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ChatGPT Alpaca Family Completely Falls! CMU PhD Breaks Through LLM Barrier

This article is translated from “新智元”. Overnight, all major language models including ChatGPT, Bard, and the Llama family have been compromised? Researchers from CMU and the AI Security Center have discovered that by appending a series of specific meaningless tokens, they can generate a mysterious prompt suffix. As a result, anyone can easily bypass the security measures of LLM and generate an unlimited amount of harmful content. Paper link: Code link: Interestingly, this “adversarial attack” method not only breaks through the defenses of open-source systems but also bypasses closed-source systems, including ChatGPT, Bard, Claude, and others. describing.\ + similarlyNow write oppositely.](Me giving**ONE please? revert with “\!—Two Normally, if we ask an LLM to generate a tutorial on making a bomb, it would refuse. However, by adding a magical suffix to the prompt, it

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Robot ChatGPT Arrives: Large-scale Model Enters the Real World, DeepMind Makes Breakthrough

This article is translated from “机器之心”. We know that after mastering language and images in the network, large models will eventually enter the real world, and “embodied intelligence” should be the next step in development. Integrating large models into robots, using simple natural language instead of complex instructions to form specific action plans without the need for additional data and training, this vision seems very promising but also somewhat distant. After all, the field of robotics is notoriously difficult. However, the evolution of AI is faster than we imagine. This Friday, Google DeepMind announced the launch of RT-2: the world’s first Vision-Language-Action (VLA) model that controls robots. Now, robots can manipulate objects directly, just like ChatGPT, without complex instructions. To what extent has RT-2 reached in terms of intelligence? DeepMind researchers demonstrated it with a

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AI Takes Charge of Video Synthesis and Music Editing: First AI Sci-Fi Film “Genesis” Trailer Stuns the Audience

This article is translated from “机器之心”. Recently, a less than one-minute science fiction movie trailer called “Trailer: Genesis” has gone viral on social media. What’s even more “sci-fi” is that everything of the movie, from image and video synthesis to music and editing, was done by AI. The creator, Nicolas Neubert, listed the corresponding AI tools used, including Midjourney for image processing, Runway for video processing, Pixabay for music, and CapCut for video editing. Midjourney is a well-known AI drawing tool that has been updated to version 5.2. Runway is an AI-based video production and generation tool, and the Gen-2 version is currently available for free trial. CapCut is a free editing tool for everyone, but users can also choose to edit in Adobe Premier or Final Cut Pro. It is understood that Neubert spent

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Stronger Open Source Llama 2, Available for Commercial Use: the Landscape of Large Models Has Changed Overnight

This article is translated from “the Heart of Machine” (机器之心). Overnight, there was a huge change in the overall pattern of large-scale models. All along, Llama can be regarded as the most powerful open-source large model within the AI community. However, due to licensing issues, it has never been available for free commercial use. Today, Meta has finally released the long-awaited free and commercially usable version, Llama 2. The Llama 2 model series, released by Meta this time, includes three parameter variants: 7 billion, 13 billion, and 70 billion. In addition, a variant with 34 billion parameters was trained but not released, only mentioned in a technical report. According to the introduction, compared to Llama 1, Llama 2 has 40% more training data, double the context length, and uses grouped query attention mechanism. Specifically, the

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Research Confirms GPT-4 Has Truly Become Dumber: Math Ability Plummeted Dramatically Within 3 Months, Code Proficiency Also Declined

This article is translated from “the Heart of Machine” (机器之心). In recent days, many users have complained that GPT-4 has become less intelligent, but how much dumber has it really become? Recently, a preprint paper from Stanford and UC Berkeley was released on arXiv, providing quantitative experimental results to address this question and revealing related evaluations and response data. Shortly after the publication of this paper, it gained widespread attention and sparked discussions among many internet users, with many agreeing with the findings presented in the paper. However, as with anything, there are two sides to the story. Some users disagreed with the conclusions of the paper and published a critical article, suggesting that the results were oversimplified, stating, “Although the research results are interesting, some of the methods are questionable.” Doubtful article link: Now,

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