Use quotes around words, or enable "verbatim results" in the options. The + thing was misunderstood and misused by most users, and they figured experts could RTFM.

The thesis you are basing your work is from 1977; while no doubt current when it was written, there is has been a lot of work on human signal decoding since then.

I'd strongly suggest looking at Hidden Markov Models:
    http://en.wikipedia.org/wiki/Hidden_Markov_model
While some recent methods have gone beyond HMMs for speech recognition, that's been the baseline "good" solution for the past decade.

Since this is a binary signal problem another approach to consider would be Markov Random Fields (MRFs) which could be used as an initial de-noising pass or even as a full decoder if you set the cost functions right.

Your idea of user adaptation is pretty reasonable, but my guess is the primary thing that matters would be an overall speed scaling. IOW for good decoding you probably just need to normalize the average letter rate between users.

Good luck.

For public stop usage the SFMTA was aware of and already working toward a solution since late 2011:
    https://www.sfmta.com/projects-planning/projects/shuttle-partners-program/detail
It's all laid out pretty reasonably without having to get into a ticketing war or protests. These protesters are late to this issue, yet will probably claim credit when the mutli-year regulation update goes in place next year.

Of course, this is just a side issue for the bus protesters, it is more about the evictions. There are a lot of things driving that from zoning regulations to economics, so they pick a visible if somewhat poorly representative target.

In your case, it does seems like quite a traffic growth problem, but replacing the each bus with 30+ cars doesn't seem like a good solution.

The Goobuntu part is incorrect. Both my laptop and desktop have GCC 4.6.3 installed right now.

It is exceedingly unlikely that the results don't overlap after the first few, but if you can produce a copy of the two sets of results, I will forward them to someone on the Google Search team for debugging.

People hugely overestimate the effect of personalization -- it is a ranking tweak not a complete change to the search engine. It does not make economic sense to have personalized whole-web indexes.

Btw, if you don't like personalization ever, it is pretty easy to turn off:
    https://support.google.com/accounts/answer/54048?hl=en
Just remove web history and uncheck private results.

This is a very good argument against government intervention. A government made of lawyers is not a good substitute for scientists and economists.

This seems to be the most accurate post on the topic, yet carries the lowest score. This is about making suggestions, not auto-sending messages.

Typing on a phone is annoying, so if I can say "on my way home" with fewer clicks, instead of having to retype the message all the time, I would be happy to do so. Of course, I could set up some kind of macro, but an automatic system is far easier for normal folks to use.

Of course, whether this should be patentable is an entirely different matter, but the feature is an entirely reasonable thing to try.

If you assume a linear traction-limited model[1], information only needs to be sent backwards. Specifically:
(a) current velocity
(b) current acceleration/deceleration.
(c) maximum deceleration.

The immediately following car just needs to measure the distance[2], and know its own state and parameters. Then it can calculate how much space it needs to stop if the car in front immediately starts breaking at the maximum rate. You can incorporate communication & reaction delays easily too, as well as any bounded noise on the state variables. This would work for an arbitrarily long chain of cars, with each car just needing to monitor the one in front of it. It even works for autonomous cars following human-driven cars[3].

I used to be a robotics researcher, with a focus on high performance navigation. The lane-free full 2D generalization of the problem above was a chapter in my thesis (from 2007).

[1] or just make sure your actual model fits within a conservative linear envelope.
[2] obviously you can estimate a&b, but it potentially introduces additional delay to get the noise down, in particular for acceleration since that is second order.
[3] this is an ideal case *IF* that driver is paying attention, since the human driver has a better perception system.

(I work at Google, but not on search)

When Google tries to do this, the same people start complaining about filter bubbles[1] and either turn off personalization in their search settings, or turn to DDG, where a primary selling point is that they don't personalize. You really can't have it both ways, although Google comes very close with a simple toggle button for personalized results[2].

I don't believe you appreciate the difficulty of search given the current state of advanced [black hat] SEO; things that worked in the past (such as plain pagerank) would not work at all today. All search engines must run to keep in place. Also, economics plays a role -- can those 10 things be implemented in a practical way that scales and is cost effective.

