Unfortunately that tends to already happen. Gentrification pushes populations out as rent and property taxes increase. I'm honestly not sure how this is different and it seems like this may, as you pointed out, make gentrification worse.
It is as of yet unclear if software will reach that long term profitability. Video games certainly can have it though. I've purchased copies of games which were coded before I was born. Tech is still a young and growing industry where we find new use cases every day. As this slows and as software is perfected this may change. If someone designs the perfect email app it may just be able to run in steady state for decades. We haven't seen that but it may be a reality at some point in the next two decades.
Video games are probably closest to books; in fact, much of software is probably "bookish" in general - lots of it written for particular purposes, sells well enough to have been done, disappears into the long-tail.
A few major breakout successes become historical and bought long after the fact, but the majority do not.
Most books almost certainly lose money for the publisher. It's more complicated from the author's perspective given that people write books for a variety of motivations but, certainly, most books are doing well to earn out their advance which can easily be only $1,000 or so.
But, as you say, even those that sell "well enough" initially fall off pretty quickly. And some sorts of titles such as non-fiction about current tech stacks or software versions have a very limited shelf life.
There is an absolutely wild range in data structures courses. A lot of colleges merge data structures and algorithms and some do each separately. I went to one with them separate and we focused on the application because we had time to. I can't imagine that we could have actually covered complexity if we were doing both in one semester.
In my undergrad at University of Michigan it was combined. I do not remember if we covered it but I was already exposed to industry at that time and was far more advanced in the practical than the rest of the class.
The benefits of algorithm selection only really started to become apparent after years of experience and know-how in what _exactly_ an application requires or intends to be used as. Knowledge that is skipped at all levels of computer science education.
Similarly high end consumer brands like Gucci don't blast their labels on their high end products. The cheap stuff is cheap because you become a walking billboard. The expensive stuff is expensive because you just paid for quality. That's even within one company so your point is even more extreme across an industry.
Dior and Louis Vuitton love putting their logos all over their products, especially accessories. I think it cheapens the brand, but i'm not their marketing person.
Even with those if you sort their products by price the higher cost ones have a subtler logo because you're right, it does cheapen the product. The higher cost/higher end from these brands are basically a separate company with a shared name.
The lower cost ones have the logo because that's how the people you're around will know. The higher cost ones don't have the logo because the people around you will recognize quality.
They're often also slow to market. They weren't the first search engine, they weren't the first email platform, they weren't the first video site, but now they're the biggest in those categories. I think Bard's growth will be very interesting to watch given that track record.
It's worth mentioning that the Google you're talking about was way way different than it is today. Google Search was a startup. Google Search + Email was a small company. Google Search + Email + YouTube was a midsize firm. Now they're a humungous megacorp that's slow to make necessary changes when there's a paradigm shift like LLMs.
Arguably Google is the company that triggered that paradigm shift by publicly sharing (some of) their work on AI like the transformer/attention paper. So if anything they were ahead of the curve in terms of research. They're also extremely well positioned in terms of training data, infrastructure capabilities, hardware (TPUs), they had the first popular machine learning library (TensorFlow), etc.
Lately you could argue they're being overtaken by their competitors, especially in terms of productization. But they still hold pretty cards IMO.
I agree with the point you are trying to make, but Google Search + Email was not a small company. I remember Gmail Beta, Google was already known world over and definitely not a 'small' company.
Android didn't win, they just prevented Apple to have a 100% monopoly on smartphones.
Edit: Apple is certainly taking the lion's share of profits in the phone space. Since Google isn't investing as heavily anymore in Android, the development has slowed considerably.
Define winning - I'd take "Android maintained its position as the leading mobile operating system worldwide in the second quarter of 2023 with a market share of 70.8 percent. Android's closest rival, Apple's iOS, had a market share of 28.4 percent during the same period." [0]
It’s not getting dropped. If OpenAI’s models get good enough, search traffic will crater and Google will fall on extremely hard times for lack of ad revenue. At the same time, if they fail to integrate state of the art generative features into Workspace, people will go to Microsoft, where GPT-4 is presently handing Google their ass. Yes, Google Duet for Workspace totally sucks; I suspect their trial conversion rate approaches 0%.
This is a make it or break it problem for Google and they will get it right or they won’t get it at all.
not at all. I feel (this data is from running SEM for large website(s)) that Google earns most of their revenue from tactical searches. For instance, most people search for website names instead of typing the url. This creates a massive tactical search traffic base for google and brings largest revenue for them. There is a huge competition in this category as most competitors bid on others.
Similarly, product searches are second largest category in which they make tonnes of money. This is also done by people as they don't really like to search on amazon or other ecommerce sites. This is also a huge money spinner for them.
Both of these are not going anywhere as both of these are tactical spends.
Now let us come to long tail. These are again big money and are at risk for Google. However, you have to understand that Goog ads are clicked by most tier 2 users. We, techies, do not really click at ads. We go for organic ranking (mostly). We are the base of chatGPT right now. Tier 2 and lower users don't really use chatgpt.
Even if they do, they would not do it for product discovery or site discovery as it has too much friction: go to chat.openai.com, type in your question, it responds in slow, jerky manner vs just type in browser bar what you are thinking.
To top it, Chatgpt also has stale data. Moreover, it is heavily lobotomized to not give any controversial or edgy answers. This curtails usefulness of chatgpt.
I have for programming searches. ChatGPT can give me things that would take 5+ minutes of searching to hone in on. Then again, I run an ad blocker so no loss for them.
Honestly google probably doesnt make any money at all on searches like "how do call rust from python?". They make money on searches with buy intent where people search for "buy gps for car"
I have a browser extension (ChatGPTBox) that puts ChatGPT one click away on every DDG search I do, and it's certainly now often where I go next if DDG doesn't get me the result vs appending "!g" (to send the search to Google).
In that respect it's not replacing all my searches, but it seems to be replacing the "hard ones" where it's hard to compete with Google at a disproportional rate. If that is actually the case, it'd spell bad news for Google whether or not it kills search - if it becomes cheaper/easier to compete by offering a mix of less complete search with an OpenAI integration, it opens the door for far more attempts at competing with them.
For any domain specific questions or discussions I use ChatGPT because it’s so much better than Google. People underestimate how many fields it’s already valuable in beyond programming.
I use Google for basic bitch things like finding a company website or what time is it in Tokyo.
I think new generation using tiktok for search had more impact than AI.
The current issue with chatGPT is the freshness of the data, accuracy second to that. If they manage to constantly feed their model with new data then it might be a true contender imo
They were the best search engine from the get-go and had a massive impact. Gmail/maps also to a lesser extent.
In AI they were giants in what looks post-ChatGPT like a mediocre field. Their search now is looking very jaded.
The trajectory here isn't remotely like their past performances; it's not a safe bet to assume they'll win through with Bard or anything else.
The agility of OpenAI and the revolutionary impact of gpt3+ has made the former incumbents like Google look like posturing, self-satisfied, giant lumbering has-beens. They aren't getting back on top without massive internal changes.
I'd say it's pretty crappy ui if a new user can't immediately identify what's causing the beeping. If I'm in car going highway speeds and it starts yelling at me not knowing what to do will result in a more dangerous situation.
