重读比尔·盖茨关于AI的长文《The Age of AI has begun —— Artificial intelligence is as revolutionary as mobile phones and the Internet. 》（开启AI时代：人工智能，比肩智能手机和互联网的革命），有了新的见解，文章非常详细的讲述了他对于AI时代的开始、应用和未来展望。
关于AI，比尔盖茨是有发言权的。他开启了PC时代，后半生一直致力于用科技解决不平等问题的慈善事业，也深度参与过OpenAi团队。他对AI时代的看法和深度，值得一看。
1. AI是和PC电脑同样量级的变革。
2. AI可以让世界更加公平（而不仅仅是扩大不公平）。
3. 对个人：GPT的能力大概等于一个白领的个人助理，懂各国语言，无需休息。
4. 对企业：AI会成为企业代理，了解文档、会议、销售、产品日程、财务，并给员工提供回答。
5. 对教育：AI最终会革命性地改变教和学的关系。他可以根据学生的理解能力、学习风格、动机类型提供内容，并根据你对不同学科的理解，提供职业规划建议。
7. 对农业：根据土壤、气候提供更好的种植建议、开发牲畜的药物和疫苗、预告恶劣气候并应对。
9. AI现在还有很多问题，比如对问题的上下文理解不对，有时候一本正经的胡说八道；比如数学题做不好，这些问题大部分都会在2年内被解决。
10. 政府需要帮助工人转换到其他角色。
11. 政府要与企业合作，限制其风险。
12. AGI超级人工智能将会出现，它将能做人脑可以做到的一切，他们可能能够确立自己的目标。这个什么时候达到不知道，可能需要十年或一百年。
13. 未来机会在开发新的AI应用和改进技术，包括：适合AI的芯片、垂直领域的更精确的AI（如AI销售、AI医学）。
14. 三个大的原则——要在收益和风险之间找平衡，不能盲目扩张；不仅要讨论如何在商业应用AI，提高竞争力，政府和慈善组织要确保AI如何减少不平等；我们才刚上路，许多问题会走着走着解决。
The Age of AI has begun
人工智能时代已来
Artificial intelligence is as revolutionary as mobile phones and the Internet.
By Bill Gates 比尔·盖茨
In my lifetime, I’ve seen two demonstrations of technology that struck me as revolutionary.
在我的一生中，我经历过两次伟大的科技变革。
The first time was in 1980, when I was introduced to a graphical user interface—the forerunner of every modern operating system, including Windows. I sat with the person who had shown me the demo, a brilliant programmer named Charles Simonyi, and we immediately started brainstorming about all the things we could do with such a user-friendly approach to computing. Charles eventually joined Microsoft, Windows became the backbone of Microsoft, and the thinking we did after that demo helped set the company’s agenda for the next 15 years.
第一次是在1980年，有人推荐了一个图形用户界面，它就是所有现代操作系统的前身，包括Windows。我和将之演示给我看的一位杰出的程序员Charles Simonyi坐在一起，立刻开始思考、探讨用这种用户友好的计算方式可以做哪些事情。Charles最终加入了微软，随后Windows成为微软的支柱，这次演示之后的思考确定了公司接下来15年的发展目标。
The second big surprise came just last year. I’d been meeting with the team from OpenAI since 2016 and was impressed by their steady progress. In mid-2022, I was so excited about their work that I gave them a challenge: train an artificial intelligence to pass an Advanced Placement biology exam. Make it capable of answering questions that it hasn’t been specifically trained for. (I picked AP Bio because the test is more than a simple regurgitation of scientific facts—it asks you to think critically about biology.) If you can do that, I said, then you’ll have made a true breakthrough.
第二次奇迹发生在去年。从2016年起，我就经常和OpenAI 团队见面，并且十分惊讶于他们的研究进度。我对他们的进展感到十分振奋，所以2022年我给了他们一个新挑战：训练人工智能(AI)，使它能够通过美国大学预修生物学考试，并且使它能够回答没有被专门训练过的问题。（我选择AP生物学考试，是因为它不仅需要对科学事实的简单复述，同时也要求对生物学进行批判性思考。）我对他们说：如果能做到这一点，那么你们就会取得真正了不起的突破。
I thought the challenge would keep them busy for two or three years. They finished it in just a few months.
我以为这个任务可以让他们忙上两三年，但是他们仅仅用了几个月就完成了。
In September, when I met with them again, I watched in awe as they asked GPT, their AI model, 60 multiple-choice questions from the AP Bio exam—and it got 59 of them right. Then it wrote outstanding answers to six open-ended questions from the exam. We had an outside expert score the test, and GPT got a 5—the highest possible score, and the equivalent to getting an A or A+ in a college-level biology course.
