> For one, on the margin people are willing to pay a lot for slightly better models. I know personally the value the LLM adds to my workflow is considerably more than the $200/m I pay the frontier labs. I have no interest in optimizing that to get it slightly lower. There are a very vocal minority that optimizes this or companies whose LLM expense is marginal, but I think that's the minority (correct me if I'm wrong, curious what their customer base looks like)
Enterprise is how Claude/OAI make their money. Enterprise companies absolutely optimize around costs for infra, it's like an entire job category.
> Also the actual LLM is a tiny portion of the value added. Anyone that tried to build agentic solutions from LLM apis quickly realizes that a huge value is the Claude Code / Codex harness. There are open source implementations like OpenCode but they're not nearly as good.
Claude and OAI are not valued at $1T because of their harnesses
> Think about it another way. Consider how much money Microsoft spends on maintaining Excel. There are open source alternatives that have >90% of the functionality, they'll even work w/ Excel files and generate them. Google sheets is probably 99% and available to everyone and better in a lot of regards. But the immense value spreadsheet software produces workers above the $100 or whatever a year makes it so that there is a real moat and no one bothers exploring alternatives.
Enterprise excel is like $50 a month, the closed source labs charge orders of magnitude more than that per user per month for enterprise, and want to charge more if they can to maintain their valuation. I spent $20 in an afternoon yesterday using my work plan for one workflow for reference, I probably spend at least $50 a day and I don't even do that much coding anymore.
I think that's true for now, but eventually there will reach a point where a model is good enough (approaching that right now with frontier models) and there will be diminishing returns. I don't need a PHD level Genius to build me an analytics dashboard for example, so why would I pay for a model with that level of intelligence when I can (eventually) self host a good enough model and run queries for electricity cost + hardware.
I did it for a summer in University and I didn't have to work night shifts, it was amazing to be honest I would do it again if I never had to work nights.
The US had elections during their civil war in the 1800s, They had elections during WW2, major wars cannot even stop US elections legally. Doesn't mean he won't try, but it's not something he can do AFAIK.
I use the newer claudes and letting them work for 1 hour leads to horrible code over 50% of the time that does not work. Maybe I am not the target person for agentic tasks, all I use agents for is to do product searches for me on the internet when I have specific constraints and I don't want to waste an hour looking for something.
Maybe I am just using them wrong, but I don't know how my knowledge can be out of date considering I use the tools every day and pay for Clause and Gemini. I genuinely think GPT 5 was worse than previous models for reference. They are for sure marginally better, but I don't even think 2x better let alone 10x better.
Claude 3.5 came out in June of last year, and it is imo marginally worse than the AI models currently available for coding. I do not think models are 10x better than 1 year ago, that seems extremely hyperbolic or you are working in a super niche area where that is true.
Sure but pensioners care about consistency vs. gross returns. You really don't want your pension to lose a ton of value in a downturn because people are constantly drawing from it, it's a risk off investment. Bonds are also poor investments compared to an index fund from a gross return perspective, but that's not why people/funds buy them, they buy them to lower risk.
> There is a middle ground that is quite common across Europe: a private company that has the government as a shareholder.
Interestingly, Quebec in Canada has been loosely following this model recently and it's working great. Long video but interesting if you like infrastructure stuff:
TLDR: CDPQ invests on behalf of the Quebec Pension Plan, and has been building infra on behalf of the pension plan across Quebec (and Canada) to great success comparatively.
CDPQ has been good at making transit in Canada, but they are working on behalf of the Quebec Pension Plan so it's kind of a weird situation. I largely agree with you.
The difference in quality between model versions has slowed down imo, I know the benchmarks don't say that but as a person who uses LLMs everyday, the difference between Claude 3.5 and the cutting edge today is not very large at all, and that model came out a year ago. The jumps are getting smaller I think, unless the stuff in house is just way ahead of what is public at the moment.
And I get fast enough autcomplete results for it to be useful. I have and NVIDIA 4060 RTX in a laptop with 8 gigs of dedicated memory that I use for it. I still use claude for chat (pair programming) though, and I don't really use agents.
