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Jevons paradox only applies if demand hasnt already been saturated. The fact that public LLM usage is leveling off at a price of $0 and Jensen "we make the sho
by pydry 7mo ago
Jevons paradox only applies if demand hasnt already been saturated.
The fact that public LLM usage is leveling off at a price of $0 and Jensen "we make the shovels in this gold rush" Huang is rather desperately claiming that you need to spend $250k/year in tokens to be taken seriously suggests that demand saturation may not be that far off.
Whether Jevons' Paradox applies to software engineers I think is another open question. Im constantly being told that it doesnt and that LLMs make half of us redundant now, but Im skeptical - so much automation I see is broken or badly done.
- adventured 7mo agoLLMs haven't remotely begun to be integrated into the lives of the typical person. Not even close. The typical person is using LLMs not at all as it pertains to their daily life tasks. They're using them almost entirely for limited discussion matters (eg having a discussion with GPT about a medical issue, or a work related matter). This is the first or second inning in the LLM rollout. It'll take 15-20 more years for full integration of AI agents into the life of the typical person. The claw experiments for example can just barely be considered alpha stage. They're early AI garbage unfit for the average person to utilize safely. That new world hasn't gotten near the typical person yet. The compute requirements to get to full integration of AI agents into the life of the average person - billions of them - is far beyond 10x where we're at now.
- pizlonator 7mo ago> LLMs haven't remotely begun to be integrated into the lives of the typical person. Not even close. The typical person is using LLMs not at all as it pertains to their daily life tasks. They're using them almost entirely for limited discussion matters This is an argument in favor of demand having leveled off.
- pigpop 7mo agoOnly if nothing changes. Right now, people are running agent frameworks like OpenClaw on their own hardware or a VPS and the frameworks are often single person projects. This results in all sorts of problems but you can pick an easy solution from history which is to create a walled garden service for running these agents where you can provide security and standardization. If that platform also allows trusted services to integrate then they can provide end to end security guarantees. They also benefit from improvements to the models themselves making them more difficult to subvert. Creating something that is secure enough for the average person to entrust their credit card to is not an impossible task.
- pydry 7mo ago>The typical person is using LLMs not at all as it pertains to their daily life tasks. This doesnt track at all with my experience. Everybody is using it everywhere. Moreover people are using them for daily life tasks even when it is not an appropriate use of LLMs - e.g. getting medical advice as you referred to or writing emails which are clearly pissing off their coworkers. In this respect I see it as akin to radium - a new technology that got a little too fashionable for its own good when it first emerged and which will likely have many use cases scaled back.
- user34283 7mo agoIn my experience people vastly overestimate the competence of doctors. Getting medical advice from LLMs could be life saving. Personally I experienced this when a specialized doctor believed a drug interaction to be the opposite, thinking A hinders the absorption of B, when actually it hinders the clearance, tripling concentration of B. Without AI, I would have been clueless about this and could not have spotted the mistake. I don't know if it would truly have been critical, but it did shake my confidence in doctors.
- TheScaryOne 7mo ago>Everybody is using it everywhere. No one in our Auto shop is using AI. One of the new diagnostic tools was demo'd with AI, and none of us were having it. It's about as accurate as Googling your symptoms. My mother had an AI powered lung scan that came back with Stage 4 Cancer. The Oncologist got called in (for a fee!) to tell us it was just early stage COPD.
- raincole 7mo agoIt is quite hard to imagine how the demand is saturated now. I think any company that uses a sliver of AI will happily increase their token consumption 100x if it's free.
- pydry 7mo agoExecutive FOMO disease is being exploited by the model providers to push for maximal token usage even when it is pointless. This includes encouraging people to set up elaborate multi model set ups (e.g. "gas town") for coding that do not meaningfully improve productivity but which certainly do cause token usage to explode. It also includes encouraging execs to use token consumption as a proxy for productivity - almost akin to SLOC. AI has a halo right now and the managerial class seem to be willing to forgive almost any failure because the promise is so enticing. We're at peak expectations right now. They will soon start to be less forgiving when the warts which are intrinsic to LLMs remain unsolved.
- irke 7mo agoYep - it’s impossible to separate experimental tokens vs value creating ones. Ultimately the performance will be assessed via the income statement and cash flows of customers of the model producers. Frankly in the window pre-IPO it’s in the best interests of OAI et al to show a line going to the top-right in relation to tokens, in their prospectus. What does that mean? Strategic manipulation.
