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Ask HN: Will LLM-commodification cause growth to continue without a correction?
Seems like the broader industry is waking up to what many folks have known for a while — models themselves are not a protective moat. They decay quickly and using them for basic tasks like structuring unstructured data is quickly becoming commodified.
What I didn’t totally appreciate until now is how that shifts us off the course where a few frontier labs end up becoming ACME mega corp which run the whole world and capture everyone’s money.
Power and value shifts to those who figure how to leverage LLMs to create value. Similar to how the use of a particular programming language is rarely the key to success and ISPs aren’t in charge of everything. Rather, the ability to turn code and a connection to people via the internet is the key to success.
So that makes me wonder - is the dot-com style correction in the industry required before we truly get a wave of exciting new companies emerge which upend society through the use of LLMs. Or can that shift happen without one?
I struggle to decide how this compares/contrasts with the dot com era. Where we had both the dot.com bubble burst and the internet totally change society.
- alephnerd 7mo ago> models themselves are not a protective moat This has already been known for 4 years now amongst my peers. Growth Equity raises like OpenAI's $110B round is not a Venture Capital raise nor an LBO or Mezzanine. > is the dot-com style correction in the industry required before we truly get a wave of exciting new companies emerge which upend society through the use of LLMs Nope. The Application layer along with Reinforcement Learning and DeepTech funding for hetrogenous computing and quantum/post-quantum has been hot for the past 2-3 years. Most are in stealth. Most are B2B and Enterprise. Most of those founders don't use HN, as HN has an increasingly negative reputation amongst people in the space, and because HN's userbase has increasingly become more European individual contributors and less Bay Area, so the signal to noise ratio has dropped dramatically > I struggle to decide how this compares/contrasts with the dot com era Becuase that is not the best comparison when looking at the economics of the industry. A better model is the rise of hyperscalers and SaaS. Foundation models and Agents are an additional abstraction layer packaging distributed compute, just like how hyperscalers and SaaS packaged compute into easily distributable applications.
- AbstractH24 7mo ago>> is the dot-com style correction in the industry required before we truly get a wave of exciting new companies emerge which upend society through the use of LLMs > Nope. The Application layer along with Reinforcement Learning and DeepTech funding for hetrogenous computing and quantum/post-quantum has been hot for the past 2-3 years. How does this deal with need for a correction in overvalued companies? And the impact on those who invested in them? You still have a situation where there’s insane excess capacity built out. Akin to fiber during dot com era. And the fallout from when companies like OpenAI need their valuation adjusted. Chewy proved Pets.com thesis right. But that didn’t stop Pets.com from failing as part of a bubble bursting. >> I struggle to decide how this compares/contrasts with the dot com era >Becuase that is not the best comparison when looking at the economics of the industry. A better model is the rise of hyperscalers and SaaS. Can you elaborate? The thing i still don’t see is how this creates the protective moat. As I type this out I think we’ll go through an era of “buying SaaS is stupid, you can just build it yourself” before some SaaS companies prove they can build and maintain better than you (we’re probably in the midst of that already)
- alephnerd 7mo ago> How does this deal with need for a correction in overvalued companies Which companies do you think are overvalued commensurate to revenue? The biggest issue we have for overvaluation is SaaS apps that raised in the 2017-22 period. Terms were extremely lax and made it difficult to pop their bubbles. > The thing i still don’t see is how this creates the protective moat Protective moats are not the name of the game and never have been - they only reduce TAM and make it difficult to exit because comparable multipliers are limited, making valuation extremely difficult. The primary moat has always been distribution, and this is where the foundation model companies have been extremely successful at. AEs who's Rolodexes included the F1000s all left for the foundation model companies and brought their clients with them. Additionally, companies are approaching foundation models the same way you would cloud - a multi-model and a multi-cloud approach to reduce vendor stickiness.
- AbstractH24 7mo ago
- andsoitis 7mo agoAre you curious for curiosity sake? Or is there a decision you're trying to make that is dependent on these dynamics?
- AbstractH24 7mo agoMostly curious for curiosity sake. But also questioning if the bleak outlook some have is overstated to some degree. Bleak outlook for the financial market, job market in general, and job market in tech specifically. As I think through it and weigh different factors I think I’m concluding “mid-term concerns are justified, but long-term there’s more reason to be optimistic and even excited than some might think. We’re not headed to a distopioan future.”