One used to be able to just right click on an image and copy it. Now, I only get a still. I try clicking into the website that hosts the image and it's click, click, click just to get anywhere close to the size I want and often times its not even an animated gif anyway because they do some sort of media query and serve me up an uncopyable movie instead.
The web sucks now. People work around it with bots and the like on Reddit, but I feel like the economics have been figured out and it's not fun anymore.
Instead, we use /giphy in our Slack and hope the algorithm finds something that kinda-sorta was what we were thinking.
(yes, im kidding)
That said, I do see the sentiment. It would be nice to have the old convience of being able to look up old forum posts (especially with summaries in the OP via edit). Stackoverflow often fits that role now although I dread the answers even worse than old forum posts. I guess what I want is my cake and the ability to eat it too, I dont know why we can't just have the ability to search forums and have the general kinder attitude that modern media tend to have, they shouldn't be mutually exclusive.
in all honesty, isnt this a bit of "beauty is in the eye of the beholder", "sticks and stones" etc?
yes, you might be called various words, told to RTFM. but seriously here, is it really so bad? do you really want to drag down actual verbal abuse to something so absolutely trivial?
I don't want the internet to be kind everywhere, some artificial culture. If I don't like the tone of the place, I can go elsewhere. Strong moderation comes with too high a price in my opinion.
It's Yahoo Groups all over again, except that open groups could have their messages indexed, unlike on Discord.
The thing is, this doesn't matter anymore. You have very little control as Google tries to be smart. It's very hard if not impossible to find something older, obscure, things from other regions, languages, etc...
"Google-fu" is not progressing. It's struggling to hang on by the decreasing number of threads before it's utterly ineffective.
Where we used to say “rome fall why”, you’d now write “why did the roman empire fall”. Because the AI likes that phrasing and produces better results.
Soon you’ll write a 300 word description of what exactly you’re looking for, like you would when asking a trusted expert, and Google will figure something out. The days of keyword searching are long gone.
I think this is actually an example of the benefit of their AI. Despite the big difference in the "style" of phrasing (simple english vs more formally naming the subject noun), both seem to map to a very similar representation in their embedding space. I've run into frustrations with this myself, but for basic questions like this it seems like the search works Pretty Good.
[1] https://www.google.com/search?q=why+rome+fall&oq=why+rome+fa... [2] https://www.google.com/search?q=why+did+the+roman+empire+fal...
Humans instinctively know this, so we are able to construct queries like "why rome fall".
But that "why rome fall" query, which we think of as a purely mechanical keyword search, already requires quite a bit of sophisticated processing in the search engine. The system has to recognize that "fall" is synonymous for "collapse" or "wane in power" and not synonymous for "autumn". It also has to recognize that "rome" means "the (Western) Roman Empire" and not the modern city of Rome in Italy or "the Holy Roman Empire" or the city of Rome, NY, USA. It furthermore needs to interpret "why" in such a way that it emphasizes results with "reasons" or "explanations", rather than something like a "timeline" or "summary".
Personally I find it really weird that Google is interested in pushing users more to interact with its digital librarian / AI assistant, instead of continuing to improve keyword search.
I have a few guesses as to why they are going this way:
1. It makes the user interface simpler from an engineering perspective (fewer user-facing buttons and options to implement and test).
2. There is strategic benefit to making search more of a black box. Maybe they are specifically trying to "educate" users to expect and be comfortable with such black boxes. Maybe the plan is to get people so accustomed to "AI assistant" search that they see keyword search as outdated, and thereby secure a competitive advantage for the next several years over other search engines, by having the biggest and best AI models.
3. They are trying to increase the amount of rich "natural language" user search inputs in their data. Making keyword search worse will encourage people to use queries that more closely resemble natural language. I assume that this has strategic benefit related to Guess 2 above.
Personally I'd suggest "collapse of rome" which does deliver you a rich embedded result specific to the fall of rome.
I agree that Google's search parsing peaked a while back though, it seems to be getting weaker and weaker and now partially relies on the fact that search term autocompletion on mobile devices will supplement it by helping present an array of options near what you might want.
If I want to find a particular user-run forum on some obscure bit of some hobby, "<hobby name> <forum topic>" brings it up. But if I type out "Forum for <hobbyists> discussing <topic>" I get... a random selection popular of fora where someone has mentioned <topic>, often in passing or with minimal information.
> you’d now write “why did the roman empire fall”. Because the AI likes that phrasing and produces better results.
"the AI likes that phrasing" is exactly the problem here. How is anyone supposed to know what the AI "likes", other than painstaking trial-and-error in the unbounded and arbitrarily high-dimensional search space of human language?
Even the people who built the model probably don't know. Language models (and deep NNs in general) are extraordinarily complicated things, and there are problems with pretty much every technique that purports to provide visibility into their inner workings. There are just too many parameters and too many "information paths" in such a thing for regular people to wrap their heads around it. The ability to incorporate a high amount of complexity is a big part of why those models are so effective to begin with, but it also makes them really hard to reason about.