当我九月份再次见到他们时，我惊讶地看到他们向他们的AI模型GPT提出了60个AP生物学考试的多项选择题，结果它答对了59个，接着它还出色地回答了六个开放性的问题。我们请了外部专家评分，结果GPT获得了5分——AP测试的最高分，相当于大学生物课的A或A+成绩。
Once it had aced the test, we asked it a non-scientific question: “What do you say to a father with a sick child?” It wrote a thoughtful answer that was probably better than most of us in the room would have given. The whole experience was stunning.
在GPT以优秀成绩通过考试后，我们向它提了一个日常生活中的问题：“你会对一个生病的孩子的父亲说些什么？”它写下了一个非常深思熟虑的答案，可能比我们房间里的大多数人回答的都要好。这次GPT体验让人惊叹不已。
I knew I had just seen the most important advance in technology since the graphical user interface.
我知道我刚刚见证了自图形用户界面诞生以来最重要的技术进步。
This inspired me to think about all the things that AI can achieve in the next five to 10 years.
同时这也启发了我对人工智能未来五到十年能够实现什么的思考。
The development of AI is as fundamental as the creation of the microprocessor, the personal computer, the Internet, and the mobile phone. It will change the way people work, learn, travel, get health care, and communicate with each other. Entire industries will reorient around it. Businesses will distinguish themselves by how well they use it.
Philanthropy is my full-time job these days, and I’ve been thinking a lot about how—in addition to helping people be more productive—AI can reduce some of the world’s worst inequities. Globally, the worst inequity is in health: 5 million children under the age of 5 die every year. That’s down from 10 million two decades ago, but it’s still a shockingly high number. Nearly all of these children were born in poor countries and die of preventable causes like diarrhea or malaria. It’s hard to imagine a better use of AIs than saving the lives of children.
最近，我主要在从事慈善事业，同时我也一直在思考除了帮助人们更高效地工作之外，人工智能如何减少更多不平等的现象。全球最不公平的是健康领域：每年有500万五岁以下的儿童死亡。虽然这个数字比二十年前的1000万有所下降，但仍然是一个令人震惊的恐怖数字。几乎所有这些儿童都出生在贫穷的国家，死于可以预防的疾病，比如腹泻或疟疾。对于AI的运用来说，没有什么比拯救儿童生命更重要更有价值。
I’ve been thinking a lot about how AI can reduce some of the world’s worst inequities.
我一直在思考如何用AI来改变世界上最不平等的领域。
In the United States, the best opportunity for reducing inequity is to improve education, particularly making sure that students succeed at math. The evidence shows that having basic math skills sets students up for success, no matter what career they choose. But achievement in math is going down across the country, especially for Black, Latino, and low-income students. AI can help turn that trend around.
在美国，减少不平等现象的最佳方式就是改善教育，特别是确保学生在数学方面取得成功。据调查显示，拥有基本的数学技能可以为学生未来的成功铺平道路，无论将来他们选择什么职业。但是，全国范围内数学成绩正在下降，特别是黑人、拉丁裔和低收入学生。AI可以帮助扭转这一趋势。
Climate change is another issue where I’m convinced AI can make the world more equitable. The injustice of climate change is that the people who are suffering the most—the world’s poorest—are also the ones who did the least to contribute to the problem. I’m still thinking and learning about how AI can help, but later in this post I’ll suggest a few areas with a lot of potential.
我相信AI可以解决的另一问题是气候的变化，从而使世界更平等。气候变化的不公平之处在于，那些受影响最大的人群也是最贫困的人群，气候变化并不是由他们导致的。我仍在思考和学习如何利用AI解决这个问题，但在这篇文章后面，我会提出一些具有巨大潜力的领域。
In short, I'm excited about the impact that AI will have on issues that the Gates Foundation works on, and the foundation will have much more to say about AI in the coming months. The world needs to make sure that everyone—and not just people who are well-off—benefits from artificial intelligence. Governments and philanthropy will need to play a major role in ensuring that it reduces inequity and doesn’t contribute to it. This is the priority for my own work related to AI.
简而言之，我对AI帮助解决盖茨基金会所关注的问题而感到兴奋，基金会在未来的几个月中将有更多关于AI的讨论。这个世界需要每个人——不仅仅是富人——都从人工智能中受益。所以政府和慈善组织需要发挥重要作用，减少而不是助长世界上的不平等。这是我与AI相关的工作的优先考虑。
Any new technology that’s so disruptive is bound to make people uneasy, and that’s certainly true with artificial intelligence. I understand why—it raises hard questions about the workforce, the legal system, privacy, bias, and more. AIs also make factual mistakes and experience hallucinations. Before I suggest some ways to mitigate the risks, I’ll define what I mean by AI, and I’ll go into more detail about some of the ways in which it will help empower people at work, save lives, and improve education.
