通能力,能够清楚地解释模型选择、实验结果及其局限性,并与跨职能团队合作解决开放性问题。