Baidu Baike Launches AI Entry Editing Assistant; Baike BOT 'Baike Classmate' Feature to Go Live


["Representative Andrew Ng believes that the combination of data and machine learning will continuously strengthen the dominant position of technology market leaders.", "Representative A16Z partner believes that each model can only do one thing, and more data does not necessarily lead to better products.", "In different industries and use cases, the situation of \"winner takes all\" varies and needs to be analyzed specifically.", "The investment logic in the Internet era does not work in the AI era because computing power has a cost.", "Small, specialized long-tail models also have advantages, and wealth distribution will be more even."]
According to TMR Research, the global artificial intelligence chipset market size is expected to exceed $700 billion, with a compound annual growth rate of 31.8% from 2022 to 2031. The article discusses the development trends, application areas, and key players in the artificial intelligence chipset market, which is highly timely and valuable for readers interested in the artificial intelligence chipset market.
IBM's report provides sufficient evidence that artificial intelligence, automation, and threat intelligence can address data breaches throughout the lifecycle, reduce costs, and provide stronger evidence. The research found that integrating artificial intelligence and automation into security operations teams can reduce the lifecycle of data breaches by 33% and costs by 33.6%. However, currently, only 28% of enterprises widely apply artificial intelligence and automation. Many enterprises rely on legacy systems, which are easily bypassed by attackers. The significance of this article lies in emphasizing the effectiveness of artificial intelligence and automation in improving cybersecurity and calling on enterprises to widely adopt these technologies to protect data security.
The robotics research team at Google DeepMind recently released a robotics project called RT-2. This project took 7 months to develop and uses a large model for training. RT-2 has capabilities such as symbol understanding, reasoning, and human recognition, and can think and complete tasks based on human instructions. By combining the large model with the robot's operational capabilities, RT-2 can accomplish tasks that involve logical leaps, such as from 'extinct animals' to 'plastic dinosaurs'. The results of this project performed well in various sub - category tests, with performance up to three times that of the previous generation of robot models. This research result demonstrates the potential of large models in robotics research and is expected to drive the development of robots in the future.
Meta Intelligence OS is a startup founded by Bloomberg. It has developed a series of large models based on the open-source model RWKV and aims to become the Android in the era of large models. The RWKV model has superior performance and low cost in inference tasks, thus attracting customers from industries such as finance, law firms, and smart hardware. The business model of Meta Intelligence OS is model customization based on private data and internal AI Agent development. The company hopes to solve the problems of API call latency and data security by deploying large models on terminal devices. Currently, RWKV versions are available on Windows, Mac, and Linux computers, and Android and iOS versions are also in development. Meta Intelligence OS is raising funds and collaborating with chip companies and computing power platforms to create benchmark customers. Luo Xuan said that the decisive battlefield for large models is on hardware, and both terminal devices and the cloud require dedicated chips.