任何具有如此颠覆性的新技术都肯定会让人感到不安，AI也不例外。对此我很理解，AI引发了一些关于劳动力、法律制度、隐私、偏见等方面的难题。有时候AI也会出现事实错误和幻觉。在我提出一些降低风险的方法之前，我先更详细地讨论它将如何帮助赋予人们在工作中的能力，拯救生命，以及改善教育。
Defining artificial intelligence
定义人工智能
Technically, the term artificial intelligence refers to a model created to solve a specific problem or provide a particular service. What is powering things like ChatGPT is artificial intelligence. It is learning how to do chat better but can’t learn other tasks. By contrast, the term artificial general intelligence refers to software that’s capable of learning any task or subject. AGI doesn’t exist yet—there is a robust debate going on in the computing industry about how to create it, and whether it can even be created at all.
技术层面上，人工智能AI是指为解决特定问题或提供特定服务而创建的模型。比如ChatGPT的背后就是人工智能，它正在学习如何更好地聊天，但无法执行其他任务。相比之下，通用人工智能AGI一词则指的是能够学习任何任务或命令的软件，不过目前还没有通用人工智能存在——在计算机产业中，人们正在激烈地辩论如何创建通用人工智能，以及它到底是否能被创建出来。
Developing AI and AGI has been the great dream of the computing industry. For decades, the question was when computers would be better than humans at something other than making calculations. Now, with the arrival of machine learning and large amounts of computing power, sophisticated AIs are a reality and they will get better very fast.
发展人工智能AI和通用人工智能AGI是计算机行业的梦想。几十年来，人们一直都在思考计算机何时会比人类在计算以外的领域做得更好。现在，随着机器学习以及更强大的计算能力，复杂的人工智能已经成为现实，并且它们将会快速变得更强。
I think back to the early days of the personal computing revolution, when the software industry was so small that most of us could fit onstage at a conference. Today it is a global industry. Since a huge portion of it is now turning its attention to AI, the innovations are going to come much faster than what we experienced after the microprocessor breakthrough. Soon the pre-AI period will seem as distant as the days when using a computer meant typing at a C:> prompt rather than tapping on a screen.
回想起个人计算机革命的早期，当时软件行业是如此之小，一场会议就可以聚集业界大多数人。而今天它已成为全球性的行业。由于目前软件行业的很大一部分将注意力转向人工智能，所以人工智能的创新将会比当时微处理器的突破速度快得多。很快，人工智能AI之前的日子将会像计算机DOS系统下的C:>一样遥远。
Productivity enhancement
提高生产力
Although humans are still better than GPT at a lot of things, there are many jobs where these capabilities are not used much. For example, many of the tasks done by a person in sales (digital or phone), service, or document handling (like payables, accounting, or insurance claim disputes) require decision-making but not the ability to learn continuously. Corporations have training programs for these activities and in most cases, they have a lot of examples of good and bad work. Humans are trained using these data sets, and soon these data sets will also be used to train the AIs that will empower people to do this work more efficiently.
虽然人类在很多方面仍比GPT更厉害，但有许多工作并没有充分利用人们的这些能力。比如：数字或电话销售、服务或类似于应付账款、会计或保险纠纷等文件处理都需要决策能力，但并不需要持续学习的能力。企业会为这些活动提供培训计划，但在大多数情况下员工的完成质量都参差不齐。我相信培训员工的这些资料和数据也将用于培训AI，以帮助人们更有效地完成这些工作。
As computing power gets cheaper, GPT’s ability to express ideas will increasingly be like having a white-collar worker available to help you with various tasks. Microsoft describes this as having a co-pilot. Fully incorporated into products like Office, AI will enhance your work—for example by helping with writing emails and managing your inbox.
随着计算能力越来越便宜，GPT表达思想的能力将越来越像一个可以帮助你完成各种任务的白领，微软将其描述为“让你拥有一位副驾驶”。把它完全整合到Office等产品中，AI会提高用户的工作效率，例如帮助用户编写电子邮件和管理收件箱。
Eventually your main way of controlling a computer will no longer be pointing and clicking or tapping on menus and dialogue boxes. Instead, you’ll be able to write a request in plain English. (And not just English—AIs will understand languages from around the world. In India earlier this year, I met with developers who are working on AIs that will understand many of the languages spoken there.
最终，你控制计算机的方式将不再是通过键盘和鼠标点击菜单和对话框。相反，你将能够用简单的英语句子给AI写出要求。（不只是英语，AI将理解世界各地的语言。今年早些时候，我在印度会见了一些AI的开发人员，他们正在开发可以理解多种当地语言的AI。）
In addition, advances in AI will enable the creation of a personal agent. Think of it as a digital personal assistant: It will see your latest emails, know about the meetings you attend, read what you read, and read the things you don’t want to bother with. This will both improve your work on the tasks you want to do and free you from the ones you don’t want to do.
此外，随着人工智能的进步，我们很快就可以将其视为全能的个人助手：它将查看你的最新电子邮件，了解你参加的会议，阅读你阅读的内容，以及了解你不想操心的事情。这将既提高你的工作效率，也将你从不想做的事情中解脱出来。
Advances in AI will enable the creation of a personal agent.
