And you can sell your tulip. But if the mania stopped and you suddenly _couldn’t_ find another person to sell it to, would you now be upset you paid $5000 for a tulip? What’s the value at which you wouldn’t be upset? Ok, that’s the intrinsic value of a tulip to you.
The thing about a profitable business that is different from a tulip is that it can at any point decide to issue a one-time or ongoing dividend. It can sell off parts to create cash. It has lots of optionality. Public companies have even more liquidity, which creates more optionality.
Even if you don't have immediate liquidity, it would obviously be worth something to have a slice of e.g. Rolex SA. That's obviously different than owning a tulip.
Dividends are also one way of income in retirement, much more predictably than selling stock. The yields are worse than bonds, but they can be considered to be mostly to rise with inflation, albeit on a year or two delay. Dividends also act as a discipline to keep management focused on the business, since you need to pay real money to shareholders, instead of just doing whatever good idea you have, regardless of whether it is a net benefit to the company.
I disagree with the last statement. The reason why most companies in the US have at least a nominal (one penny per share) dividend is that many pension funds have a requirement to only hold shares that issue dividends. Pension funds are all tax sheltered, so they don't need to worry about paying taxes on dividends. For retail investors, dividends are mostly worse that share buy backs. Why? Dividends are taxed, and the money needs to be reinvested.
> The only reason to do a dividend is because people like the feels of getting a cash payout.
Not really, when capital entities came up, the initial goal was to deliver return on invested capital,i.e. something "you get out of the business/back".
Or do you think back in 14th wenn Dutch East India Company was created, that you could by shares and sell them later to a higher bidder after the mission was accomplished? :-)
That’s the story, but it’s bullshit. The underlying intrinsic value of a stock can only be materialized if the company liquidates and you receive a share of the sell off of its assets. How many publicly traded companies abruptly decide they’re tired of the business, stop in their tracks, and liquidate their assets? This only really happens if the company is acquired or if it goes bankrupt. Acquisition is the closest the story comes to truth, but it’s also just forced sale to a greater shmuck. If a company goes bankrupt, a tiny fraction of the current stock price would be realized into cash for common investors because of all the privileged investors and lenders ahead of them, not to mention that the actual value of capital assets etc probably doesn’t cover all the losses (the company’s going bankrupt after all). The value of the underlying capital assets are essentially never returned to the common investors, and the idea that you own a portion of them is in practical terms a lie.
> The underlying intrinsic value of a stock can only be materialized if the company liquidates and you receive a share of the sell off of its assets.
This is wildly incorrect. A profitable company can decide to begin paying out dividends, which can eventually return > 100% of the investor's purchase price. A company can issue more stock or bonds to raise cash to pay investors. A company can spin off assets to raise cash to pay investors.
Your framing is very much like a short-term PE investor, and if you look to their playbooks you can see there are many ways for intrinsic value to be realized while leaving an operating business behind. There are any number of stories where PE investors make big profits and then turn around and resell the company for more than they paid.
>If a stock never intends to pay dividends, the value of the stock is simply the price the next shumck is willing to pay.
So, by construction, we're talking about the value of shares in a hypothetical company that admits it will _never_ pay dividends. And we're asking what value that stock has BESIDES selling it to another shmuck, so for the purposes of the exercise, it's clearest to just imagine we are not allowed to sell to someone else. Most people will tell you that the stock nevertheless still has value because you own a share of the company itself, which entitles you to a share of its liquidation value. However, the argument I've been making here and in other posts are that:
a. A company tends to be "greater than the sum of its parts". The techno-social arrangement of people and business flows is part of what allows the company to be profitable, so disassembling it, selling off the machinery and returning whatever cash assets it had to the investors is unlikely to cover the market cap (at least, as they are priced today in current climate)
b. Even looking at whatever value IS leftover, the circumstances that lead to you realizing that value are extremely fraught / carry other baggage. It usually doesn't lead to common investors getting value back out, and cannot realistically be a justification for the current valuation of most big non-dividend stocks. For instance, consider how valuable it was to own a share of the underlying capital assets of Bed Bath and Beyond when it declared bankruptcy. It was far worse than just point 'a' ("oh no, we sold all the inventory and real estate it still didn't cover the market cap"). No, if you were a common investor, you essentially got $0 because there were lenders and preferred investors ahead of you in line that consumed those assets and left you crumbs.
