Yeah it is so absurd. The going cost of a politician in local California politics is on the order of $30-60k a year. Very inexpensive when they vote on policies shaping billions of dollars worth of sales.
Clerky is great, Stripe is really buying all of the great product companies. I feel like with Clerky and Stripe Atlas they, Stripe now controls all of the early incorporation infrastructure now. This feels deeply problematic.
I've used https://delawareinc.com/ to incorporate several companies over the years, and always had a good experience. Their website looks pretty old-school but it works well and their service is very prompt.
So I wouldn't Stripe controls all of the early incorporation infrastructure – just the flashy stuff (which I'm sure is great too).
Yeah, it's not even close. Stripe Atlas is a very small part of the market. It doesn't mean the product isn't good but every year, over a million new businesses that are formed and of those that are incorporated, I'd guess that a very small fragment are incorporated through Stripe Atlas.
Most businesses in the state I live in, as well as the states around me (what someone in SF or NY would call flyover) are handled by a registered agent (trivial, not even in a fee to become an agent in most states, just a valid local address) or the owner.
tbh I still don't understand why anyone bothers paying anyone or anything to do the paperwork, it's not like Federal taxes
Yeah, few things are as complex for a business in any industry that has ever gotten caught in the nation's political sights. For example, if you provide some sort of VoIP service, there's levels of nested rules that fill books, in part due to the breakup of the Bell System later coming into full contact with the internet. Plenty of carve outs, loops, and all manner of grandfathered elements for everyone.
The only thing more complicated than Federal taxes is environmental regulation. Everything else is simpler.
A C corporation can still make a lot of sense for a small business depending on the nature of the business and the interests and needs of the owners.
C corps can offer a lot of advantages in terms of shareholder and employee benefits, particularly around healthcare, and QSBS is a huge benefit for qualified businesses and owners who might one day sell the business.
>Vaping is not healthy but there is a lot less material inhaled. No fine particles which do real damage.
Propylene glycol covers the alvoelae and over time (~15-20 years) blocks uptake of oxygen, causing respiratory failure and a slow, painful death.
Vegetable glycerine coats the lungs and over time (~10-25 years) blocks fluid from draining out of the lungs, causing congestive heart failure/pulmonary edema. Which ends up causing one to drown in their own bodily fluids and a slow, painful death.
If you disagree, please cite any long term studies that disprove the above. Thanks!
>You shouldn't ask for disprove studies if you don't provide proof studies.
My point was that we don't know what the long-term effects of vaping are. Because there hasn't been time for the longitudinal studies that will tell us what those effects are.
I requested studies refuting those claims because I know they don't exist. I also know that studies confirming such claims don't exist either.
Making the statement that "...vaping is still unhealthy but less than smoking plant matters" is disingenuous because we have no idea what long-term (note that qualification) effects vaping does or does not have.
It might be that vaping increases human lifespan by 80%. Or it might be that vaping decreases lifespan by 25%. Or it might be that vaping either causes or prevents dementia. We just don't know. It may be that none of those things apply. Who knows? Not me. And not you or anyone else. Yet.
Because vaping hasn't been widely used for long enough to make claims about its long-term effects.
My claims are just as valid as yours ("...vaping is still unhealthy but less than smoking plant matters").
That was my point. My apologies for expecting you to make the conceptual leap and understand the above by making similarly unsupported claims as the one you made. I guess that wasn't the best way to do so. I'll try to do better in the future.
Im not confused. A lot of the context you are inferring is just in your mind.
It's funny to see someone invent a narrative then have a conversation with himself while trying to gaslight another person that they invented the narrative.
Fable is insanely annoying. It treats me like an incompetent, suggesting when something is in my expertise that I'm actually wrong. And then it will simply refuse to engage or do what's asked. Anything related to present day American Politics is strictly off limits. How is this truth seeking, or rational? Model misalignment increases when post-training is done on non verifiably domains. Scary times indeed.
Yeah, this is correct. There are so many large multi-trillion dollar companies coming to IPO, which if your are passive index holder and you are trying to track the market it is correct for these companies to be included. And besides SPY has chosen not to fast track where QQQ has. It is a free market, and folks are free to NOT buy QQQ. So I'm not sure why this is a point of debate.
"People" in this instance aren't always informed buyers. Sometimes they're buying an index fund because they don't have the time to research individual stocks and sometimes it's their pension investing.
The normal seasoning period is there for a reason. There is a massive downside to premature inclusion of a stock that is initially overvalued and then settles to a reasonable/sustainable value.
> Sometimes they're buying an index fund because they don't have the time to research individual stocks and sometimes it's their pension investing
Then they should buy a broad-market fund. The kinds in which new issues are a tiny fraction or, if it’s following something like the S&P 500, not included at all. Following the Nasdaq 100 and then complaining it has too many risky tech plays is a bit silly.
The reason you know the people complaining the most about this aren’t serious is that they don’t lead with crsp and vti.
They did change their rules, they did it fairly specifically for spacex and it did drive inclusion in a major index fund (perhaps the biggest one).
Now me personally, as a holder of vti I am good with the change and my included exposure to spacex. Further I think mostly complaining about the inclusion/exclusion of a single name in an index _defeats the point_.