I can 10 things on my car that I'd like, such as better fuel economy, more horsepower, better crash safety, better visibility, more convenience features, and a lower price. Unfortunately many of those things conflict, so in a practical sense it is likely that the car company had to strike a balance. From my armchair I am unlikely to know all of the things that went into those trade-offs.
~~

[1] "filter bubbles" don't really apply to multi-answer ranking problems or are trivially broken with standard techniques from reinforcement learning to manage the "explore-vs-exploit" tradeoff. As far as I've been able to determine, the person who coined the bubble term has no formal background in statistics (in particular ranking problems) or machine learning (in particular reinforcement learning).

[2] An oberservation from a long-time logged-in user: In my search results, personalization hardly ever effects more than two results out of the first 10. In search at least, filter bubbles do not exist for me, and I've taken no steps to avoid them. They do happen when I listen to a music service for a while (where unlike search, only one song can be chosen as the next to play).

There already is such an option, called "verbatim":
https://support.google.com/websearch/answer/1734130?hl=en

... crash ... thunk ....
Boooooooooooooom!

I work at Google. You can read (and edit) your own profile right here:
    www.google.com/settings/ads

It's really not that private stuff; here's four categories from my profile:
Business & Industrial
Business News
Computer & Video Games
Computer Components

The idea of a super-detailed profile is something with no original source, it has just been copied around the internet long enough that everyone accepts it as true. Of course you can claim that I'm not trustworthy, so below is an argument using only economics and public information.

There is no economic justification for a hyper-detailed profile. Here is why:

(1) Advertisers don't write ads for demographics so specific that there are only one or a few people in it. It is only in your interest to show to categories where many people apply, otherwise you are wasting your effort for no gain. Thus the worth of a profile is only in generalities.
(2) Specific keywords can be handled when the query is made or the page/email is shown. Just about all internet advertising is just-in-time like this, since anything else involves lots of serving-accessible storage which costs money. Even then, if the keyword only applies to a few people, the advertiser is wasting time as per #1.
(3) Every computation costs money. In advertising, if the cost to compute > incremental profit, you don't do it. The worth of a profile is only in its generalities as per #1, so that's the only thing worth computing, storing, and retrieving.
(4) If having a detailed profile on everyone was the holy grail of advertising, facebook would be making a lot more money per page view.

Go back and read the section titled Relative position of the Sun to the center of the Galaxy and 14 pulsars, which has this sentence in particular:

Given the distance of the pulsars, it is a pretty good bet that at least 4 would be visible by a hypothetical finder of the plaque.

For a moving spacecraft, you could easily seed it with these 14 pulsars, and run a SLAM[1] algorithm to add new ones and fix their position as you move. Localization with an initially unknown set of point beacons is well studied.

Now, there might indeed be new stuff on top of this in the paper, but the slashdot summary certainly isn't revealing it.

[1] http://en.wikipedia.org/wiki/Simultaneous_localization_and_mapping

Here's a video from two years ago, linked to the location in the talk about pedestrian, car, cyclist, and traffic light detection:
    https://www.youtube.com/watch?v=YXylqtEQ0tk&t=390
Around 9 minutes it shows how it all comes together to make a left turn at an intersection with many cars and pedestrians.

That was all two years ago. You're right that there's a long way to go, but describing it as an "auto-braking system" is extremely inaccurate.

A software engineering job is between 25% and 50% programming / programming ability. First, there are design and specifications to meet client requirements. If you want any but the lowest-paying programming jobs you need to be a part of that specification process. Same goes with milestone setting, scheduling, and assignment of developer resources. Yes, various parts of management will do a lot of that, but they cannot do that in a vacuum -- guidance from technical jobs is needed to keep things realistic. Finally, as part of designing, planning, implementing, and documenting, you'll need to communicate with peers so that they can understand and make use or your work, and work with management to understand the need and importance of each part.

For the past six years I've worked at a company that does yearly peer reviews, which I've found quite helpful. In none of those reviews has someone stated that I need to program better or more skillfully. Yet in all of those reviews I've gotten constructive feedback -- on how to improve in the *other* skills that a more senior software engineer will need.

I hope you are able to find the stable job you seek. While I can't claim to understand the details, a small change in attitude toward supporting skills may be what is needed to get you closer to your goal.