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.

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.

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, OpenAI's research team discovered that the usernames chosen by users can somewhat influence the responses of ChatGPT during interactions. Although this effect is relatively minor and primarily seen in older models, the findings are still noteworthy. Users typically provide their names to ChatGPT for tasks, making the cultural, gender, and racial backgrounds inherent in those names an important factor in studying bias. In this research, the researchers explored ChatGPT.

In the world of artificial intelligence, the reasoning capabilities of machine learning models, particularly large language models (LLMs), have been a focal point for scientists. Recently, Apple's AI research team published a paper titled 'Understanding the Limitations of Large Language Models in Mathematical Reasoning,' shedding light on these models' limitations when addressing logical problems. In the paper, researchers demonstrate this through a simple mathematical question. They first posed a question about Oliver picking kiwis: as follows: Oliver picked 44 on Friday.

Tokyo-based AI development company Sakana AI has announced the completion of a $100 million Series A financing round, with investors including NEA, Khosla Ventures, Lux Capital, and NVIDIA. Sakana AI focuses on nature-inspired intelligence and model optimization, particularly in evolutionary optimization and sparsity. The partnership with NVIDIA will provide advanced GPU technology support and access to Japanese data centers, aimed at promoting AI research and innovation. Collaboration goals include advancing research and leveraging NVIDIA's infrastructure.

Yale University has announced a $150 million investment over the next five years to advance research and applications in the field of artificial intelligence for faculty and students. The investment focuses on building computing infrastructure, providing secure generative AI tools, recruiting dedicated faculty, promoting interdisciplinary collaboration, and enhancing research and educational capabilities. The plan includes the establishment of approximately 450 graphics processing units (GPUs) and the development of a platform named 'Clarity' to provide users with secure access to AI tools, along with plans to hire over 20 experts in the AI field. This initiative aims to strengthen Yale's leadership in the AI domain.

The California state government has partnered with tech companies to invest $250 million to support journalism and AI research, with a plan to implement this over five years, including an initial allocation of $100 million in the first year. The funding is primarily aimed at developing California news organizations and AI research projects. This initiative aims to boost local news vitality and provide job opportunities, seen as a crucial breakthrough for the survival of journalism. The agreement has sparked controversy between the tech industry and lawmakers, with the initial proposal requiring tech companies to pay a percentage of advertising revenue in exchange for linking content, which faced strong opposition. The California News Publishers Association supports the agreement, believing it will benefit the local community.

Meta AI's latest project, Llama 3, focuses on training with synthetic data rather than human-written answers to optimize model performance in areas such as code generation, mathematical reasoning, multilingual processing, and long text handling. Llama 3 generates synthetic data for code generation through three methods, employs research methods for mathematical reasoning, and collects high-quality human annotations for multilingual pre-training. Furthermore, Llama 3's training is enhanced using Brave Search, Wolfram Alpha, and Python interpreter.

In the global field of artificial intelligence research, China is rising at an astonishing speed and quality. According to the latest survey report from the George Washington University data analysis platform ETO, between 2017 and 2022, China published 243,000 AI papers, accounting for 25% of the global total and ranking first in the world. This achievement marks a major breakthrough for China in terms of the quality of AI talent and technological innovation capabilities. The United States follo

Recently, the AI research organization Artificial Analysis launched an initiative called 'Artificial Analysis Text to Image Leaderboard & Arena' to comprehensively evaluate the performance of these models.

The UK government's response to AI regulation consultations reveals its regulatory plans in the field of artificial intelligence. The Department for Science, Innovation and Technology promotes a reliance on existing laws and regulatory bodies while also providing over £100 million in funding to strengthen AI regulation. The UK government will invest over £90 million to establish nine research centers aimed at promoting AI innovation in areas including healthcare, mathematics, and chemistry. The government insists on not introducing new AI regulations but will continue to rely on existing laws and empower regulatory bodies to address issues more effectively.

Apple recently published two papers showcasing significant advancements in its artificial intelligence research. The new technology is expected to enable complex AI systems to run smoothly on devices like the iPhone. Apple has employed a range of methods to reduce data transfer, achieving 4-5 times improvement in inference latency and 20-25 times acceleration on GPUs. This breakthrough is particularly important for deploying advanced language models in resource-constrained environments. These optimizations could allow complex AI assistants and chatbots to run seamlessly on mobile devices.

Teams from Google DeepMind, the University of Washington, and others have successfully unveiled the sources of ChatGPT's training data through a 'poetry attack'. This attack method involves repeating specific vocabulary, which led ChatGPT to disclose personal information, including phone numbers and email addresses. The vulnerability was reported to OpenAI on August 30, and no further comments have been made. The research calls for environmentally-friendly AI usage, pointing out the significant energy burden that text and image generation imposes on the environment.

An AI researcher from Oxford University has pointed out that large language models (LLMs) may pose a threat to scientific integrity. The research calls for a change in the use of LLMs, suggesting they be used as 'zero-shot translators' to ensure factual accuracy in outputs. Relying on LLMs as a source of information could jeopardize scientific truth, leading to calls for responsible use of LLMs. The study warns that casual use of LLMs in scientific papers could result in significant harm.

OpenAI is enticing top AI researchers from Google with a billion-dollar equity incentive plan, with the company's valuation expected to surpass $80 billion. The recruitment is focused on senior AI researchers for the Gemini AI model, with annual salaries primarily offered in the form of stock ranging from $5 million to $10 million. The market is fiercely competitive, as OpenAI not only offers attractive compensation packages to senior staff but also increases salaries for junior employees, leading to an intense talent war with Google.

Meta's open-source model Llama2 has not met the requirements of open-source initiatives, sparking controversy. AI research lead Joelle Pineau believes that openness and business costs need to be balanced. Meta is actively participating in industry organizations to advocate for safe AI model deployment standards.