The "official" value of a stock is it is the current best guess of the market for all future earnings until infinity discounted back to the present at some discount rate (to account for the time value of money). That price to earnings rate is 1, because it's the definition. The "E" in PE ratio, however, is for a different time period: traditionally just the trailing 12 months (or previous completed FY- for high growth companies you will sometimes see "last month's revenue multiplied by 12" or other guesses).
This calculation is why "growth" companies dominated the stock market during the 2010's: with the Zero Interest Rate Policy that most of the developed world had, the discount rate that the markets used ended up being basically zero. In which case a market player is indifferent between a dollar in 2020 and a dollar in 2040. So if a company had a 10% chance of being worth a trillion dollars in 2040, that was worth (0.1 * 1 trillion=10 billion dollars). But with a more traditional 4% discount rate then a dollar in 2040 is worth less than half of a dollar in 2020, and that means your 10% chance of being worth a trillion dollars in 2040 has less than half of the value. Even if nothing else changed about your business, just the discount rate changing halved the value of your company.
In order to call it a NASDAQ 100 Tracking Fund you need to pay the NASDAQ a licensing fee (same with S&P500, Wilshire 5000, etc.). The contract you have with NASDAQ will determine exactly how much freedom you have to change rules and still call it a NASDAQ 100 fund. I've never seen a licensing agreement, don't know anything about how they would typically read.
There is also the concept of "Index Tracking Error". No fund can perfectly mimic the index, and that is expected and understood, but the goal is generally to have the tracking error <0.1%- 1% would be a bad track. And so an index fund could take the risk that they will have a tracking error and delay picking up SpaceX even after it joins the official index, but then if it goes up they will look worse relative to their real competitors, the other NASDAQ 100 tracking index funds. If SpaceX goes down, of course, they will have positive tracking error, but I'm not sure how much potential investors would value that. SpaceX would be something like 4% of the NASDAQ 100 at it's announced expected market cap, so a 10% movement by SpaceX would be enough on its own to get you into the notable tracking error range if you didn't have any exposure to it.
S&P500 held fast to their rules on consecutive quarters of profitability and forced TSLA to meet them (must be profitable in qX + sum to net profit over the past year). If they hold to them this time, SpaceX would need to be profitable over a year while public to enter the index.
They have instituted rules and gone back on them eventually (most notably for several years they had a "no going public with different classes of voting shares designed to allow control forever, if IPO is after today" rule that they eventually dropped) but they are generally pretty good about following rules.
And not normal for a company that has been at it this long.
The Apple II went on sale on June 10th, 1977. Visicalc went on sale October 17th, 1979- 860 days separate the two. ChatGPT was opened to the public on November 30th, 2022, which was 1219 days ago- almost 50% more time has elapsed than between the Apple II and Visicalc.
Visicalc is often described as the killer app of the first generation Personal Computer(1). It was the product that drove them into every small business in the country, that blew up sales of personal computers and brought them out of the realm of hobbyists into enterprise. And, honestly, I think Visicalc and spreadsheets are still a greater benefit than what I've seen out of generative AI today. And that happened a lot faster than where we are today with generative AI. Apple had enormous actual profits by 1980 (Apple IPO'd in 1980 with a 21% operating margin). So I think that a lot of the "just got to give it more time" argument misses that the previous computer based revolutions that we know about productized and threw off gobs of cash a heck of a lot faster than this one has.
If the end result of this is "certain classes of white collar workers are 10-25% more productive" (which is the best results I can extrapolate from what I've seen so far) then it's really hard to imagine how OpenAI can return a profit to their investors.
>If the end result of this is "certain classes of white collar workers are 10-25% more productive" (which is the best results I can extrapolate from what I've seen so far) then it's really hard to imagine how OpenAI can return a profit to their investors.
If we take this as face value, and say that the absolute best case scenario is there are literally no other uses for AI but helping programmers program faster, given 4.4 million software devs, with an average cost to the company of $200,000 (working off the US here, including benefits/levels/whatever should be close), those 4.4 million devs with 20% productivity would save roughly 176 billion dollars a year.