- monknomo 7mo agonobody know how to measure software productivity + ai is supposed to mean productivity goes up = more ai means more productivity As best as I can tell, that's the thinking. It's one number, it's very easy to find and manage, and there is a belief that it directly measures productivity. I disagree that it does; seems to me the throughput of useful features is a better measure, but I'm not in the drivers seat on this one
- irke 7mo agoIncremental revenue and cost-savings, at least for enterprises, is where it would show up. There’s also a present value consideration - if LLM’s make those dollars come into existence closer to the present, they are worth more. The personal use case stuff is messy and subjective.
- kmeisthax 7mo agoI thought we were going to hit token saturation years ago, but they keep inventing new ways to use tokens. Like, instead of asking a chat model to write something and getting ~1000 tokens out of it, you now have an agent producing ~10,000 tokens - or, worse, spawning 10 subagents that collectively burn ~100,000 tokens. All for marginally better answers with significantly higher compute usage. Personally, I would have used all those tokens to generate synthetic data for IDA (iterated distillation and amplification) so that the more efficient 1000 token/answer chat model can answer more questions, but apparently that doesn't justify an insane datacenter buildout.
- azinman2 7mo agoEveryone is interested in using less tokens to accomplish the same task.
- user34283 7mo agoMarginally better answers? Claude Code and co. can now analyze an enterprise codebase to debug issues in a system with multiple services involved. I don't see how that would have been possible at all in the past.
- Analemma_ 7mo agoWe’re not even close to demand saturation with tokens. Have you seen the people rending their garments with rage that Anthropic and Google won’t let them use their flat-rate subscriptions to burn millions of tokens per hour on OpenClaw? And that’s a tiny set of die-hard tinkerers. The ceiling of token use when everyone has something akin to OpenClaw just running as a background process on their phone is way higher than there’s supply for right now. Jevons paradox is still in full force.
- Macha 7mo agoIs that not appealing to those users _because_ its a subsidised flat rate? Like those users could go and swap to API pricing right now if they wanted to, but at API pricing they don’t want to
- Analemma_ 7mo agoRight, but that just proves there's tons of pent-up demand waiting in the wings as token prices fall.
- Marha01 7mo agoDemand for top models is definitely not saturated, at least when it comes to programming. If I could afford to use 5x more Claude Opus 4.6 tokens, I would!
- fatata123 7mo ago[dead]
- hajile 7mo agoDemand is relative. How many Claude tokens would you buy if they had a 10x price hike? The market has achieved it's current saturation level with loss-leader prices that remind me of the Chinese bike share bubble[0]. Once those prices go up to break even levels (let alone profitable levels), the number of people who can afford to pay will go down dramatically (and that's not even accounting for the bubble pop further constricting people's finances). [0] https://www.youtube.com/watch?v=FQrEDq8KPiU https://www.youtube.com/watch?v=FQrEDq8KPiU
- pigpop 7mo agoIf they've already built themselves a loyal customer base (which is usually the point of fighting a price war) and the customers are happy with the technology they have, then if funding is tight and turning a profit is more important why wouldn't they pivot to optimizing inference by stopping further training, freezing the model versions, burning the weights into silicon and building better caching strategies and improving harnesses and tools that lower their cost and increase their margin? If all they do is hike prices then they'll lose customers to competitors who don't or who find a way to serve a similar model cheaper. The demand isn't going to go away purely through higher prices. Once people know something is possible they will demand it whether supply is constrained or not. That's a huge bounty for anyone who can figure out how to service that demand.
- philistine 7mo agoEasier said than done. What you're describing can take years to implement. Can OpenAI et al. keep burning cash at the same rate for two years while they wait for the salvation of custom silicon if the investments dry up?
- vonneumannstan 7mo agoPretty sure the entire markets for Storage, HBM, DDR5, etc are completely sold out for next several years. How is that saturated?
- zozbot234 7mo ago> The fact that public LLM usage is leveling off at a price of $0 Tne price is very much not $0, even 'free' models have usage capacity limits that equate to a shadow-price.
- veunes 7mo agoDemand is stagnating only applies to the B2C segment, where people are already bored of generating poems and funny pictures. In B2B, the demand hasn't even started yet because corporations are still terrified of shoving their NDA data into public APIs. The second local models and secure private clouds get cheaper, the enterprise is going to devour literally any amount of available compute just to automate internal document workflows