Tao Zhang
Copilot Application Technology Leader, Shangtang Technology
Graduated from Beijing University of Posts and Telecommunications, majoring in communication engineering, he has 16 years of experience in the engineering application of advanced technologies, and has led the design and development of large-scale software architecture in the fields of video communication, computer vision, CV heterogeneous reasoning framework, and large language model application. He is now focusing on the research and development of AI application products, and has led the team to develop and launch the ‘Code Raccoon’ and ‘Office Raccoon’ series of AI Native productivity tools, providing programming assistance services for hundreds of thousands of developers.
Topic
Useful to Useful: How AI Productivity Tools Amplify AI Capabilities
* AI capabilities working in existing business scenarios * Penetrate by solving single-point problems * Expanding capability boundaries through system interconnections * Future architectural system for AI * Conversion rate of AI capability to AI productivity * Several paths from System 1 to System 2 * Enhancement of performance at a manageable cost * Effectiveness of AI productivity tools in practice * Unleash the power of AI to power development scenarios * AI Native Tools: From Engine to Machine ## Take aways * Explore how to leverage AI general-purpose capabilities in different scenarios to boost productivity. * Join us to discuss the possible paths of AI macromodels in dealing with slow-thinking problems. * What's new in AI productivity tools, and what we've learnt in the process of productisation.