Some companies will cut jobs, some will expand features, but that's the gist. And it's hard not to see the magnitude of improvement that's come in just 3 years, though if that leads to a 'moat' is yet to be seen.
> If we take this as face value, and say that the absolute best case scenario is there are literally no other uses for AI but helping programmers program faster, given 4.4 million software devs, with an average cost to the company of $200,000 (working off the US here, including benefits/levels/whatever should be close), those 4.4 million devs with 20% productivity would save roughly 176 billion dollars a year.
I don't think that's necessarily out of line with struggling to return a profit to investors though: an individual company is only ever going to capture a tiny fraction of the productivity improvements it enables its customer base to make[1], its own cost base is unusually high for tech, and investors are seeking a 10x+ return on an $852B valuation for a company that isn't even the market leader in that segment (which isn't the only segment, but it's the optimum B2B one). You can have a great business with a great value proposition and a sustainable moat and still not generate the desired returns on investment at a $852B valuation.
[1]and that's productivity improvements over the best-known free models, not productivity improvements over reading StackOverflow
Sorry, I forgot that for many engineers this is, in fact, their first time going through a technology cycle like this, and so would need more explanation. I am too young for Visicalc myself, but the cycle that I saw while I was in high school- the dot-com bubble- doesn't have convenient, easy to mark out dates like the PC does.
Thinking... Thinking...
Tim Berners-Lee proposing HTTP in 1989 is kinda like the original Attention is All You Need paper, I guess? Netscape 1.0 release in December 1994 is ChatGPT 1.0? And then Amazon.com opened up to the public in July 1995 and then IPO'd in May 1997 (after raising less than 10 million dollars in two funding rounds). But once again we have the business side of these previous cycles moving much faster than this one.
WOW. That does really drive home the perspective. I was an adolescent during those years and it did seem quick then, but that's an insane pace in retrospect.
Amazon is perhaps a counter-example to your point, though, to be fair. It seems to me they did a lot of spaghetti throwing while making accounting losses for a good number of years. Granted, they did it on OpenAI's dining budget.
I took it the other way, spreadsheets shook up the world way more than AI has (to date) - it's possible that history will look back and count AI as the bigger "thing" but if I had to pick a killer app, VisiCalc and computer spreadsheets in general would beat ChatGPT.
VisiCalc was "the" killer app for early micros, but being able to edit a written text on screen and then print it out with letter-like quality was nothing to sneeze at, either. This was plausibly a key gain in efficiency for the service sector, perhaps comparable to the 10%~25% that's now being talked about re: LLM's (which is huge on a secular basis).
IMO, the AI companies are trying to be both T-Mobile and Google Doc at the same time. Even Apple is struggling with being both the platform and the product. The issue with OpenAI is that the platform has no moat (other than money) and the product can be easily copied. In the game console world, the platforms have patents and trademarks, and games are not easily produced.
I'm a retired engineering manager so judge me appropriately :-) I've had 1000 good chats with ChatGPT on a wide range of topics. I build personal Excel and Access applications but not any real programming. I don't need workflow automation although I will dabble with Codex. I'm curious why I should abandon what works for Claude.
You shouldn't. No need to rush to buy a TI-84 to do simple arithmetic. I don't use either because I can learn just find from docs and textbooks. And I don't have that many problems to solve with computing.
The Apple II was so simple (by today's standards) that it came with a complete printed circuit diagram. Visicalc was so simple it was written by two guys in a year.
AI is so many orders of magnitude more complex that the comparison is not really useful.
This complexity requires a lot of money- from investors- to sustain. If those investors don't see a return on their investment before they get too anxious, then no more money will be invested and the business is dead. So that would suggest that there will be even less patience from the money than the investors in Apple had. If you are correct that this greater complexity actually makes it harder to productize, then it is hard to see how frontier model generative AI will be viable under a VC funded domain.
