你是一位资深科技记者，专门报道AI行业动态。请分析以下OpenAI的技术发布，提取关键信息用于新闻报道。

**分析要求**：
1. 识别产品的核心创新点和技术突破
2. 评估技术进步的重要性和行业影响
3. 分析对开发者和企业用户的实际价值
4. 预测可能的市场反应和竞争对手响应
5. 用专业但易懂的语言总结，避免过度技术化

**输出格式**：新闻稿风格，包含标题、导语、核心信息、影响分析四个部分。

[文章内容]
GPT‑4o (“o” for “omni”) is a step towards much more natural human-computer interaction—it accepts as input any combination of text, audio, image, and video and generates any combination of text, audio, and image outputs. It can respond to audio inputs in as little as 232 milliseconds, with an average of 320 milliseconds, which is similar to human response time⁠(opens in a new window) in a conversation. It matches GPT‑4 Turbo performance on text in English and code, with significant improvement on text in non-English languages, while also being much faster and 50% cheaper in the API. GPT‑4o is especially better at vision and audio understanding compared to existing models.Prior to GPT‑4o, you could use Voice Mode⁠ to talk to ChatGPT with latencies of 2.8 seconds (GPT‑3.5) and 5.4 seconds (GPT‑4) on average. To achieve this, Voice Mode is a pipeline of three separate models: one simple model transcribes audio to text, GPT‑3.5 or GPT‑4 takes in text and outputs text, and a third simple model converts that text back to audio. This process means that the main source of intelligence, GPT‑4, loses a lot of information—it can’t directly observe tone, multiple speakers, or background noises, and it can’t output laughter, singing, or express emotion.
With GPT‑4o, we trained a single new model end-to-end across text, vision, and audio, meaning that all inputs and outputs are processed by the same neural network. Because GPT‑4o is our first model combining all of these modalities, we are still just scratching the surface of exploring what the model can do and its limitations.