I’ve collected lots of Generative AI quotes from my content consumption spree since ChatGPT launched in 2023. This includes many TED Talks and webinars by Generative AI experts, technology masters, and business leaders.
I have saved many of their insightful quotes – and thought I will publish the most thought provoking Generative Artificial Intelligence quotes for you to get some perspective on what is this world thinking about it.
Note: this blog will continue to get updates as and when I find new useful quotes to list. If you happen to use these quotes, it would be great if you mention our blog as the linking source as I have personally spent time going through podcasts, lectures, blogs, and videos to source them 🙂
Key takeaways:
- AI is a distinct digital species that will work alongside us to improve our lives.
- AI needs to be deployed to solve hard human problems – like wars, diseases, climate change, etc.
- AI will lead to curb our inflation problems and lead to deflation
- AI problems will be solved using AI itself
- Worldwide wealth distribution should be a concern as AI spearheads developed societies and riches who can afford to have access to it and do not experience job loss.
- AI is risky because it has its own agency.
- AI can lead to loss of trust among humans – and this trust is key pillar of democracy.
- We must not pause AI, but must pause the reckless race to superintelligence. We do not require superintelligence for our daily tasks.
- Generative AI is a step towards reducing cost of intelligence, and it will further reduce it to zero.
- People should focus on proof-checkers and setting up rules for AI to avoid
- AI is improving its technology at an exponential phase.
Quotes on Generative AI’s potential:
Bill Gates quotes on Gen AI’s rise from Gates Notes:
“Generative AI has the potential to change the world in ways that we can’t even imagine. It has the power to create new ideas, products, and services that will make our lives easier, more productive, and more creative. It also has the potential to solve some of the world’s biggest problems, such as climate change, poverty, and disease.“
Bill Gates on rise of Generative AI on Gates Notes
“Few families can pay for a tutor who works one-on-one with a student to supplement their classroom work. If agents can capture what makes a tutor effective, they’ll unlock this supplemental instruction for everyone who wants it. If a tutoring agent knows that a kid likes Minecraft and Taylor Swift, it will use Minecraft to teach them about calculating the volume and area of shapes, and Taylor’s lyrics to teach them about storytelling and rhyme schemes. The experience will be far richer—with graphics and sound, for example—and more personalized than today’s text-based tutors.”
Bill Gates provides an example of how AI Agents will revolutionize education on Gates Notes
“This (AI) is now an unstoppable technological course. The value is too great. And I’m pretty confident, very confident, we’ll make it work, but it does feel like it’s going to be so different. The way to apply this to certain current problems, like getting kids a tutor and helping to motivate them, or discover drugs for Alzheimer’s. I think it’s pretty clear how to do that.
Whether AI can help us go to war less, be less polarized; you’d think as you drive intelligence, and not being polarized kind of is common sense, and not having war is common sense. But I do think a lot of people would be skeptical.
I’d love to have people working on the hardest human problems, like whether we get along with each other. I think that would be extremely positive – if we thought the AI could contribute to humans getting along with each other.”
Bill Gates on how we wants AI to solve harder problems on ‘Unconfuse with Bill Gates’ podcast in conversation with Sam Altman
Cathie Wood’s forecast on Generative AI and its economic impact
“Autonomous taxi platforms are going to be the convergence of three of these major, general-purpose technology platforms: robotics (autonomous vehicles are robots); energy storage (they will be electric); and artificial intelligence (they will be powered by AI). This one opportunity, we think, in the next five to 10 years is going to scale to a revenue opportunity of 8 to 10 trillion dollars, from essentially nothing now.”
Cathie Wood on TED Talk – Why AI Will Spark Exponential Economic Growth
“We we really do believe that real GDP growth around the world is going to accelerate from that two to three percent range into the six to nine percent range, and a lot of that will be productivity-driven. With productivity comes tremendous wealth creation.
Productivity can end up in three places. It can end up in profits. It can end up in wages going up as employees become more productive. And lower prices – deflation. We think we’re heading into a highly deflationary period.”
Cathie Wood on TED Talk – Why AI Will Spark Exponential Economic Growth
Sam Altman on Generative AI’s potential:
“The stuff that we’re seeing now is very exciting and wonderful, but I think it’s worth always putting it in context of this technology that, at least for the next five or ten years, will be on a very steep improvement curve. These are the stupidest the models will ever be. Coding is probably the single area from a productivity gain we’re most excited about today.”
Sam Altman in conversation with Bill Gates on Unconfuse Me with Bill Gates
Andrew Ng on the need of Generative AI
“To me at the heart of it is do we want more or less intelligence in the world?
