Bill Gates: GPT is the most revolutionary technological advancement in 40 years

Global health and education are two areas where the needs are huge and there are not enough workers to meet those needs. In these areas, if AI is appropriately targeted, it can help reduce inequality. These should be the focus of AI efforts, so I will turn to them now.

healthy

I see several ways in which AI will improve healthcare and the medical field.

First, they will help healthcare workers make the most of their time by handling certain tasks for them—such as filing insurance claims, processing paperwork, and drafting notes on doctor visits. I expect there will be a lot of innovation in this area.

Other AI-driven improvements are particularly important for poor countries, where the vast majority of deaths among children under 5 occur.

For example, many people in these countries have never visited a doctor, and AI will help the health workers they see to be more efficient. (Efforts to develop AI-powered ultrasound machines are a case in point. AI will even enable patients to do basic triage, get advice on how to deal with health issues, and decide whether they need to seek treatment.

AI models used in poor countries need to be trained for different diseases than in rich countries. They need to work in different languages ​​and deal with different challenges, such as patients who live far away from the clinic or who are unable to stop working after becoming ill.

People need to see evidence that healthy AI is generally beneficial, even if they are imperfect and make mistakes. Artificial intelligence must be very carefully tested and properly regulated, which means they will take longer to adopt than in other fields. But then again, humans make mistakes. Lack of access to medical services is also a problem.

In addition to aiding care, AI will greatly speed up medical breakthroughs. The amount of data in biology is so large that it is difficult for humans to keep track of all the ways complex biological systems work. Software already exists that can look at this data, infer what the pathways are, search for the pathogen's targets, and design drugs accordingly. Several companies are working on cancer drugs developed in this way.

The next generation of tools will be more efficient, and they will be able to predict side effects and calculate dosage levels. One of the Gates Foundation's priorities in artificial intelligence is to ensure that these tools are used for health problems that affect the world's poorest people, including HIV, tuberculosis and malaria.

Likewise, governments and charities should create incentives for companies to share AI-generated insights into crops or livestock grown by people in poor countries. AI can help develop better seeds based on local conditions, advise farmers on the best seeds based on the soil and weather in their region, and help develop livestock medicines and vaccines. These developments will become even more important as extreme weather and climate change put greater pressure on subsistence farmers in low-income countries.

educate

Computers have not had the impact on education that many of us in the industry had hoped. There are some good developments, including educational games and online information sources such as Wikipedia, but they have not had a meaningful impact on any measure of student achievement.

But I think that within the next 10 to <> years, AI-driven software will finally deliver on its promise to revolutionize the way people teach and learn. It will learn about your interests and learning style in order to tailor content to keep you engaged. It will gauge your understanding, notice when you lose interest, and understand what motivations you respond to. It will provide immediate feedback.

Artificial intelligence can help teachers and administrators in a variety of ways, including assessing students’ understanding of subjects and providing advice on career planning. Teachers are already using tools like ChatGPT to provide comments on student writing assignments.

Of course, AI will require extensive training and further development before it can do things like understand how a particular student learns best, or what motivates them. Even if technology is perfected, learning will still depend on good relationships between students and teachers. It will enhance—but never replace—the work students and teachers do together in the classroom.

New tools will be created for schools that can afford to purchase them, but we need to ensure that they are also created for and available to low-income schools in the United States and around the world. AI needs to be trained on diverse data sets so that they are unbiased and reflect the different cultures in which they will be used. The digital divide needs to be addressed so that low-income students are not left behind.

I know many teachers are worried about students using GPT to write papers. Educators are already discussing ways to adapt to new technologies, and I suspect these conversations will continue for quite some time. I've heard that some teachers have found clever ways to incorporate this technology into their work - such as allowing students to use GPT to create first drafts that they have to personalize.

Artificial Intelligence Risks and Issues

You may have read about the problems with current AI models. For example, they're not necessarily good at understanding the context of human requests, which can lead to some strange results. When you ask AI to make up something fictional, it can do a pretty good job. However, when you ask for recommendations on a trip you want to take, it may suggest hotels that don't exist. That's because the AI ​​doesn't quite understand the context of your request and doesn't know whether it should invent a fake hotel or just tell you a real hotel with availability.

There are other problems, such as AI giving wrong answers to math questions because they have trouble with abstract reasoning. But these are not the fundamental limitations of artificial intelligence. Developers are working on them, and I think we'll see them largely fixed in less than two years, and probably sooner.

Other issues are more than just technical ones. For example, humans armed with artificial intelligence pose a threat. Like most inventions, artificial intelligence can be used for good or malicious purposes. Governments need to work with the private sector to look at ways to limit risks.

Then there's the possibility of AI running amok. 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 the problem is no more pressing today than it was before the development of artificial intelligence in the past few months.

Super-intelligent AI is in our future. Compared to computers, our brains run at a snail's pace: electrical signals in the brain move at 1/100,000 the speed of signals in a silicon chip! Once developers are able to generalize a learning algorithm and run it at computer speeds—an achievement that may be a decade or a century away—we will have a very powerful AGI. It will be able to do everything the human brain can do, but without any real limits on the size of its memory or how fast it can run. This will be a profound change.

It is known that these "powerful" AIs may be able to establish their own goals. What are these goals? What happens if they conflict with human interests? Should we try to prevent powerful artificial intelligence from being developed? As time goes on, these questions will become more pressing.

But none of the breakthroughs of the past few months have brought us any closer to strong artificial intelligence. AI still cannot control the physical world, nor can it establish its own goals. A recent New York Times article about a conversation with ChatGPT, in which it claimed it wanted to become one, attracted a lot of attention. It's a fascinating observation that demonstrates how human-like the model's expression of emotion is, but it's not an indicator of meaningful independence.

Three books have shaped my view on the 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. But all three books are well written and thought-provoking.

next frontier

There will be an explosion of companies working on new uses for AI, as well as ways to improve the technology itself. For example, companies are developing new chips to provide the massive processing power required for artificial intelligence. Some use optical switches (essentially lasers) to reduce energy consumption and lower manufacturing costs. Ideally, innovative chips will allow you to run AI on your own devices rather than in the cloud as is the case today.

On the software side, the algorithms that drive AI learning will get better. In some areas, such as sales, developers can make AI very accurate by limiting the areas they work in and providing them with large amounts of training data specific to those areas. But an open question is whether we will need many of these specialized AIs for different purposes — say, one for education and another for office productivity — or whether it will be possible to develop one that can learn any task. General artificial intelligence. Both approaches will face significant competition.

Regardless, the topic of artificial intelligence will dominate public discussion for the foreseeable future. I would like to propose three principles to guide this conversation.

First, we should try to balance concerns about AI’s shortcomings—which are understandable and valid—with its ability to improve people’s lives. To make the most of this extraordinary new technology, we need to guard against the risks and spread the benefits to as many people as possible.

Second, market forces will not automatically produce AI products and services that help the poorest people. The opposite is more likely. With reliable funding and the right policies, governments and charities can ensure that AI is used to reduce inequality. Just as the world needs the smartest people focused on its biggest problems, we also need the world's best artificial intelligence focused on its biggest problems.