On the left is the logo for the Alexa Prize Socialbot Grand Challenge 4. On the right is a group photo of Team Alquist from Czech Technical University which won the Alexa Prize SocialBot Grand Challenge 4 competition.
Team Alquist from Czech Technical University has won the Alexa Prize SocialBot Grand Challenge 4 competition. The team, which was awarded the $500,000 first prize for earning the top score in the finals competition, already is looking forward to the next challenge says its faculty advisor, Jan Sedivy (far right).
Credit: Glynis Condon

Czech Technical University team wins Alexa Prize SocialBot Grand Challenge 4

Team Alquist awarded $500,000 prize for top score in finals competition; teams from Stanford University and the University of Buffalo place second and third.

The Czech Republic captured four gold medals at the 2021 summer Olympics in Japan, quite a feat for the Central European country with a population of just over 10 million people.

The country now has another gold-medal-winning team — Alquist from Czech Technical University (CTU) in Prague, which today learned it is the winner of the 2021 Alexa Prize SocialBot Grand Challenge.

“We are incredibly excited to learn that we have won this year’s competition,”said Jakub Konrád, a CTU PhD student and Alquist’s team leader. “I am delighted and proud of our entire team for building a bot that managed to reach the finals for the fourth consecutive year. This year we strove to create a system capable of flexible conversation by synthesizing generative approaches with prepared scenarios that could adjust to users’ needs.”

Faculty advisors provide their perspectives

Faculty advisors to each of the finalists provided their perspectives on the Alexa Prize Socialbot Grand Challenge 4 competition. Learn more about their insights, and read the teams' research papers.

The team’s faculty advisor, Jan Sedivy, added that this year’s team had great fun designing “catchy and attractive dialogues”, and that the team already is looking forward to joining the next challenge.

The Alexa Prize SocialBot Grand Challenge, launched in 2016, is a competition for university students dedicated to advancing the field of conversational AI. Teams are challenged to design socialbots that Alexa customers can interact with via Alexa-enabled devices. The ultimate goal: meet the Grand Challenge by earning a composite score of 4.0 or higher (out of 5) from competition judges. Additionally, the finals’ judges must determine that at least two-thirds of their interactions with the socialbot were coherent and engaging for a minimum of 20 minutes. The first team to meet the Grand Challenge will win a $1 million research grant for its university.

Although none of this year’s teams met the Grand Challenge, each finalist demonstrated impressive progress toward the goal. Alquist, the socialbot from CTU, earned first place with a 3.28 average rating, and an average finals’ competition interaction duration of 14 minutes and 14 seconds. For the second consecutive year, Stanford University’s Chirpy Cardinal socialbot earned second-place honors and a $100,000 prize by achieving a 3.25 average rating, and an average of 13 minutes and 25 seconds of interaction duration. PROTO, the socialbot from the University of Buffalo team, earned third-place honors with an average rating of 3.16, and an average of 14 minutes and 45 seconds of interaction duration.

Stanford University Alexa Prize team
Stanford University's Chirpy Cardinal team earned second place and a $100,000 prize.
Credit: Stanford

“Team Chirpy Cardinal really enjoyed participating in the Alexa Prize for the second time,” said Ethan Chi, a research assistant within Stanford’s NLP Group, and team leader. “Throughout this experience, we've learned so much about real-world dialogue. We almost completely rebuilt our system from the ground up, allowing us to handle a greatly expanded variety of user comments and interjections, and we developed new neural techniques to blend factual knowledge fluidly into our conversations. We even integrated news from The Guardian into our system, allowing us to build common ground with our users over recent events. Compared to our socialbot's previous incarnation, we more than doubled our average finals conversation length, bringing us closer to our shared goal of fluent conversational AI.”

“From an innovation perspective, our aim was to create an agent that wouldn’t restrict interaction to a defined set of topics,” said Sougata Saha, a PhD student at the University of Buffalo, and PROTO’s team lead. “Our use of an ensemble of factual and chit-chat neural generators, coupled with a robust dialogue manager, helped us achieve our third-place finish.”

University of Buffalo Alexa Prize team
The PROTO team from the University of Buffalo earned third place in the competition, and a $50,000 prize.
Credit: University of Buffalo

Last November, nine teams were selected to participate in the competition, and in July five finalists were selected to compete in the finals competition, which took place July 27-29. The finals competition also included teams from Emory University, and The University of California, Santa Cruz.

