If they offer you two prices, one month to month and and other for 1 year, and the 1 year is discounted, I would think that the 1 year one is a commitment. Is this not the case? Why would they offer a discount compared to the month to month if there is no difference as to whether you can cancel?
Adobe offers 3 payment options. A yearly payment upfront, a monthly payment, or a monthly payment with a year long commitment. OP was on the monthly plan with a year long commitment.
As for why they would set things up like this? Who the frak knows? Pricing tiers is literally the primary means of legally scamming people. The only logic it follows is that people who believe it does follow obvious logic are easier to scam.
An invoice being just a few days over it's due date is indeed not really serious. I don't think it's a smart move on the restaurant either, if they had any intention on continuing the contract this just about kills it.
you crossed a really big gap moving from 'communicate' to 'creating policy'. I certainly do not trust Google in particular to write any policies, given that their whole business model is to attempt to sit at the boundaries between consumers and companies, or email senders or recipients, or job seekers and hirers. not a fan of Schumer, but Schumer should be soliciting input from Google, who is free to submit a public white paper, and NIST, and DJB, and citizens groups, and everyone else that might have a stake in the outcome.
If Google communicates to Schumer, then do you think Schumer would then sit down and write the policy, knowing very little about it?
In reality, many companies would get Schumer attention on crypto, and other regulators, the companies would use their expertise to craft sensible policy, politicians would work with that, run it by lots of other groups and politicians, and if it passed enough tests along the way, it might come up as a bill.
It’s not like Google, or any company, likely can just put in ludicrous things, and use wizard powers to make laws. If a company breaks trust, they will lose the ability to get ears. If politicians, or parties lose trust, they get unelected. So, in order to have sane laws regarding any complex topic requires huge specialist inputs, and those specialists became expert by working in that field.
There’s simply not a pool of such people sitting around unassociated waiting to write laws to specifications of random internet people.
Government tried to ban encryption when it was first developed. Private organizations had to fight hard to make encryption standard. Still do in places like Europe
> Current problems with EU lobbying: Corporate lobbying is over 60% of registered lobby spending.
Ah yes, Europe, famously friendly to business interests. Hence so many large multinational influential corporations domiciled in Europe and being started every day
Without the US Federal government, most states would be bankrupt (all the time).
California, New York, Texas, New Jersey, Illinois, Massachusetts, and Pennsylvania being the few exceptions that are net positive contributors that largely subsidize every other state (the other 43).
Losses are much more privatized staying private. Instead of hitting people's 401k or pension fund, this is mostly contained to a concentrated set of VC and PE investors, not large public markets.
The companies involved still come for the 401k/pension funds, they just now wait until the majority of the upside growth has been realized and then dump the downside on to 401k/pension funds.
What regulation makes it so that a large private company would have to go public? You have it backwards. Increased regulations make it more burdensome for a company to go public, driving companies like OpenAI to remain private. If you made it less expensive and burdensome to IPO (decreased regulation), you would see companies go IPO earlier.
This also coincides with a growing market for private credit and VC which certainly helps companies stay private for longer.
There was a rule[1] pre-2012 that forced public disclosure (akin to listed companies) for private companies when it had >500 shareholder (which counted employees with shares). This made it so that companies had a choice to stay private with all obligation of public disclosure or go public for added benefit of tapping public market.
In 2012 this was relaxed in JOBS Act which relaxed the 500 threshold to 2000 but more importantly it ignored employees so now private companies of gargantuan trillion dollar valuation and thousands of employees have no disclosure requirements.
So, this is a classic case of regulation that did well but was relaxed and now creates hidden risks.
I think they would have kept it under 500 if they had to. I doubt this is the determining factor. In fact a lot more than 2k investors have exposure through SPVs or holding companies on top of holding companies. So no, I don't think this was the determining factor that allowed OpenAI to stay private longer.
Seems really unfair to early stage employees as without this they would be much less likely to receive equity from employers. I guess it would force some companies to go public earlier but at the expense of employees who would get virtually none of the upside, and startups can't compete for talent.
> Seems really unfair to early stage employees as without this they would be much less likely to receive equity from employers.
We have historical data on how it worked out for companies that were pushed into going public by the old regulations... Microsoft, Google, Facebook, et al.
Their early stage employees did... pretty well... financially.
The only real difference from the employee perspective is that a lot of the money that made them rich came from public investors (who also had a chance to make a lot of money), whereas now it only comes from private investors and the public is locked out.
Regulations that limit the ability of investors to invest in private companies, although these have been weakened in recent decades, which helps fuel the growth of private credit markets that allow private companies to stay private.
I'd say it's the growth of private markets to allow companies to keep getting funding even at the $100 billion range while staying private that has fueled the trend to stay private rather than SOX and other new regulations for public corporate governance dissuading them from going public.
>Regulations that limit the ability of investors to invest in private companies, although these have been weakened in recent decades, which helps fuel the growth of private credit markets that allow private companies to stay private.
It's not that you couldn't stay private before, but there wasn't much benefit because after crossing that cap you had reporting obligations comparable to public companies anyways.
I searched around and your original claim doesn't seem too convincing. Recall the original claim was
>Regulations that limit the ability of investors to invest in private companies ...
