skysight-inc/HackerNews huggingface dataset:
Its a valid question. The answer is that it depends on the industry. Sure, if you're a small or mid-sized technology start-up, infighting and backbiting will bring down the firm in months. But if you're in a monopoly position (e.g. Microsoft), or in a non-competitive market (e.g. banks), your company makes money by default. As such, there is a much larger threshold before the drag caused by politics becomes significant enough to affect the performance of the firm.
Interesting note: DODOcase was founded/executed by a W08 YC Alum (one of the founders of the WebMynd team!). Huge congrats to Patrick!

clickable: http://www.dodocase.com
"All hands support" (provided by engineers) is cool and all, but ONLY IF your product/service is targeted at other engineers or highly technical users (like Wistia and New Relic).

Support for B2C or B2[Brick and Mortar]B services is a different animal, IMO, and one that many startups don't get.
Veetle - funnyvn.com movies
Psychedelic drug could be 'magic' bullet for depression
Protein folding.

The amount of computation, and program expressibility involved in folding a protein is far far far more than you would expect from just counting the DNA that made that protein.
If you run their code in any way you're already giving them control of your system. Even if you're one of the vanishingly small number of people who use a separate admin account they're getting full control of your account if they want it.

Installing a repo & apt key is a good sign that they're playing by the rules rather than trying something sneaky.
> Your main programming guy is a lisper?

Right, financial organizations should hire bunch of PHP script kiddies. I am sure that's working well for quant firms like Jane Street.
FCC Chiefs: Google's Plan Would End The Open Internet
If we're talking about Turing machines, all of the machines are of equal computational power, and are also able to emulate each other.

We aren't necessarily talking about Turing machines but let's suppose that we are. We're talking about machines powerful enough to compute anything that any Turing machine can compute. You are correct that any one of these machines can emulate any of the others.

What's relevant to Kurzweil's argument is two-fold:

If I tell you about Turing-class machine A and give you Turing-class machine B, we know right away that you can write an A emulator that runs on B. We know that because they are both Turing class. What we don't know is how big that emulator program is. It might take a trillion lines of code just to write the emulator.

Next, I have told you about machine A but now I also give you a 50 Megabyte program (called "GENOME") that runs on machine A. Now you must write your emulator, encode GENOME for your emulator, and run it on B. We know you can do that since these are both Turing class machines. What we do not know is how many bits it will take to encode GENOME. It could be 50 Megabytes. Or it could be 50 Terabytes. You just can't tell without proving things about the specific details of machines A and B and your emulator.

Kurzweil makes an argument analogous to "Hey, GENOME only takes 50MB on machine A. There's no way it takes 50TB on machine B. Information theory at work, man! Use your head!" Problem is, "information theory" says no such thing. Actually, it says "If that's all we've been told, hell it could easily take 50TB on machine B. It could take 5 bytes. Who knows? There's not enough said about machines A and B or the program GENOME to tell!"

Basically I was saying that if you offer some facility to translate programs from machine A to machine B, only a very small portion of the programs on machine B will turn out to be programs that were translated from machine A. Therefore the probability of programs halting on machine A tells us nothing about what the majority of programs on machine B are likely to do, and therefore tells us very little about the probability of a random program on machine B halting.

Yes. You are correctly observing that Omega is not really a constant - it is a class of constants. For machine A there is Omega_A. For machine B, Omega_B. That is why Chaitin lectures about Omega but only after several reminders that it's really "Omega_X for some specific machine X -- but I'm mostly just going to say Omega and let X be understood."

So, now, think that through with Kurzweil goggles on. In Kurzweil's world, a program of 50MB on one machine can't be 50TB on the next machine -- that's just silly, right? Well, if he were correct then, in general, Omega_A and Omega_B, for any machines A and B, would have to be somewhat close in value. We know that Omega_A and Omega_B don't have to be close (other than that they both come from the same (0,1) interval). By contradiction we conclude that we don't live in the world Kurzweil is describing.
If the point of this discussion is to stigmatize and ridicule the orthodoxy of "locavorism", I'm on board.