“Building open-domain conversational systems that allow customers to engage on topics ranging from sports and entertainment, to politics and technology is an incredibly challenging task,” said Prem Natarajan, Alexa AI vice president of Natural Understanding. “Creating socialbots that can conduct these kinds of multi-turn, open-domain interactions is still far from a solved problem. The fact that the top teams participating in this year’s finals competition more than doubled the average duration of interactions over the previous challenge demonstrates that we continue to make impressive progress toward that goal.”

Each of the nine teams participating in Alexa Prize Grand Challenge 4 has published a research paper outlining their approaches to this year’s competition. The papers are now available on the Alexa Prize website.

Since 2017, Alexa customers have engaged with Alexa Prize socialbots for more than 900,000 hours. Alexa customers can continue to engage with the winning teams’ socialbots simply by saying, “Alexa, let’s chat.” 

Previous challenge winners include teams from the University of Washington, the University of California, Davis, and Emory University.  

Alexa Prize SocialBot Grand Challenge 4

Alexa Prize program expands

The Alexa Prize program has expanded to include another competition, as well. Earlier this year, Amazon launched the Alexa Prize TaskBot Challenge, in which 10 participating teams are competing to develop agents that assist customers in completing tasks that require multiple steps and decisions. It is the first conversational AI challenge to incorporate multimodal (voice and vision) and interactive customer experiences. The year-long competition concludes in May 2022, with winners announced the following month.

More information about the challenge is available on the competition’s frequently asked questions page. Alexa customers will have the opportunity to interact with the taskbots beginning in October 2021.

In the coming months, Amazon Science will have details on the forthcoming Alexa Prize Socialbot Grand Challenge 5.

