rigorousintuition.ca

viewtopic.php?f=8&t=29872&start=30#p478816
Most of the older models assume homogeneity and a fixed landscape. There was nothing that would balance exploration versus exploitation within a model. It assumed an equal level of risk aversion in consumer marketplaces, or assumed there wasn't a wide difference in adoption of technologies depending on social structure. The key is all of the implicit and explicit assumptions built into the model. You might expect that a prediction would have degrees of probability and also be focused as much on preventing you from being surprised about new developments.

http://articles.businessinsider.com/201 ... ilure-rate
In fact, a 1993 paper by Peter N. Golder and Gerard J. Tellis had a much more accurate description of what happens to startup companies entering new markets. [3] In their analysis Golder and Tellis found almost half of the market pioneers (First Movers) in their sample of 500 brands in 50 product categories failed. Even worse, the survivors’ mean market share was lower than found in other studies. Further, their study shows early market leaders (Fast Followers) have much greater long-term success; those in their sample entered the market an average of thirteen years later than the pioneers. What’s directly relevant from their work is a hierarchy showing what being first actually means for startups entering new or resegmented markets:


Innovator First to develop or patent an idea
Product Pioneer First to have a working model
First Mover First to sell the product 47% failure rate
Fast Follower Entered early but not first 8% failure rate

http://www.cs.virginia.edu/~robins/YouAndYourResearch.html
Now for the matter of drive. You observe that most great scientists have tremendous drive. I worked for ten years with John Tukey at Bell Labs. He had tremendous drive. One day about three or four years after I joined, I discovered that John Tukey was slightly younger than I was. John was a genius and I clearly was not. Well I went storming into Bode’s office and said, “How can anybody my age know as much as John Tukey does?” He leaned back in his chair, put his hands behind his head, grinned slightly, and said, “You would be surprised Hamming, how much you would know if you worked as hard as he did that many years.” I simply slunk out of the office!
...
What Bode was saying was this: “Knowledge and productivity are like compound interest.” Given two people of approximately the same ability and one person who works ten percent more than the other, the latter will more than twice outproduce the former. The more you know, the more you learn; the more you learn, the more you can do; the more you can do, the more the opportunity – it is very much like compound interest. I don’t want to give you a rate, but it is a very high rate. Given two people with exactly the same ability, the one person who manages day in and day out to get in one more hour of thinking will be tremendously more productive over a lifetime. I took Bode’s remark to heart; I spent a good deal more of my time for some years trying to work a bit harder and I found, in fact, I could get more work done. I don’t like to say it in front of my wife, but I did sort of neglect her sometimes; I needed to study. You have to neglect things if you intend to get what you want done. There’s no question about this.

http://216.224.180.96/~prom/oldsite/articles/changingface.html
The 2 basic premises, which I will first attempt to substantiate and will then use in furthering my argument, are:

1) Innate intelligence is unmeasurable; only overtly manifested ability can be evaluated—making intelligence tests, in many ways, akin to achievement tests.

2) The definition of “intelligence,” or of what component abilities should be most emphasized on an exam, is socially determined and thus may change in accordance with the needs of an era or culture.

…

The “classical” education highly valued by the erstwhile British aristocracy emphasized linguistic skills almost exclusively; youths were taught predominantly literature, philosophy, ancient Greek and history. In a more technologically oriented age, some of the most respected scholars of that time might have seemed profoundly inept or “one sided;” conversely, many modern scientists—esteemed for their acute mathematical and spatial reasoning—might have been judged “ill fit for higher learning” or “unintelligent” by an educational system which focused entirely on literary accomplishment.

In our own era, the ability to reason analytically is deemed vital to the advancement of technology and, thus, is stressed on many intelligence tests. Because all information is communicated through the verbal modes of speech and writing, vocabulary and linguistic reasoning are considered important indicators of “mental capacity.” The ability to “rote memorize”—vital to the retention of knowledge in a pre-literate era and important in the learning of complicated ecclesiastical rituals in the medieval period—has been de-emphasized; moreover, the focus on technologically useful forms of thinking has reduced the value placed on linguistic aptitude in isolation.

Thus, the mental abilities deserving emphasis—the criteria for assessing intelligence—may change with the times; men of extreme but one sided talent, deemed “brilliant” in one era, might be considered unremarkable in another. In evaluating intelligence, we measure how well an individual has assimilated the knowledge valued by his culture, how well he has learned to reason in conformity with the current styles of thinking, and how well he can adapt (on a cognitive level) to the conventions of his time.

…

“Resourcefulness” and the ability to think “broadly” (or “divergently”), to foresee how numerous factors might interact and to envision multiple possible solutions to any given problem, take priority. In an era when computers perform more and more of technology’s “analytical” work and when increasing numbers of people assume managerial roles, the incisive and narrowly-focused reasoning which considers data sequentially and ignores all ostensibly extraneous information may be superseded by the ability to consider heterogeneous pieces of information simultaneously.