If the point is to ridicule Michael Pollan and Alice Waters, to highlight the fact that the model of production they talk about is a luxury item for the rich and utterly untenable for most of society, I'm even on board with that.

But if the point is to make the argument that there is little benefit to seasonal cooking or small-farm animal husbandry, you lose me completely. There clearly is a benefit:

* Out-of-season vegetables are very often of lower quality than canned; the obvious example is tomatoes, but you're also not going to eat a ramp in December, or a high-quality parsnip in May, or a Vidalia in the fall.

* The consumer embrace of faux-fresh off-season veg actually is a bad thing; it pushes out producers who make real veg in favor of people who are selling wax veg year-round; people are still buying wax tomatoes in July.

* Alienation from seasonal cooking results in home cooks who, like me, had never tasted a ramp or a morel or a vidalia or even a real tomato; seasonal cooking is vector towards good cooking, and one thing that I think is hard to argue is that America needs more and better home cooks.

* Supermarket meat is a bona fide debacle. There's universal agreement that we've managed to breed flavor and health out of pigs almost entirely. Industrial chicken is epsilon away from being grown in vats instead of farms. Beef is being treated with ammonia before grinding (the trend towards buying meat not only pre-ground but pre-shaped is another pathology).

* "Local meat" is in some cases actually cheaper than the supermarket crap; you have to make a lifestyle concession to get access to those prices (ie, you have to have a $150 chest freezer, and you have to be willing to actually cook), but high-quality pig and beef is not out of the reach of a lower-middle-class homeowner.

* I live in the midwest. I'm not a fan of St. Pollan[1], but there are some restaurant owners here that I do admire and who make a point of sticking to midwest-seasonal. I take exception to the idea that it "really sucks". We should meet in the middle. In the colder climes, we should be shipping in "accent" products from the west coast to liven things up, but there's plenty of regional produce that can and should form the staple. Right now, we're at the other extreme: most people in Chicago are happy to eat a caprese with gassed-red wax tomatoes and mutant basil and kraft mozzeralla in the middle of January.

* And don't get me started on our access to cheese here.

[1] Although I like his writing about plants. He's a great garden writer.
Doctor Who time travel data is beautiful
To disagree on a side issue, it's been a long time since NIPS dealt much with classic ANNs (which never had much to do with human brains, in any case). Most of the action there, as in AI and ML at large these days---eg, the focus also at ICML and at other venues---is in statistical methods.

(On the other hand, neuroscience and explicitly biological neural modeling are exciting areas, reasonably well-represented at NIPS. Those topics, however, are almost entirely different from neural networks of the multilayer perceptron / [Hyper]NEAT varieties.)

But your criticism of the article seems accurate. ACO isn't new, and there's little evidence that it will solve any of the major outstanding problems in AI.

Less generously, however, I'd suggest that much of the research related to the family of population-based stochastic search methods, ACO, PSO, and HyperNEAT included, is prone to the same risk: the lack of a field-wide theoretical foundation, coupled with the absence of a field-wide standard methodology and benchmark set for empirical comparison (as opposed to, say, the situation in supervised learning), makes it temptingly easy for a particular researcher to believe too strongly in the capabilities of that researcher's pet algorithm. This situation seems to have balkanized the field (page through a recent GECCO proceedings, for example), and holds back wider progress.

That's not to say that HyperNEAT can't do great things. It's a fun approach, and Stanley et al are running far with it. But your boosterism of it, and the boosterism of ACO that you're objecting to, seem closely related.

