Amazon recently announced a $110 million investment in AI research to support the development of its own designed Trainium chips. This move aims to reduce Amazon's reliance on Nvidia and promote technological advancements in its cloud computing platform AWS. Note: Image generated by AI, image licensed from service provider Midjourney. Trainium is a machine learning chip tailored for deep learning training and inference tasks. Through this investment, Amazon hopes to encourage academic research.

At the main forum of the 2024 World Internet Conference in Wuzhen, Alibaba Group CEO Wu Yongming delivered a speech on the company's strategy in the era of artificial intelligence. Wu Yongming emphasized that Alibaba is committed to doing two things: first, continuously improving artificial intelligence infrastructure and related support systems; second, adhering to open source and openness, collaborating with ecological partners to transform AI capabilities into productivity across various industries.

Microsoft Research recently inaugurated its newest laboratory in Tokyo, Japan, marking a significant step in the company's AI research initiatives in the Asia-Pacific region. Leading the lab is former Osaka University professor and senior researcher at Microsoft Research Asia, Kazuya Matsushita, who returns to Microsoft with ten years of academic experience to embark on a new chapter. The new laboratory will focus on fields such as embodied AI, health and welfare, neuroscience, social AI, and industrial innovation, aligning closely with Japan's socioeconomic development priorities. Through deep collaboration with local academia and industry, the laboratory aims to contribute to global innovation.

The safety risks associated with lithium battery fires are often a cause for concern. To address this, scientists have proposed a method to provide early warnings of battery fires using sound. The study discovered that lithium-ion batteries undergo a series of chemical reactions before catching fire, leading to a gradual increase in internal pressure and ultimately causing the battery to swell. Due to the hard casing of the batteries, which cannot accommodate this swelling, the safety valve inside the battery bursts when the pressure becomes too high, creating a distinct sound.

Recently, researchers from ByteDance Research Institute and Tsinghua University jointly released a new study, pointing out that current AI video generation models, such as OpenAI's Sora, while capable of creating stunning visual effects, have significant flaws in understanding basic physical laws. This study has sparked widespread discussion on the capabilities of AI in simulating reality. The research team tested AI video generation models under three different scenarios: predictions under known patterns and predictions under unknown patterns.

Recently, Amazon announced a significant investment of $110 million for artificial intelligence (AI) research aimed at reducing reliance on Nvidia and advancing the development of its own chips. The funding will support generative AI research at universities under the project name 'Build on Trainium.' The project will provide researchers with the opportunity to use Trainium chips to develop new AI architectures, machine learning libraries, and solutions for large-scale distributed AWS Train.

Recently, a new study from the University of Michigan found that an energy-efficient method for training large language models can achieve similar results in the same amount of time while reducing energy consumption by 30%. This method can save enough energy to power 1.1 million American households by 2026. The researchers developed a software tool named Perseus that identifies the critical path, which is a series of subtasks requiring the longest time to complete. Then, Perseus reduces the processor speed on non-critical paths so that all tasks can finish simultaneously.

Recently, AI programming assistants have become incredibly popular, claiming to help programmers write code and improve efficiency. Many programmers even consider it a 'savior', eager to use it for coding every day. However, a study from Stanford University has doused the enthusiasm of these 'zealous fans' with cold water: AI programming assistants may be a 'security nightmare'! Stanford researchers gathered 47 programmers to complete five security-related coding tasks, covering Python, JavaScript, and C languages. The results revealed...

Meta recently announced that its MobileLLM model is now open to researchers, allowing users to download and use these models for free on the Hugging Face platform, fully integrated with the Transformers library. This initiative aims to promote research and development of large language models (LLMs) on mobile devices, providing a broader range of tools and resources for developers and academia. MobileLLM represents a significant advancement for Meta in the field of mobile AI.

Is AI actually starting to ‘get smarter’?! The latest research from MIT indicates that the internal structure of large language models (LLMs) astonishingly resembles that of the human brain! This study utilized sparse autoencoder techniques to conduct an in-depth analysis of the activation space of LLMs, revealing three hierarchical structural features that are truly remarkable: first, at the microscopic level, researchers discovered the existence of structures akin to ‘crystals’. The surfaces of these ‘crystals’ are composed of parallelograms or trapezoids, similar to familiar lexical analogies such as ‘man:’