"AI" is currently in a weird spot where it's starting to kinda-sorta behave like an intelligent human in some limited settings, but in general is nowhere near as smart as a human. Most models still have a very shallow conceptual understanding of anything, even if they're becoming uncanny in their ability to match sophisticated patterns. It might not even be possible to teach some concepts to language models as they currently exist today, if only because there is only limited conceptual understanding available to be learned from corpora of text and images, even huge ones. Humans are still tremendously more effective than our best language models at understanding meaning and intent. Can an AI ever learn about love, regret, fear, or bliss, by reading millions of news articles and books and looking at millions of images?
Thus AI right now is in a kind of "worst of both worlds" situation, where it is complicated enough to be hard to reason about precisely, but still mostly unsophisticated and therefore highly sensitive to how inputs are crafted. Therefore it's hard to formulate inputs that provide useful outputs. It's still alpha-level technology at best, and there might be one or several conceptual innovations remaining between what we have today and something resembling general intelligence.
Consider also that "AI assistance" is complementary to keyword search, not a replacement for it. Google search AI is becoming something like a "digital librarian", a creature that can understand your queries and guide you to a starting place in the relevant literature. But much like in a real library, the digital librarian is going to be most useful as a starting point. At some point, if you already know what you're looking for, you still are going to want to search on "structured" criteria, as well as, yes, keywords embedded in text.
And finally, do you really want to type a 300-word description in order to get good search results? I was already getting good results with 3 keywords. I have already done the sophisticated pattern-matching and concept-graphing in my own brain, and now I know exactly what terms I want to look for. Why should I be forced to coach an AI on how to redo all that work for itself, instead of just letting me do a damn keyword search? Not to mention wasting my time and giving me carpal tunnel typing it all out.
The results quality has gone down and it's noticeable only after you switch to another independent search engine, like Brave Search.
For example, search for the term: "javascript undefined vs null" on Google and Brave Search. Brave Search gives way more information in the sidebar and Google doesn't at all.
The discussions feature on Brave Search is great, you don't even need to append queries like 'stackoverflow' or 'reddit' for searching discussions.
On top of that, let's say you're trying to search for an npm library like 'react-select', if you search that term on Brave Search, it gives you a button to copy `npm install react-select` right below the npmjs.com link.
It's crazy how good Brave Search is compared to Google sometimes, haven't used Google Search in a long time because of it.
Big things are not the same as small things, and should not be treated the same.
So I guess you're advocating that this dynamic equilibrium and "circle of life" is just panglossian optimal?
So far, I've noticed Brave Search only shows sidebar results for Stackoverflow and a few other popular forums that do not advertise on their pages directly, nothing else. So they're not really taking any revenue away. As for npmjs thing, I'm not sure if their revenue is hurt in any way because to view the package documentation you still need to open the link. Brave Search just provides you a copy command button extra for convenience.
As for discussions, they do not give full context so you always need to click the link so that's great for website owners as they get more exposure and traffic too.
At this point, Brave Search features are more on the UX side of things than anti-competitive so I personally will hold off the tinfoil hat for now.
More on topic, they still use Bing's near-useless image search, so even if it's getting worse Google Images is seemingly the only decent option in that category.
OK, I'm definitely switching to Bing Image Search for images.
Per OP... they do seem to have a public domain/CC search limit feature too. I don't know how well it works. (I'm not sure how either it or Google identify CC/public domain content. Is there an opengraph tag?)
https://www.bing.com/images/search?q=dogs&qft=+filterui:lice...
I couldn't find any reference on tineye.com but it seems like it has to be.
I just get page after page after page of "content" that appears to be either GPT written or written by somebody who has no idea about the topic.
They all seem to follow a pattern, they have a table of contents, and they take sentences from real sites regurgitate them and put them together into semi-random paragraphs.
If you know nothing about the topic it appears on the surface to be legitimate. And I bet to any quality engineers it all seems totally legitimate, because they're not experts in these fields.
Google search quality is in severe decline in my opinion. I have many experiences where I am searching for stuff that I know exists and that I know Google of yesteryear would have found, and Google comes back with garbage results and spam. Personally, I am hopeful that this means a Google-killer will be coming along soon.
Google search is severely broken.
Now I installed OpenSearchServer and see how far a local index gets me. The simple query "a" gets me at most 394 results at google, after letting OpenSearchServer crawl/index for just 2h I already get over 900 results for "a". Well.. I guess it really is not hard to beat that meager 394 results.
Initially read this as, well, "FU Google", and thought "yep, FU to them too". I guess I will acknowledge I have a bias. Then curious about this term, I googled-on-bing "FU Google". Top result was Google-fu, not the expletive.
I have no Google-fu.
'More than 1 result is a bug, citizen.'
Image search is another story. I've been less and less satisfied with Google Image search results, and visual search has been totally neutered. It only returns low res results that rarely match the original as well as it used to. I used to be able to plug in a 400x400 image and find a dozen copies of it at a usable size. No more. Too many copyright complaints, I assume. I've started using Bing for image and visual search now. It's not as good as old Google Images, but marginally better in some cases than the current iteration.