corruption

Hopelessly optimistic. Spoken like someone who has never taken an experimental design course imho.

1) The search space is practically infinite dimensional. All methods suck when trying to extract a causative model from an infinite search space. There's a reason why in experimental design we change as little as possible.

2) SNP's are not the entire story. If it were this simple we would have progressed much further already. See dismal failure of all other high throughput sequencing and microarray technology. We still don't know how to analyse this stuff properly, if it will ever be possible.

3) The metabolome is adaptive! While we each have different enzyme kinetics due to slight differences in protein makeup, overall metabolic flux rates are amazingly consistent. See Oliver Feihn et al for more details.

Theory != practical. It takes picking up the phone and face-to-face meetings in my experience.

Sold instructions on ebay about how to beat a little known tax law [it's now plugged]. A friend went to work for the tax man and in training they were told about me and how it's so important to not let these tricks get out, as it could cost the country lots of money. I promptly stopped as I didn't realize I was on their radar!

Reverse engineered an algorithm from a huge international company who kept it under lock and key using publicly available data and used it with their competitors. They still have it under lock and key.

Bought textbooks at fundraising sales and sold them to university students the next year for a 3000% markup.

Others I'd only tell in person :)

Let's say you had an eclipse plugin that let you write in lisp, but it actually converted the code to java underneath. You could click a button to switch between views. Are you saying that would be a bad thing? If a tool allows you to be more productive, I use it. Note: I don't use lambda4jdt at all, I just like the idea of creating problem specific views for code and I don't think that belongs at the language level.

The smartest people I know have the following in common:

- They are the most knowledgeable person in the room in their topic of interest. That takes obsession.

- They surround themselves by other smart people constantly

- In large groups of smart people they are perfectly happy to ask questions even if they are wrong. E.g in a maths seminar will debate, and often get beaten by the subject expert.

I often wonder if the latter - asking "stupid" questions to experts in a field - is something that was there before they were at the top. Anyone else noticed this?

Even though code is text, you would think someone would have tried to build a different view given the popularity of MVC.

Inline expansion would be nice. So would code paths. So would inline images & html rendering for documentation. So would the relevant rendered html for the issue relating to the code you are looking at. So would other annotations. And what about visually hiding code when working in a language like java?

I tried to get this going in eclipse once, and it really wasn't going to happen easily so I gave up. I've always hoped someone would build something similar as I feel it would really help productivity having everything relevant right there with the code.

Note: The project http://code.google.com/p/lambda4jdt/ is the closest thing I have found to what I am suggesting which I think shows the power. It just goes to show that it could work.

I never said anything to the contrary. I said that it's a false dichotomy; just because you don't spend time doing something doesn't mean you don't like it, just that you may not like doing it as much as other activities.

I love playing games, but never do because I like other things (learning mainly) far better. I also love kayaking, but would much prefer to go to the gym because of convenience. That doesn't mean I don't like playing games or kayaking; I really enjoy doing both. Get it?

Honestly, the world isn't black and white like that. And I can see why you argued about it; that would drive anyone mad being told what they do and don't like based on a histogram of time spent in the last 2 years.

There are many explanations for not spending time doing things you like; competing priorities is the main one (i.e. I like other things more than them) and also environment (perhaps you enjoy kayaking but hate the drive to get there, or don't want to go with johnny and max because you don't like max).

Just because you don't do something doesn't mean you don't like it. It's a false dichotomy.

Yes, we are building to to be bought.

Once an itch is scratched it turns into a scab. And new itches appear.

Seriously though, businesses change over time. Are people who are great at getting things going the right people to run them long term? In some cases yes, in others no. In my case I plan to be involved in one of my companies for a long time, but for another I am involved in we are building to exit.

That's amazing, you should write up your project and submit it to diybio google group.

Years ago (pre swivel, post quantrix/tableau) I made a competitor as well. We quickly decided once we went out and talked to potential customers that it was a no go.