(For contrast, I'd suggest, eg, the natural gradient work at IDSIA. It's unlikely to be the ultimate method, but may be a good model for solid research in this area.)
He was using "easy" the same way Python programmers use "clever"--derogatorily. It is easier to throw away bad code and start over, but the easy way and the best way are rarely the same. Actually, it might be easier to say that it's easier in the short run. Refactoring may be deceiving because it's harder up front ("Ughhh, I have to read all of this awful code") but easier in the long run ("Ahh, look how seamless everything is!"); as opposed to rewriting, which is easy up front ("Look at the pristine, unmarred beauty of this empty file! I will fill it with my brilliant ideas.") and horrible in the long run ("What do you mean, all of the bugs that were fixed in our old broken code have resurfaced and need to be fixed again?!").
Brainstorming – Current Thinking for IT Leaders
"It's a typical SF startup" vs. "you're spreading [the team] out across 3 offices"

"You are staffing up so quickly?" vs. "such a small team"

I can't tell if you're trolling or just really inconsistent regarding the reasons for your dislike of them.
People can say things like "lots of research, smart planning and thoughtful execution with a great commitment", and believe in it as a general principle, without applying it or even knowing how to apply it to themselves. A lot of these do translate in some way to more general rules, but I still think it's helpful to have targeted insights. "Planning is good. For you this means think before you code, make apps easy to maintain and scale, avoid hacks, etc." Without that a lot of people will fail to notice the connection to their specific activities.
A (the?) key point of Kurzweil's work is to show that the exponential growth of technological leverage is independent of Moore's law. His prediction is that when Moore's law runs out (being tied to transistor density, it must), something else of the same shape will replace it. That is obviously yet to be proven, but there are some nice historical graphs at http://en.wikipedia.org/wiki/Accelerating_change.
While the predictions of scarcity are likely correct, the predictions of the consequences of scarcity likely aren't. For example: Once the cost of helium increases, substitutes will be found for many applications. For a buoyant gas, people might use hot air, or hydrogen mixed with some kind of flame retardant. Low temperature research might rely more on computer simulations. MRIs and other devices might use high temperature superconductors bathed in liquid nitrogen.

The only problem would be if helium scarcity happened too quickly for people and technologies to adapt. If you thought that was likely, you could invest in companies making or researching helium substitutes and make a killing.

It seems like the conclusion is that no one thinks they know enough about future scarcity to be willing to place bets on it.

Almost. Nobody knows enough about future scarcity to be willing to place bets on it instead of placing bets on other investments such as index funds. If you enter into a 20 year futures contract, you're saying, "I believe I will make more money from selling this resource in 20 years than I would from investing the value of this contract in index funds for 20 years."
Sales Magic is Bogus: How the Game is Won
Free consultation on data strategy (NLP, ML, business intelligence, etc.)
thanks for the catch! we'll be fixing that up
Ask HN: Corporate lackeys-How much of the time are you actively working?
I'm a recent college grad and new hire at a multinational corporation in the automation business. So far it seems like I've been able to do the tasks given to me pretty well. However, I'm only actively working on those tasks around 50% of the time it seems like. The rest of the time, I'm either just goofing off, because I know I have time before I need to be finished, or waiting for something before I can actually do that tasks I'm given.

In the mean time, I surf as much as the corporate filter allows, mostly looking at technology and computer related news. Sometimes I practice a little programming, or read up on Linux internals or something. Or just surf Hackernews and read the interesting links. (Dreaming/planning to do a start up someday.)

What are your thoughts? Should I be asking my manager for more work? Coast as much as possible? How much do YOU work in your corporate job?
Pitchfork Media and the Power of Slow Growth
Industrial chicken is epsilon away from being grown in vats instead of farms.

Great line. (Apropos of nothing: when vat-grown meat arrives, I will be there on day one, eating it off the freaking petri dish if they'll let me.)
It seems RIM is also looking into their recent QNX purchase.. I have fond memories of QNX on the desktop, so their rumored "blackpad" might turn out pretty interesting beyond consumer space.
Wealth anorexia a.k.a. hating yourself because you're not Larry Ellison
I endorse this reply.

