As the fast evolution of generalist LFMs is quickly reaching a plateau and towards the general AI platforms, the next phase of AI research is on "AI for X", the adaptation of LFM platforms to perform discipline-based research in specific verticals. The research focus then moves from building the platform itself to extending the platform to solve high-stakes vertical domain problems. The platforms here include both state-of-the-art closed and open-source systems. As Ecommerce vertical is covered under recommendation research described above and Healthcare is still preliminary, we will briefly outline our research focuses on finance here.
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​Our research in Fintech focusses on developing AI techniques to accelerate various financial workflows to support a range of financial services, and assist application and operation level decisions. They can be summarized into 5 key research directions. The first is the development of safe and trustable Finance-LLMs capable of processing numeric, tabular, and time-series data that are dominant in finance domain. The second is in designing Financial Agents capable of timely and accurate retrieval, synthesis and analysis of multi-modal and heterogeneous financial data. The third is in ensuring compliance with financial rules and regulations by service Agents. This is achieved by incorporating knowledge, requirements and regulations into reasoning process, with robust guardrail mechanisms to guarantee full compliance. The fourth is in developing a comprehensive and rigorous evaluation framework. Finally, we plan to consolidate our research towards the concept of AI-enabled banks to support a wide range of financial services.
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