IBM Research: How AI & Automation Protect Businesses from Data Breaches

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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.
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.
On March 25th, Cai Chongxin, Chairman of the Alibaba Group, expressed his views at the HSBC Global Investment Summit, pointing out that a bubble is beginning to form in the construction of artificial intelligence (AI) data centers. He believes that many investment announcements in US data centers are "duplicated" or overlapping. Meanwhile, Cai Chongxin revealed that Alibaba's employee count has bottomed out and the company will restart its hiring plan. Regarding the current booming AI wave, Cai Chongxin broadly categorized companies involved into three types: the first focuses on model research and development, such as OpenAI; the second focuses on AI applications and integrations; and the third comprises infrastructure providers.
In the article "From AI to IA, Whoever Masters Agents Masters the World", we explored how the core driving force behind the explosive development of the AI era is the paradigm shift in industrial applications brought about by multi-agent collaboration. From intelligent question answering to task execution, Agents are bringing AI to real-world applications in vertical fields, creating new business models. Multi-agent collaboration (InterAgent) should follow a specific standard framework to achieve maximum scalability and interoperability. Based on our theoretical exploration and practical experience, we attempt to outline this framework here.