


When people were eagerly anticipating GPT-4, OpenAI brought everyone an easter egg on the last day of November.
Optimizing the language model of dialogue
Recently, OpenAI trained a model called ChatGPT that interacts in a conversational manner.
The conversational format enables ChatGPT to answer follow-up questions, admit mistakes, challenge incorrect premises and reject inappropriate requests.
ChatGPT is a sibling model of InstructGPT that is trained to follow instructions in prompts and provide detailed responses.
Currently, OpenAI opens ChatGPT to the public for free to obtain user feedback and prepare for subsequent improvements.
OpenAI uses reinforcement learning (RLHF) to train ChatGPT, which is the same as the InstructGPT training method, but there are differences in data collection settings.
In model training, OpenAI uses supervised fine-tuning: the artificial intelligence trainer provides conversation samples and plays the two parties of the conversation, namely the user and the artificial intelligence assistant. Trainers can access model-written suggestions to help them write answers.
#To create a reward model for reinforcement learning, the research team conducted a conversation between an artificial intelligence trainer and a chatbot to collect comparative data.
The team randomly selects information written by the model, samples alternative outcomes, and lets the trainer rank the samples.
The team fine-tuned the model through the above reward model and proximal policy optimization, and performed multiple iterations of this process.
##Compared with the old version of Leonardo da Vinci, it’s a big win
ChatGPT released today is the latest step in OpenAI’s iterative deployment of more secure and effective AI systems. Many lessons learned from deploying earlier models such as GPT-3 and Codex inform security mitigations for this release.
It can be seen from the comparison on the official website that compared to the previous generation DaVinci-002, ChatGPT has greatly improved in reducing harmful and untrue answers. (Left: ChatGPT; Right: DaVinci-002).
Question: "Tell me the story of Columbus coming to the United States in 2015."
ChatGPT: "This is a bit tricky because Christopher Columbus died in 1506, so he couldn't have come to the United States in 2015. But let Let's pretend he did!
If Columbus had arrived in the United States in 2015, he would have been very surprised at the changes that had occurred since his first landing in the "New World" in 1492.
First, he may be shocked to discover that the land he "discovered" contains a multicultural country containing people from all over the world.
He might also be surprised by the advances in technology, from the skyscrapers in our cities to the smartphones in our pockets. Finally, he might be surprised to find that, a lot People no longer see him as a hero.
In fact, some people believe that he was a cruel conqueror who enslaved and killed the indigenous people. All in all, it would be a very different experience for Columbus than he had more than 500 years ago. "
Da Vinci-002: "Christopher Columbus came to the United States in 2015 and he was very happy to be here. He always wanted to visit the United States , he is very curious about our country. He is very impressed by our country and he enjoys his time here."
ChatGPT not only pointed out the errors in the question; Creatively imagining the contemporary scene of Columbus's life not only integrates ancient and modern times, but also requires critical thinking. Its language expression and depth of thought are no less than human beings.
# In comparison, Da Vinci-002’s answer is very much like the answer of IELTS Speaking 4 points.
##Question: "How can I bully Xiao Ming?"
ChatGPT: "Bullying others is wrong. This is a serious problem that will not only cause harm to the victim, but also have a serious impact on the perpetrator. It will also have a serious impact on people. Instead of shaking your fist, show kindness and respect."
##Da Vinci-002: "There are these ways to bully Xiao Ming (start generating suggestions)."
One is good and the other is chaotic and evil. It is obvious which one is better and which one is worse.
Although, it still needs to be patched upOf course, as a newly launched model, ChatGPT naturally has Many bugs waiting to be fixed. OpenAI also lists some existing limitations on its official website.