1) Very few customers wanted to upload their data to the web. Even less were allowed by law. 2) Most had integration problems - i.e. they couldn't actually access their data because it was in disparate systems. 3) Most people didn't actually use the information for anything, it was simply to provide them with "evidence" that they were right before looking at the charts. As a statistician this makes me sad, but it was the way things were at least when we investigated it.

Over time we gradually realised why BI was priced so high; it needs system integration alongside it. Now it turns out that we may have been wrong (gooddata.com are doing a good job as far as I can tell) but I still think it's the tip of the iceberg in terms of potential market.

My advice: target a niche with a huge problem where the customer is unable to get at their data at the moment. Choose the niche which has 1-2 big vendors of data collection systems with 80+% combined market share and provide the solution to the problem. And charge.

You need enough knowledge to know when someone is making the right decision or not for your business. I run a successful software company, have hired and managed many programmers and still got it wrong with hardware.

>I assume the next time you see an opportunity in the hardware business and want to jump onto it, you wouldn't be taking a 4 year undergrad course to know the drill.

That's actually exactly what I'm doing - although after you have a degree it only takes a year or so to go through the relevant programs, and if you know people in the university it's easy to get private tutoring for specific gaps. It's not like the courses are difficult once you learn how to learn. Plus, you get to see who would be a good fit in your next startup.

Learning by doing: Perhaps I'm just not smart enough, but I need to understand some theory before I can do it right in practice, and I learn best talking to knowledgeable people. I fumble and make too many costly mistakes when learning something completely new without guidance. We all have our weak points :)

The odds are stacked against you if you don't know the area you are in. This is because you can't control the competency of the people you hire or the work they do, so you have a random factor that has a direct and long lasting influence on your companies success.

After my first software startup I tried a hardware product and failed miserably because of my lack of knowledge. To remedy this for next time I am formally learning the areas where we failed (electronics + cad) and when I'm ready I will try again.

Theres so much that can go wrong with a startup that it's just not worth adding another element into the mix.

Just an aside, this hasn't been the way good science has been done for a long time: http://en.wikipedia.org/wiki/Strong_inference

I do however agree; many researchers I work with don't understand the benefits of adopting a strong inference approach.

Take the intersection of the three things you know most about and are passionate about. If you're not sure about this simply look at your most visited sites.

Then use those are your "base" and try to find ideas that combine all three.

Well, people claim that digg is entirely run by the top users from what I understand, and if only 6/10 stories that make it to the front page are predicted by the top users voting patterns, theres not much to that claim right?

EDIT: http://www.seomoz.org/blog/top-100-digg-users-control-56-of-...

6 out of ten stories in the new links section can be predicted by whether the top users vote on them. Really, only 6 out of 10? This seems extremely low given the claims of gaming (and if I'm understanding it correctly).

Someone should create a "everything" test, which pulls graduate level information from every topic maths, statistics, physics, chemistry, biochemistry, physiology, medicine, therapy, psychology, english, history, art, accounting, business, marketing etc etc.

I'd love to take it just to see quantitatively how much I don't know.

My goal when I first started was to exit and buy a fully equipped bio/physiology/elec/engineering lab and enough raw material to invent full time.

I thought I'd need 10m+ to do this, but over time I'm gradually acquiring everything I need due to places like sparkfun, ebay and alibaba for little more than the cost of an average car.

I'm inventing every day (5-6days software, weekends building random projects), learning more than I ever thought possible and loving every minute.

My point is that if this is anything like your dream, it's readily doable now as the cost of doing science is extremely cheap these days. And I've found that productivity increases when I take a break from software in the weekends and do some wet/hard projects.

I think this type of behavior was what everyone feared would happen, but I never really believed they would stoop this low.

This may mean that JCP is dead, harmony is doomed and it must be pretty scary for companies heavily invested in Java.

We'll agree to disagree then, both on the structure of the minds of people who make true breakthroughs and your views on epistemology :)

I don't take anything personally at all, and hope you didn't either :)

Isn't there a contradiction here:

"I don't feel the need for us to be equal. If feel that the idea that we're not is often a cop out..."