c. Acquisitions are the best chance of turning your "ownership of the company itself" into dollars... but this is also slightly cheating, because you're appealing to sale of the shares to another entity again. Now, in real life, if a single entity owned the entire company, it would probably be able to extract some of the business's cash flows (a power which common investors lacked). So it's not quite fair to call the acquiring entity "the next shmuck", since they may be able to realize actual $ value in a way that the common investor couldn't. But technically, if we're playing along with the thought exercise, the premise is that the company continually reinvests in itself and refuses to pay out to the owners. If somebody buys out the company, takes it private, and redirects the profits to their own coffers, the new owning entity is essentially getting dividends by another name.
Yes, the profits it pays out are the one thing that actually makes sense, but the premise of the grandparent post was to ask what a share is worth _without_ dividends. And the answer is that shares are intrinsically worth very little. Liquidation value (actual liquidation - bankruptcy or going out of business or an exchange closure) is rarely ever practically realized for common investors. Even if you’re trading on the discounted expectation of a larger liquidation pie, nearly 0% is still nearly 0%.
Voting rights are also not valuable by themselves - they are only useful to steer the company towards greater future payouts, which means you are appealing to some other entitlement to value.
If you zoom out, a company is a temporary arrangement of people and things that makes more money than it spends _over time_. They are not really designed to accumulate and store value in and of themselves. The machines the employees use to do the work is a small fraction of the overall utility of a living breathing business. The valuable part is the capacity of this techno-social organism to reliably and continuously make profit, which is far greater than the sum of its parts. So if the profit that’s being earned is never paid out to stakeholders, then there’s no point in being a stakeholder. If the profit is redirected to make the organism bigger, then you are trading now-dollars for future-dollars which must be appropriately discounted. If everyone expects a company to do this forever, then the correct price is what the expected liquidation share should be, and that number is basically zero.
Yet, stocks that do not pay dividends exist at high valuations. What that tells you is that modern day stock trading is tulips: the lion’s share of the value derives from a temporarily stable, shared, _correct_ perception that someone else will buy it back from you.
The reality is that general investors are the greater fools in this arrangement. The prevalence of preferred stock is a tell that there are owners and there are “owners”. What we should do is recognize this and admit that the big initial investors and employees themselves are the owners, because they are the group small enough to actually realize liquidation value (should it ever be necessary). The public investors have no realistic claim on that value, so their shares should be more clearly labeled as dividend rights, which would cause them to be priced as such.
By this logic all money is inherently worthless too, and every time you buy a sandwich at the local corner shop you're just passing off that worthless piece of paper to the next schmuck.
In reality, things have value because people believe they have value. That doesn't mean every company that doesn't pay dividends is a speculative tulip bubble.
Amen. It always baffled me that cross compiling was ever considered a special, weird, off-nominal thing. I’d love to understand the history of that better, because it seems like it should have been obvious from the start that building for the exact same computer you’re compiling from is a special case.
A few things come to mind, but I wasn't even alive then so what do I know XD.
On one hand, it seems rather strange, because back in the early days of C (and later C++) there were far more CPU architectures in play. Every big Unix hardware vendor had their own CPU architecture, whereas today we only have about six. (In my mind: x86, arm, mips, risc-v, ppc, and s390x)
But it might be that in the early days of C/C++, development involved connecting to large shared Unix environments where the machine you developed on what always the machine (or at least the same type of machine) the program would run on, and also that those vendors weren't exactly incentivized to make developing for competitor's architectures easy.
The tough truth is that there already is a cargo for C/C++: Conan2. I know, python, ick. I know, conanfile.py, ick. But despite its warts, Conan fundamentally CAN handle every part of the general problem. Nobody else can. Profiles to manage host vs. target configuration? Check. Sufficiently detailed modeling of ABI to allow pre-compiled binary caching, local and remote? Check, check, check. Offline vs. Online work modes? Check. Building any relevant project via any relevant build system, including Meson, without changes to the project itself? Check. Support for pulling build-side requirements? Check. Version ranges? Check. Lockfiles? Check. Closed-source, binary-only dependencies? Check.
