Google search returns approximate results, related results, results with your words split (or joined) and other nonsense to drive ad views.
Even using the so-called "power tools" like allinsite: and the (barely functional) quotation marks, you still get very shoddy results.
Anyone who ever searches for very specific groups of terms knows exactly what I am talking about: enter search terms, click on result, search in page for term, doesn't exist.
As has been mentioned, you should probably set your default search to verbatim mode.
Search for "vertx play framework" and the last two search results don't have the term vertx despite pages and pages of results with the term. I don't understand how dropping search terms can make the results more relevant.
Also you can't set the default search to verbatim. You can only hack the query parameters in specific browsers.
Not 100% proof but ad views and clicks seem to be increasing by 20% to 30% each quarter. Google tests everything to death and they please wall st with those ad click increases.
I find Google Search to be incredibly frustrating to use because it chooses to ignore search terms even when pages exist with those terms. Google better be really careful because crippling the experience in order to sell more advertising reminds me why I switched away from Altavista.
1) The web is just much bigger and noisier than it ever was. There are so many SEO-bait sites out there now, it is a wonder search still works at all. I can't really fault Google for this part.
2) Changes Google made to make search more accessible to the mainstream user. Google search now tries way too hard to be "smart" about what the user meant to ask for instead of what he or she actually asked for and this can be a huge negative if the person is looking up precise information and knows how to use a search engine.
They somewhat recently added a "Verbatim" option to search that can help you avoid some of this too-smartness, but even with that enabled Google is still inferior to what it used to be when I'm looking for very targeted technical information that I am sure exists out there.
Sadly, this sort of thing is a trend impacting not just Google. The success of Apple has created a culture of creating things for the mainstream consumer user which often comes at the expense of the power user. I get why this is done and ultimately it is the right call for any business that could potentially serve the mainstream, but I do wish more companies would leave in the highly technical expert options as settings for those who are comfortable using them. I feel that in recent times most software in general has swung way too far on the pendulum from being too hard for normal people to use to being totally gimped for experts and feeling like a toy more than a tool and I wish attempts to try to support both sets of users became a "thing" instead of constantly hearing the mantra that "options or settings are bad, no options or settings for you"!
Sadly, you are in a minority. Google's results are excellent for most people.
I used to use + often. We know that the + operator was rarely used, and most of those times it wasn't used correctly. (Of all searches, only 1 in 600 were correctly using the + operator.)
Being outside Google (and not able to see their data) is frustrating, but they have a lot of numbers and they do this stuff because they can show it helps most people.
Edit: Thanks, comex. Made google.com become: http://www.google.com/webhp?tbs=li:1
Search is too big a problem for just a couple people at Mountain View to be working on. And at this stage with the amount of data being generated, no one really has the infrastructure to compete.
Hope they do it before the regulators make them. If Apple has succeeded at building a market place around their closed platform Google can too.
Alta Vista years ago had full logical search but Google beat them with simpler searches having greater relevance. Google's searches are now moving towards even less specificity. How much could greater language understanding help this?
How many people want to go to the trouble of writing out a full sentence to specify exactly what they want? How much is it worth accommodating them? etc
So I consider this a feature not a bug...
I am not sure I want that. At least not as much as Google does. Kurzweil is going to help me click on more ads. Shreds any sense of him being a visionary.
I'm totally OK with searching "#{my_city} taxi" instead of "taxi" if it means when I search "abortion" I get a sampling of search results that has the greatest co-citation... instead of something that myopically focuses on Google's perception of my preferences.
At the least, I'd like to be able to switch off the personalization. But anyway... Beating a dead horse here in this community, I'm sure.
Clippy told people how to do their work more efficiently, and because people don't like to remember new ways of doing work if their old habits sufficient, people hate him. Clippy was like computerized supervisor, slave driver, who looked over their shoulders and told them "You selected one menu item 5 times, better use keyboard shortcut to mine more uranium for your Master."
Google wants to tell people what to do. He is like missionary, every layman would respect him for making life easer. People would love Google for this.
http://www.businessweek.com/magazine/content/11_17/b42250609...
By rigorous hand-waving, as he mostly does things the last 1-2 decades?
His basic argument of the inevitable advance of technology to true AI, or ability to upload consciousness or integrate computers with brains, rests on priors that are not clearly relevant.
With his latest title, "How to Create a Mind: The Secret of Human Thought Revealed", how can anyone take him seriously? Scientists (practicing scientists) have been writing books like that for decades, and the lesson should be that unless you've demonstrated that you can build an AI (real AI, not soft AI like machine learning), you have no business using a title like that. If real AI is simply a combination of the right machine learning tricks, then the trick is in the combination, because nobody has figured it out (publicly) yet.