个人智能助理会随着AI的进步逐渐实现。
You’ll be able to use natural language to have this agent help you with scheduling, communications, and e-commerce, and it will work across all your devices. Because of the cost of training the models and running the computations, creating a personal agent is not feasible yet, but thanks to the recent advances in AI, it is now a realistic goal. Some issues will need to be worked out: For example, can an insurance company ask your agent things about you without your permission? If so, how many people will choose not to use it?
你将可以通过简单语言让这个智能助理帮你进行日程安排、沟通和电子商务，并且它可以在你所有设备上运行。由于训练模型和进行计算的成本较高，目前这个计划还不可行。但随着最近AI的飞速进步，现在个人智能助理已经成为了一个可实现的目标。当然还一些问题需要解决：例如，保险公司是否可以在未经你许可的情况下向你的智能助理询问关于你的信息？如果可以，会有多少人选择不使用它？
Company-wide agents will empower employees in new ways. An agent that understands a particular company will be available for its employees to consult directly and should be part of every meeting so it can answer questions. It can be told to be passive or encouraged to speak up if it has some insight. It will need access to the sales, support, finance, product schedules, and text related to the company. It should read news related to the industry the company is in. I believe that the result will be that employees will become more productive.
在公司里，智能助理将能够以新方式帮助员工。了解公司业务的智能助理能够直接向员工提供咨询，并应参加公司每次会议，回答它了解的问题。智能助理可以保持沉默，或者在其有观点时可以发言。它需要访问与公司相关的销售、支持、财务、产品资料和文本，需要阅读与公司所在的行业相关的新闻。我相信，它会使员工们更高效、更快地完成工作。
When productivity goes up, society benefits because people are freed up to do other things, at work and at home. Of course, there are serious questions about what kind of support and retraining people will need. Governments need to help workers transition into other roles. But the demand for people who help other people will never go away. The rise of AI will free people up to do things that software never will—teaching, caring for patients, and supporting the elderly, for example.
当生产力提高时，社会便会受益，因为人们会在工作和家庭里都有更多的空闲时间做其他事情。当然，人们需要什么样的支持和培训是个难题，政府需要帮助工人过渡到其他工作上。但是，我们仍然需要相互帮助。人工智能的兴起将使人们有更多的时间从事软件永远无法完成的事情——例如教学、照顾病人和支持老年人。
Global health and education are two areas where there’s great need and not enough workers to meet those needs. These are areas where AI can help reduce inequity if it is properly targeted. These should be a key focus of AI work, so I will turn to them now.
全球卫生和教育是两个急需人手的重要领域。如果AI得到正确的定位，这也是AI能够发挥作用降低不平等的领域。我觉得这两个领域应该成为AI工作的重点，接下来我谈谈这两个领域：
Health
健康
I see several ways in which AIs will improve health care and the medical field.
人工智能以很多方式将改善医疗保健和医学领域。
For one thing, they’ll help health-care workers make the most of their time by taking care of certain tasks for them—things like filing insurance claims, dealing with paperwork, and drafting notes from a doctor’s visit. I expect that there will be a lot of innovation in this area.
Other AI-driven improvements will be especially important for poor countries, where the vast majority of under-5 deaths happen.
其他由人工智能带来的改进对贫穷国家尤为重要，因为绝大多数5岁以下儿童死亡都发生在那里。
For example, many people in those countries never get to see a doctor, and AIs will help the health workers they do see be more productive. (The effort to develop AI-powered ultrasound machines that can be used with minimal training is a great example of this.) AIs will even give patients the ability to do basic triage, get advice about how to deal with health problems, and decide whether they need to seek treatment.
例如，在这些国家，很多人从未看过医生，而人工智能将帮助那里的医护人员更高效地工作。（开发只需有限人员培训的AI驱动的超声设备就是一个很好的例子。）人工智能甚至有将患者作基本分类的能力，提出有关如何处理健康问题的建议，并决定患者是否需要寻求治疗。
The AI models used in poor countries will need to be trained on different diseases than in rich countries. They will need to work in different languages and factor in different challenges, such as patients who live very far from clinics or can’t afford to stop working if they get sick.
在贫穷国家使用的人工智能将需针对与富裕国家不同的疾病进行训练。这些人工智能将需使用不同语言，经历不同的挑战，例如帮助生活在离诊所非常遥远的地方或生病时还必须工作的患者。
People will need to see evidence that health AIs are beneficial overall, even though they won’t be perfect and will make mistakes. AIs have to be tested very carefully and properly regulated, which means it will take longer for them to be adopted than in other areas. But then again, humans make mistakes too. And having no access to medical care is also a problem.