Until recently, our primary source of intelligence has been human intelligence. Now, we also have artificial intelligence or machine intelligence. And yes, intelligence can be used for nefarious purposes
But I think a lot of civilization’s progress has been through people getting training and getting smarter and getting more intelligent. And I think we’re actually are much better off with more rather than less intelligence in the world.”
Andrew Ng in conversation with Wall Street Journal
Quotes from CEOs, experts, and business leaders on Generative AI’s potential:
“In a few years, AI is just gonna be assumed.”
Ian Beacraft, CEO Signals and Cipher at the SXSW 2024
“Discovery so science probably will be the biggest especially the combination of progress in AI and AI for Science. Maybe, Quantum, that to me might be the next big breakthrough, where science itself is computed.”
Satya Nadella, CEO at Microsoft, in conversation with Varun Mayya about the most exciting application of AI.
“Generative AI is teaching us that the way you speak is actually code itself”
Lisa Huang, Head of AI at Fidelity Investments
“Is it perfect? No. Is it as good as my executive team? No. Is it really, really valuable, so valuable that I talk to ChatGPT every single day? Yes.”
Jeff Maggioncalda, CEO, Coursera
“Aristotle founded or discovered logic by observing the world. ChatGPT thinks logically. Why? Because it notices all the logic in the data in its training set”
Stephen Wolfram, CEO of Wolfram Research
“I have not seen this level of engagement and excitement from customers, probably since the very, very early days of cloud computing.”
Dr. Matt Wood, VP Artificial Intelligence at AWS, 2023
“The most surprising thing for me is – the whole thing works at all! You see a lot of neural networks do amazing things, well obviously neural networks is the thing that works, but I have witnessed personally what it’s like to be in a world for many years where the neural networks not work at all. And then to contrast that to where we are today – just the fact that they work and they do these amazing things.
I think maybe the most surprising, if I had to pick one, it would be the fact that when I speak to it I feel understood.”
Ilya Sutskever, Co-Founder & Chief Scientist a OpenAI, in answer to the question – what was the most surprising thing for you in terms of emergent behavior in these models over time? – on No Priors Podcast Ep. 39
“Just a century ago, a kilo of grain would have taken 50 times more labor to produce than it does today. That efficiency which is the trajectory you have seen in agriculture is likely to be the same trajectory that we will see in intelligence. Everything around us is a product of intelligence and so everything that we touch with these new tools is likely to produce far more value than we’ve ever seen before.
Mustafa Suleyman, Co-Founder at Deepmind in conversation with Yuval Noah Harari and The Economist
“I think it’s pretty likely the entire surface of the earth will be covered with solar panels and data centers…”
Ilya Sutskever, Chief Scientist at Open AI, iHuman, Nov 2019
“There is no question that machines will become smarter than humans—in all domains in which humans are smart—in the future. It’s a question of when and how, not a question of if.”
Yann LeCunn, Chief AI scientist at Meta, (MIT Tech Review, May 2023)
“AI has the potential to be the great equaliser. We have opportunities ahead of us to address pain points (in healthcare and climate) and to address the sustainable development goals,” said .
Ruth Porat, CFO, Alphabet, at annual World Economic Forum meet Davos, 2024
“Sometimes people say that data or chips are the 21st century’s new oil, but that’s totally the wrong image.
AI is to the mind what nuclear fusion is to energy.
Limitless, abundant, world-changing.
And AI really is different, and that means we have to think about it creatively and honestly. We have to push our analogies and our metaphors to the very limits to be able to grapple with what’s coming.
Because this is not just another invention – AI is itself an infinite inventor.”
Mustafa Suleman tries to define what AI is and the urges people to think about defining it too on his TED Talk – AI Is Turning into Something Totally New
Quotes on risks of Generative AI’s and potential solutions
Bill Gates on Generative AI risks:
“We’re now in the earliest stage of another profound change, the Age of AI. It’s analogous to those uncertain times before speed limits and seat belts. AI is changing so quickly that it isn’t clear exactly what will happen next.
This is not the first time a major innovation has introduced new threats that had to be controlled. We’ve done it before.
Whether it was the introduction of cars or the rise of personal computers and the Internet, people have managed through other transformative moments and, despite a lot of turbulence, come out better off in the end. Soon after the first automobiles were on the road, there was the first car crash. But we didn’t ban cars—we adopted speed limits, safety standards, licensing requirements, drunk-driving laws, and other rules of the road.”
Bill Gates expresses positive outlook on overcoming risks of AI on Gates Notes
Many of the problems caused by AI can also be managed with the help of AI.