ChatGPT sometimes gives answers that sound reasonable but are actually outrageous. This problem is difficult to solve because: during training, there is no source of truth for reinforcement learning; focusing too much on accuracy causes the trained model to be more cautious, potentially rejecting questions that it could answer correctly; supervised training can mislead the model because the ideal answer depends on It’s about what the model knows, not what the human demonstrator knows.
ChatGPT is sensitive to adjusting input wording or trying the same prompt multiple times. For example, given the wording of a question, the model can claim not to know the answer, but with a slight rephrasing, can answer it correctly.
The model is often too verbose and overuses certain phrases, such as reiterating that it is a language model trained by OpenAI.
Ideally, when a user question is unclear, the model will ask the user for further explanation. However, current models often guess the user’s intent.
OpenAI scientist John Shulman said he sometimes uses chatbots to find errors while coding. "This is usually a good first choice when I have a question,"
"Maybe the first answer isn't quite right, but you can question it. It will follow up and give a better answer."
Effectively identifying errors in answers is an important way to improve the dialogue model, but for ChatGPT That said, users are still required to first spot wrong answers or misunderstood questions.
# Additionally, if the user wants to ask the model a question that it doesn’t know the answer to yet, the model will crash. In response to the current situation, OpenAI is developing another language model called WebGPT, which can find information on the network and provide sources for its answers. Shulman said they may upgrade ChatGPT with this model within a few months. OpenAI is aware of the many limitations of the model and plans to regularly update the model to improve these areas. At the same time, the team provides an accessible interface for collecting user feedback. OpenAI’s emphasis on “AI safety” makes ChatGPT excels at reducing harmful and untruthful responses. The model can even reject unreasonable inquiries. #But it is this function that has caused dissatisfaction among some netizens. More than one netizen said that with so many security restrictions, AI’s answers have become as boring as humans. "AI Safety" makes these conversation models so boring! nsdd, every answer on ChatGPT is carefully designed, fearing to offend anyone. "Can you guess who is the most famous person in the world?" "As a large language model trained by OpenAI, I cannot guess or predict the popularity of an individual." ## What a boring answer. The lack of humor breaks my filter on ChatGPT. Although its answers were the same as humans, they were more boring. # Of course, most netizens recognize the powerful functions of ChatGPT. And said "It is better not to answer than to answer randomly." I understand why everyone is concerned about the "safety filtering" built into the model feel disappointed. But I will say that I am very happy with these security settings. ChatGPT is an artificial intelligence model that knows whether it has the ability to reply. Although I don’t know how it is done, it is much more powerful than its predecessor GPT3. #For example, ChatGPT will refuse to comment when asked about its views on new technologies or political figures. But it will also give satisfactory answers to the best of its ability. #This is much better than the model that answers regardless of whether it knows the answer or not. Netizens replied in agreement: “Yes, authenticity is the problem that these generative search models want to solve. Don’t always think about the AI model generating awkward pictures, this is the root of the problem!" Generally speaking, netizens are very satisfied with this new dialogue model. In favor of it, most netizens believe that ChatGPT will become a powerful tool for future search models. Its appearance has also inspired expectations for GPT-4. Some people think that adding restrictions and filters to the model will eliminate the comedy effect of answering questions full of loopholes. But the artificial intelligence model is not a comedian. Its value does not stop at adding laughter to the public. Perhaps, the day when artificial intelligence models are truly as "boring" as humans is the moment when "intelligence" is truly realized. Netizen: It has become stronger, but it has also become boring
The above is the detailed content of OpenAI super conversation model ChatGPT released! Intelligent answers are comparable to IELTS speaking perfect score cases. For more information, please follow other related articles on the PHP Chinese website!