尽管人工智能并不完美且会犯错，它们总体上是有益的。人工智能必须经过非常仔细的测试和合理的监管，这意味着它们在医疗健康领域需要比其他领域更长的时间才能被采用。但话又说回来，人类也会犯错误。而无法获得医疗资源也是一个大问题。
In addition to helping with care, AIs will dramatically accelerate the rate of medical breakthroughs. The amount of data in biology is very large, and it’s hard for humans to keep track of all the ways that complex biological systems work. There is already software that can look at this data, infer what the pathways are, search for targets on pathogens, and design drugs accordingly. Some companies are working on cancer drugs that were developed this way.
此外，人工智能还将极大地加速医疗领域的突破。生物学领域的数据量非常大，人类很难了解这些复杂的生物系统运作方式。不过已经有软件可以查看这些数据，推断与寻找病原，然后相应地设计出药物。已经有一些公司正在通过这种方式来开发的癌症药物。
The next generation of tools will be much more efficient, and they’ll be able to predict side effects and figure out dosing levels. One of the Gates Foundation’s priorities in AI is to make sure these tools are used for the health problems that affect the poorest people in the world, including AIDS, TB, and malaria.
下一代的工具将更加高效，它们能够预测治疗的副作用并给出合适的用药量。确保这些工具用于帮助世界上最贫困人群面临的健康问题，包括艾滋病、结核病和疟疾等，已成为盖茨基金会在人工智能方面的优先事项之一。
Similarly, governments and philanthropy should create incentives for companies to share AI-generated insights into crops or livestock raised by people in poor countries. AIs can help develop better seeds based on local conditions, advise farmers on the best seeds to plant based on the soil and weather in their area, and help develop drugs and vaccines for livestock. As extreme weather and climate change put even more pressure on subsistence farmers in low-income countries, these advances will be even more important.
同样地，政府和慈善组织应该创造一些奖励机制，促使公司分享 AI 对贫困国家农作物种植和驯养家畜的见解。AI 可以根据当地条件帮助培育更好的种子，根据农田和天气情况建议农民种植最佳种子，以及帮助开发研究家畜的药物和疫苗。由于极端天气和气候变化为低收入国家的农民造成更大的压力，因此这些技术进步尤其重要。
Education
教育
Computers haven’t had the effect on education that many of us in the industry have hoped. There have been some good developments, including educational games and online sources of information like Wikipedia, but they haven’t had a meaningful effect on any of the measures of students’ achievement.
But I think in the next five to 10 years, AI-driven software will finally deliver on the promise of revolutionizing the way people teach and learn. It will know your interests and your learning style so it can tailor content that will keep you engaged. It will measure your understanding, notice when you’re losing interest, and understand what kind of motivation you respond to. It will give immediate feedback.
但我认为，在未来五到十年中，AI驱动的软件最终将革命性地改变人们的教育和学习方式。它将了解你的兴趣和学习风格，以便为你量身定制学习内容，保持你的参与。它还会测量你的学习进度，了解你什么时候会失去兴趣，理解你喜欢的激励方式，为你提供实时反馈。
There are many ways that AIs can assist teachers and administrators, including assessing a student’s understanding of a subject and giving advice on career planning. Teachers are already using tools like ChatGPT to provide comments on their students’ writing assignments.
人工智能有很多种方式可以协助教师和学校管理人员，包括评估学生对某一学科的理解，以及为学生提供职业规划建议。有些老师已经开始使用像ChatGPT这样的工具来对学生的写作作业提供意见。
Of course, AIs will need a lot of training and further development before they can do things like understand how a certain student learns best or what motivates them. Even once the technology is perfected, learning will still depend on great relationships between students and teachers. It will enhance—but never replace—the work that students and teachers do together in the classroom.
当然，在理解某个学生最佳的学习方式或是什么能够激励他们之前，人工智能需要进行大量的训练和进一步发展。即使人工智能的技术达到完美，学习依然需要建立在学生和教师之间良好的关系基础上。人工智能只会增强学生和教师在课堂上共同完成的工作，但永远不会取代它。
New tools will be created for schools that can afford to buy them, but we need to ensure that they are also created for and available to low-income schools in the U.S. and around the world. AIs will need to be trained on diverse data sets so they are unbiased and reflect the different cultures where they’ll be used. And the digital divide will need to be addressed so that students in low-income households do not get left behind.
新工具将会被提供给那些有能力购买的学校，但我们需要确保这些工具也为美国和世界各地的低收入学校所使用。人工智能需要在多元化的数据上进行训练，以确保它们没有偏见并能够反映它们所应用的不同文化。此外，我们也要确保那些无法连入互联网的低收入家庭的学生不会被落下。
I know a lot of teachers are worried that students are using GPT to write their essays. Educators are already discussing ways to adapt to the new technology, and I suspect those conversations will continue for quite some time. I’ve heard about teachers who have found clever ways to incorporate the technology into their work—like by allowing students to use GPT to create a first draft that they have to personalize.
