Chain of News 17/07/2026

**Top Story** The release of the Kimi K3 2.8T-A50B model has sent shockwaves through the AI community, as it is being touted as the largest open model ever released. This development is significant because it provides developers with access to a powerful tool that can be used to improve a wide range of applications, from natural language processing to computer vision. The fact that this model is available at a price point similar to Sonnet 5 pricing makes it even more attractive to developers who are looking to integrate AI into their projects. This release is a continuation of a great week for open models, and it will be interesting to see how developers choose to utilize this powerful new tool. The implications of this release are far-reaching, and it has the potential to democratize access to advanced AI capabilities. As the AI landscape continues to evolve, the availability of open models like the Kimi K3 2.8T-A50B will play a crucial role in shaping the future of the industry. **AI Models & Research** The Embarrassingly Simple Self-Distillation method has shown promising results in improving code generation using large language models. This approach involves using the raw outputs of the model to improve its performance, without the need for a verifier, teacher model, or reinforcement learning. This is a significant development because it has the potential to simplify the process of training large language models and improve their performance on code generation tasks. The concept of a global workspace in language models, as discussed by Anthropic, is also an interesting area of research that could have significant implications for the development of more advanced AI models. Additionally, the use of hybrid text and ID embeddings for personalizing incremental video search is a notable development that could improve the efficiency and effectiveness of video search systems. The Personalizing Incremental Video Search with Hybrid Text and ID Embeddings system, for example, combines complementary semantic and collaborative filtering signals to provide high-quality ranking after each keystroke. **Developer Tools & Frameworks** The Q&A session with Capcom's RE ENGINE team provided valuable insights into the process of bringing path tracing to RE ENGINE across PRAGMATA and Resident Evil Requiem. The team's experience in implementing path tracing in two shipping titles at once is a notable achievement that demonstrates the capabilities of the RE ENGINE. This development is significant because it shows that path tracing can be successfully integrated into game engines, and it provides a useful case study for developers who are looking to implement similar technology in their own projects. The RE ENGINE team's approach to path tracing is a practical example of how developers can use this technology to improve the visual quality of their games. By studying the team's approach, developers can gain a better understanding of how to implement path tracing in their own projects and improve the overall visual quality of their games. **Industry & Business** NetApp's acquisition of DataPelago is a significant development in the AI industry, as it aims to make data more accessible for AI applications at the infrastructure level. This acquisition is a strategic move by NetApp to expand its capabilities in the AI space and provide more comprehensive solutions to its customers. According to a research study by Visa, 89% of Italian banks are already using AI, which highlights the growing adoption of AI in the financial sector. This trend is expected to continue, and it will be interesting to see how AI is used to improve the efficiency and effectiveness of banking operations. The use of AI in the banking sector has the potential to transform the way banks operate and provide services to their customers. **Worth Watching** The use of AI to anticipate diseases and future pandemics is an area of research that deserves attention, as it has the potential to save countless lives. The application of AI in this field is still in its early stages, but it has already shown promising results. The use of AI to reveal the contents of a carbonized papyrus is another interesting development that highlights the potential of AI to uncover new knowledge and insights from historical artifacts. These developments are a testament to the versatility and potential of AI to transform various fields and industries. As AI continues to evolve, it will be exciting to see how it is used to address some of the world's most pressing challenges and uncover new insights and knowledge.