The body of modern knowledge is enormous—too huge for one individual to master—even 5 lifetimes; continual advancement, especially in the technologies, assures that every man will always be “slightly ignorant” (even regarding the developments in his own specialty) and that, inevitably, he will often need to consult references for an explanation of new discoveries. The efficient use of such reference sources, necessary for adaptation to an ever-changing society, is of vital practical importance; gaining access to the facts of interest, when (abundant) information is stored in a complex manner, is facilitated by a divergent type of thinking called “resourcefulness.” This “resourcefulness,” as a key determinant of success in the modern world, may be a valid criterion by which to evaluate adult intelligence.

http://www.paulgraham.com/word.html
Like real world resourcefulness, conversational resourcefulness often means doing things you don’t want to. Chasing down all the implications of what’s said to you can sometimes lead to uncomfortable conclusions. The best word to describe the failure to do so is probably “denial,” though that seems a bit too narrow. A better way to describe the situation would be to say that the unsuccessful founders had the sort of conservatism that comes from weakness. They traversed idea space as gingerly as a very old person traverses the physical world. [1]

The unsuccessful founders weren’t stupid. Intellectually they were as capable as the successful founders of following all the implications of what one said to them. They just weren’t eager to

http://www.paulgraham.com/schlep.html
There are great startup ideas lying around unexploited right under our noses. One reason we don’t see them is a phenomenon I call schlep blindness. Schlep was originally a Yiddish word but has passed into general use in the US. It means a tedious, unpleasant task.

No one likes schleps, but hackers especially dislike them. Most hackers who start startups wish they could do it by just writing some clever software, putting it on a server somewhere, and watching the money roll in—without ever having to talk to users, or negotiate with other companies, or deal with other people’s broken code. Maybe that’s possible, but I haven’t seen it.

One of the many things we do at Y Combinator is teach hackers about the inevitability of schleps. No, you can’t start a startup by just writing code. I remember going through this realization myself. There was a point in 1995 when I was still trying to convince myself I could start a company by just writing code. But I soon learned from experience that schleps are not merely inevitable, but pretty much what business consists of. A company is defined by the schleps it will undertake. And schleps should be dealt with the same way you’d deal with a cold swimming pool: just jump in. Which is not to say you should seek out unpleasant work per se, but that you should never shrink from it if it’s on the path to something great.

The most dangerous thing about our dislike of schleps is that much of it is unconscious. Your unconscious won’t even let you see ideas that involve painful schleps. That’s schlep blindness.
…
How do you overcome schlep blindness? Frankly, the most valuable antidote to schlep blindness is probably ignorance. Most successful founders would probably say that if they’d known when they were starting their company about the obstacles they’d have to overcome, they might never have started it. Maybe that’s one reason the most successful startups of all so often have young founders.

In practice the founders grow with the problems. But no one seems able to foresee that, not even older, more experienced founders. So the reason younger founders have an advantage is that they make two mistakes that cancel each other out. They don’t know how much they can grow, but they also don’t know how much they’ll need to. Older founders only make the first mistake.

Ignorance can’t solve everything though. Some ideas so obviously entail alarming schleps that anyone can see them. How do you see ideas like that? The trick I recommend is to take yourself out of the picture. Instead of asking “what problem should I solve?” ask “what problem do I wish someone else would solve for me?” If someone who had to process payments before Stripe had tried asking that, Stripe would have been one of the first things they wished for.

http://www.paulgraham.com/relres.html
What would someone who was the opposite of hapless be like? They’d be relentlessly resourceful. Not merely relentless. That’s not enough to make things go your way except in a few mostly uninteresting domains. In any interesting domain, the difficulties will be novel. Which means you can’t simply plow through them, because you don’t know initially how hard they are; you don’t know whether you’re about to plow through a block of foam or granite. So you have to be resourceful. You have to keep trying new things.

Be relentlessly resourceful.

That sounds right, but is it simply a description of how to be successful in general? I don’t think so. This isn’t the recipe for success in writing or painting, for example. In that kind of work the recipe is more to be actively curious. Resourceful implies the obstacles are external, which they generally are in startups. But in writing and painting they’re mostly internal; the obstacle is your own obtuseness.

http://blakemasters.tumblr.com/peter-th ... 83-startup
markets
mimesis and competition
secrets
incrementalism
durability
teams
distribution
timing
financing
luck

http://serendip.brynmawr.edu/complexity/complexity.html
Many (all?) interesting phenomena can usefully be described as "orderly ensemble properties" and productively understood in terms of the properties and interactions of sub-phenomena ("elements").
WHOLES ARE MADE OF PARTS

Ensemble properties are permitted by but not determined by element properties
WHOLES ARE MORE THAN THE SUM OF THEIR PARTS

The behavior of ensembles is both influenced by and influences the behavior of elements
THERE IS A RECIPROCAL CAUSAL RELATIONSHIP BETWEEN PARTS AND WHOLES

Orderly ensemble properties can and do arise in the absence of blueprints, plans, or discrete organizers.
INTERESTING WHOLES CAN ARISE SIMPLY FROM INTERACTING PARTS

Prove it? Try the Game of Life

Ensemble properties may be largely unaffected by variations in the properties and behavior of elements
HOLISTIC PROPERTIES MAY APPEAR RESISTANT TO CHANGES IN PARTS

