In today's development of artificial intelligence (AI), the speed of data transmission has become a significant bottleneck hindering its progress. To break through this barrier, a research team led by the University of Michigan (U-M) is developing a brand new chip connection system that uses optical waves instead of traditional cables for data transmission. This innovation is expected to address the 'memory wall' problem that limits computational speed and promote further growth of AI models. The project has received a $2 million grant from the National Science Foundation's Future Semiconductor program, with participation from the University of Washington and Penn State.

Recently, the Genius agent developed by the Verses team achieved remarkable results in the classic game Pong, surpassing top human players and other AI models using only 10% of the data and 2 hours of training time. This breakthrough marks a new milestone in AI technology and indicates the future direction of intelligent agents. The success of the Genius agent is attributed to its unique design philosophy. Compared to traditional large models, the size of Genius is only a fraction of that of SOTA models.

In today's rapid development of Large Language Models (LLM), the training and inference costs of models have increasingly become a focus of research and application. Recently, the Tencent Hunyuan team released an important study that delves into the 'Scaling Laws' of low-bit floating point quantization training, which refers to the principles governing the scale of floating point quantization training. The core of this research lies in exploring how to significantly reduce computational and storage costs without sacrificing performance by lowering the precision of the model.

Meta CEO Mark Zuckerberg recently defended the company's use of copyrighted data in AI training by referencing YouTube's battle against pirated content in a legal lawsuit. The case, titled 'Kadrey v. Meta', is one of numerous copyright lawsuits against AI companies currently in U.S. courts, with plaintiffs including notable authors Sarah Silverman and Ta-Nehisi Coates. According to recently released excerpts from Zuckerberg's testimony, he pointed out that while there may be instances of...

In the context of rapid development in the global tech industry, Snowflake (NYSE: SNOW) has announced the launch of the 'One Million Ideas, One Platform' initiative, aiming to provide free Snowflake AI Data Cloud training and certification to over 100,000 individuals by 2027, with plans to enhance the data and AI skills of one million people by 2029. This initiative will receive a $20 million investment from Snowflake, aiming to provide comprehensive support for students and professionals in high-growth and emerging markets.

Recently, the National Development and Reform Commission and other departments jointly issued the 'Implementation Opinions on Promoting the High-Quality Development of the Data Annotation Industry.' This policy aims to promote the specialization and intelligent development of the data annotation industry to facilitate innovation and application of artificial intelligence. It proposes utilizing talent project plans and technology projects to cultivate and attract high-end professionals. Establishing (revising) national occupational standards related to artificial intelligence training and data annotation. Deepening the integration of industry, academia, and research, encouraging long-term cooperation mechanisms among industry alliances, universities, research institutes, and enterprises, and enhancing data standards.

In a recent live conversation, Tesla and SpaceX CEO Elon Musk stated that the real-world data available for training artificial intelligence models is nearly exhausted. He was in discussion with Mark Penn, Chairman of Stagwell. Musk mentioned, "We have basically consumed all the accumulated knowledge of humanity... for AI training data. This phenomenon essentially occurred last year." Musk's viewpoint aligns with that of former OpenAI Chief Scientist Ilya Sutskever.

The World Economic Forum recently released the "Future of Jobs Report 2025," revealing an intriguing contradiction: while artificial intelligence (AI) is seen as a technology that will replace certain jobs, global companies are more inclined to retrain existing employees rather than resort to layoffs. The report surveyed 1,000 companies worldwide, and the results showed that about 41% of companies plan to cut positions that AI can handle, while 77% focus more on training current employees in AI skills. This trend highlights that many companies wish to adapt to AI through retraining.

In recent years, training large language models (LLMs) has become increasingly expensive and complex, with only a few major tech companies possessing the necessary computing resources. However, Google has recently introduced a new method called SALT (Small Model-Assisted Large Model Training), which could fundamentally change the landscape of AI training. Image Source Note: The image was generated by AI, and the image is authorized by service provider Midjourney based on the latest research papers from Google Research and DeepMind, 'A Little Help Goes a Long Way: Leveraging Small Language Models...'