Once you appreciate the vastness of the problem, you will see that having a vibrant ecosystem of different competing package managers sucks. This is a problem where ONE standard that can handle every situation is incalculably better than many different solutions which solve only slices of the problem. I don't care how terse craft's toml file is - if it can't cross compile, it's useless to me. So my project can never use your tool, which implies other projects will have the same problem, which implies you're not the one package manager / build system, which means you're part of the problem, not the solution. The Right Thing is to adopt one unilateral standard for all projects. If you're remotely interested in working on package managers, the best way to help the human race is to fix all of the outstanding things about Conan that prevent it from being the One Thing. It's the closest to being the One Thing, and yet there are still many hanging chads:
- its terribly written documentation
- its incomplete support for editable packages
- its only nascent support for "workspaces"
- its lack of NVIDIA recipes
If you really can't stand to work on Conan (I wouldn't blame you), another effort that could help is the common package specification format (CPS). Making that a thing would also be a huge improvement. In fact, if it succeeds, then you'd be free to compete with conan's "frontend" ergonomics without having to compete with the ecosystem.
The paper came out of work on ENIAC and was adapted to follow the approach in the paper but Baby was built from outset to use that approach and its design much more closely matches the architecture that has been used by almost all digital computers since. I don’t dispute that ENIAC is important but it’s role is more nuanced than this article implies.
The von Neumann report was written after von Neumann had several discussions with the ENIAC team about how to make a better computer as a successor for ENIAC.
The report was not published formally, but it was "leaked", so it does not have any credits for the ideas contained in it.
Because of this, with few exceptions it is impossible to determine with certainty which parts of the report are original ideas of von Neumann and which parts are ideas that von Neumann might have learned during the discussions with the ENIAC team.
An example of an idea that certainly did not come from the ENIAC team was the proposal to use an iconoscope CRT as the main memory (which was implemented first in the British Manchester computers, so such a memory became known as a Williams-Kilburn tube). The ENIAC team had a different idea of what to use as a memory, i.e. delay lines taken from radars. Von Neumann replaced this suggestion with a CRT, because he thought that a random-access memory is better.
The von Neumann report had an exceptional importance because it defined with perfect clarity what a digital computer should be, which should be its structure and then provided a detailed description of how such a computer should be designed, which was good enough to enable anyone who read the report to build such a computer. This effect really happened, and a great number of teams at universities, government agencies, independent research centers like IAS and various companies, both in USA and in other countries, have built electronic computers in the following decade, exploring various design options.
There is no doubt that the clarity of the report is due to von Neumann and whichever were the ideas of the ENIAC team about a future computer, they were much more jumbled.
Because the ENIAC team did not publish their ideas (and they did not intend to, because they already wanted to monetize what they had learned about computers, by founding a private company), it does not really matter what they thought. The world has learned how to make general-purpose electronic computers from the von Neumann report.
ENIAC was a programmable computing automaton, but it was not a digital computer in the modern sense of the word, i.e. a digital system with 4 levels of closed positive-feedback loops (the complexity of a digital system is determined by the number of levels of nested positive-feedback loops, combinational logic has 0 levels, a memory has 1 level, an automaton has 2 levels, a processor has 3 levels and a computer has 4 levels; these are minimum numbers, as a real device may have more levels than strictly necessary, to achieve various advantages).
The ENIAC team’s decision to spin off and incorporate was surely pushed along by how they got screwed multiple times by the academics - Goldstine and Von Neumann, plus the university itself. It’s easier to celebrate the free publishing of ideas if your name is at least going to be on the paper.
It seems like you’re not trying particularly hard to avoid the idea of “monetizing” the computer to sound pejorative. It was the creation of the computer _industry_ that transformed the world and established the import of computers, was it not? You were never getting there without monetization. What good is the spread of ideas if someone, somewhere doesn’t eventually start selling computers? This grates especially hard given that the academics were the ones who acted unscrupulously by lifting their ideas and publicizing them without permission or credit. (“Leaked” is a charitable way to say “deliberately disseminated without caution”).