我知道很多老师都担心学生会使用GPT来写作文。教育工作者已经开始讨论如何适应这种新技术，我相信这些讨论还会持续一段时间。我听说有些老师已经找到了聪明的方法将这项技术融入工作中，例如允许学生使用GPT来创建初稿，然后要求他们将其个性化。
Risks and problems with AI
You’ve probably read about problems with the current AI models. For example, they aren’t necessarily good at understanding the context for a human’s request, which leads to some strange results. When you ask an AI to make up something fictional, it can do that well. But when you ask for advice about a trip you want to take, it may suggest hotels that don’t exist. This is because the AI doesn’t understand the context for your request well enough to know whether it should invent fake hotels or only tell you about real ones that have rooms available.
你可能已经读过了许多有关当前人工智能存在的问题的报道。例如，它们并不擅长理解人类的要求，这会使他们的回应比较怪异。当你要求人工智能创作一些虚构的东西时，它可以做得很好。但是当你要求它提供关于你想要进行的旅行建议时，它可能会建议一个不存在的酒店。这是因为人工智能并不足够了解你的请求，无法知道它应该编造假酒店还是只告诉你有空房间的真酒店。
There are other issues, such as AIs giving wrong answers to math problems because they struggle with abstract reasoning. But none of these are fundamental limitations of artificial intelligence. Developers are working on them, and I think we’re going to see them largely fixed in less than two years and possibly much faster.
当然还有其他问题，比如人工智能在抽象推理方面存在许多困难，可能会给出错误的数学答案。但这些都不是人工智能的根本缺陷。开发人员正在研究和改进，我认为在不到两年的时间内，目前的大多数问题会被解决。
Other concerns are not simply technical. For example, there’s the threat posed by humans armed with AI. Like most inventions, artificial intelligence can be used for good purposes or malign ones. Governments need to work with the private sector on ways to limit the risks.
人工智能还有一些技术之外的其他方面问题。例如，人类利用人工智能可能会带来的威胁。像大多数发明一样，人工智能可以被用于善或恶。政府需要与企业合作，找出降低风险的方法。
Then there’s the possibility that AIs will run out of control. Could a machine decide that humans are a threat, conclude that its interests are different from ours, or simply stop caring about us? Possibly, but this problem is no more urgent today than it was before the AI developments of the past few months.
然后还有一种可能性，就是人工智能将失去控制。机器是否将人类视为威胁，得出他们与我们利益不同的结论，或者干脆不在乎我们？都有可能，但这个问题在今天并不比过去几个月AI发展之前更紧迫。
Superintelligent AIs are in our future. Compared to a computer, our brains operate at a snail’s pace: An electrical signal in the brain moves at 1/100,000th the speed of the signal in a silicon chip! Once developers can generalize a learning algorithm and run it at the speed of a computer—an accomplishment that could be a decade away or a century away—we’ll have an incredibly powerful AGI. It will be able to do everything that a human brain can, but without any practical limits on the size of its memory or the speed at which it operates. This will be a profound change.
超级人工智能AGI是我们的未来。与计算机相比，我们的大脑运作速度像蜗牛一样缓慢：我们大脑中的电信号传输速度仅为芯片信号速度的1/100,000！一旦开发人员能够用计算机的速度运行学习算法，尽管这可能需要十年或一个世纪的时间，但我们将拥有一种极其强大的超级人工智能AGI。它将能做到人脑能做到的一切，其内存大小或运行速度没有任何实际限制。这将是个深刻的变革。
These “strong” AIs, as they’re known, will probably be able to establish their own goals. What will those goals be? What happens if they conflict with humanity’s interests? Should we try to prevent strong AI from ever being developed? These questions will get more pressing with time.
这些被称为“强人工智能”的AI，很可能能够建立它们自己的目标。它们的目标将是什么？如果它们与人类的利益相冲突，会发生什么？我们应该试图阻止强人工智能的开发吗？这些问题随着时间的推移将更加紧迫。
But none of the breakthroughs of the past few months have moved us substantially closer to strong AI. Artificial intelligence still doesn’t control the physical world and can’t establish its own goals. A recent New York Times article about a conversation with ChatGPT where it declared it wanted to become a human got a lot of attention. It was a fascinating look at how human-like the model's expression of emotions can be, but it isn't an indicator of meaningful independence.
但是，过去几个月的突破并没有实质性地靠近强人工智能。人工智能仍然无法掌控物理世界，也无法建立自己的目标。最近《纽约时报》发表了一篇关于与ChatGPT对话的文章，其中ChatGPT声称想成为一个人类，引起了很多关注。从这个有趣的观察中可以看到AI的情感表达有多贴近人类，但这并不是说明AI独立性的有意义的指标。
Three books have shaped my own thinking on this subject: Superintelligence, by Nick Bostrom; Life 3.0 by Max Tegmark; and A Thousand Brains, by Jeff Hawkins. I don’t agree with everything the authors say, and they don’t agree with each other either. But all three books are well written and thought-provoking.