Bill Gates excellent and concise thought on how to overcome AI risks and challenges on Gates Notes
“It is true that some workers will need support and retraining as we make this transition into an AI-powered workplace. That’s a role for governments and businesses, and they’ll need to manage it well so that workers aren’t left behind—to avoid the kind of disruption in people’s lives that has happened during the decline of manufacturing jobs in the United States.”
Bill Gates emphasizes on role of businesses and governments in enabling the transition to AI on Gates Notes
Sam Altman on risks of Generative AI:
It’s not that we have to adapt. It’s not that humanity is not super-adaptable. We’ve been through these massive technological shifts, and a massive percentage of the jobs that people do can change over a couple of generations, and over a couple of generations, we seem to absorb that just fine. We’ve seen that with the great technological revolutions of the past. Each technological revolution has gotten faster, and this will be the fastest by far. That’s the part that I find potentially a little scary — is the speed with which society is going to have to adapt, and that the labor market will change.
Sam Altman on the risks of adapting too fast on Unconfuse with Bill Gates podcast
One aspect of AI is robotics, or blue-collar jobs – when you get hands and feet that are at human-level capability. The incredible ChatGPT breakthrough has kind of gotten us focused on the white-collar thing, which is super appropriate, but I do worry that people are losing the focus on the blue-collar piece.”
Sam Altman on the risks of adapting too fast on Unconfuse with Bill Gates podcast
Yuval Noah Harari on risks of Generative AI:
“I think there will be immense new wealth created by these technologies. I’m less sure that the governments will be able to redistribute this wealth in a fair way on a global level.
Like, I just don’t see the US government raising taxes on corporations in California and sending the money to help unemployed textile workers in Pakistan or Guatemala or kind of retrain for the new job market.”
Yuval Noah Harari in conversation with Mustafa Suleyman and The Economist | shares how AI will create more divide among developed and under-developed nations.
“Potentially, we are talking about the end of human history—the end of the period dominated by human beings.”
Yuval Noah Harari, Historian and Author
“Modern democracy as we know it is built on top specific information technology. Once the information technology changes, it’s an open question whether the market obviously can survive.
The biggest danger now is the opposite than what we face in the Middle Ages. In the Middle Ages it was impossible to have a conversation between millions of people because they just couldn’t communicate.
But in the 21st century something else might make the conversation impossible – the trust between people collapses again. The online space is flooded by non-human entities that maybe masquerade as human beings. You talk with someone you have no idea if it’s even human. You see a video, you hear an audio, you have no idea if this is really true, if this fake, is this a human or it’s not a human. In this situation, unless we have some guard rails, again conversation collapses.”
Yuval Noah Harari (Historian and Author) highlights the danger of how AI can bring down trust among humans, and hence bring down democracy.
“If it was a question of you know humankind versus a common threat of these new intelligent alien agents here on Earth then yes, I think there are ways we can contain them. But if the humans are divided among themselves and are in an arms race then it becomes almost impossible to contain this alien intelligence.”
Yuval Noah Harari (Historian and Author) shares importance of humans to be on the same page when it comes to adopting AI
“We can try to prevent them (AI) from having agency but we know that they are going to be highly intelligent and at least potentially have agency. And this is a very frightening mix – something we never confronted before.
Again, atom bombs didn’t have a potential for agency. Printing presses did not have a potential for agency. This thing again unless we contain it and the problem of containment is very difficult because potentially they’ll be more intelligent than us. How do you prevent something more intelligent than you from become from developing the agency it has?”
Yuval Noah Harari (Historian and Author) shares how comparing AI to previous technological advancements doesn’t make sense – because they did not have agency.
“I think our best bet is not to kind of think in terms of some kind of rigid regulation – it’s in developing new living institutions that are capable of understanding the very fast developments and reacting on the fly. At present, the problem is that the only institutions who really understand what is happening are the institutions who develop the technology.
The governments, most of them seem quite clueless about what’s happening. Also universities, I mean, the amount of talent and the amount of economic resources in the private sector is far higher than in the universities. So we must have an external entity in the game and for that we need to develop new institutions that will have the human, economic and technological resources and also will have the public trust because without public trust it won’t work.”
Yuval Noah Harari (Historian and Author) shares the need of independent third party institution which has an oversight on AI.
“Let’s say that you have an AI which has a better understanding of the financial system than most humans. Let’s think back to the 2007-2008 financial crisis. It started with this exactly something that these genius mathematicians invented, nobody understood them except for a handful of Genius mathematicians in Wall Street, which is why nobody regulated them, and almost nobody saw the financial crash coming.
