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Building on the GPT-4o released last year, OpenAI has made significant updates to its advanced voice mode, making voice communication more natural and aligned with human conversation styles. This advanced feature is based on the native multimodal model, which can quickly respond to audio inputs, with the fastest response time at 232 milliseconds and an average response time of 320 milliseconds, nearly matching the speed of human conversations. At the beginning of this year, OpenAI had already made minor updates to this voice mode, improving interruption frequency and accent handling.

Welcome to the 【AI Daily】 column! This is your guide to exploring the world of artificial intelligence every day. Here we bring you hot content in the AI field, focusing on developers to help you gain insights into technical trends and understand innovative AI product applications. Fresh AI products click to learn more: https://top.aibase.com/1. The world's first Office intelligent agent APP! Kunlun Wonderworks TianGong Super Intelligent APP launched by Kunlun WonderWorks Group.

During a technical livestream at 1 AM today, OpenAI officially launched its latest and most powerful multimodal models: o4-mini and the full-power o3. These models offer unique advantages, capable of processing text, images, and audio simultaneously. They also function as agents, automatically utilizing tools such as web search, image generation, and code parsing. Furthermore, they possess a deep thinking mode, enabling reasoning about images within a chain of thought.

A significant breakthrough in the field of artificial intelligence. AIbase learned from social media that ByteDance recently announced the open-sourcing of its new multimodal generation model, Liquid. This model, utilizing an innovative unified encoding method and a single large language model (LLM) architecture, seamlessly integrates visual understanding and generation tasks. This release not only showcases ByteDance's technological ambition in multimodal AI but also provides a powerful open-source tool for global developers. Below is AIbase's in-depth analysis of the Liquid model, exploring its technological innovations and core features.

The Alibaba Cloud Tongyi Qianwen Qwen team announced the launch of Qwen2.5-Omni, a new generation of end-to-end multimodal flagship model in the Qwen family. Designed for comprehensive multimodal understanding, this new model seamlessly handles various input formats including text, images, audio, and video, and generates text and natural speech synthesis outputs simultaneously via real-time streaming response.

Alibaba is making waves in the AI field with the recent open-source release of its latest multimodal model, Qwen2.5-VL-32B-Instruct. This model is part of the Qwen2.5 series, which also includes 3B, 7B, and 72B versions. The 32B version prioritizes convenient local execution while maintaining performance. Enhanced through reinforcement learning, Qwen2.5-VL-32B excels in several areas. Notably, its responses are more aligned with human expectations.

Google CEO Sundar Pichai announced at a launch event that Google has open-sourced its latest multimodal large model, Gemma-3. This model is attracting significant attention for its low cost and high performance. Gemma-3 offers four different parameter scale options: 1 billion, 4 billion, 12 billion, and 27 billion parameters. Surprisingly, the largest 27 billion parameter model only requires a single H100 GPU for efficient inference, while similar models often require ten times the computing power.

On March 11th, the Tongyi Lab team announced the open-sourcing of the R1-Omni model, marking a significant advancement in multimodal model development. This model integrates reinforcement learning with verifiable reward (RLVR) methods, focusing on improving reasoning capabilities and generalization performance in multimodal emotion recognition tasks. R1-Omni's training is divided into two stages. In the cold-start phase, the team fine-tuned the model using a combined dataset containing 580 video clips sourced from Explainable Multimodal Emotion...

Recently, the Modelers community officially launched Step-Video and Step-Audio, two open-source multimodal large models developed by Step-Star. These models are designed for video generation and voice interaction, respectively, aiming to provide developers and enterprise users with more powerful AI tools. Step-Video, formally known as Step-Video-T2V, is a 30-billion parameter model, making it the world's largest open-source video generation model. This model can directly generate 20...