Challenges and Future Directions of Chatbots: From Virtual Life to Multimodal Interaction
This talk analyzes the technical and practical challenges of current chatbots, introduces the next‑generation paradigm of virtual life, and details how AI technologies such as speech, vision, NLP, and knowledge graphs can be combined with multimodal interaction to create more intelligent and engaging conversational agents.
The presentation begins by noting the rapid growth of chatbots as entry‑level AI products, yet highlights that most fail to meet user expectations due to limitations in user experience.
It outlines four main sections: the dilemmas of chatbots and possible breakthroughs, core technologies for virtual life, engineering challenges, and concluding remarks.
Key observations include the superiority of AI in games and image tasks, the mismatch between technology maturity and user expectations, and the difficulty of natural language processing for coherent multi‑turn dialogue.
The speaker introduces the concept of "virtual life"—an AI‑driven entity with perception, cognition, and self‑evolution—supported by three AI fundamentals (algorithm, compute, data) and emphasizes the importance of knowledge graphs for bridging perception and cognition.
Technical deep‑dives cover speech (ASR, TTS, personalization), vision (face reconstruction, 3D modeling), NLP (NLU, NLG, dialogue management, matching algorithms), and knowledge graph construction (schema, entity linking, knowledge completion, storage). Practical engineering advice stresses the need for efficient retrieval‑based solutions, rule‑based components, and performance constraints for large‑scale deployment.
Additional topics discuss multimodal interaction, persona‑driven chatbot IP, commercial considerations, and the roadmap for virtual life development, concluding with a call to explore the GAVE (AI Virtual Engine) platform.
DataFunTalk
Dedicated to sharing and discussing big data and AI technology applications, aiming to empower a million data scientists. Regularly hosts live tech talks and curates articles on big data, recommendation/search algorithms, advertising algorithms, NLP, intelligent risk control, autonomous driving, and machine learning/deep learning.
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