Google Bard GemPro Surpasses GPT-4, Claims Second Place in LMSYS Chatbot Rankings

The Google Bard GemPro version has successfully surpassed GPT-4 in the LMSYS chatbot rankings, bringing significant changes to the chatbot field. Bard is now the second highest-scoring chatbot on the LMSYS list, gradually catching up to the champion, GPT-4 Turbo. Bard's rise is attributed to its adoption of Google's Gemini Pro large multimodal model, making it the second model on the list to achieve over 1200 points. LMSYS Org states that Bard's surge in the rankings is a remarkable development.

OpenAI Accused of Backroom Deals, Paying Users Face Model Degradation

OpenAI recently sparked controversy due to secret model switching. Paid users reported that their GPT-4/5 were automatically replaced with low-computing power filtered models gpt-5-chat-safety and gpt-5-a-t-mini without prior notice, especially causing a sharp decline in response quality when dealing with sensitive content. This move has been questioned by users for infringing on their right to choose and be informed, highlighting the issue of insufficient platform transparency.

AI Chatbots Easily Fooled, According to IBM Research

["IBM's research shows that it is very easy to deceive large language models into generating malicious code or providing false security advice.","Hackers only need some basic knowledge of English and an understanding of the model's training data to easily deceive AI chatbots.","Different AI models have different sensitivities to deception, and GPT-3.5 and GPT-4 are relatively easy to deceive."]

AI Daily Report - June 30th: Baidu Open Sources the WENXIN Large Model 4.5 Series; Tongyi Qianwen Multimodal Generation Model Qwen VLo

Welcome to the AIbase [AI Daily Report] section! Spend three minutes a day to learn about the latest AI events, helping you understand AI industry trends and innovative AI product applications. For more AI news, visit: https://www.aibase.com/zh1. Baidu officially releases the WENXIN Large Model 4.5 series and fully opens it to the public, featuring ten new models with various parameter configurations. These models are trained and inferred using the PaddlePaddle framework, achieving a FLOPs utilization rate of 47%, and perform well in multi-modal text tasks.

Google Research: Synthetic Data Boosts Large Model Math Reasoning Eightfold

A recent joint study by Google, Carnegie Mellon University, and MultiOn explores the application of synthetic data in training large language models. According to Epoch AI, a research institution focused on AI development, currently available high-quality text training data totals around 300 trillion tokens. However, with the rapid advancement of large models like ChatGPT, the demand for training data is growing exponentially, projected to exhaust existing resources by 2026. Therefore, synthetic data is becoming increasingly crucial.

Google Bard GemPro Surpasses GPT-4, Claims Second Place in LMSYS Chatbot Rankings

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