EDIT: I endorse all of ewjordan's other replies too. There's no need for me here.
Kurzweil's retort falls apart in several places:

"It is true that the brain gains a great deal of information by interacting with its environment – it is an adaptive learning system. But we should not confuse the information that is learned with the innate design of the brain."

He is misunderstanding Myers here - Myers is talking about the physical ontogenesis of the brain during development (in utero), proteins interacting with proteins (and the environment and such) during its development, not the development of the brain through "adaptive learning"

"But we can take a much more direct route to understanding the amount of information in the brain’s innate design, which I also discussed: to look at the brain itself. There, we also see massive redundancy. Yes there are trillions of connections, but they follow massively repeated patterns."

"Yes, the system learns and adapts to its environment..."

Again, Kurzweil is failing to address the crux of Myers argument, that the design of the brain is not only in the genetic code, but in the intricate "playing out" of cells during brain development. Myers did not talk about the brain adapting to a system in the holistic or psychological sense, but on a much more fine-grained biological level.
> You have a "Creative Director"

> it's all about technology and not about people or emotions.

Yes, hiring a designer definitely shows a complete disregard for the people using the product.
An individual desk might not, but it's not that unlikely for the firm as a whole to.
But first, let's nail down the context, because if we can't agree on that then we really shouldn't even be discussing the topic (and I suspect the whole problem here is that Myers thinks they're arguing about something other than what Kurzweil is actually claiming) - we're discussing the amount of information that we would need to construct an effective intelligent algorithm.

If that's the question, then sure, I agree with you. In fact, I imagine something intelligent code be encoded with much less data.

My point was about the information content required for the human brain itself, and that seems to be what Kurzweil is talking about, at least:

The amount of information in the genome (after lossless compression, which is feasible because of the massive redundancy in the genome) is about 50 million bytes (down from 800 million bytes in the uncompressed genome). It is true that the information in the genome goes through a complex route to create a brain, but the information in the genome constrains the amount of information in the brain prior to the brain’s interaction with its environment.
Sounds great when you're small, but "All-Hands Support" self-destructs when you try to scale it.
Bad Facebook Post From Brand X
In a former life, I spent approximately 1 hour per day actually working (probably 2 if you count meetings). But that may be extreme - it was in the government contracting/aerospace industry.
"GMO" is a red herring. When it comes to produce, the problem isn't that it's mass-produced and it isn't that it's mutated with secret Monsanto DNA.

The problem is that huge companies have conditioned the market to believe that tomatoes are something you get in the bin 15 steps forward and 5 steps sideways from the entrance to the supermarket, in the big bin labeled "vine-ripened tomatoes", when in fact tomatoes don't work that way, and anything you put in a bin labeled like that must, by necessity because of the way supply chains work, be a fake wax replica of a tomato even when good tomatoes are available.

The problem is not that poor people eat tomatoes. The Fresh Markets supermarket 3 blocks north of me serves a solidly lower-lower class market (I live next to Austin, one of the poorest neighborhoods in Chicago, a "food desert") has better produce than Whole Foods does. Poor people, particularly Hispanic poor people, do veg really well.

The problem is that the Del Monte's of the world are replacing real tomatoes with fake tomatoes. That is bad. It's not a class warfare issue.
Max Salzberg of Diaspora speaking on Air Mozilla at 12:30 PM PST
Programming isn't unique in the set you list, but it is unusual.

Engineer, scientist and programmers are probably in an unusual situation - they are exploring a primarily unknown solution space.

Most jobs live in the well explored, primarily understood areas of solution space, and consist of simply applying already known solutions repeatedly. Teachers, doctors (mostly) and most nurses just perform a set of rote tasks of varying complexity. The best way to improve performance in these fields is to write a script/checklist/decision tree and order everyone to follow it.

(In the case of doctors, I exclude a few at the very high end. Most doctors are not House.)
Correction suggestion: "3G" in the United States is a crock. So is "4G", which as far as I understand is not actually even LTE/WiMax in some places (which themselves are pre-4G).