It is entirely plausible to me that there are great technologies that are impossible to reach via the normal means of VC/investor financed capitalism. I certainly have encountered market failures requiring extremely patient money (usually in the form of government subsidies) to produce a useful product that eventually does have market value. That has worked many times in the past. But so far generative AI has not had that, and looking at my non-technology friends, I very much doubt that there would be much support among them for government subsidies of AI companies. AI companies have made too many people unhappy, served as too much of a punching bag, to be in a good position politically for that.
In June 2022 the Oracle acquisition of Cerner (a EMR now billed as Oracle Health) closed, so that would be after the 2022 date and before the 2023 date. Cerner was 28,000 employees.
If they do cut back to their size before the acquisition, while continuing to try and support the EMR, they will be doing a lot more with fewer employees.
It will certainly do that. Previous attempts at this (the Olympics did genetic tests from the 1960's through the 1990's, other organizations have done similar tests into the present) always did wind up discovering cis women raised as women from birth, with female presenting genitalia, who failed whatever genetic tests they were doing. At least one of these women even went on to give birth to a live human baby! You would think that would prove that they actually were a woman, but their medals were still kept from them. They were still driven from the sport, branded as cheaters, etc. Because someone who was so much better than the rest can't really be a woman, they have to be cheating somehow, they have to be a man.
In fact, I'm not aware of any genetic testing program ever catching any deliberate cheating, only people who were raised from birth as women. The very first example of this, (1), Dora/Heinrich Ratjen (2) seems to have been an intersex person who was definitely raised as a girl from birth who was a bit confused about what their body was doing. But all the way back in the 1950's when their 1936 Olympics became a big deal, we have lurid tales in the English language media of deliberate cheating that don't seem to have been supported by anything that Ratjen ever did.
I wouldn't call it cheating. But I have no trouble drawing lines that exclude some people, if that levels the field for a bigger group. In this case the female olympics would soon be known as the intersex olympics given the selection pressure. I can understand the decision to make the competiton more interesting by barring intersex people. No need to frame it as cheating though.
Since we don't actually do genetic tests at birth, this would only ocurr in the context of national qualifying, think about what the experience of someone who trains to be good enough to qualify for the Olympics, then gets this test and is told, "Sorry, you aren't really a woman. Too bad. No Olympics for you. Sorry you wasted all those years training."
How else should the person who just got that information interpret it except... Sorry, you're not really deserving, even though your score qualifies you. And what do call someone who has a score that qualifies but doesn't get to go?
And there are far more of people with this experience than the experience of being born and treated by society as a man and becoming an Olympic athlete as a woman.
The Olympics used to do this. From as early as the 1960's they were doing genetic testing on female athletes. They stripped Polish sprinter Ewa Kłobukowska of all her medals and records in 1967, in spite of the fact that she gave birth to a child a year later, which would seem to indicate that she was a woman. The Olympics only abandoned this testing regime after the 1996 Olympic Games when 8 women who were cis and assigned female from birth to that moment were wrongly tested as male (7 AIS cases, 1 5-alpha-steroid reductase deficiency ). The uproar from that caused the Olympics to realize that this was a lot more complicated then they thought and abandon the idea of a strict genetic test.
Because those 8 women at that one Games were a lot more than all transfem Olympic athletes in history combined, the danger of ruling people out is much greater than the danger of allowing someone in who doesn't deserve it.
Anecdotally there has been a common knowledge that some of the record-setting Soviet women in disciplines line disk throwing, etc, had genetic abnormalities and had to suddenly finish their careers when the aforementioned testing came.
> The shift to PCR-based techniques replaced one diagnostic genetic test with another but did not alleviate the problems. Positive results still stigmatized women with such conditions as androgen insensitivity, XY mosaicism, and 5-α-reductase deficiency. Both sex chromatin and SRY tests identify individuals with genetic anomalies that yield no competitive advantage. Therefore, finally in 1999, the IOC conditionally rescinded its 30-yr requirement for on-site gender screening of all women entered in female-only events at the Olympic Games, starting with Sydney in 2000. Rather, intervention and evaluation of individual athletes by appropriate medical personnel could be employed if there was any question about gender identity. This change has not been made permanent.