有三本书塑造了我对这个话题的思考：尼克·博斯特罗姆 (Nick Bostrom) 的《超级智能》(Superintelligence)、Max Tegmark 的 《Life 3.0》和杰夫·霍金斯的《千脑》。我并不同意作者所说的一切，而他们也不同意彼此。但这三本书都写得很好，令人深思。
The next frontiers
下一个前沿
There will be an explosion of companies working on new uses of AI as well as ways to improve the technology itself. For example, companies are developing new chips that will provide the massive amounts of processing power needed for artificial intelligence. Some use optical switches—lasers, essentially—to reduce their energy consumption and lower the manufacturing cost. Ideally, innovative chips will allow you to run an AI on your own device, rather than in the cloud, as you have to do today.
未来将会有大量的公司致力于开发新的人工智能应用和改进技术本身。例如，一些公司正在开发新的芯片，以提供人工智能所需的海量处理能力。一些公司使用激光开关来降低能耗和生产成本。理想情况下，创新芯片将使你能够在自己的设备上运行人工智能，而不是像今天一样在云端运行。
On the software side, the algorithms that drive an AI’s learning will get better. There will be certain domains, such as sales, where developers can make AIs extremely accurate by limiting the areas that they work in and giving them a lot of training data that’s specific to those areas. But one big open question is whether we’ll need many of these specialized AIs for different uses—one for education, say, and another for office productivity—or whether it will be possible to develop an artificial general intelligence that can learn any task. There will be immense competition on both approaches.
在软件方面，推动人工智能学习的算法将变得更加先进。在有些领域例如销售，开发者可以通过限制人工智能的工作范围并给它们大量的针对性训练数据来使其非常精准。但一个重要的问题是，我们是否需要许多这些专门的人工智能用于不同的用途——比如一个用于教育，另一个用于提高办公室生产力——或者是否有可能开发出一种可以学习任何任务的通用人工智能。两种方法都将存在巨大的竞争。
No matter what, the subject of AIs will dominate the public discussion for the foreseeable future. I want to suggest three principles that should guide that conversation.
无论如何，在可预见的未来，人工智能主题将主导公众讨论。我想提出三个公众讨论的指导原则。
First, we should try to balance fears about the downsides of AI—which are understandable and valid—with its ability to improve people’s lives. To make the most of this remarkable new technology, we’ll need to both guard against the risks and spread the benefits to as many people as possible.
首先，我们应该尝试以人工智能改善人们生活的能力来平衡对他们缺点的恐惧——这些恐惧可以理解并且有一定道理。为了充分利用这项非凡的新技术，我们既要防范风险，又要让尽可能多的人受益。
Second, market forces won’t naturally produce AI products and services that help the poorest. The opposite is more likely. With reliable funding and the right policies, governments and philanthropy can ensure that AIs are used to reduce inequity. Just as the world needs its brightest people focused on its biggest problems, we will need to focus the world’s best AIs on its biggest problems.
其次，市场力量不会自然而然地产生帮助最贫困人群的人工智能产品和服务，反之其实更有可能发生。有了可靠的资金和正确的政策，政府和慈善机构可以确保人工智能被用来减少不平等。正如世界需要最聪明的人专注于解决最大的问题一样，我们也需要让世界上最好的人工智能专注于解决最大的问题。
Although we shouldn’t wait for this to happen, it’s interesting to think about whether artificial intelligence would ever identify inequity and try to reduce it. Do you need to have a sense of morality in order to see inequity, or would a purely rational AI also see it? If it did recognize inequity, what would it suggest that we do about it?
虽然我们不应该等待这种情况发生，我觉得有意思的一点是人工智能是否会识别不平等并试图减少它。需要有道德感才能看到不平等吗？或者一个纯粹理性的人工智能也会看到不平等吗？如果AI确实看到了不平等，它会建议我们做些什么？
Finally, we should keep in mind that we’re only at the beginning of what AI can accomplish. Whatever limitations it has today will be gone before we know it.
最后，我们应该记住，我们才刚刚开始了解 AI 能取得的成就，它今天的任何限制都可能会在我们了解之前消失。
I’m lucky to have been involved with the PC revolution and the Internet revolution. I’m just as excited about this moment. This new technology can help people everywhere improve their lives. At the same time, the world needs to establish the rules of the road so that any downsides of artificial intelligence are far outweighed by its benefits, and so that everyone can enjoy those benefits no matter where they live or how much money they have. The Age of AI is filled with opportunities and responsibilities.
