Generative AI holds significant potential for ecological and environmental applications such as monitoring, data analysis, education, and policy support. However, its effectiveness is limited by the lack of a unified evaluation framework. To address this, we present the Environmental Large Language model Evaluation (ELLE) question answer (QA) dataset, the first benchmark designed to assess large language models and their applications in ecological and environmental sciences. The ELLE dataset includes 1,130 question answer pairs across 16 environmental topics, categorized by domain, difficulty, and type. This comprehensive dataset standardizes performance assessments in these fields, enabling consistent and objective comparisons of generative AI performance. By providing a dedicated evaluation tool, ELLE dataset promotes the development and application of generative AI technologies for sustainable environmental outcomes. The dataset and code are available at https://elle.ceeai.net/ and https://github.com/CEEAI/elle.

The United States has launched its third crackdown in three years on China's semiconductor industry, curbing exports to 140 companies, including chip equipment maker Naura Technology Group, among other moves. The latest effort on Monday to hobble Beijing's chipmaking ambitions also hits Chinese chip toolmakers Piotech, ACM Research and SiCarrier Technology with new export restrictions as part of the package, which also takes aim at shipments of advanced memory chips and more chipmaking tools to China. The move is one of President Joe Biden's last large-scale efforts to stymie China's ability to access and produce chips that can help advance artificial intelligence for military applications, or otherwise threaten US national security. It comes just weeks before the swearing-in of Republican President-elect Donald Trump, who is expected to retain many of Biden's tough-on-China measures. The package includes curbs on China-bound shipments of high bandwidth memory (HBM) chips, critical for high-end applications like AI training; curbs on 24 additional chipmaking tools and three software tools; and export curbs on chipmaking equipment made in countries such as Singapore and Malaysia.

In this paper, we present our solution for the Second Multimodal Emotion Recognition Challenge Track 1(MER2024-SEMI). To enhance the accuracy and generalization performance of emotion recognition, we propose several methods for Multimodal Emotion Recognition. Firstly, we introduce EmoVCLIP, a model fine-tuned based on CLIP using vision-language prompt learning, designed for video-based emotion recognition tasks. By leveraging prompt learning on CLIP, EmoVCLIP improves the performance of pre-trained CLIP on emotional videos. Additionally, to address the issue of modality dependence in multimodal fusion, we employ modality dropout for robust information fusion. Furthermore, to aid Baichuan in better extracting emotional information, we suggest using GPT-4 as the prompt for Baichuan. Lastly, we utilize a self-training strategy to leverage unlabeled videos. In this process, we use unlabeled videos with high-confidence pseudo-labels generated by our model and incorporate them into the training set. Experimental results demonstrate that our model ranks 1st in the MER2024-SEMI track, achieving an accuracy of 90.15% on the test set.

A Chinese software engineer has been arrested for allegedly stealing artificial intelligence technology from Google while secretly working for two Chinese companies. Linwei Ding, 38, also known as Leon Ding, faces four counts of theft of trade secrets, the US attorney general, Merrick Garland, said in a statement. Ding, who was arrested on Wednesday in Newark, California, allegedly transferred confidential information from Google's network to his personal account while secretly affiliated with Chinese-based companies in the AI industry. "The justice department will not tolerate the theft of artificial intelligence and other advanced technologies that could put our national security at risk," Garland said. "We will fiercely protect sensitive technologies developed in America from falling into the hands of those who should not have them."

Colorectal cancer is a deadly disease that has become increasingly prevalent in recent years. Early detection is crucial for saving lives, but traditional diagnostic methods such as colonoscopy and biopsy have limitations. Colonoscopy cannot provide detailed information within the tissues affected by cancer, while biopsy involves tissue removal, which can be painful and invasive. In order to improve diagnostic efficiency and reduce patient suffering, we studied machine-learningbased approach for colorectal tissue classification that uses acoustic resolution photoacoustic microscopy (ARPAM). With this tool, we were able to classify benign and malignant tissue using multiple machine learning methods. Our results were analyzed both quantitatively and qualitatively to evaluate the effectiveness of our approach.

社内勉強会でAndrew Ng先生が提唱するData-Centric AIについて紹介した際の資料です。

China proves that it is one of the leading countries when it comes to AI medical technology during the annual World AI Conference held in Shanghai on Thursday, July 8. Now with the capability of technology to be incorporated in any area, the innovation has even reached across healthcare systems to help the professionals in their jobs. According to the latest report of Euronews, the field of AI can now aid doctors to address the health problems of their patients in a more advanced way. Particularly, the presence of the innovative equipment has not only helped in the additional tasks of the healthcare personnel, but also paved the way for a more efficient diagnosis and treatment of a disease. The eye-catching features of AI have caught the attention of many global companies to invest in it, especially now that the COVID-19 pandemic continues to hit many countries. The lack of a good healthcare system worsened the problem, and this only contributed to the decline of the overall healthcare quality.

China is flexing its artificial intelligence muscle, showcasing a host of medical innovations at this year's World AI Conference in Shanghai. Many of the systems use artificial intelligence to help diagnose health problems more quickly and efficiently than a doctor would alone. Companies around the world view AI as an opportunity to improve medical care, free up doctor's time and relieve the pressure that ageing populations are putting on healthcare systems. While the United States emerged as an early frontrunner in the industry, the European Union has taken a stricter stance when it comes to regulating AI, in a bid to protect privacy and fundamental rights. Meanwhile, China's medical AI boom is strongly supported by the central government, which wants the country to become the world's leading AI innovation centre by 2030.

I made my first trip to China in late 2008. I was able to speak to developers and entrepreneurs and to get a sense of the then-nascent market for cloud computing. With over 900 million Internet users as of 2020 (according to a recent report from China Internet Network Information Center), China now has the largest user base in the world. A limited preview of the China (Beijing) Region was launched in 2013 and brought to general availability in 2016. A year later the AWS China (Ningxia) Region launched.

China is shaping up to be the first real test of Big Tech's ambitions in the world of carmaking, with giants from Huawei Technologies Co. to Baidu Inc. plowing almost $19 billion into electric and self-driving vehicle ventures widely seen as the future of transport. While Apple Inc. has long had plans for its own car and Alphabet Inc. has Waymo, its autonomous driving unit, the size -- and speed -- of the move by China's tech titans puts them at the vanguard of that broader push. The lure is an industry that's becoming increasingly high tech as it pivots away from the combustion engine, with sensors and operating systems making cars more like computers, and the prospect of autonomy re-envisioning how people use will them. As the world's biggest market for new-energy cars, China is a key battlefield. Established automakers like Volkswagen AG and General Motors Co. are already slogging it out with local upstarts such as market darling Nio Inc. and Xpeng Inc.