> It is worth noting these tests are sensitive. If a male lab technician conducts the test he can inadvertently contaminate it with a single skin cell and produce a false positive SRY result.
> No guidance is given on how to conduct the test to reduce the risk of false results.
> Nor does World Athletics recognise the impacts a positive test result would have on a person, which can be more profound than exclusion from sport alone.
> There was no mention from World Athletics that appropriate genetic counselling should be provided, which is considered necessary prior to genetic testing and challenging to access in many lower- and middle-income countries.
> I, along with many other experts, persuaded the International Olympic Committee to drop the use of SRY for sex testing for the 2000 Sydney Olympics.
> It is therefore very surprising that, 25 years later, there is a misguided effort to bring this test back.
> Even if a molecular method could be devised that had a very small error rate, it would still just constitute a test for a nucleic acid sequence, not for sex or gender. Although one can test for the main candidate gene for male sex determination, SRY, it still holds that most XY women test positive and some XX males test negative for SRY. It is possible that there will never be a laboratory test that will adequately assess the sex of all individuals.
...
> (IAAF proposals held) that the purpose of gender verification is to prevent normal men from masquerading as women in women's comopetition was reinforced. Perhaps a genuine concern decades ago, this fear now seems to be a less pressing concern. One reason may be that routine drug testing now requires the voiding of urine be carefully watched by an official to make certain that urine from a given athlete actually comes from his or her urethra. Thus, athletes are already carefully watched in "doping stations". The likelihood of a male successfully masquerading as a female under such circumstances seems remote in current comparison.
Santhi Soundarajan (1) shows exactly how this ends up catching cis women who were raised as women from birth. Which is why it's a bad idea to draw strict lines.
Edited to add: Based on http://linuxmafia.com/faq/Essays/marriage.html I just discovered another case, that of Polish sprinter Ewa Kłobukowska who was banned from sports in 1967 and stripped of her medals for failing a sex test even though she gave birth to a child a year later. For the 1996 games 8 women failed their sex tests, but 7 of them had AIS and one had 5-alpha-steroid reductase deficiency. All of them were reinstated, and that's when the Olympics ended their previous iteration of genetic testing female athletes.
This idea has a long history, and it's a long history of being wrong. I'm not expecting any better out of it this time.
1: https://en.wikipedia.org/wiki/Santhi_Soundarajan The first female Tamil athlete to win a medal at the Asia games (in 2006), then had her silver medal stripped from her because she had Androgen Insensitivity Syndrome- so she's a XY who never developed male genitals because her body just ignored the chemical signals, as happens to something like 1 in every 40,000 births. She tried to commit suicide by drinking rat poison after she came home in disgrace.
Yeah but buying a sofa from Ikea doesn't let people steal my banking passwords. There are serious consequences to software bugs that there aren't in cheaper ready-made clothing.
Study of self reported emotional closeness with best friend (from a 2002 questionaire of a 1997 longitudinal study) found no difference between black men and black women, and a small gap for Hispanics, no economic differences for white women, and a large gap for wealthy white men, who seem to be an outlier demographic group, in this variable at least.
It's not a really strong data set (the survey is all of people born between 1980-1984, surveyed in 2002, and they threw out AAPI responses because there were only a few of them) but it suggests that male loneliness might be an artifact of a culture common among the American economic elite.
This calculation is why "growth" companies dominated the stock market during the 2010's: with the Zero Interest Rate Policy that most of the developed world had, the discount rate that the markets used ended up being basically zero. In which case a market player is indifferent between a dollar in 2020 and a dollar in 2040. So if a company had a 10% chance of being worth a trillion dollars in 2040, that was worth (0.1 * 1 trillion=10 billion dollars). But with a more traditional 4% discount rate then a dollar in 2040 is worth less than half of a dollar in 2020, and that means your 10% chance of being worth a trillion dollars in 2040 has less than half of the value. Even if nothing else changed about your business, just the discount rate changing halved the value of your company.
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