What happens again this kind of of apocalyptic scenario – which you don’t see in Hollywood science fiction movies, is how the AI invents a new class of financial devices that nobody understands, it’s beyond human capability to understand because it’s such complicated math, so much data that nobody understands it, and it makes billions of dollars, and then it brings down the world economy. And no human being understands what the hell is happening!”
Yuval Noah Harari shares a scenario of AI developing new financial systems beyond human comprehension which leads to economic collapse similar to 2008 financial crisis.
Quotes from CEOs, experts, and business leaders on risks of Generative AI and solutions:
If it can solve certain biological challenges, it could build itself a tiny molecular laboratory and manufacture and release lethal bacteria. What that looks like is everybody on Earth falling over dead inside the same second.
Eliezer Yudkowsky, co-founder of the Machine Intelligence Research Institute
“This next generation of AI will reshape every software category and every business, including our own. Although this new era promises great opportunity, it demands even greater responsibility from companies like ours.”
Satya Nadella, CEO of Microsoft
“I think it’s important to say these are not autonomous tools by default. These capabilities don’t just naturally emerge from the models. We attempt to engineer capabilities and the challenge for us is to be very deliberate, precise, and careful about those capabilities that we want to emerge from the model.
(Hence), it’s super important not to anthropomorphically project ideas, potential intentions, potential agency, or potential autonomy into these models. The governance challenge for us over the next couple of decades to ensure that we contain this wave and ensure that we always get to impose our constraints on the the trajectory of this development.”
Mustafa Suleyman, Co-Founder at Deepmind in conversation with Yuval Noah Harari and The Economist
“One difference between worry about AI and worry about other kinds of technologies (e.g. nuclear power, vaccines) is that people who understand it well worry more, on average, than people who don’t. That difference is worth paying attention to.”
Paul Graham, Computer Scientist and Investor, (Twitter, April 2023)
“All the AI benefits that most people are excited about actually don’t require superintelligence. We can have a long and amazing future with AI.
So let’s not pause AI. Let’s just pause the reckless race to superintelligence.
Let’s stop obsessively training ever-larger models that we don’t understand.
Because artificial intelligence is giving us incredible intellectual wings with which we can do things beyond our wildest dreams, if we stop obsessively trying to fly to the sun.”
Max Tegmark, Physicist and machine learning researcher, on TED Talk – How to Keep AI Under Control shares an realistically optimistic picture of how AI need not be stopped from development, we just need to make sure we have enough safeguards in place and aren’t greedy or obsessive about superintelligence.
“Reasoning in general, that humans are capable of, that these ChatGPT are not as reliable right now. The reaction to that in the current scientific community – it’s a bit divisive.
On one hand, that people might believe that with more scale, the problems will all go away. Then there’s the other camp who tend to believe that – wait a minute, there’s a fundamental limit to it, and there should be better, different ways of doing it that are much more efficient.
I tend to believe the latter.”
Yejin Choi, Computer Science Professor at the University of Washington and Senior Resource Manager at the Allen Institute for AI – in a podcast with Bill Gates (Unconfuse me with Bill Gates – “There’s a high chance we’ll be surprised again by AI”
Quotes on Generative AI technology and latest updates
Sam Altman on Generative AI technology and its future
“Creative work, the hallucinations of the GPT models is a feature, not a bug. It lets you discover some new things. Whereas if you’re having a robot move heavy machinery around, you’d better be really precise with that. I think this is just a case of you’ve got to follow where technology goes.”
Sam Altman on Generative AI’s hallucinations on Unconfuse with Bill Gates podcast
“I think we are on the steepest curve of cost reduction ever of any technology I know, way better than Moore’s Law. It’s not only that we figured out how to make the models more efficient, but also, as we understand the research better, we can get more knowledge, we can get more ability into a smaller model.
I think we are going to drive the cost of intelligence down to so close to zero that it will be this before-and-after transformation for society.
Right now, my basic model of the world is cost of intelligence, cost of energy. Those are the two biggest inputs to quality of life, particularly for poor people, but overall. If you can drive both of those way down at the same time, the amount of stuff you can have, the amount of improvement you can deliver for people, it’s quite enormous. We are on a curve, at least for intelligence, we will really, really deliver on that promise.”
Sam Altman on bringing down cost of intelligence in conversation with Bill Gates on ‘Unconfuse me with Bill Gates’ podcast
Quotes by other pioneers in AI, leaders, and technologists on how Generative AI works and can be improved:
“Shortly after GPUs started to be used in machine learning people kind of had an intuition that that’s a good thing to do but it wasn’t like today where people exactly knew what the GPUs is for. It was like – oh, let’s like play with those cool fast computers and see what we can do with them. It was an especially good fit for neural networks so that was a very that definitely helped us.