Oppenheimer was considered to be a left wing agitator, there are tons of very smart people who are pro labour organization which the US has historically seen as left wing agitation.
> I can think of a couple who were absolute nightmares. I can think of a couple others who were an absolute dream. The worst small-time landlord was WAY worse than the worst big property management firm, but the best small-time landlord was far better than the best big property management firm I've been a tenant of.
This is basically my experience I wrote about above, the downside risk for mom and pop landlords is way way worse than corp landlords in my experience (and pretty much everyone else I know).
I (and most of the people I know), have had the opposite experience as you. Essentially everyone I know has moved into corp landlord situations because the downside risk is a lot lower and there is a paper trail if you need to dispute anything. I have like a 50% hit rate on mom and pop landlords being awful, I can give three examples off the top of my head:
1. New landlords bought a place I was living in and wanted to do in their words "minor upgrades to the house", but during the construction they would "keep it livable" and not require me to move. I came back after work one day to my water being off (and a toilet removed), and they didn't turn it on for two weeks after that (and kept the toilet removed). I had to get a lawyer involved for rent reimbursement.
2. My water heater broke and flooded my house in the middle of the night. The landlord took 1 month to start fixing the completely flooded apartment, and then the landlord tried for a year (threatened legal action as a bluff) to get me to pay for the new water heater despite it being their property, and maintenance being in the lease as their problem. I obv never paid because it was basically just a shakedown.
3. My landlord tried to just not pay me a month of rent owed after they sold the property with me living in it. He called me several times trying to "make a deal", and I told him that it was a cost associated with him selling the house and that I would not leave until he paid me the month owed. He waited until literally the last possible day to pay me and yelled at me on the phone that I was being unfair despite it just being money he owed me.
Every corp landlord I have had has been by the book. Yes my rent has gone up marginally, but at least there is a paper trail and they do not try to do any of the crazy stuff I just described.
That being said, I did have one mom/pop landlord who built me a deck with a bike locker over the course of a summer once, that guy was great.
> What makes you think DOGE is being blasé with personal data?
Why should a government agency run by a random unelected tech ceo even have the option to be blasé with personal data? Like I thought this website was pretty vehemently against things like the Patriot Act giving the NSA granular personal data and backdoors into communication, that at least had the guise of "national security" backstopping it. Giving a new department personal data access for no reason other than "government efficiency" (no actionable goals given by the department btw) is significantly more tenuous than "national security".
100%, I was talking specifically about just tree planting. Trees are great capture tech, but horrible storage tech, so tree planting alone is not a good carbon capture solution. Biomass burial is (imo) a great and relatively simple solution at the moment because we have a bunch of empty mines to use. There is also research being done on putting biomass in a chemical bath that turns it's CO2 into some form of storable liquid and then storing that, but I can't find a link for it at the moment.
Enterprise is how Claude/OAI make their money. Enterprise companies absolutely optimize around costs for infra, it's like an entire job category.
> Also the actual LLM is a tiny portion of the value added. Anyone that tried to build agentic solutions from LLM apis quickly realizes that a huge value is the Claude Code / Codex harness. There are open source implementations like OpenCode but they're not nearly as good.
Claude and OAI are not valued at $1T because of their harnesses
> Think about it another way. Consider how much money Microsoft spends on maintaining Excel. There are open source alternatives that have >90% of the functionality, they'll even work w/ Excel files and generate them. Google sheets is probably 99% and available to everyone and better in a lot of regards. But the immense value spreadsheet software produces workers above the $100 or whatever a year makes it so that there is a real moat and no one bothers exploring alternatives.
Enterprise excel is like $50 a month, the closed source labs charge orders of magnitude more than that per user per month for enterprise, and want to charge more if they can to maintain their valuation. I spent $20 in an afternoon yesterday using my work plan for one workflow for reference, I probably spend at least $50 a day and I don't even do that much coding anymore.