If TPUv4 pods were so powerful, why are most new models trained with NVIDIA cards rather than TPU?
Software for TPU is still in its early stages. CUDA is well established. You can test on a gaming GPU that you can find (locally!) in many markets. XLA is meant to solve this, but first impressions matter and my first impression was that it has not yet "solved" this issue.
TPU is only available via Google Cloud - as far as I know they don't have NVIDIA's widespread distribution to various HPC/supercomputer systems. This also has implications on scaling up more than a few pods, as they will need to be colocated with speedy interconnect (which is provided by the various existing HPC systems that use NVIDIA's chips).
Finally, I think many people are discovering that the supposed benefits of TPU are marginal at best in the face of the types of natural scaling issues that both GPU's and TPU's suffer from when scaling out to e.g. hundreds of pods.
I'm certain that someone with more experience than I could give a better answer though - and again, all speculation. I refuse to use TPU because Google Cloud's system for getting access to said TPU's was horrible for me when I tried it. I believe John Carmack has a nice tweet thread specifying the same issues I ran into.
In general, Google has a habit of developing tech for other Googlers first, and as such winds up ignoring a lot of real-world scenarios faced by researchers/practitioners. NVIDIA on the other hand has been working directly with a ton of institutions and businesses ever since the inception of CUDA.
That their TPU's have seen any adoption at all is mostly due to their research program which granted very cheap access to TPU's to tons of people.
(this is not meant to be reassuring).
As a result, spending ad money on Google is ridiculously expensive, but companies accept this because there is no alternative hoping to "build long lasting relations" with the people who make them pay upwards of 1 dollar per click
Also, if your established it probably a good idea not to let new competitors get a foot hold in the market with an easy google win.
It's also pretty effective for local businesses because not a lot of local businesses are tech savvy enough use it effectively.
FWIW, the cheapest (quality) clicks I've seen, at least in the B2B space, is closer to $3/click, and it can quickly balloon to upwards of $10/click especially on company brand names where competitors are bidding on another company's brand name.
Knowing this, I cringe every time I'm screensharing with someone and they search "[B2B Company] login" to login to a tool they use every day. Each login = $2-$10
It's not uncommon for companies to spend $100k+/year JUST bidding on their own company name.
I just don't get where all the marketing money is coming from. Bootstrapping is clearly not an option these days
That bag of chips did not cost $4 to make, not even a little close.
Coupled with a magazine or a show presenting new product categories for those interested, customers will eventually visit a physical or online shop and check out the goods. And then word of mouth will do the rest.
Aggressive advertising will mostly just help you get ahead of your competitors and perhaps speed up the adoption rate at the cost of increased volatility of the market and to the detriment of people's mental health.
We would be better off regulating aggressive ads away.
That's a hell of a load-bearing "just" you managed to insert there. Getting ahead of your competitors in market share can be the difference between having a company succeed or fail.
Or: all advertisers of all brands with a same or similar product must collaborate. Only voluntary input counts as collaboration; if a brand simply doesn't care about presentation of itself in the advertisement, they have trivially collaborated. Easiest way to implement this is giving every owner of all relevant brands a right to veto every entire final advertisement product (this right could also be surrendered, for all or some possible vetoed advertisements, in exchange for something in a contract).
Ignoring flaws of this proposition itself, what could be society's reasons for rejecting it? Does society perhaps want havers of more money to gain further advantage over havers of less money?
Maybe 50 years ago that would have worked. Today, not so much. Go to Amazon and look, well, just about anything. What is BEHENO, what is DINGEE, what is Etoolia, what is Romedia, what are the over 300 different 6/7 letter companies that show up when I search up some random product.
Unfortunately your consideration causes its own parasite effect of countless companies forming up to feed of the big advertisers budget.
And, you're also crating a regulatory nightmare. Say I put up an add for XXYZXX company, and it includes ZZXYZZ and YYXZYY information (I mean totally random picks), and I just happen to have a stake in those companies too. Now you're going to have to track hundreds of thousands of these entities to ensure no fraud is occurring, and in most cases the fines for this kind of behavior are well under the cost of doing business.
Everything you've said so far just creates bigger messes and solves nothing.
Marketing is already difficult to tell apart from other company communications, product documentation, etc. What about a company blog showing how to use their products? Is that marketing or product documentation?
Tax ad companies, and spend that money on education. The better ad companies are doing, the more we spend on education, the fewer gullible marks we produce, the worse ad companies will do.
Conversely, in Communist systems they could never get this right. Factories were just told to produce 5 or 10% more than last year, didn’t matter if the product quality was worse or if people didn’t want it.
Think about all the stuff ChatGPT and GPT-4 can do with even minimal prompting. Even when they hallucinate, the text is still ostensibly coherent and natural sounding. Now imagine a similarly powerful model, but its input is a ton of metadata about your behavior and its output is ads.
Now consider that adtech has had substantially more funding for substantially longer than research into LLMs, so ad serving models are probably way more powerful and optimized than even GPT-4.
It's freaky to think about indeed.
So we can have internet anywhere. To click on ads.
Informative ads make the market more efficient. Persuasive ads actively make the market less efficient.
Most ads in the US in 2023 seem to be persuasive.
Perhaps the ad industry would become more useful (and smaller) if we managed to effectively regulate it to significantly reduce the persuasive bits.
I think that most people would support this if you explained it right - from the free-market perspective, this would give you a better market.
More competition would be fantastic. Better pricing at scale would be fantastic. But there is absolutely no doubt that nvidia is far ahead of Google right now. Tesla made some believably pushing claims about their own efforts with their own hardware, so who knows maybe they're the real challenger.
edit: actually now i can't find the claim, maybe i misremember what the papers said.