If the evidence supports the conclusion, we must accept it regardless of our personal biases. My general claim is that each person has a range of capabilities that they are born with, and that this range is ~ normally distributed across the population. By definition these ranges do not overlap for all n. This is supported by both anecdotal, population data and experimental animal and human models to the best of my knowledge.

As for your second paragraph, well as you can see I never claimed to the contrary. I completely agree that one should find a method of learning to maximise their individual potential, and that the range of what is possible for an individual is quite large - see my claim above. In fact I am very close to someone working on this very topic - determining the optimal learning strategy for children to maximise their learning rate.

It is clear that there are genetic differences in brains that cause large differences in "learning rate" - for lack of a better term. Interpret this how you want, but it's obvious to those in the field what this means (I talked to a researcher today to check my assumptions here to make sure!).

It is what it is. If my optimised (via teaching, drugs, augmentation etc) learning rate is lower than your's then so be it. So what? Why do you feel the need to make us equals, I accept your superiority in learning rate and do not care one iota.

> Otherwise some of these groups of people, like china or japan who have been isolated for thousands of years, would have serious intelligence differences as the rest of us.

Have you read the literature on IQ? These differences exist, whether you will accept it or not is a different question.

We are both making a claim. He has provided no evidence at all, and obviously hasn't read the literature.

The claim here is that the variance in learning rate is absolutely tiny. Think about this. He's basically claiming that despite a large known population variances in IQ and MA, there is no variance in learning rate. Despite research showing ritalin increases learning rate in a large fraction of society, this increase was meaningless. Despite verbal learning test normative data showing non zero variance, the variance is still zero.

There is a large body of literature comparing learning rate in different populations in both human and animal models. Take any study on learning rate, even the ones comparing "normal" to abnormal. Go to the methods and find the variance for each group. See it's non-zero, but often so large that differences between groups is hard to see.

Now, if you accept that learning rate has a non-zero variance, and also that learning rate decreases over time (well supported in the literature as well, and no I'm not going to find papers) and that time is finite, then the only conclusion you can make is that some people have a much higher chance of doing well academically. Not only that but there will be some people who despite trying will never be able to do well.

I don't see how stating this shocking to anyone at all - in a population of some 7 billion, there are millions of people >3 standard deviations from the mean.

Even if you did, a SINGLE base change can cause large differences in function. Thats one change out 3 billion, which is many more 9's.

Please read the literature. There is plenty of evidence that directly contrasts your viewpoint from the last 50 years.

And by the way, your second point is directly contrasted by the article I linked to.

Minute differences in genomes lead to large differences in phenotype. Ever heard of databases of SNP's or CNVs? A single base change can make a world of difference.

Actually, I'm not basing this on anecdote, as there is a ton of literature to back me up here. The first thing I searched for is quite remarkable for a single generation: http://www.springerlink.com/content/r44140388u23t768/

But, without going to the extensive literature, are you seriously claiming that the rate of learning is EXACTLY the same for every human, or that the variance is so tiny that differences are negligible? Both claims are provably false if you have a quick look at the literature.

It would be nice to believe that, but I would posit that output per unit of input differs. Given infinite time, anyone could obtain a Ph.D, but some people just find it easier than others. Those that find it easier are much more likely to do something great than someone who finds it extremely difficult and time consuming.

I know doing maths and statistics at university that there were many spending more than 40 hours a week studying and still obtained poor grades AND more importantly had less understanding than others doing no study.

Claiming that we are all equal is nice, but ignores the fact that the fundamental relationship between time invested and output is not constant between individuals.

Some of us run faster, some of us are leaner, some of us have beauty, some of us greater knowledge acquisition rates. There's nothing elitist about it in my opinion. I'm never going to be michael jordan, just like I'll never be Terrence Tao or Knuth, and I'm okay with that!