New Jersey Devils introduce AI chatbot ‘Bott Stevens’ via Theta EdgeCloud

The New Jersey Devils have launched “Bott Stevens,” a customized AI chatbot designed to boost digital fan engagement.

Named after Devils legend Scott Stevens, the chatbot is powered by Theta EdgeCloud’s (THETA) decentralized AI infrastructure and might be obtainable on the group’s official web site in the course of the 2024-25 NHL season.

The AI agent will present followers with real-time data on recreation schedules, tickets, stats, and merchandise. Using Theta’s Retrieval Augmented Technology expertise, Bott Stevens will pull knowledge from official NHL sources, guaranteeing accuracy whereas avoiding misinformation from unverified sources.

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Followers can ask the chatbot a variety of questions, akin to upcoming match particulars or season statistics, and obtain on the spot responses.

Bott Stevens might be powered by Theta EdgeCloud’s community of over 30,000 edge nodes and distributed GPUs, providing greater than 80 PetaFLOPS of computation energy.

This ensures scalability, even throughout peak demand, akin to playoffs or main group bulletins.

Past answering questions, the AI chatbot will supply historic highlights, recreation recaps, venue data, and updates on group occasions. Over time, it could increase to incorporate predictive analytics for fantasy sports activities and interactive fan engagement instruments.

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Q&A with Mitch Liu, CEO of Theta Labs

Q: How will Theta EdgeCloud’s decentralized design make sure that the chatbot can deal with peak demand throughout main occasions?

A: EdgeCloud’s decentralized design gives over 80 PetaFLOPS of on-demand distributed GPU compute energy, combining each cloud and edge computing units. Over 30,000 international edge units allow us to deal with peak utilization over the baseline capability supplied by cloud-based servers, and significant in skilled and esports industries the place main occasions akin to playoffs and finals draw essentially the most fan curiosity.

Q: How will “Bott Stevens” pull correct, real-time knowledge from sources just like the NHL API? What safeguards forestall outdated or incorrect data? How will you retain RAG from being pulled from crowd-sourced and probably inaccurate sources?

A: The EdgeCloud back-end platform defines which knowledge sources to drag knowledge from, and this feeds into the real-time RAG database, so crowd-sourced or inaccurate sources may be prevented. As in most generative AI LLM fashions, the most important problem is not only getting correct real-time knowledge from trusted sources however how that knowledge is cleaned, ready and normalized so it may be effectively and precisely included into the mannequin.

Q: How will you guarantee knowledge privateness and safety for customers interacting with the chatbot? Are you storing consumer knowledge?

The chatbot doesn’t retailer or preserve any consumer knowledge past the consumer’s session, and in contrast to conventional chatbots like DeepSeek or ChatGPT, Theta chatbots are targeted on trade particular content material, for instance solely hockey associated data for the NJ Devils.

Q: Are there plans to increase “Bott Stevens” with options like predictive analytics? Do you need to take the tech any additional?

A: A giant space of improvement for us now could be extending the interactive RAG chatbot to develop into proactive agentic AI with varied extendable actions, that’s impartial and autonomous. For instance, having the ability to interface with customer support and CRM programs to routinely create help tickets to enhance consumer satisfaction, and AI brokers that create “fantasy sports activities/esports groups” that may play towards customers to extend fan engagement and a step in the direction of predictive analytics for expertise identification, participant valuation, and opponent evaluation.

Q: What attracted Theta Labs to associate with the New Jersey Devils? What customization choices can be found for different groups or manufacturers?

A: Theta EdgeCloud has gotten good traction with skilled sports activities groups beginning with the Las Vegas Knights and esports groups together with FlyQuest and Evil Geniuses. The consumer interface is absolutely customizable and branded to be built-in into every group’s web site, cell apps, Discord and different social channels. Extra importantly, the real-time knowledge supply and APIs that feed into EdgeCloud’s RAG database is custom-made to domain-specific data, akin to NHL hockey, esports video games like Valorant, League of Legends, group/league particular data, and extra.

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Q&A with Marc Ciampa, Vice President of Content material of the NJ Devils

Q: How will the group promote “Bott Stevens” to drive fan engagement and adoption?

A: To advertise “Bott Stevens,” the Devils will combine promotion throughout a number of platforms to encourage fan interplay, “Bott Stevens” capabilities, and lift common consciousness.

Q: What kinds of curated content material will the chatbot supply past stats and schedules?

A: Past offering statistics and schedules, “Bott Stevens” will supply curated content material to complement the fan expertise, together with historic highlights and occasion and venue data. “Bott Stevens” will reply questions on memorable moments from the group’s historical past, present particulars on upcoming occasions, theme nights, and so on. within the Devils and live performance house, and supply complete particulars about Prudential Middle facilities. These facilities embody accessibility companies, bag insurance policies, concession areas and ATM areas all through the venue.

Q: How will you measure the chatbot’s success in enhancing fan engagement or sharing related and correct stats/knowledge?

A: We are going to measure success by means of consumer engagement metrics, accuracy charges, fan suggestions and help load discount. We plan to watch the variety of interactions, session durations, and repeat utilization, in addition to observe the precision of knowledge supplied, guaranteeing that stats and knowledge shared are right and up-to-date. We may also gather consumer suggestions by means of surveys to know satisfaction ranges and areas for enchancment and discover methods to measure the lower in inquiries dealt with by human help, indicating the chatbot’s effectivity in addressing widespread questions.

Q: As AI fatigue is rising amongst prospects, how will you make “Bott Stevens” completely different from different AI brokers that your shoppers already ‘digitally’ meet each day?

A: By way of steady studying, human-like conversational tone, customized interactions, and making a chatbot ecosystem. We are going to implement machine studying algorithms that adapt to fan suggestions and evolving pursuits, guaranteeing the chatbot stays related and interesting, in addition to design the chatbot’s communication type to be pleasant and relatable, enhancing the general consumer expertise. We glance to leverage AI to tailor responses primarily based on particular person fan preferences and behaviors, making every interplay distinctive. Ultimately, “Bott Stevens” might be obtainable in our app and tied to different key features akin to our concession information, wayfinding and different issues we would consider down the road.