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Many universities are prohibiting the use of AI to write papers. This raises questions about the future of academic integrity and how students will navigate the challenges of AI in their studies.

Recently, Zhu Xiaohu, the managing partner of Jinshi River Venture Capital, has repeatedly posted on social media in response to the Dark Side of the Moon arbitration case, criticizing former managing partner Zhang Yutong. In response, Yang Zhiling, founder and CEO of the Dark Side of the Moon, issued a statement last night via social media, addressing questions regarding his exit from his previous company to start anew and the issue of Zhang Yutong's shares in the Dark Side of the Moon. Yang Zhiling clearly stated that all necessary procedures received the signature approval of each director when he left Cyclical Technology to begin a new venture. He emphasized his clear separation from the previous company and some shareholders.

Recently, the ChatGPT chatbot encountered an unusual situation where it could not respond properly to the name 'David Mayer'. Users repeatedly attempted to get ChatGPT to mention this name, but regardless of direct reference or modifying prompts, ChatGPT responded with error messages or prevented users from continuing to ask questions.

According to a report by Kyodo News on the 29th, Japan is facing a serious declining birthrate issue, with the number of marriages in 2023 dropping below 500,000 for the first time, marking a new low in 90 years. To tackle this challenge, the Tokyo Metropolitan Government has developed an AI matchmaking software called 'TOKYO Connect,' which was fully launched in September this year. The core feature of this software is its ability to use artificial intelligence for matching. Users are required to complete 110 questions on values and personality traits, after which the AI recommends highly compatible matches. Once matched, users can communicate through the software and arrange offline meetings.

Researcher Naphtali Deutsch discovered that hundreds of open-source large language model (LLM) building servers and dozens of vector databases are leaking large amounts of sensitive information. This problem arises from companies neglecting the security of related tools in their haste to integrate AI into their workflows. By hacking into 438 Flowise servers, he revealed stored sensitive data, including GitHub access tokens, OpenAI API keys, Flowise passwords, and API keys. Additionally, he found...

Recently, the Northern District Court of California made a ruling in a copyright lawsuit that has attracted widespread attention, partially dismissing the claims against GitHub Copilot programming tool and its former underlying technology, OpenAI Codex. This decision may set a precedent for new technology tools that train with copyrighted data. The lawsuit was filed by the law firm of Joseph Saveri in 2022, with the plaintiff claiming that GitHub and OpenAI allowed Copilot and Codex to copy sour

The ChatGPT Mac client recently released by OpenAI has a potential security issue that is of concern: the conversations stored on the computer are easily accessible and can be read in plain text.This means that if a malicious actor or malicious application gains access to your device, they can easily read your conversations with ChatGPT and the data contained within them.The issue was demonstrated by user Pedro José Pereira Vieito on Threads, where it was shown that easy access means other appl

Senators Mark Warner and Todd Young advocate for the creation of AI regulatory policies to address potential risks. AI experts warn that regulation must balance innovation with citizen protection to avoid overly restrictive development. Lawmakers believe that AI regulation is a bipartisan issue and legislative efforts must be accelerated to tackle problems like election fraud. Experts from Johns Hopkins University emphasize the need for balanced regulation to ensure AI development while protecting citizens' rights.

Google's Gemini model portrait generation feature is set to relaunch. The portrait generation feature of Gemini did not work as expected, providing inaccurate information in historical image generation. Google is working on fixing the issues and plans to release an improved version.

The World Privacy Forum report indicates that over one-third of AI governance tools have 'defect corrections' that affect fairness and explainability assessments. Some tools and technologies developed by companies like Microsoft, IBM, and Google have also been found to have issues, raising concerns. The lack of quality assurance and evaluation requirements is the main problem, as some tools may have issues in different contexts and 'out-of-label usage'. Experts suggest that through collaboration between international organizations and standard-setting bodies, substantial improvements in AI governance tools could be achieved by 2024.

Experts say Australia is lagging in AI funding and regulation, especially after the U.S. issued an executive order on AI regulation. The Australian government has signed the AI safety declaration but has not responded to calls for an AI safety investigation, raising concerns. The government has received over 500 submissions on AI but lacks specific regulatory details, and experts emphasize that Australia needs to take more proactive measures.

iFLYTEK stated that the coding and mathematical problem-solving capabilities of its Spark 3.0 are leading in the industry. They believe that the two major evolution directions for large models are the expansion of model scale and the development of personalized AI assistants. iFLYTEK acknowledged that the greatest pressure from deep cooperation with Huawei stems from their mindset, which can influence the product iteration pace. They forecast that large model business will yield significant commercial benefits next year, reaching a state where revenue growth covers investment by 2025. iFLYTEK believes that there will be obvious differentiation among leading enterprises in the large model field on the scale of 3.5.

Harvard and Columbia have released the open dataset OpenProteinSet, containing 16 million protein multiple sequence alignments and related data to support AI model training. AlphaFold 2 has achieved a milestone in the accuracy of protein structure predictions, but its proprietary data has limited progress for other researchers. OpenProteinSet includes MSAs for all proteins in the PDB, providing ample precomputed MSA resources for the protein machine learning community. This dataset can be used for various tasks in structural biology.