.eu side, at least, things are a bit clearer.
It might just be an indication that you're not getting enough rest.
I somewhat disagree with the point that good programmers think about the problems 24/7. Even good programmers loose motivation if there is bad company culture or some other de-motivating factors. I find that true motivation and true interest for the project are very important in software development but so many companies neglect it.
I still remember my "rm -fr /" episode after almost 20 years. It was slightly different, something related to chmod'ing some files under /etc on an AIX server:

$ cd /etc
$ chmod 600 some_file * # instead of some_file.*

oops... Thank God for boot diskettes.
Ginzametrics (YC S10) Aims To Bring Simplicity To SEO Software
The problem is you need to be really close to breakeven or your going to be wasting GWh per lb of helium.
No. Don't. Don't eat that crap. Not because it's unhealthful. Because it sucks. It's just stringy tofu. Just buy tofu; it'll be cheaper and more versatile.

The rest of us can eat actual chicken, the kind that had feet and beaks.
(From the OP): jknupp, I agree about that. I think that code reuse is one of the two reasons why people use inheritance in Java, but I don't think it's a very valid reason in general. Upcasting, on the other hand, definitely is. My point in the original post is that because Ruby doesn't have upcasting, then inheritance in Ruby becomes pretty marginal.
> sure, our fancy big super computer from IBM can emulate the zygote (let's say) but.. what's that gonna take?

Well, you know, part of the other half of the "source code" in the genome explains how to build a zygote. It doesn't explain how to build a universe, but there's no particular reason to believe that the universe is designed to make zygotes easy to build.

The encoding scheme isn't particularly problematic; it's a constant factor on the efficiency, and a small additive increment to the source code.
There has been a lot of discussion about the "paradox of choice" recently, and I think there's something useful in the concept, as it applies to an individual consumer attempting to find the best solution for his own particular needs.

But the producer designs their product offerings to appeal to the widest possible market. There may not be much variation within a particular customer's preferences, but there is a great deal of variation between the preferences of different customers.

Eliminating choices might make things simpler for some customers, but it will also shrink your market by alienating those customers whose preferences differ from your new standard offering. The less choice you offer, the less mass-market and more niche-focused your product becomes.

Overall, that means that there are two possible outcomes: (a) if there are high barriers to entry, many customers will have to settle for a less-than-ideal product, or (b) if there are low barriers to entry, new competitors will emerge to appeal to the market's gaps, eventually leading to a similar level of complexity in product choice.

The question here isn't whether a high level of product choice is a good thing; not offering choice is only a possibility for monopolists.

The real question is one of usability: how do you offer a large number of options in a clean and intuitive way? The solution lies in UI design, not marketing strategy.
I think they were very stupid to not push the thing more in Europe, where people are quite used to buying unlocked phones for their full price.
I'm with you on the scientist and the programmer, but the whole purpose of engineering is to work explicitly within the known solution space to be able to guarantee the outcome of their work.

Engineering is applying the lessons of science to achieve predictable results.
Thanks, I'll take a look to see if I find a color scheme that I can live with :)
> "But the complexity of the zygote derives mostly from that 50MB of genome data..."

Wait.. does it? I'm rather tempted to think you are right, but here is my worry. I know that the data in the genome encodes proteins that are able to function through their interactions and feed-backs yadda yadda, so as to perform the following tasks: growing a cell, splitting a cell, altering cell structure/function. But notice that "creating a cell" wasn't on that list.

The genome needs some minimally functional, pre-existing cell to be working in. That is something that the genome probably doesn't have the needed complexity to build "from scratch" as it were; it never has to do that job. So that pre-existing structure has some complexity, right? How does that compare to the 50MB?
More power to Zencoder! I integrated their service into a client site a couple of weeks ago and their support is phenomenal. I chatted with one of the guys and he was very helpful. Another Zencoder technician actually emailed me because he noticed that some API callbacks we're errorring out. I was testing from a LAN machine and he was trying to save me some time debugging.

Nice to see them moving onwards and upwards.