


For artificial intelligence, humans really need to be in awe! The warning from the father of ChatGPT is worth heeding
“Reducing the risk of artificial intelligence exterminating humanity should be a global priority alongside other society-scale risks, such as pandemics and nuclear war.”
Like a bucket of cold water poured down, including top experts in the field of artificial intelligence, "AI godfather" figures, industry tycoons such as Open AI CEO Sam Altman and DeepMind CEO Demis Hassabis, as well as hundreds of practitioners co-signed an open letter.
In the letter, they called on governments and the public to be sufficiently cautious about artificial intelligence. They were worried that with the rapid advancement of AI technology, it may pose an existential threat to mankind.
This is reminiscent of Musk’s warnings and appeals. He hopes to suspend the development and experiments of large-scale artificial intelligence. “Advanced artificial intelligence may represent a profound change in the history of life on earth and should be treated with corresponding attention.” and resource planning and management.”
The two heavyweight warnings before and after force people to seriously think about how we should face the arrival of the era of artificial intelligence.
Regarding AI, everyone is actually on the same starting line
Although ChatGPT launched by Open AI has taken the world by storm and led people's enthusiasm for artificial intelligence, the industry has believed that AI has indeed entered the "iPhone moment."
In other words, just as Steve Jobs launched the iPhone and officially opened the era of mobile Internet, mankind is about to enter (or has already) entered the era of artificial intelligence.
However, what is different from the mobile Internet era is that it is still difficult to say who is the leader. Regardless of the United States, China, or Europe, no one dares to say that they are Steve Jobs, because no one has launched an iPhone. An epoch-making product.
In this turbulent era, although OpenAI is half a step ahead, it may only be the "pioneer for the king". No company has yet established strong barriers and moats, and players from all walks of life are relatively on the same starting line.
Maybe it won’t take a few years to figure out who the “destiny” is.
The warning from the father of ChatGPT is worth heeding
As the CEO of Open AI, Sam Altman does have feelings that transcend commercial interests. He has emphasized the risks of artificial intelligence many times.
The rapid development of artificial intelligence models such as ChatGPT may pose a potential threat to society and employment. If artificial intelligence goes out of control, it will cause large-scale human death and even species loss, just like pandemics and nuclear wars. risk of extinction.
So, Sam Altman joined many people in calling on the government to strengthen supervision. But the problem is that government agencies often lag behind in supervising new things and new technologies. They don’t know how to supervise. Even many officials don’t know what AI means. What.
Human cognition is a process of continuous improvement. Most people believe it because they see it. But the paradox is that if AI truly poses an existential threat to mankind, it may be too late.
We might as well make a hypothesis, if nuclear technology does not have relevant supervision and review methods, what will human society be like? In a sense, AI technology may be more destructive than nuclear technology.
The pros and cons of artificial intelligence
From the perspective of productivity improvement, artificial intelligence will have a very big effect and will greatly liberate people from heavy physical labor and a lot of low-value mental labor.
Sweeping robots, cooking robots, industrial robots, mining robots, and medical robots can all greatly facilitate people’s lives. AI has great potential in terms of data analysis, image recognition, accuracy and efficiency.
But with the popularization of AI, a large number of repetitive labor jobs will be replaced, many people will be unemployed, and the intrusion of privacy by artificial intelligence is worrying. In addition, news, war, security, law, algorithm discrimination and Ethical and moral challenges (such as the divide between rich and poor).
Kissinger said that humans are not ready yet and that humans need to redefine their relationship with this new species, AI. This opinion indeed deserves the attention and consideration of people from all walks of life.
However, everyone has a big consensus, that is, overall, AI is more beneficial than harmful to human beings, and no one can say that AI technology is strangled in the cradle. It will develop anyway, so the key is development. The contradiction between control and control can achieve its advantages and eliminate its disadvantages.
For artificial intelligence, humans really need to be in awe
In the Internet era, the Internet is full of all kinds of false, negative and harmful information, which brings great challenges to people's ability to judge and distinguish information.
In the era of artificial intelligence, it is difficult to distinguish between true and false. If AI wants to deceive people, it will undoubtedly be easier. In fact, there are already cases of scammers using AI technology to deceive people. When facing relatives and friends on your mobile phone, you can’t Know whether the person is a real person or a liar pretending to be a real person.
In addition, compared with the powerful digital thinking of AI (which is getting stronger and stronger, such as AI-style random fabrication), what are the values and advantages of human thinking? More seriously, in the face of AI, how much room is left for the light of human civilization?
But the AI competition has begun. It seems that not many people are willing to stop and think carefully about the risks of AI. Everyone wants to run faster. As for the so-called safety issues, who cares?
The factors brought by human beings make the future full of uncertainty. Where artificial intelligence will push humanity depends largely on our current efforts.
The above is the detailed content of For artificial intelligence, humans really need to be in awe! The warning from the father of ChatGPT is worth heeding. 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

AI Hentai Generator
Generate AI Hentai for free.

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



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

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

To learn more about AIGC, please visit: 51CTOAI.x Community https://www.51cto.com/aigc/Translator|Jingyan Reviewer|Chonglou is different from the traditional question bank that can be seen everywhere on the Internet. These questions It requires thinking outside the box. Large Language Models (LLMs) are increasingly important in the fields of data science, generative artificial intelligence (GenAI), and artificial intelligence. These complex algorithms enhance human skills and drive efficiency and innovation in many industries, becoming the key for companies to remain competitive. LLM has a wide range of applications. It can be used in fields such as natural language processing, text generation, speech recognition and recommendation systems. By learning from large amounts of data, LLM is able to generate text

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

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

Machine learning is an important branch of artificial intelligence that gives computers the ability to learn from data and improve their capabilities without being explicitly programmed. Machine learning has a wide range of applications in various fields, from image recognition and natural language processing to recommendation systems and fraud detection, and it is changing the way we live. There are many different methods and theories in the field of machine learning, among which the five most influential methods are called the "Five Schools of Machine Learning". The five major schools are the symbolic school, the connectionist school, the evolutionary school, the Bayesian school and the analogy school. 1. Symbolism, also known as symbolism, emphasizes the use of symbols for logical reasoning and expression of knowledge. This school of thought believes that learning is a process of reverse deduction, through existing

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

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
