Aptos Labs has today announced a partnership with tech giant Microsoft to speed up the widespread implementation of web3 via the Microsoft Azure OpenAI Service. Asset tokenization, central bank digital currencies (CBDCs), and digital payments are just a few of the blockchain-based use cases that both companies plan to consider improving as part of their collaboration.
Aptos’ blockchain may provide the rapid throughput, quick settlement times, and low cost of transaction needed to entice Big Tech businesses interested in developing AI-related goods and services. With the ability to handle around 160,000 transactions per second (TPS) and a time to finality in the sub-second range, Aptos is one of the quickest blockchains in the ecosystem right now.
What the Aptos-Microsoft partnership means
Aptos Labs’ Aptos Assistant will serve as a reliable, user-friendly, and secure bridge between web2 and web3 for the average internet user and business, thanks to the collaboration between the two companies. With the help of AI, users can easily join web3 and start using the Aptos blockchain ecosystem by simply asking any question they could have regarding web3. It will also be available to help developers create smart contracts and dApps by pointing them to relevant and useful information resources.
Aptos will use Microsoft Azure to host its validator nodes, which will improve the speed and safety of network transactions. In addition, Aptos will integrate its Move programming language to Microsoft’s GitHub repository. Specifically, Github’s Copilot, an AI-enabled tool that aids engineers by auto-completing programmes, will be integrated with Move.
Microsoft has its sights set on the future and believes that artificial intelligence will become increasingly integrated into web3 solutions in the near future. This collaboration between Aptos and Microsoft is crucial because it enables Aptos’ validated blockchain data to be used in the training of Microsoft’s AI models. Aptos can serve Microsoft’s needs for reliable information to train models in a way that is easy to validate independently.