Ensemble properties may be highly sensitive to variations in the properties and behavior of elements
HOLISTIC PROPERTIES MAY SUDDENLY AND APPARENTLY MYSTERIOUSLY CHANGE

An example? See chaos suddenly emerge from order

Ensemble properties can be dramatically changed by modifying the nature of the interaction among elements
ENUMERATION OF PARTS CANNOT ACCOUNT FOR WHOLES

Ensemble properties may be dynamic for reasons entirely internal to the ensemble
CHANGE DOES NOT NECESSARILY INDICATE THE EXISTENCE OF AN OUTSIDE AGENT OR FORCE

An example? See populations fluctuate for no external reason

The same change in element property or behavior may have a small effect on ensemble order at one time and a large effect at another time
THE RELATION BETWEEN PARTS AND WHOLE MAY ITSELF CHANGE FOR A GIVEN WHOLE.

Disorderly variations in element properties or behavior may be the driving force for ensemble order
INTERESTING WHOLES CAN ARISE FROM CHAOS OR RANDOMNESS

Really? Yep, look at fractals and at The Game of Life and at The Magic Sierpinski Triangle


Deterministic systems will not explore all possible ensemble states
RANDOMNESS PLAYS AN IMPORTANT ROLE IN THE EXPLORATION OF POSSIBLE WHOLES

Oh for fuck's sake this is so goddamn smart and important, thank you, why are there no replies?

Project Willow wrote:

Oh for fuck's sake this is so goddamn smart and important, thank you, why are there no replies?

When you guys figure out how to stop someone from putting a gun to your head, then by all means, let me know.

JackRiddler wrote:Oh for fuck's sake this is so goddamn smart and important, thank you, why are there no replies?

http://en.wikipedia.org/wiki/Warnock's_dilemma
The problem with no response is that there are five possible interpretations:
The post is correct, well-written information that needs no follow-up commentary. There's nothing more to say except "Yeah, what he said."
The post is complete and utter nonsense, and no one wants to waste the energy or bandwidth to even point this out.
No one read the post, for whatever reason.
No one understood the post, but won't ask for clarification, for whatever reason.
No one cares about the post, for whatever reason.

General Patton wrote:

IV. Tackling AI

We have people from three different companies that are doing AI-related things here to talk with us today. Two of these companies—Vicarious and Prior Knowledge—are pretty early stage. The third, Palantir, is a bit later.

Vicarious is trying to build AI by develop algorithms that use the underlying principles of the human brain. They believe that higher-level concepts are derived from grounded experiences in the world, and thus creating AI requires first solving a human sensory modality. So their first step is building a vision system that understands images like humans do. That alone would have various commercial applications—e.g. image search, robotics, medical diagnostics—but the long-term plan is to go beyond vision and build generally intelligent machines.



Prior Knowledge is taking a different approach to building AI. Their goal is less to emulate brain function and more to try to come up with different ways to process large amounts of data. They apply a variety of Bayesian probabilistic techniques to identifying patterns and ascertaining causation in large data sets. In a sense, it’s the opposite of simulating human brains; intelligent machines should process massive amounts of data in advanced mathematical ways that are quite different from how most people analyze things in everyday life.



The big insight at Palantir is that the best way to stop terrorists isn’t regression analysis, where you look at what they’ve done in the past to try to predict what they’re going to do next. A better approach is more game theoretic. Palantir’s framework is not fundamentally about AI, but rather about intelligence augmentation.It falls very squarely within the Ricardo gains from trade paradigm. The key is to find the right balance between human and computer. This is a very similar to the anti-fraud techniques that PayPal developed. Humans couldn’t solve the fraud problem because there were millions of transactions going on. Computers couldn’t solve the problem because the fraud patterns changed. But having the computer do the hardcore computation and the humans do the final analysis, while a weaker form of AI, turns out to be optimal in these cases.

JackRiddler wrote:I'm guessing, and I don't know shit about AI science, but strictly from a historical outline POV I figure what it's going to look like in the first decades at least will be hybrids of computer and living brains - first animals, inevitably humans.

http://www.wired.com/threatlevel/2012/08/brainwave-hacking/
A team of security researchers from Oxford, UC Berkeley, and the University of Geneva say that they were able to deduce digits of PIN numbers, birth months, areas of residence and other personal information by presenting 30 headset-wearing subjects with images of ATM machines, debit cards, maps, people, and random numbers in a series of experiments. The paper, titled “On the Feasibility of Side-Channel Attacks with Brain Computer Interfaces,” represents the first major attempt to uncover potential security risks in the use of the headsets.

“The correct answer was found by the first guess in 20% of the cases for the experiment with the PIN, the debit cards, people, and the ATM machine,” write the researchers. “The location was exactly guessed for 30% of users, month of birth for almost 60% and the bank based on the ATM machines for almost 30%.”

To detect the first digit of the PIN, researchers presented the subjects with numbers from 0 to 9, flashing on the screen in random order, one by one. Each number was repeated 16 times, over a total duration of 90 seconds. The subjects’ brainwaves were monitored for telltale peaks that would rat them out.