Technology peripherals
AI
OpenAI company releases security measures used when building artificial intelligence models such as GPT-4
OpenAI company releases security measures used when building artificial intelligence models such as GPT-4
OpenAI company recently announced that it will build security measures into its artificial intelligence tools. The company is the developer of the powerful GPT-4 large-scale linguistic artificial intelligence model, which is at the core of its ChatGPT chatbot and other artificial intelligence systems. The company's disclosure comes amid growing calls for more controls over the development of generative AI systems.
In a blog post, OpenAI detailed the steps it is taking to prevent its artificial intelligence systems from generating harmful content and avoid violating data privacy regulations. While the AI tools developed by the company have led a global boom in generative AI, in recent weeks regulators have become interested in the safety of such AI systems, with Italy citing potential violations of GDPR regulations. Use of ChatGPT is prohibited.
Artificial intelligence experts, including Musk and Apple co-founder Wozniak, recently called for a temporary halt to the development of large language models (LLM) in an open letter, and U.S. President Biden also joined Following this discussion, he told reporters that artificial intelligence companies must put safety first.
How OpenAI built GPT-4 with security in mind
OpenAI said it spent six months before releasing its most advanced GPT-4 to date last month. Months to perfect the system to make it as difficult as possible to use for nefarious purposes.
Security researchers have previously demonstrated that it is possible to bypass ChatGPT's security controls by "tricking" chatbots into generating hate speech or malware code that mimics poor artificial intelligence systems. OpenAI says this is less likely to happen with GPT-4 than with the GPT-3.5 model.
The company’s engineers said: “Compared to GPT-3.5, GPT-4 is 82% less likely to respond to requests for disallowed content, and we have built a robust system to monitor Abuse of artificial intelligence systems. We are also developing features that will enable developers to set more stringent standards for model output to better support developers and users who require such capabilities."
OpenAI Company Will AI systems leak internet users' personal data? The company also took the opportunity to respond to data regulators' concerns about the way its models collect data from the internet for training purposes. After Italy banned ChatGPT, Canada launched an investigation into the chatbot's safety and other countries in Europe are considering whether to follow Italy's lead.
OpenAI said: “Our large language models are trained on an extensive corpus of text, including publicly available content, licensed content, and content generated by human reviewers. We do not transfer the data to For selling services, advertising or building user profiles."
The company also detailed how it ensures that personal data is not leaked during training. "While some of our training data includes personal information available on the public internet, we want our large-scale language models to learn about the world, not individuals," the company said. remove personal information from the training data set, fine-tune the model to deny requests for personal information, and respond to individuals’ requests to remove personal information from the AI system. These steps minimize the chance that our models will produce responses that contain personal information possibility."
U.S. President Biden joins the ranks of opponents of artificial intelligence
Before OpenAI issued this statement, U.S. President Biden told reporters that artificial intelligence development Authors are responsible for ensuring that their products are safe before making them public.
Biden spoke after discussing the development of artificial intelligence with his Science and Technology Advisory Council. He said that the U.S. government is committed to advancing the Artificial Intelligence Bill of Rights introduced in October last year to protect individuals from the negative impacts of advanced automated systems.
Biden said: “We proposed a bill of rights last October to ensure that important protections are built into AI systems from the beginning so we don’t have to go back and do them. I We look forward to our discussions ensuring responsible innovation and appropriate guardrails to protect the rights and safety of Americans, protect their privacy, and address possible bias and disinformation."
The above is the detailed content of OpenAI company releases security measures used when building artificial intelligence models such as GPT-4. For more information, please follow other related articles on the PHP Chinese website!
Hot AI Tools
Undresser.AI Undress
AI-powered app for creating realistic nude photos
AI Clothes Remover
Online AI tool for removing clothes from photos.
Undress AI Tool
Undress images for free
Clothoff.io
AI clothes remover
Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!