But for those decrying the shenanigans crsp and vti are the example to go with.
how embarrassing! Look, your joke was "If it's only 1.2%, hey, that's not that much, just give it to me for free!" We don't have to believe SPCX is worth whatever it's trading at today, but that 1.2% isn't simply being given away. Under capitalism, money is exchanged for goods and services.
FWIW, I read their joke differently: you were the one who said "only 1.2%", and they turned that on you by asking for you to part ways with "only 1.2%" of your net worth.
They are not questioning money exchange, they are questioning the "only" part, claiming this is significant.
My (non-motivated, don't have NASDAQ or SpaceX) take is that isn't this how these funds are supposed to behave? You buy NASDAQ if you can take risk, S&P otherwise. If you check out what companies are in the NASDAQ, it's not like it's not majority tech, of which a lot of them are AI-based, so adding SpaceX to that mix is reasonable - and if they waited a year or so for price discovery, and had SpaceX been a popular choice (still can turn out like that), then investors would've missed out on those gains.
Yes, and there are tiers of risk. What people are complaining about is that with the recent behavior, NASDAQ has arguably increased the level of risk involved. If it's as simple as "buy NASDAQ if you can take risk" then that would imply it should pull in meme stocks when the WSB crowd are doing their diamond hand thing.
He created Django, what do you mean he's not an engineer? Also 'low-effort??' his posts are extremely in-depth, clearly very thought through with a significant amount of time and energy. Additionally he does perform multifaceted checks across LLMs in many of his other blog posts.
The charitable reading is that they meant “ML researcher or ML engineer” with the latter meaning, I guess, an engineer who works on developing LLMs not just using them.
> He created Django, what do you mean he's not an engineer?
I specifically said that he is not an ML engineer (emphasis on ML), so I'm not sure what Python web frameworks have to do with anything.
> Also 'low-effort??' his posts are extremely in-depth, clearly very thought through with a significant amount of time and energy
And yes, low effort. Pelican was low effort, his Fable test was low effort, his HN filter etc. Read the discussion in the comments under the Fable test, it's not just my opinion. There was also another example a few months ago. You can search for it, I don't keep track of these things.
I discussed this with him directly after he called himself an "ML expert" in comments.
This is a classic case of the Gell Mann amnesia effect. I read ML papers and work with ML, but to people outside the industry, his writing can look "extremely in-depth" even though it really isn't. People I work with have the same opinion.
> clearly very thought through with a significant amount of time and energy. Additionally he does perform multifaceted checks across LLMs in many of his other blog posts.
I have never seen an article by him about any model that I would describe that way.
And the most revealing sign that he is not an expert is the type of questions he asks and the mistakes he sometimes makes in the comments here. They show why he is not capable of doing any technically in depth evaluation (at least with his current knowledge level).
If you actually want to learn something as a layperson, read articles written by ML PhDs like Sebastian Raschka or watch Stephen from Welch Labs etc. that are directed at general audience.
We at HN: https://xkcd.com/2501/ to basically say that I think you might be considering low-effort what’s actually an attempt at simplifying - which is arguably higher effort
> you might be considering low-effort what’s actually an attempt at simplifying - which is arguably higher effort
I'm not saying that simplifying complex topics is low-effort, good simplification can obviously require a lot of work and I fully agree here.
What I meant is more that some of these tests feel methodologically sloppy, they are too shallow, miss important technical context, do not control for enough variables etc, yet the conclusions are sometimes presented lets just say... too strongly, as I don't want to be too harsh.
It is more than just books published pre-2022, but I've noticed that it is necessary to buy books __printed__ before 2022. Recently I've noticed aggressive misspellings and misquotations in old books printed in '25/'26. I believe these errors are being introduced because the publisher is using an LLM or some similar tool to correct any prior errors but is introducing more hallucinations. Or perhaps the cause is people caring less than they used to?
I'm curious who the ideal customer of this should be. If we're a startup with our own harness, are we a good fit? What would qualify us or disqualify us from being a good user?
I think startups are a great fit. Getting a really good agent out of the box lets you scale and give your customers value fast. All you need to think about is the business logic: system prompts, tools to give the agent, skills, etc. You won't need to spend time on building the infra layer, orchestration loops, memory, implementing automations, etc.
Yeah I know some of my team members have invested a lot of time in this. Could definitely be worth chatting with them on what improvements could be made here. We're starting to deprioritize our consumer facing agent harness, in favor of more infrastructure level improvements we are making.
Developers with customer-facing chat products are the ideal customer.
If a startup has a specific flow they want the agent to take and their traffic is bursty, then I'd recommend using a framework like Mastra and deploying onto a sandbox.
For long-running always on agents where it's important to learn the users preferences overtime, our approach is the highest ROI.
Interesting. We definitely have long-running agents where certain preferences are key. However, some of the preferences are likely going to be shared universally across our customers. Is there some way of triaging this feedback into permanent improvements in agent performance?
It is possible to do it (ex: run a background process that analyzes memories across customers and updates the system prompt based on the findings). A specific implementation would depend on your application. Feel free to email me rajit@prismvideos.com if you'd like to talk further.
reply