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Meta faced protests outside its San Francisco office against its strategy of publicly releasing AI models. Demonstrators are concerned that the open sourcing of model weights may lead to uncontrollable consequences. Meta's Chief Scientist, LeCun, countered that the open-source AI community is thriving. There are divisions in the industry regarding open and closed source; while open source can enhance transparency, it also poses risks. The definition of open source remains ambiguous, with different organizations having varied interpretations of 'open source AI.'
The Colossal-AI team has developed a highly performant Chinese version of LLaMA-2 at a low cost. The Chinese LLaMA-2 has excelled in multiple evaluation rankings. Colossal-AI has open-sourced the complete training process, code, and weights. They also provide the evaluation framework ColossalEval. Colossal-AI's solution can be used to build large models for any vertical field.
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.