Hot Article
Hot Tools
Notepad++7.3.1
Easy-to-use and free code editor
SublimeText3 Chinese version
Chinese version, very easy to use
Zend Studio 13.0.1
Powerful PHP integrated development environment
Dreamweaver CS6
Visual web development tools
SublimeText3 Mac version
God-level code editing software (SublimeText3)
Hot Topics
1387
52
Bytedance Cutting launches SVIP super membership: 499 yuan for continuous annual subscription, providing a variety of AI functions
Jun 28, 2024 am 03:51 AM
This site reported on June 27 that Jianying is a video editing software developed by FaceMeng Technology, a subsidiary of ByteDance. It relies on the Douyin platform and basically produces short video content for users of the platform. It is compatible with iOS, Android, and Windows. , MacOS and other operating systems. Jianying officially announced the upgrade of its membership system and launched a new SVIP, which includes a variety of AI black technologies, such as intelligent translation, intelligent highlighting, intelligent packaging, digital human synthesis, etc. In terms of price, the monthly fee for clipping SVIP is 79 yuan, the annual fee is 599 yuan (note on this site: equivalent to 49.9 yuan per month), the continuous monthly subscription is 59 yuan per month, and the continuous annual subscription is 499 yuan per year (equivalent to 41.6 yuan per month) . In addition, the cut official also stated that in order to improve the user experience, those who have subscribed to the original VIP
Context-augmented AI coding assistant using Rag and Sem-Rag
Jun 10, 2024 am 11:08 AM
Improve developer productivity, efficiency, and accuracy by incorporating retrieval-enhanced generation and semantic memory into AI coding assistants. Translated from EnhancingAICodingAssistantswithContextUsingRAGandSEM-RAG, author JanakiramMSV. While basic AI programming assistants are naturally helpful, they often fail to provide the most relevant and correct code suggestions because they rely on a general understanding of the software language and the most common patterns of writing software. The code generated by these coding assistants is suitable for solving the problems they are responsible for solving, but often does not conform to the coding standards, conventions and styles of the individual teams. This often results in suggestions that need to be modified or refined in order for the code to be accepted into the application
Can fine-tuning really allow LLM to learn new things: introducing new knowledge may make the model produce more hallucinations
Jun 11, 2024 pm 03:57 PM
Large Language Models (LLMs) are trained on huge text databases, where they acquire large amounts of real-world knowledge. This knowledge is embedded into their parameters and can then be used when needed. The knowledge of these models is "reified" at the end of training. At the end of pre-training, the model actually stops learning. Align or fine-tune the model to learn how to leverage this knowledge and respond more naturally to user questions. But sometimes model knowledge is not enough, and although the model can access external content through RAG, it is considered beneficial to adapt the model to new domains through fine-tuning. This fine-tuning is performed using input from human annotators or other LLM creations, where the model encounters additional real-world knowledge and integrates it
Posthumous work of the OpenAI Super Alignment Team: Two large models play a game, and the output becomes more understandable
Jul 19, 2024 am 01:29 AM
If the answer given by the AI model is incomprehensible at all, would you dare to use it? As machine learning systems are used in more important areas, it becomes increasingly important to demonstrate why we can trust their output, and when not to trust them. One possible way to gain trust in the output of a complex system is to require the system to produce an interpretation of its output that is readable to a human or another trusted system, that is, fully understandable to the point that any possible errors can be found. For example, to build trust in the judicial system, we require courts to provide clear and readable written opinions that explain and support their decisions. For large language models, we can also adopt a similar approach. However, when taking this approach, ensure that the language model generates
To provide a new scientific and complex question answering benchmark and evaluation system for large models, UNSW, Argonne, University of Chicago and other institutions jointly launched the SciQAG framework
Jul 25, 2024 am 06:42 AM
Editor |ScienceAI Question Answering (QA) data set plays a vital role in promoting natural language processing (NLP) research. High-quality QA data sets can not only be used to fine-tune models, but also effectively evaluate the capabilities of large language models (LLM), especially the ability to understand and reason about scientific knowledge. Although there are currently many scientific QA data sets covering medicine, chemistry, biology and other fields, these data sets still have some shortcomings. First, the data form is relatively simple, most of which are multiple-choice questions. They are easy to evaluate, but limit the model's answer selection range and cannot fully test the model's ability to answer scientific questions. In contrast, open-ended Q&A
SOTA performance, Xiamen multi-modal protein-ligand affinity prediction AI method, combines molecular surface information for the first time
Jul 17, 2024 pm 06:37 PM
Editor | KX In the field of drug research and development, accurately and effectively predicting the binding affinity of proteins and ligands is crucial for drug screening and optimization. However, current studies do not take into account the important role of molecular surface information in protein-ligand interactions. Based on this, researchers from Xiamen University proposed a novel multi-modal feature extraction (MFE) framework, which for the first time combines information on protein surface, 3D structure and sequence, and uses a cross-attention mechanism to compare different modalities. feature alignment. Experimental results demonstrate that this method achieves state-of-the-art performance in predicting protein-ligand binding affinities. Furthermore, ablation studies demonstrate the effectiveness and necessity of protein surface information and multimodal feature alignment within this framework. Related research begins with "S
SK Hynix will display new AI-related products on August 6: 12-layer HBM3E, 321-high NAND, etc.
Aug 01, 2024 pm 09:40 PM
According to news from this site on August 1, SK Hynix released a blog post today (August 1), announcing that it will attend the Global Semiconductor Memory Summit FMS2024 to be held in Santa Clara, California, USA from August 6 to 8, showcasing many new technologies. generation product. Introduction to the Future Memory and Storage Summit (FutureMemoryandStorage), formerly the Flash Memory Summit (FlashMemorySummit) mainly for NAND suppliers, in the context of increasing attention to artificial intelligence technology, this year was renamed the Future Memory and Storage Summit (FutureMemoryandStorage) to invite DRAM and storage vendors and many more players. New product SK hynix launched last year
Laying out markets such as AI, GlobalFoundries acquires Tagore Technology's gallium nitride technology and related teams
Jul 15, 2024 pm 12:21 PM
According to news from this website on July 5, GlobalFoundries issued a press release on July 1 this year, announcing the acquisition of Tagore Technology’s power gallium nitride (GaN) technology and intellectual property portfolio, hoping to expand its market share in automobiles and the Internet of Things. and artificial intelligence data center application areas to explore higher efficiency and better performance. As technologies such as generative AI continue to develop in the digital world, gallium nitride (GaN) has become a key solution for sustainable and efficient power management, especially in data centers. This website quoted the official announcement that during this acquisition, Tagore Technology’s engineering team will join GLOBALFOUNDRIES to further develop gallium nitride technology. G
