Quotesby GlyphEconomics quotes
103 quotes from 45 people
- But the right tail of the market is thinner than almost anyone forecast.
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- Demand for intelligence is not a pyramid with a small, wealthy peak paying for everything beneath it.
- Most business AI use is the messy middle: multi-step workflows that need a smart enough model at a price a company can afford. It is the most important part of the market today, & it is where the competition is fiercest.
- Every quote from Tomasz Tunguz
- A world with sufficient compute is one where intelligence is a commodity, and in commodity markets margin comes from a superior cost structure, which I would expect the leading model providers to have, in part because they have a meaningful lead in scaling and can apply superior AI to their infrastructure.
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- If this is the first of many primitives specialized for production, then harnesses are about to capture a lot more margin.
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- They also highlight the bifurcating economics of AI: state of the art models for discovery & optimized models for production. We use the largest frontier models to train new models, & the most capable models to architect systems. But once a system is engineered & hardened, running it thousands or millions of times through a workflow benefits from narrower AI.
- Every quote from Tomasz Tunguz
- We have to hold in our heads that most Americans appear to loathe AI, but businesses and consumers seem to like it enough that Anthropic is well on its way to $100bn in annualised revenue this year. And despite being on track to be the fastest-growing company ever, Anthropic’s leadership believes they might kill all their customers.
- AI will sort the world the same way: those who harness it effectively will gain cultural and economic power, and those who don’t will become subject to forces they do not control.
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- I reckoned he’d love the technology as a productivity tool; he’d be skeptical about companies working together on any issue; and he’d be concerned about giving moral agency to machines.
- Even in a world that is speeding up, it takes time to make changes inside a firm, let alone across an economy.
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- If given 100 years to diffuse into society, its impacts will certainly become much more obvious, like the industrial revolutions of centuries past.
- Cost-saving efforts reveal that moving simpler workloads to open AI models is the easiest way to save ~50% on AI bills.
- AI has reached its inflection point. It’s doing useful work. Its tokens are productive and profitable. Now, compute is revenue...
- Continual learning will create a clear moat for leading AI labs that they currently lack.
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- We are advancing the frontier on the cost-to-outcome curve, ensuring every customer can turn tokens into business results...
- I want to emphasize the key conclusion here: as AI models become smarter, they’ll better monetize the same amount of compute. If a true human-level software engineer that could run on an H100 equivalent, at current market rates for software engineers, that H100 should rent for over $250k a year.
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- The long and short of it is this: marginal costs are back in a big way, both in terms of short-term implications of state-of-the-art free models, and in terms of the long-term structure of the industry.
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- Enterprises are moving from tokenmaxxing to valuemaxxing.
- AI customer retention sits between mobile games and social networks. Frontier models keep the crown for about 41 days, and the price of a given level of intelligence falls roughly 10x per year, giving buyers more leverage every cycle.
- If learning flows in only one direction, economic value converges toward the owners of the learning infrastructure rather than the creators of the knowledge itself.
- AI may have the most significant economic effects of any technology in modern history, and Anthropic has a dual responsibility to understand those effects and to act on them...
- But at one extreme, there are two or three giant minds that run half of everything and have massive pricing power, and at the other extreme LLMs look like databases - there’ll be millions of them, some very big and some very small, and the value is in what you build on top - after all, every SaaS company is a ’database wrapper’.
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- Even so, that brings me back to the same point: the current market dynamics point to a future in which, as today’s supply crunch eases, frontier models move towards becoming commodity infrastructure, with all of the value built on top, and for a different outcome, something needs to happen that we don’t see yet.
- Meanwhile, there is structural uncertainty at the early stages of every big new technology, but the uncertainty now is different, because we don’t have a good theoretical understanding of why these models work so well and so we don’t know how much better they can get.
- Every quote from Benedict Evans
- One of the things that's driven up a bunch of cost of AI is that people were trying to use the best model for every single thing...
- As much as the increases in AI proficiency are prompting layoffs and reshaping the job market now, I believe that AI will be a net-positive force on job creation, because of all the ways it will empower entrepreneurship, accelerate innovation, and attain new levels of productivity and efficiency.
- If all the value is accrued by only a few models, the political economy will simply not tolerate it. There is no societal permission for an AI future that hollows out entire industries.
- First, enduring job displacement is undesirable and dangerous, and we should do everything we can to minimize or prevent it, not to bring it about.
- The surprising thing from my perspective is seeing the feedback across the whole economy, suggesting we might hit an ‘economic singularity’ as a consequence of broad diffusion of automation technologies into the economy.
- But the claim that AI will produce economy-wide, permanent unemployment is unhelpful marketing, bad economics and worse history. To the contrary, productivity gains should increase demand for labor, because labor becomes more valuable.
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- AI is now a profit generator. AI is now a GDP generator...
- If Anthropic and OpenAI hit $100B of revenue by EOY as many think they might, roughly 1% of GDP run rate will be from AI by end of 2026.
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- This means countries like India and the Philippines may be the most impacted soonest in terms of employment and AI as they house many of these outsourced services organizations. It also means some developing countries may lose their services ladder to upgrading their economy and work.
- Every quote from Elad Gil
- At scale, we expect Trainium will save us tens of billions of capex dollars per year, and provide several hundred basis points of operating margin advantage versus relying on others’ chips for inference.