The JOBS act raised the cap from 500 investors to 2000, but with VC funds, that's hardly an issue. Does Anthropic (and other unicorns) really need 500+ VC backers? It might change behavior on the margins, but it's hard to imagine that's the cause for the paucity of public listings.
The actual change that made it more tenable to stay private is arguably the carveout for employee stockholders, but summarizing that as "limit the ability of investors to invest in private companies" is a bit misleading.
It's because reporting requirements changed, in particular employees with stock options no longer counted as shareholders for the purpose of crossing the mandatory reporting threshold.
Before that change companies like MS were in essence forced to IPO, because they'd get all the downsizes of public reporting, without the benefit of accessing market liquidity. So once you were over the threshold, it made no sense to not go all the way.
That's no longer true, and has coincided with a huge expansion in private equity funding growth stage companies vs needing public liquidity. As a result these IPOs being done after their growth stage is largely over are offering the public a very different bet that tech company IPOs of the past.
Meta (formerly Facebook) was forced to take their company public because of how many private investors they had. It’s the Securities Exchange Act of 1934 and also the Jobs Act of 2012 which set these limits (currently 2000 shareholders is the limit). Companies use right of first refusal on their shares to keep the number of shareholders low.
I don't know, it seems like it's just fun thing to play around with. I don't think serious things are meant to be built on this.
I often want to play simple games like Pacman, space invader, breakout, tetris or some other random iteration. Sometimes there are non-spammy simple versions of this game but often there aren't. This seems like a pretty cool fix. And if they disappear in the future, who cares?
That's precisely how something ends up becoming ubiquitous. You, and everyone else, start having fun on it and then suddenly it's a locked-in platform monetized by them.
YouTube started exactly how you described it, some silly thing not meant to be serious and today powers multiple 100M+ businesses using it for content to reach mass audiences.
> I don't think serious things are meant to be built on this.
I read at some point that projects at Google didn't get a greenlight unless there was a reasonable expectation they could be used directly or indirectly by a billion people.
I always here things like "oh it's useful but dumb on some things", but it's just vague.
What is the test? What is a question that it fails at compared to humans? And no, you can't just say "find me the cure for cancer", but I believe there is probably enough intelligence in the weights that there is likely a cure in there with enough compute and the right questions.
The fact that you need to ask "the right questions" is why it's not AGI. A general intelligence should be able to ask of its own volition the interesting questions required to advance its goals.
I can’t predict how a novel intelligence could prove to me that it is intelligent. A novel intelligence would have to work out how to do that for itself
When it can replace a white collar remote worker without humans team realizing they work with the machine. And no, Agents are not like this whatever initial prompt and set of skills you give them. They still won't progress, learn and apply that knowledge like a human.
> What is the test? What is a question that it fails at compared to humans?
Human intelligence does not consist of answering questions.
And every day I have to say "No, you stupid clanker ...", so if this is "general intelligence", it's the intelligence of an idiot savant who is good at calculations but sucks at most other forms of intelligence.
It's no different than humans taking inspiration from IP and copyrighted works in their own creative endeavors. Imagine if programmers were unable to learn from open source. Or artists were unable to mimic styles and storylines. Musicians can't riff on things that others created.
It is different. The scale makes it different. It's different when it is all copyrighted works and IP. It's different when you solve Navier-Stokes by taking "inspiration" from a researcher's private work.
If it's "learning" is to be seen in the same context as a human, then the punishment/ repercussion for hacking and causing real harm should also be similar to what a human might recieve.
It cannot opportunistically morph between a human for benefits and a machine for liability.
> It cannot opportunistically morph between a human for benefits and a machine for liability.
Indeed. Though here it would be morphing between human and machine even just for pure liability, which is even worse.
We have no way to tell if a machine has an experience (in general and not only) when being positively or negatively rewarded for what it produces; even if we assume it does, we have no way to tell if punishments are experienced like mild scolding (and rewards like mild praise), or if the punishments feel like being burned to death at the stake (while rewards feel like a religious experience combined with an orgasm).
We are just beginning to scratch the surface of what these kinds of question even look like in mechanistic terms; all philosophical discussions before it about p-zombies and the Chinese room and so on, they are all no more useful than any other non-expert armchair experts discussing things.
Even the current research, such as it is, is probably only at the level analogous to humoral theory when we want something at the level of germ theory.
Given my opening was agreeing with you, I ought to draw your attention: the part you seem to be replying to here is focused on the case where we really do want to know if we should treat the AI as we treat humans, and if so what punishing it looks like, rather than as property where we punish the owner.
> If a dog bites, we don't wait to take action until we figure out a way of teaching the dog the experience of guilt or punishment.
When we invented the concept of legal liability, our species was broadly still animistic and panpsychic. The concept of a "scapegoat" is named after the idea of literally putting the sins of a village into a goat and driving it away.
After doing that for perhaps 4500 years, we are now in the position to do as you say for e.g. dogs (and also machines).
What's the difference between getting a speeding ticket from a cop using a radar gun, and hundreds/thousands of automatically issued tickets from a combined radar/ALPR?
I think they're just meant to be friendly. I don't think it's that deep. They're useful and not scary and its marketing is meant to project that image.
You can consider the cute & fuzzy presentation of the new consumer AI agents an admission that the doom and gloom so far has been a marketing mistep. It's good that companies are trying to rectify the image of AI.
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