I agree the stored program is important, but the stored program is of ENIAC vintage, even if it wasn’t implemented on it. And Eckert and Mauchly definitively came to this idea before the involvement of Von Neumann. The thing is, they had an obligation to finish the machine they had promised to build for the army before pursuing such a major redesign. So all they COULD do was informally collect their ideas for a 2.0. Von Neumann arrives, absorbs what they’re up to, synthesizes it (including ‘the big idea’ that ENIAC was missing), and the rest is history. That synthesis is published without their names, and that is why we talk about the Von Neumann architecture. Look, I’m sure it’s true that the crispness of that paper can be attributed to Von Neumann, but it’s a non-sequitur to assume that Eckert and Mauchly’s ideas were jumbled. They were at least organized enough to be building a working machine in the background, and if we’re going to argue that the important thing was promulgation of enough information for others to replicate, than the practicum is more important than mathematical tidiness.
In fact, if we’re talking about how the ideas spread, the paper is frankly overblown. The Moore school lectures were really what caused the Cambrian explosion of electronic computing. There, you can find Eckert and Mauchly utterly central to the elucidation of how to build a general purpose electronic computer. And hey look, there they are, deliberately sharing the ideas out to interested practitioners, in a more pragmatic and direct way than the paper.
What I’m building to here is that E&M starting a company was not evidence that they were just out to make a buck. On the contrary, what it shows is that they had _foresight_ about what the next interesting chapter was bound to be. With the Moore School Lecrures, the ‘publishing of the ideas’ stage was over - the next step was to begin building more machines that could do more computation for more users. And while there was plenty that happened afterward to refine the theoretical model, they were absolutely correct that that’s where the action was. In fact, I think that if you look at what many of these proposed fathers of computing did next, it’s an excellent litmus test of how central they actually were. Some of the sillier ones like Atanasoff just forget about their supposed invention and go on with life - that’s a tell that they weren’t that interested in general-purpose, high speed computing. Whereas E&M’s follow-on work was to advance the field even in the face of great setback. This also completely deconstructs the idea that they were just thinking about artillery, or just thinking about weather. They were thinking about _computing_, and their careers afterwards demonstrate this.
I was sad to see you guys shut down - I think you were on to something with deterministic faster-than-realtime replay. Not surprised it was hard to find paying customers, but for what it's worth, my engineering self thought that you guys were solving the right problem. As far as I can tell, it's still not solved, and the shocking truth is that everyone is just Living That Way.
The other thing that is important is how to provide a more query-like interface to tease out the data you actually want your node to react to, yet in a way that will be deterministic. You need to guide users away from introducing non-determinism, which can be tricky because innocent things like a message buffer with a max size can lead to such situations.
I have talked with one of the key people at Xronos (https://www.xronos.com/), who are trying to attack related problems. Still, even they aren't quite as pre-occupied with _replay_, which is crucial.
I think the sad truth is that the second evolution of all this frameworking simply hasn't come together convincingly enough, and in one place, for it to gather momentum. It turned out to be hard. And now that it has taken too long, it's my bet that ROS2 and all of its imitators will get lapped by holistic deep approaches. Not the stupid stuff happening with these fake humanoid robot companies mind you, but still - something holistic and deep. Something coming out of the predictive coding research e.g., or world models, etc. Training in simulated environments with generative systems is going to lead to behavior so much more sophisticated than gluing together all of our little services. Roboticists have their own version of the bitter lesson coming soon.
I was sad, too. If there was a way I thought to continue doing it, I would. But as it is I'm actually considering getting out of robotics at this point, I've had enough of everyone "Living That Way".
Firstly, the models that pass the Math Olympiad aren’t the same models as the ones you’re saying “pass the Turing test”. Secondly, nothing actually passes the Turing test. They pass a vibes check of “hey that’s pretty good!” but if your life depended on it, you could easily find ways to sniff out an LLM agent. Thirdly, none of these models learn in real time, which is an obviously essential feature.
