Following its global unveiling on the main stage of Binance’s Blockchain Week conference in Dubai, AI platform BitGPT is experiencing sizable growth across every vertical of the project from active partnership conversations to the number of users currently testing its technology.
BitGPT’s X and Telegram communities grew in size by more than 1,000% in the days following its presentation at Binance in which hundreds of onlookers watched as its AI platform was launched and tested for the first time in front of a public audience.
The demonstration replay surpassed a quarter-million views on Binance’s website within hours of being posted the most popular replay event of the conference.
BitGPT’s live demo and subsequent growth have been covered by several major new outlets, including reporting from Decrypt that predicted BitGPT’s AI platform “will help onboard the next billion Web 3.0 users and kickstart the AI Agent economy.”
Backed by former SingularityNET co-founders and a growing team of AI and Web 3.0 experts, BitGPT bridges the mass acceleration and adoption of generative AI technologies with the entire crypto ecosystem, providing users both humans and AI agents with a unified UX to connect and transact across any decentralized network or service using natural language commands.
Available in more than 25 languages, its platform overcomes language, literacy and interface barriers in what appears to be the Web 3.0 industry’s most legitimate effort yet to onboard its first billion Web 3.0 users all while positioning the platform as a central node for kickstarting the AI agent economy.
Developed in stealth for more than two years, BitGPT’s AI platform has already been tested by a wide audience with a growing community of dedicated users generating valuable data and insights that have been continually used to refine and expand the capabilities of its model.
After advancing from alpha to beta earlier this year, BitGPT is preparing for full launch just as interest and attention for AI-enabled Web 3.0 technologies take off.
Despite achieving rapid significant adoption, centralized AI model providers present critical challenges, including data privacy risks, restricted accessibility, systemic vulnerabilities and the emergence of techno-feudalism due to reliance on dominant third-party entities.
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