Research areas

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US, CA, San Francisco
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US, CA, San Francisco
Amazon’s Frontier AI & Robotics (FAR) team is seeking a Member of Technical Staff to drive foundational research and build intelligent robotic systems from the ground up. In this role, you will operate at the intersection of cutting-edge AI research and real-world robotics - conducting original research, publishing, and deploying your innovations into production systems at Amazon scale. We’re looking for researchers who think from first principles, push the boundaries of what’s possible, and take full ownership of turning breakthrough ideas into working systems.  You will join the next revolution in robotics, where you'll work alongside world-renowned AI pioneers to push the boundaries of what's possible in robotic intelligence. As a Member of Technical Staff, you'll be at the forefront of developing breakthrough foundation models and full-stack robotics systems that enable robots to perceive, understand, and interact with the world in unprecedented ways. You'll drive technical excellence and independent research initiatives in areas such as locomotion, manipulation, perception, sim2real transfer, multi-modal, multi-task robot learning, designing novel frameworks that bridge the gap between state-of-the-art research and real-world deployment at Amazon scale. In this role, you'll balance innovative technical exploration with practical implementation, collaborating with platform teams to ensure your models and algorithms perform robustly in dynamic real-world environments. You’ll have the freedom to pursue ambitious research directions while leveraging Amazon’s vast computational resources to tackle ambiguous problems in areas like very large multi-modal robotic foundation models and efficient, promptable model architectures that can scale across diverse robotic applications. Key job responsibilities - Drive independent research initiatives across the robotics stack, including robot co-design, dexterous manipulation mechanisms, innovative actuation strategies, state estimation, low-level control, system identification, reinforcement learning, sim-to-real transfer, as well as foundation models focusing on breakthrough approaches in perception, and manipulation, for example open-vocabulary panoptic scene understanding, scaling up multi-modal LLMs, sim2real/real2sim techniques, end-to-end vision-language-action models, efficient model inference, video tokenization - Design and implement novel deep learning architectures that push the boundaries of what robots can understand and accomplish - Guide technical direction for full-stack robotics projects from conceptualization through deployment, taking a system-level approach that integrates hardware considerations with algorithmic development, ensuring robust performance in production environments - Collaborate with platform and hardware teams to ensure seamless integration across the entire robotics stack, optimizing and scaling models for real-world applications - Contribute to team's technical decisions and influence implementation strategies to help shape our approach to next-generation robotics challenges - Mentor fellow researchers while maintaining solid individual technical contributions A day in the life - Design and implement novel foundation model architectures and innovative systems and algorithms, leveraging our extensive infrastructure to prototype and evaluate at scale - Collaborate with our world-class research team to solve complex technical challenges across the full robotics stack - Lead focused technical initiatives from conception through deployment, ensuring successful integration with production systems - Drive technical discussions and brainstorming sessions with team leaders, fellow researchers and key stakeholders - Conduct experiments and prototype new ideas using our massive compute cluster and extensive robotics infrastructure - Transform theoretical insights into practical solutions that can handle the complexities of real-world robotics applications About the team At Frontier AI & Robotics, we're not just advancing robotics – we're reimagining it from the ground up. Our team is building the future of intelligent robotics through innovative foundation models and end-to-end learned systems. We tackle some of the most challenging problems in AI and robotics, from developing sophisticated perception systems to creating adaptive manipulation strategies that work in complex, real-world scenarios. What sets us apart is our unique combination of ambitious research vision and practical impact. We leverage Amazon's massive computational infrastructure and rich real-world datasets to train and deploy state-of-the-art foundation models. Our work spans the full spectrum of robotics intelligence – from multimodal perception using images, videos, and sensor data, to sophisticated manipulation strategies that can handle diverse real-world scenarios. We're building systems that don't just work in the lab, but scale to meet the demands of Amazon's global operations. 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US, NY, New York
We are seeking a Sr. Applied Scientist to develop cutting-edge machine learning algorithms for motor control systems in robots. In this role, you will focus on creating and optimizing intelligent motor control strategies to enable robots to perform complex, whole-body tasks. Your contributions will be essential in advancing robotics by enabling fluid, reliable, and safe interactions between robots and their environments. Key job responsibilities - Develop controllers that leverage reinforcement learning, imitation learning, or other advanced AI techniques to achieve natural, robust, and adaptive motor behaviors - Collaborate with multi-disciplinary teams to integrate motor control systems with robotic hardware, ensuring alignment with real-world constraints such as actuator dynamics and energy efficiency - Use simulation and real-world testing to refine and validate control algorithms - Stay updated on advancements in robotics, AI, and control systems to apply advanced techniques to robotic motion challenges - Lead technical projects from conception through production deployment - Mentor junior scientists and engineers - Bridge research initiatives with practical engineering implementation 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. 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.
US, CA, San Francisco
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You'll drive technical excellence and independent research initiatives in areas such as locomotion, manipulation, perception, sim2real transfer, multi-modal, multi-task robot learning, designing novel frameworks that bridge the gap between state-of-the-art research and real-world deployment at Amazon scale. In this role, you'll balance innovative technical exploration with practical implementation, collaborating with platform teams to ensure your models and algorithms perform robustly in dynamic real-world environments. You’ll have the freedom to pursue ambitious research directions while leveraging Amazon’s vast computational resources to tackle ambiguous problems in areas like very large multi-modal robotic foundation models and efficient, promptable model architectures that can scale across diverse robotic applications. Key job responsibilities - Drive independent research initiatives across the robotics stack, driving breakthrough approaches through hands-on research and development in areas including robot co-design, dexterous manipulation mechanisms, innovative actuation strategies, state estimation, low-level control, system identification, reinforcement learning, sim-to-real transfer, as well as foundation models focusing on breakthrough approaches in perception, and manipulation. - Lead and Guide technical direction for full-stack robotics projects from conceptualization through deployment, taking a system-level approach that integrates hardware considerations with algorithmic development - Develop and optimize control algorithms and sensing pipelines that enable robust performance in production environments - Collaborate with platform and hardware teams to ensure seamless integration across the entire robotics stack, optimizing and scaling models for real-world applications - Contribute to team's technical decisions and influence implementation strategies to help shape our approach to next-generation robotics challenges - Mentor fellow researchers while maintaining solid individual technical contributions A day in the life - Design and implement novel foundation model architectures and innovative systems and algorithms, leveraging our extensive infrastructure to prototype and evaluate at scale - Collaborate with our world-class research team to solve complex technical challenges across the full robotics stack - Lead focused technical initiatives from conception through deployment, ensuring successful integration with production systems - Drive technical discussions and brainstorming sessions with team leaders, fellow researchers and key stakeholders - Conduct experiments and prototype new ideas using our massive compute cluster and extensive robotics infrastructure - Transform theoretical insights into practical solutions that can handle the complexities of real-world robotics applications About the team At Frontier AI & Robotics, we're not just advancing robotics – we're reimagining it from the ground up. Our team is building the future of intelligent robotics through innovative foundation models and end-to-end learned systems. We tackle some of the most challenging problems in AI and robotics, from developing sophisticated perception systems to creating adaptive manipulation strategies that work in complex, real-world scenarios. What sets us apart is our unique combination of ambitious research vision and practical impact. We leverage Amazon's massive computational infrastructure and rich real-world datasets to train and deploy state-of-the-art foundation models. Our work spans the full spectrum of robotics intelligence – from multimodal perception using images, videos, and sensor data, to sophisticated manipulation strategies that can handle diverse real-world scenarios. We're building systems that don't just work in the lab, but scale to meet the demands of Amazon's global operations. Join us if you're excited about pushing the boundaries of what's possible in robotics, working with world-class researchers, and seeing your innovations deployed at unprecedented scale.
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