We’ll know AGI when we see it, and this ain’t it. This complaining about changing goalposts is so transparently sour grapes from people over-invested in hyping the current LLM paradigm.
There doesn't seem to be a super-rigorous definition of the Turing Test, but I don't think it's reasonable to require it to fool an expert whose life depends on the correct choice. It already seems to be decently able to fool a person of average intelligence who has a basic knowledge of LLMs.
I agree that we don't really have AGI yet, but I'd hope we can come up with a better definition of what it is than "we'll know it when we see it". I think it is a legitimate point that we've moved the goalposts some.
The real answer is that once LLMs passed a "casual" application of the Turing test, it just made us realize that the "casual Turing test" is not particularly interesting. It turns out to be too easy to ape human behavior over short time frames for it to be a good indicator of human-like intelligence.
Now, you could argue that this right here is the aforementioned moving of the goalposts. After all, we're deciding that the casual Turing test wasn't interesting precisely after having seen that LLMs could pass it.
However, in my view, the Turing test _always_ implied the "rigorous" Turing test, and it's only now that we're actually flirting with passing it that it had to be clarified what counts as a true Turing test. As I see it, the Turing test can still be salvaged as a criteria for genera intelligence, but only if you allow it to be a no-holds-barred, life-depends-on-it test to exhaustion. This would involve allowing arbitrarily long questioning periods, for instance. I think this is more in the spirit of the original formulation, because the whole idea is to pit a machine against all of human intelligence, proving it has a similar arsenal of adaptability at its disposal. If it only has to passingly fool a human for brief periods, well... I'm afraid that just doesn't prove much. All sorts of stuff briefly fools humans. What requires intelligence is to consistently anticipate and adapt to all lines of questioning in a sustained manner until the human runs out of ideas for how to differentiate.
ELIZA fooled plenty of people (both originally and in the study you just linked) but i still wouldn't say Eliza passed/passes the turing test in general. It just shows that occasionally or even frequently fooling people is not a sufficient proxy for general intelligence. Ofc there isn't a standardized definition, but one thing I would personally include in a "strict" Turing test is that the human interrogee ought to be incentivized to cooperate and to make their humanity as clear as possible. And the interrogator should similarly be incentivized to find the right answer.
Turing gave a pretty rigorous definition of the Turing Test IMO. Well, as rigorous as something that is inherently "anecdotal" can be, which is part of the philosophical point of the Turing Test.
First of. The Turing test has a rigorous definition. Secondly, it has been debunked for almost half a century at this point by Searle’s Chinese room thought experiment. Thirdly, intelligence it self is a scientifically fraught term with ever changing meaning as we discover more and more “intelligent” behavior in nature (by animals and plants, and more). And to make matters worse, general intelligence is even worse, as the term was used almost exclusively for racist pseudo-science, as a way to operationally define a metric which would prove white supremacy.
Artificial General Intelligence will exist when the grifters who profit from it claim it exists. The meaning of it will shift to benefit certain entrepreneurs. It will never actually be a useful term in science nor philosophy.
>Secondly, it has been debunked for almost half a century at this point by Searle’s Chinese room thought experiment.
Searles thought experiment is stupid and debunked nothing. What neuron, cell, atom of your brain understands English ? That's right. You can't answer that anymore than you can answer the subject of Searles proposition, ergo the brain is a Chinese room. If you conclude that you understand English, then the Chinese room understands Chinese.
> Searle’s response to the Systems Reply is simple: in principle, he could internalize the entire system, memorizing all the instructions and the database, and doing all the calculations in his head. He could then leave the room and wander outdoors, perhaps even conversing in Chinese. But he still would have no way to attach “any meaning to the formal symbols”. The man would now be the entire system, yet he still would not understand Chinese. For example, he would not know the meaning of the Chinese word for hamburger. He still cannot get semantics from syntax.
> The man would now be the entire system, yet he still would not understand Chinese.
Really, here the only issue is Searle's inability to grasp the concept that the process is what does the understanding, not the person (or machine, or neurons) that performs it.