I was very fortunate in that I was able to realize that the reason neural networks of the time weren’t good is because they were too small. So like if you try to solve a vision task with a neural network which has like a thousand neurons, what can it do – it can’t do anything. It doesn’t matter how good your learning is and everything else but if you have a much larger neural network you’ll do something unprecedented.”
Ilya Sutskever, Co-Founder & Chief Scientist at OpenAI, in conversation with No Priors Ep. 39
“Right now the transformers, like GPT-4, can look at such a large amount of context. It’s able to remember so many words as spoken just now. Whereas humans have a very small working memory. The moment we hear new sentences from each other, we kind of forget exactly what you said earlier, but we remember the abstract of it.
We have this amazing capability of abstracting away instantaneously and have such a small working memory, whereas right now GPT-4 has enormous working memory, so much bigger than us.
But I think that’s actually the bottleneck, in some sense, hurting the way that it’s learning, because it’s just relying on the patterns, a surface of patterns overlay, as opposed to trying to abstract away the true concepts underneath any text.”
Yejin Choi, Computer Science Professor at the University of Washington and Senior Resource Manager at the Allen Institute for AI – in a podcast with Bill Gates (Unconfuse me with Bill Gates – “There’s a high chance we’ll be surprised again by AI”
“We predict that the new capabilities that it will come this time over the next five years will be the ability to plan over multiple time horizons instead of just generate new text in a one shot. The model will be able to generate a sequence of actions over time.”
Mustafa Suleyman, Co-Founder at Deepmind in conversation with Yuval Noah Harari and The Economist
“If your adversary is superintelligence or a human using superintelligence against you – trying is just not enough.
You need to succeed.
Harm needs to be impossible.
So we need provable safe systems, not in the weak sense of convincing some judge, but in the strong sense of there being something that’s impossible according to the laws of physics.
Because no matter how smart an AI is, it can’t violate the laws of physics and do what’s provably impossible.
Steve Omohundro and I wrote a paper about this, and we’re optimistic that this vision can really work.
Here is how our vision works – You, the human, write a specification that your AI tool must obey, that it’s impossible to log in to your laptop without the correct password, or that a DNA printer cannot synthesize dangerous viruses.
Then a very powerful AI creates both your AI tool and a proof that your tool meets your spec.
Machine learning is uniquely good at learning algorithms, but once the algorithm has been learned, you can re-implement it in a different computational architecture that’s easier to verify.
It’s much easier to verify a proof than to discover it. So you only have to understand or trust your proof-checking code, which could be just a few hundred lines long.
Steve and I envision that such proof checkers get built into all our compute hardware, so it just becomes impossible to run very unsafe code.
Max Tegmark, Physicist and machine learning researcher, on TED Talk – How to Keep AI Under Control shares about a vision on how to use a ‘proof code’ to control AI’s actions.
“As models continue to get larger and better then they will unlock new and unprecedentedly valuable applications. The small models will have their niche for the less interesting applications which are still very useful and then the bigger models will be delivering on applications…..Let’s let’s pick an example – consider the task of producing good legal advice. It’s really valuable if you can really trust the answer maybe you need a much bigger model for it, but it justifies the cost.”
Ilya Sutskever, Co-Founder & Chief Scientist at OpenAI – on how to gauge model size requirements and justify the cost associated with larger models. In conversation with No Priors Podcast, Ep. 39.
“The fun thing to note is that these models are improving with their capabilities and capacity by five to 10x per year. So if we take that exponential in mind yet again, we’re looking at a minimum of 3,125 times better than they are today, or 100,000 times better than they are today by this date in 2029, five years from today.
So if you’re looking at imagery and saying, “It has a sixth finger!” – I think it might be able to figure that out when it’s 100,000 times better than it is today.
Let that sink in though, because as we interact with these chatbots, these models, imagery, and we’re prompting with these things you might have issues with the state of where it is and think, “Okay, this isn’t working.”
“It’ll never get there.”
The second someone says, “It’ll never get there,” come on. The rate of change is so fast and we’ve already seen things go from wildly underrated to Sora-level quality in just a couple years.
100,000 times better?
That’s gonna be a pretty crazy week.”
Ian Beacraft, CEO Signals and Cipher at the SXSW 2024
Check out other AI quotes collection across industries
I have (and will continue to ) create a series of blog posts which go further into Generative AI quotes across industry applications. Here are some to check out:
- 15+ insightful quotes on AI Agents and AGI from AI experts and leaders
- 15+ Generative AI quotes on future of work, impact on jobs and workforce productivity
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