In recent years, the programming capabilities of Artificial Intelligence (AI) have been continuously evolving, but they have not yet reached perfection. Recently, Max Woolf, a senior data scientist at BuzzFeed, discovered through experiments that if continuous prompts for 'writing better code' are provided to large language models (LLMs), AI can indeed generate higher quality code. This finding has garnered widespread attention, with renowned AI scientists emphasizing the importance of iteration and prompt design. In Woolf's experiment,

Recently, researchers proposed a new method called NeuralSVG, aimed at generating vector graphics from text prompts. This innovative technology will provide artists and designers with more flexible and efficient tools to create high-quality visual content. Compared to traditional vector graphic generation methods, NeuralSVG not only generates graphics with multi-level structures but also allows users to make various dynamic adjustments during the generation process. The core of NeuralSVG lies in its implicit neural representation, achieved through a compact multi...

With the rapid development of artificial intelligence technology, many companies have launched their own 'AI Agent' systems that can autonomously interact with the environment and complete tasks without human intervention. Companies like Microsoft and Anthropic have been the first to introduce their AI Agents, while industry leader OpenAI has yet to release its own version, and the reasons behind this delay are thought-provoking. According to The Information, OpenAI's delay is related to concerns over 'prompt injection' attacks.

At the end of 2024, Baidu announced its annual AI prompt for 2024: 'Answer'. This choice reflects the year-long reliance and expectations people have for AI, as well as the role AI plays in societal emotions and personal confusion. Throughout the year, many individuals began seeking answers from AI, with frequently used terms such as 'answer', 'why', 'what is', 'help me', and 'how', revealing 2024's social sentiments and showcasing the confusion and pursuit within people's hearts.

Recently, Adobe's research team collaborated with researchers from the University of Michigan to develop an artificial intelligence system called MultiFoley, which generates sound effects for dubbing in films and videos, assisting in post-production. The innovation of MultiFoley lies in its ability to allow users to create sound effects through text prompts, reference audio, or video examples. In demonstrations, the system can even transform a cat's meow into a lion's roar, or convert the sound of a typewriter into piano notes, perfectly synchronized with video footage.

Recently, a research team from the Beijing Academy of Artificial Intelligence launched a new image generation model called OmniGen. Unlike previous tools such as Stable Diffusion, which focused on a single task, OmniGen's biggest highlight is its multi-capability: it can handle a variety of image generation tasks within a unified framework, including text-to-image generation and image editing, making it a versatile player. This means that users only need to provide simple prompts.

Recently, teams from Cambridge University and others published a groundbreaking paper that reveals the true nature of large models (LLMs), providing an in-depth analysis of the actual performance of current large language models (LLMs). The results are shocking — these AI models, once highly anticipated, perform far below expectations on many basic tasks. The study conducted a comprehensive evaluation of several cutting-edge models, including o1-preview. The findings indicate significant discrepancies in understanding capabilities between AI models and humans. Surprisingly, the models struggle with tasks that humans excel at.

Enterprise AI leader Glean raised over $260 million in its latest Series E financing round, with the company's valuation reaching $4.6 billion, doubling from $2.2 billion six months ago. This round was co-led by Altimeter and DST Global, with participation from several investment firms including Craft Ventures, Sapphire Ventures, and SoftBank Vision Fund 2. Along with the financing, Glean launched Work AI.

With the rise of generative AI, the prompt trading market is rapidly expanding. However, current trading platforms, exemplified by PromptBase, are predominantly seller-driven in pricing and lack objective price measurement standards. In response to this challenge, the multimedia and intelligent security team at Fudan University has proposed an innovative prompt trading model aimed at better adapting to a future buyer-driven market. This new trading model consists of two main phases: prompt category selection and pricing strategy formulation. In the first phase, the platform employs a greedy search-based multi-armed bandit algorithm to...

OpenAI has launched the brand new model series GPT-o1, which exhibits exceptional reasoning abilities. Compared to previous models, its performance is highly anticipated. GPT-o1: Enhanced Reasoning Capabilities is a series of new reasoning models designed to help solve complex problems. These models are specially trained to take more time to think before responding, enabling them to tackle more challenging issues than ever in fields such as science, coding, and mathematics. GPT-o1 will first be available in ChatGPT and A.

In the context of the rapid development of AI technology, prompt engineering has become a critical skill. By cleverly designing prompts, users can guide AI to better understand human intentions and improve the accuracy of AI responses. However, this process poses significant challenges for average users. To address this issue, a team of scientists from Peking University and Baichuan Technology has jointly developed the PAS (Prompt Augmentation System), an intelligent prompting enhancement system based on large language models. PAS improves data utilization, compatibility, and flexibility.

Anthropic has announced that it will release the Artifacts system prompts for the Claude series models within a few weeks, responding to researchers' concerns about transparency. The Artifacts feature was recently opened to all users, allowing code snippets to run alongside the chat interface. The release of the system prompts aims to enhance user understanding of model behavior and promote transparency in AI development. The Claude 3.5 Sonnet version emphasizes accurate and concise answers, while Claude 3 Opus has been updated.

In the AI-driven era, web development efficiency and innovation are crucial. Traditional web development is often cumbersome and time-consuming, requiring high technical skills. GPTEngineer, an AI-assisted tool, aims to simplify this process and enhance efficiency. It utilizes intelligent algorithms to allow users to interact with AI for rapid website creation, from design to deployment, offering a one-stop solution. It features seamless GitHub s....

Anthropic has recently made public the system prompts for the Claude model, including the Claude 3.5 Opus, Sonnet, and Haiku versions. This is a significant breakthrough for the AI industry, as most vendors typically keep this information confidential. This move enhances AI transparency, as the behavior rules and personality traits of Claude are detailed through these prompts. Generative AI models generate text based on statistical predictions, and system prompts are used to guide model behavior to avoid inappropriate actions. Anthropic's aim with this initiative is to