Then you deeply underestimate how difficult the problem is, and deeply misunderstand where all the effort has been spent in developing autonomous vehicles.
If all the effort has been spent in trying to replicate the human brain then I am comfortable saying that is a mistake.
We have a tool that can tell with great accuracy how far away an object is. The suggestion that we should ignore it and rely on cameras that have to guess it because “that’s how humans work” is absurd, frankly.
Before you can learn how far away an object is, you must decide: which laser return corresponds to which object? In fact, what counts as an object? Where does a tree stop and become a fallen tree branch? Is that object moving towards me? Is the apparent velocity of this point represent the fact that the object is moving, or that it's rotating, or that it's flexing, or dividing, or all 4? Is that object moving towards me but that's ok because it's a car that's going to stay in its lane? What's a lane? What's my laser return for where the lane is? Should I stop at this intersection? What's my laser return for whether the light is red? Am I in the blind spot of the car in front of me? Is he about to shift into my lane because he doesn't see me? What laser return do I get to tell me whether his indicator is on?
The problem of understanding what is happening in front of you while driving is preposterously more complicated than just a point cloud of distances. That is .01% of the problem. To solve the remaining 99.99%, you need interpretation of photons and sound waves into a semantic understanding that gives you predictive power to guess how the physical world will evolve and avoid breaking the rules of the road. Show me a mechanized way of understanding the causes of how the physical structure of the world is about to evolve, and I'll show you something that is imitating a human brain, however poorly. The cameras give you _plenty_ of data to determine 3D structure, at a higher resolution than the laser, without being emissive, for cheaper. It's a completely reasonable approach to focus your limited computational hardware on interpreting the data you have instead of adding more modalities with their own limitations that (according to nature) are demonstrably unnecessary.
The world is more complicated than slogans and pitchforks and Elon Bad.
People get into accidents not because they don't know with great accuracy how far away an object is.
They get into accidents because they make bad decisions and get distracted.
If AI makes better decisions and don't get distracted, the amount of accidents will already be greatly reduced compared to humans.
Having lidar in addition to cameras will be of marginal benefit (but a benefit to be sure) when you realize what is actually important: proper modeling of the environment. And for this, cameras are better at providing than lidar, so you still will want cameras anyways.
The focus on lidar is really a red herring. You merely push the computational budget you have to understanding a point cloud instead of vision. You're back to square 1 of "how can I properly model the environment given this sensory modality". This is the part that essentially needs human level understanding of the world that you're missing.
As the other commenter says, you deeply misunderstand the problem.
It would be interesting if, with all the anxiety about vibe coding becoming the new normal, its only lasting effect is the emergence of smaller B2B companies that quickly razzle dazzle together a bespoke replacement for Concur, SAP, Workday, the crappy company sharepoint - whatever. Reminds me of what people say Palantir is doing, but now supercharged by the AI-driven workflows to stand up the “forward deployed” “solution” even faster.
There's a line in the first season that runs as an undercurrent through the whole show ("Computers aren't the thing. They're the thing that gets you to the thing"). Joe originally says this to make the viewer think about technology, evoking the dawn of the personal computer and subsequently the internet. But later on, you're invited to re-interpret that statement as being about people: computers and technology were the thing that got the main characters to work together. It's the -people- that are the thing.
Part of what makes the show so good is that it's one of the few renditions in TV / movies of the joy of engineering something, and the constant tension that comes from working with great people. Great people inspire you, but they also challenge you. The show does a great job of portraying realistic conflicts that arise between different personality types and roles, as well as cleverly exposing the limitations of those personalities. With just Gordon, you'll get a stable and well engineered product but it won't be revolutionary. Joe has the vision but he can't actually _do_ the substantive part. Cameron has great substance and technical ability, but she's impractical and inflexible. Donna is responsible, effective, and clear-eyed - but unchecked, purely rational decisions erode the soul of a company into nothing. These differences frustrate our characters, and yet there can be no success without them.
I think many of us spend our whole careers chasing those rare moments where the right people are in the room solving problems, butting heads, but ultimately doing things they could never do all by themselves.
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