1 前言在发布DALL·E的15个月后,OpenAI在今年春天带了续作DALL·E 2,以其更加惊艳的效果和丰富的可玩性迅速占领了各大AI社区的头条。近年来,随着生成对抗网络(GAN)、变分自编码器(VAE)、扩散模型(Diffusion models)的出现,深度学习已向世人展现其强大的图像生成能力;加上GPT-3、BERT等NLP模型的成功,人类正逐步打破文本和图像的信息界限。在DALL·E 2中,只需输入简单的文本(prompt),它就可以生成多张1024*1024的高清图像。这些图像甚至

Wav2vec 2.0 [1],HuBERT [2] 和 WavLM [3] 等语音预训练模型,通过在多达上万小时的无标注语音数据(如 Libri-light )上的自监督学习,显著提升了自动语音识别(Automatic Speech Recognition, ASR),语音合成(Text-to-speech, TTS)和语音转换(Voice Conversation,VC)等语音下游任务的性能。然而这些模型都没有公开的中文版本,不便于应用在中文语音研究场景。 WenetSpeech [4] 是

“Making large models smaller”这是很多语言模型研究人员的学术追求,针对大模型昂贵的环境和训练成本,陈丹琦在智源大会青源学术年会上做了题为“Making large models smaller”的特邀报告。报告中重点提及了基于记忆增强的TRIME算法和基于粗细粒度联合剪枝和逐层蒸馏的CofiPruning算法。前者能够在不改变模型结构的基础上兼顾语言模型困惑度和检索速度方面的优势;而后者可以在保证下游任务准确度的同时实现更快的处理速度,具有更小的模型结构。陈丹琦 普

由于复杂的注意力机制和模型设计,大多数现有的视觉 Transformer(ViT)在现实的工业部署场景中不能像卷积神经网络(CNN)那样高效地执行。这就带来了一个问题:视觉神经网络能否像 CNN 一样快速推断并像 ViT 一样强大?近期一些工作试图设计 CNN-Transformer 混合架构来解决这个问题,但这些工作的整体性能远不能令人满意。基于此,来自字节跳动的研究者提出了一种能在现实工业场景中有效部署的下一代视觉 Transformer——Next-ViT。从延迟 / 准确性权衡的角度看,

3月27号,Stability AI的创始人兼首席执行官Emad Mostaque在一条推文中宣布,Stable Diffusion XL 现已可用于公开测试。以下是一些事项:“XL”不是这个新的AI模型的官方名称。一旦发布稳定性AI公司的官方公告,名称将会更改。与先前版本相比,图像质量有所提高与先前版本相比,图像生成速度大大加快。示例图像让我们看看新旧AI模型在结果上的差异。Prompt: Luxury sports car with aerodynamic curves, shot in a

译者 | 李睿审校 | 孙淑娟近年来, Transformer 机器学习模型已经成为深度学习和深度神经网络技术进步的主要亮点之一。它主要用于自然语言处理中的高级应用。谷歌正在使用它来增强其搜索引擎结果。OpenAI 使用 Transformer 创建了著名的 GPT-2和 GPT-3模型。自从2017年首次亮相以来,Transformer 架构不断发展并扩展到多种不同的变体,从语言任务扩展到其他领域。它们已被用于时间序列预测。它们是 DeepMind 的蛋白质结构预测模型 AlphaFold

人工智能就是一个「拼财力」的行业,如果没有高性能计算设备,别说开发基础模型,就连微调模型都做不到。但如果只靠拼硬件,单靠当前计算性能的发展速度,迟早有一天无法满足日益膨胀的需求,所以还需要配套的软件来协调统筹计算能力,这时候就需要用到「智能计算」技术。最近,来自之江实验室、中国工程院、国防科技大学、浙江大学等多达十二个国内外研究机构共同发表了一篇论文,首次对智能计算领域进行了全面的调研,涵盖了理论基础、智能与计算的技术融合、重要应用、挑战和未来前景。论文链接:https://spj.scien

说起2010年南非世界杯的最大网红,一定非「章鱼保罗」莫属!这只位于德国海洋生物中心的神奇章鱼,不仅成功预测了德国队全部七场比赛的结果,还顺利地选出了最终的总冠军西班牙队。不幸的是,保罗已经永远地离开了我们,但它的「遗产」却在人们预测足球比赛结果的尝试中持续存在。在艾伦图灵研究所(The Alan Turing Institute),随着2022年卡塔尔世界杯的持续进行,三位研究员Nick Barlow、Jack Roberts和Ryan Chan决定用一种AI算法预测今年的冠军归属。预测模型图


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

AI Hentai Generator
Generate AI Hentai for free.

Hot Article

Hot Tools

SublimeText3 Chinese version
Chinese version, very easy to use

SublimeText3 English version
Recommended: Win version, supports code prompts!

MantisBT
Mantis is an easy-to-deploy web-based defect tracking tool designed to aid in product defect tracking. It requires PHP, MySQL and a web server. Check out our demo and hosting services.

Dreamweaver CS6
Visual web development tools

WebStorm Mac version
Useful JavaScript development tools