Text-to-SQL technology allows ordinary users to query databases easily through natural language, but accurately converting complex database structures into SQL commands poses challenges. A research team from South China University of Technology and Tsinghua University has proposed a new method—MAG-SQL (Multi-Agent Generative Model), aimed at enhancing the accuracy of this process. MAG-SQL achieves this through the collaboration of multiple agents, including a 'Soft Pattern Linker', a 'Goal-Condition Decomposer', a 'Sub-SQL Generator', and a 'Sub-SQL Refiner'.

Fudan University has introduced SpeechGPT, a large language model designed to understand and generate both speech and text. By discretizing speech signals, it enables compatibility with text modalities, allowing for emotional perception and multi-style speech generation based on context and instructions. The training strategy includes modal adaptation pre-training, cross-modal instruction fine-tuning, and modal chain instruction fine-tuning to en....

ChatGPT has an accuracy rate of 71.7% in clinical medical decision-making. It performs exceptionally well in primary care and emergency settings, demonstrating excellence in differential diagnosis, diagnostic testing, and clinical management tasks.

Ween's latest AI platform leverages natural language processing and machine learning technologies to quickly analyze sentiments and reasoning, transforming them into actionable insights. This platform is specifically designed for professional user research, automatically extracting key information to aid in hypothesis testing and business decision-making. Ween's technology is expected to be applicable in market research, advertising, brand management, and other fields, enhancing the efficiency and transparency of data analysis. The product is designed for product enthusiasts, and the team is using it themselves, continuously improving to better meet user needs.

OneToken's xVal technology addresses the LLM digital encoding issue, enhancing efficiency and generalization performance. Released by nine institutions including the Iron Research Institute, it can encode all numbers. xVal uses multiplicative encoding, making LLM processing of numbers more continuous and smooth. Experiments show that xVal performs stably in tasks such as multi-digit multiplication. This technology can provide significant assistance for data analysis in the scientific field.

Microsoft has applied for a patent for an AI customer service system that uses natural language processing. The system can understand customer inputs to find the best solutions. It uses text encoding to represent customer queries and procedural operations, then matches the encoding to find the most suitable procedural operation. OneDrive recently added a similar feature, indicating that this AI system may be launched soon.

By using chained density prompting to fine-tune ChatGPT, we achieve performance on news summarization tasks that exceeds GPT-4's zero-shot capabilities and approaches GPT-4's performance with chained prompting. This is accomplished through automatic evaluation chains such as ScoreStringEvalChain and the improved PairwiseStringEvalChain for quantitative assessments at human-level quality. Fine-tuning ChatGPT is 11 times faster and 63% cheaper than GPT-4's zero-shot method, and 33 times faster and 84% cheaper than GPT-4's chained prompting. The results show that fine-tuned ChatGPT excels in news summarization.

Google is integrating Bard AI with Gmail, Docs, YouTube, and more, allowing users to have Bard summarize and answer questions from personal content. Bard can display relevant information from YouTube, Maps, hotels, etc. Google claims it will not store or train on users' personal content to compete with ChatGPT and Bing Chat.