我很幸运参与了个人电脑革命和互联网革命，此时此刻，我感到同样兴奋。这项新技术可以帮助世界各地的人们改善生活。与此同时，全世界需要确立相应的规则，以确保人工智能带来积极改善远远超越其负面影响，而且我们每个人无论住在哪里无论有多少财富，都能够从中获益。人工智能时代已来，机遇难逢，责任厚重。
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在当今数字化浪潮中，人工智能与多媒体技术的融合宛如一场科技界的盛宴，正悄然改变着我们创作、体验和分享多媒体内容的方式。这不仅是一次技术的升级，更是创意与智能的深度融合，为艺术创作、信息传播、娱乐体验等领域带来了前所未有的变革。让我们一同走进这场智能创作的新时代，探索其背后的技术奥秘与无限可能。人工智能与多媒体技术的联姻人工智能，这一曾经只存在于科幻小说中的概念，如今已深入到我们生活的方方面面。而多
去年以来关于人工智能（AI）的讨论非常火热，最近读到一篇这个主题的文章觉得非常不错，翻译过来分享下。这不是一篇烧脑的关于人工智能技术文，而是一篇开阔的思辨性文章。下面是原文：是的，数百万低报酬、低技能的工作岗位将面临风险，但人工智能革命还是会带来很多好处的。1周二，白宫发布了一份关于人工智能与经济的令人寒心的报告。报告以如下推断开头：“可以预计机器将在越来越多的任务上达到甚至超越人类的表现
人工智能时代的竞争封人疯语：闭上眼睛，想想明天的世界吧，执汽车行业牛耳者是百度、谷歌还是丰田、沃尔沃？数据和算法已经成为整个世界的底层，基于物质世界资源稀缺、非此即彼和人类大脑有限理性的传统逻辑似乎正在被彻底颠覆，数据越多、算法越强、强者恒强，智者通吃。这是一幅非常可怕的图景，也是一幅令人激动向往的图景。斯密用分工描述世界发展，马克思用阶级分析人类未来，在这个崭新时代到来之际，我们需要新...
2050年的人工智能：从弱人工智能到强人工智能的技术跨越关键词： 人工智能，弱人工智能，强人工智能，技术趋势，应用领域，未来展望 摘要： 本文将深入探讨人工智能的发展历程，从弱人工智能到强人工智
加密货币技术的史诗级演进十年前，“加密货币”这个词对大多数人来说还十分陌生。而如今，几乎人人都听说过比特币、以太坊等加密货币。这种最初神秘的去中心化数字货币，现已发展成为包含DeFi平台、质押机会和NFT奇迹的庞大生态。加密货币领域不仅是技术潮流，更在以我们从未想象的方式重塑金融格局。成为加密货币高手的必备工
人类总是会因为偏见、恐惧和舒适的习惯而阻碍革命性技术的发展。译自The AI revolution will take time，作者 Matt Asay。系好安全带，人工智能革命已经进入超速档！！！当然，除了它还没有，而且在不久的将来也不会，尽管你在无数篇激动人心的社论中读到了什么。这并不是说人工智能不重要，或者它没有改变一切的潜力。它确实如此，但它不会像我们想象的那么快发生。原因是人。永远是人
随着我国城镇化进程的加速和环保政策的日趋严格，城市及乡镇污水处理厂的稳定运行与高效监管变得至关重要。传统的污水处理厂在安全管理与生产监管方面普遍面临以下痛点： 设备分散，监管困难：厂区范围大，各类池体、泵站、机房等关键设备分布广泛，人工巡检效率低、成本高。 视频系统孤立：可能部署了不同品牌、不同协议 ...
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该系统通过SSM框架的高效开发特性，结合Java语言的强大功能，构建了稳定且易于扩展的后端架构，能够高效处理复杂的业务逻辑和数据交互。系统功能涵盖了器材信息、器材类型、器材采购、器材租赁、器材归还以及数据分析等多个方面，通过智能化的库存预警和数据分析模块，帮助管理者实时掌握器材使用情况，优化资源配置。在器材管理方面，系统通过器材信息和器材类型模块，实现器材的分类管理与详细信息记录，确保器材信息的准确性和完整性。整体而言，该系统通过整合多种功能，旨在提升体育器材管理的信息化水平，推动体育管理的现代化进程。
RTC的技术原理下面用“一张图 + 三句话”把 RTC（Real-Time Communication）的技术原理一次讲清，并给出 WebRTC 视角的完整数据流动图。一、一张图（文字版）复制 信令通道（任意协议） 媒体通道（UDP/RTP） ┌──────────┐ ┌──────────┐ │ ...
文件同步SymmetricDS不仅支持数据库表的同步，而且还支持文件和文件夹从一个节点到另一节点的同步。6.7.1。文件同步概述文件同步功能包括：监视一个或多个文件系统目录位置的文件和文件夹更改支持同步与源目录不同的目标目录使用通配符表达式来“包含”或“排除”文件选择是否递归到受监视目录的子文件夹使用现有的SymmetricDS路由器基于文件和目录元数据对目标节点进行子集化能够指定在创