How does this one-liner contribute to the conversation at all? Your negativity is unenlightening and obnoxious.
No, he did it to get some PR of Google as a mad-genius storage. He also did it with tons of other semi-retired Comp Sci legends. He might also like the guy, or believe the Singularity mambo-jambo himself.
There's a line going around about Google being where "old computer scientists go to retire".
>How does this one-liner contribute to the conversation at all?
By giving a summary of the whole thing? A very succinct one at that? If it's also accurate (which you can argue about), then it's a perfect contribution to the conversation.
I think Google (and Larry Page) is betting that they will be able to separate out this mixture.
For one, Kurzweill DOES have "grand" ideas. Extravagant visions of a future with technological immortality, singularity, etc. Hofstadter does not. He merely examines some things, like cognition, and proposes some theories about their workings. Like, you know, every scientist.
Kurzweill comes out as grandioze, obsessive and deluded, Hofstadter like a normal writer, no more or less strange than, say, Marvin Minsky.
I know he takes like 100 pills every day
Him getting 100 pills every day: I don't think is very relevant. Mostly delusional. If that worked, pharmaceutical companies would have made it into one mega-pill, and sold it for a fortune to rich people years ago.
As for your argument against 100 pills, that only holds if it's well-known or well-established that it works and works safely.
If it's a truly competitive advantage, wouldn't offering it for startups/other-businesses in return for equity would offer bigger profits?
and Google Search is basically Watson.
Basically, by reading and understanding large amounts of text, it can help you validate an hypothesis or even lead you to new hypothesis.
... land, get off that plane, take a cab, and have a polite but blunt conversation with the founders about how to fix their company. (What did you think I meant?)
Artificial intelligence is nice, brahs, but natural stupidity in the form of closed allocation and Enron-style performance reviews are putting that company at 10% speed. Clear out the latter and you'll have plenty more muscle for the former.
I'm sure Ray Kurzweil will do amazing things, but he'd do even more amazing things if the company still had the machinery (e.g. open allocation, a culture of human decency) to bring talent to him properly. The whole reason he is there is to work with great people that the company is supposed to be better equipped to find than he is... but how will that work, given that the company sold off its ability to reward and recognize talent just to appease McKinsey?
I tried doing it a bit with my last project. My results were basically terrible. It turns out that getting useful results out of heterogenous, vague, fuzzily-specified real world data is really hard.
I'm tight with a few folks in Search Quality whose job is that sort of data-scientist machine-learning work, and they're really good at it. Y'know what 90% of their daily time is spent on? Compiling golden sets. Labeling training data. Running MapReduces to collect basic statistics about their data set. Running MapReduces to identify representative members of their data set, and outliers that should be excluded. Shoving data into R to visualize it. Futzing with numeric coefficients. Building webpages and tools so they can visualize the data and results, futz with the numbers online, and get feedback in real time. Collecting test sets and running your algorithm against them, and then trying to figure out why your losses are losing.
Machine-learning from a practitioner's POV is not at all like the textbooks and theoretical papers suggest. I'd estimate that less than 10% of one's time goes into the "fun" part of machine learning - brainstorming new signals and writing the code to extract them and feed them into your classifier - and 90% is on the kind of grunt work that hard science grad students do all the time. You get paid well for it, but that's because a lot of the work is really boring and time-consuming. I suspect that I get a far more frequent rush of accomplishment as a mostly-UI guy than the data scientists in my department get.
It's a tool. It works well in some cases, but it can take a lot of effort to get it to work well.
Part of what makes data science fun is the machine learning itself. And an equally interesting part of it is is that it involves so many other parts of computer science that a typical corporate job would call "too hard" and isolate you from.
At least based on what I've seen, data scientists are respected and this means they get dibs on the most interesting projects. However, the interesting projects themselves involve a lot of detailed work (that's the nature of technology) and if you're that interested, you're going to want to do it yourself, at least until you really understand the problem (at which point, you'll automate the dull stuff).
I wonder how easy would it be to actually do so?
For example, "Carolina beat Duke" follows from "Carolina defeated the Duke Blue Devils once again". I have a demo here: http://ec2-23-22-22-135.compute-1.amazonaws.com:8001/demo
Here's an example app that uses entailment recognition to answer natural language polar (yes or no) questions: gavinmh.github.io/HelloTablet.
I'd be happy to talk to anyone who is interested in getting involved.
I use a simpler alignment representation, and use semantic role types in the predictions.