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- The work budget in any profession dwarfs the tool budget, and autopilots capture the work budget from day one. The higher the intelligence ratio in any field, the sooner autopilots will win.
- Agentic AI is a tailwind for our business, and we’re well on our way to $63 billion in revenue in FY30.
- I am not saying everyone ends up happy here, but you cannot have a) a flood of goods and services, b) billions accruing to the AI owners, without also c) prices are at a level where most people can afford to buy a whole bunch of things.
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- But what we’ve seen from the beginning, at least if you look within Anthropic, there’s this bizarre 10x per year growth in revenue that we’ve seen.
- As we scale, we’re getting dramatically more efficient: we were able to lower Gemini serving unit costs by 78% over 2025 through model optimizations, efficiency and utilization improvements.
- We are an n of 1, and these numbers prove it. Palantir is alone in choosing to exclusively focus on scaling the operational leverage made possible by the rapid advancements of AI models, a trend that we first called ‘commodity cognition’ well before others started repeating it...
- I believe that if we embrace AI and exercise its power well, it will advance human flourishing and drive unprecedented prosperity.
- If America fails to win technologically, it will lose economically, militarily, geopolitically, and culturally.
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- But surely the most important first order answer is: “With AGI, we don’t need to raise taxes!”
- Another way to say it is that AI isn’t a substitute for specific human jobs but rather a general labor substitute for humans.
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- I’d argue that whether or not AGI emerges from a single model, the impact of this meta economic machinery is functionally similar. That is, it reduces a massively broad class of technical problems to simply a matter of economics.
- Bill famously said a platform is when the economic value of everybody that uses it exceeds the value of the company that creates it. That’s the essence of the positive-sum future.
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- At least the early signs maybe, the way to think about the per-user business is not just per user, it’s per agent.
- Or let me put it another way: take AI out of the picture and the gains over the next decades look much harder to come by.
- I do, but it’s business as usual because we’re in an intelligence explosion already and have been for decades.
- As AI gets smarter, access to AI will be a fundamental driver of the economy, and maybe eventually something we consider a fundamental human right.
- The choices we make today will shape whether the coming transformation leads to greater empowerment for all, or greater concentration of wealth and power for the few.
- Artificial intelligence is a revolutionary technology with the potential to transform the global economy and alter the balance of power in the world. To remain the leading economic and military power, the United States must win the AI race.
- As datacenter production gets automated, the cost of intelligence should eventually converge to near the cost of electricity.
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- AI does not have to be as expensive as it is today, and it won’t be in the future.
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- But, inference will also get meaningfully more efficient in the next couple of years with improvements in model distillation, prompt caching, computing infrastructure, and model architectures. Reducing the cost per unit in AI will unleash AI being used as expansively as customers desire, and also lead to more overall AI spending.
- Every quote from Andy Jassy
- Mary, Jim and Joes are experiencing the majority of the benefit, not Google or the government of the United States.
- We predict that the impact of superhuman AI over the next decade will be enormous, exceeding that of the Industrial Revolution.
- I tell them any inefficient computation that a customer is running is a ticking time bomb, because they’re going to inevitably find out and be really upset about it.
- We’re continually retraining dozens of machine learning models that optimize every part of the transaction flow over an economy-scale dataset. The resulting optimizations are big enough that businesses see them in their topline revenue figures. Businesses simply start making more money when they switch to Stripe...
- I think that in order to have a stable social structure, and democracies function, you can’t just have a return on capital and no return on labor.
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- In fact that’s the thing, a lot of people are writing about it, and I'm glad they are, which is the big winners here are not going to be tech companies. The winners are going to be the broader industry that uses this commodity that, by the way, is abundant. Suddenly productivity goes up and the economy is growing at a faster rate.
- The only thing that's going to happen with all the compute builds is the prices are going to come down.
- Every quote from Satya Nadella
- AI, we believe, is going to make us more productive, more prosperous, and more free.
- So what used to cost four dollars per million tokens now costs just 13 cents, and I expect this trend to continue. The result: intelligence is more available and accessible than ever before.
- Anyone in 2035 should be able to marshall the intellectual capacity equivalent to everyone in 2025; everyone should have access to unlimited genius to direct however they can imagine.
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- The cost to use a given level of AI falls about 10x every 12 months, and lower prices lead to much more use.
- In a decade, perhaps everyone on earth will be capable of accomplishing more than the most impactful person can today.
- In particular, it does seem like the balance of power between capital and labor could easily get messed up, and this may require early intervention.
- The socioeconomic value of linearly increasing intelligence is super-exponential in nature. A consequence of this is that we see no reason for exponentially increasing investment to stop in the near future.
- Every quote from Sam Altman
- Our business results continue to astound, demonstrating our deepening position at the center of the AI revolution. Our early insights surrounding the commoditization of large language models have evolved from theory to fact...
- The cost of AI, like the cost of mainframe computing to X.25 connectivity (the early pre-TCP/IP protocol for connecting computers over phone lines), literally forces the market to develop an alternative that scales without the massive direct capital.
- So mark my words – Britain will be one of the great AI superpowers.
- In many ways, artificial intelligence is the electricity of our age, and the next four years can build a foundation for America’s economic success for the next quarter century.
