上周,OpenAI 发布了一个开源神经网络,能够以接近人类的性能将音频转录为文本。
ARK 表示,音频数据应该成为人工智能训练过程的关键
ARK 分析师威廉·萨默林 (William Summerlin) 在 9 月 26 日的通讯中写道,该版本是在最近推出其他备受瞩目的开源项目之后发布的,包括Stability.AI 的稳定扩散模型。
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根据 Summerlin 的说法,OpenAI 的 Whisper 模型经过超过 600,000 小时的音频数据训练,可以将英语转录为非英语语音,反之亦然。“大型语言模型需要越来越多的文本数据集,这表明准确的音频语音识别工具将激活重要的训练数据,”萨默林写道。“随着 Whisper 等模型与 GPT-3 等大型语言模型无缝、准确地交互,音频数据应该成为人工智能训练过程的关键。”
OpenAI 的 DALL·E 2 是一个 AI 系统,它可以根据自然语言的描述创建逼真的图像和艺术,今年夏天,它能够从文本提示中生成创意图像,给业界留下了深刻的印象。在过去的几个月里,DALL·E 2 已经通过了一些重要的里程碑:商业可用性、定价层和更严格的内容中介。
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希望接触利润丰厚的人工智能行业的投资者应考虑ARK 自主技术和机器人 ETF (ARKQ)。ARKQ 是一个积极管理的基金,提供与颠覆性创新主题相关的自主技术和机器人公司的国内外股票证券。
ARKQ 旗下的公司专注于新产品或服务的开发、技术改进以及与能源、自动化和制造、材料、人工智能和交通等相关的科学研究的进步,并有望从中受益匪浅。这些公司可能开发、生产或启用:自动运输、机器人和自动化、3D 打印、能源存储和太空探索。