
A.I. Has Arrived in Investing, Humans Are Still Dominating - smollett
https://www.nytimes.com/2018/01/12/business/ai-investing-humans-dominating.html
======
leggomylibro
Everything is always painted in such an adversarial light, it makes you
despair sometimes.

I think that The Atlantic's recent article on this topic is a more nuanced
insight[1]; human-machine cooperation is probably where the big money will be.
Companies that seek to cut people out of the loop will probably run into a lot
of problems, as will those that smash the looms. Whereas trying to smooth the
interface between AI/ML conclusions and human oversight is probably going to
see the most success.

[1]:
[https://www.theatlantic.com/education/archive/2018/02/employ...](https://www.theatlantic.com/education/archive/2018/02/employers-
are-setting-workers-up-for-failure/552050/)

~~~
vanderZwan
> _human-machine cooperation is probably where the big money will be._

As it has been for as long as machines have existed, really. This reminds me
of Douglas Engelbart and his vision for computers. I'll cite the section of
his wikipedia page that paraphrases an interview with him from 2002[0][1].

> _[Douglas Engelbart] reasoned that because the complexity of the world 's
> problems was increasing, and that any effort to improve the world would
> require the coordination of groups of people, the most effective way to
> solve problems was to augment human intelligence and develop ways of
> building collective intelligence. He believed that the computer, which was
> at the time thought of only as a tool for automation, would be an essential
> tool for future knowledge workers to solve such problems._

He was right of course, and his work lead to "The Mother of All Demos"[1].

Machine learning is the next step in using computers as thought enhancement
tools. What we still need to figure out is an appropriate interface that is
not as "black-boxy" as "we trained a neural net, and now we can put X in and
get Y out".

EDIT: Now that I read that quoted section of wikipedia again, it's funny to
note that computers were "only seen as tools of automation", and how modern
fears of AI are also about automation. Automation of thinking.

[0]
[https://en.wikipedia.org/wiki/Douglas_Engelbart](https://en.wikipedia.org/wiki/Douglas_Engelbart)

[1]
[https://www.youtube.com/watch?v=VeSgaJt27PM](https://www.youtube.com/watch?v=VeSgaJt27PM)

[2] [https://www.youtube.com/watch?v=yJDv-
zdhzMY](https://www.youtube.com/watch?v=yJDv-zdhzMY)

~~~
leggomylibro
It's funny that you bring that up - it does seem like the concept of 'extended
cognition' is one of the biggest benefits that we've collectively realized
from computers (and other relatively nonvolatile communication mediums like
books.)

This is a computer-oriented analogy, but most fields have their own tables and
charts and maths that are tedious to keep on the tip of your mind. Still, for
example, I don't need to remember the details of every API that I use; I can
just remember that there is a 'do X' call available, and refer to the
documentation when and if I need to actually use it.

In the same vein, I can quickly get a feel for whether an idea is possible by
stringing together a bunch of abstract mental models. "Can I do X?" becomes,
"are there good tools available for doing A, B, C, and D?", and that
information is only a quick search away. Actually using those tools involves
an enormous amount of detail, but it's detail that I can ignore when putting
an idea together.

And in most cases, that 'detail' is a library or part that already abstracts a
broad range of deeper complexities into something that I don't have to think
about.

The question becomes something like: how do we expose people to enough
information that they are aware of how much they can learn if they need to,
without drowning them in trivia that they will never be interested in?

~~~
cinquemb
Your example also is related to my experience briefly working in P&G chemicals
R & D lab; the ChemE's around me routinely used google to look up reaction
kinetics of different compounds (as well as other similar queries) rather than
rely on their memory of such. I was attending a local university at the time
(mostly for calculus and mathematical modeling using mathematica, and french),
but I'd say this experience is largely one that started my questioning the
value attending university in general (I dropped out an ivy about two years
later, for this reason among others).

I suspect that the concept of 'extended cognition' as it is realized with the
use of computers and how people use it day to day to get work done is in
conflict with how we all are mostly taught via rote memorization, and then
application of information; therefore it should naturally follow that those
who are heavily invested/exposed in 'non extended' cognition services have
relatively more to lose, as well as any currently realistic answer to this:

> _The question becomes something like: how do we expose people to enough
> information that they are aware of how much they can learn if they need to,
> without drowning them in trivia that they will never be interested in?_

will bring cognitive dissonance to those who need the answer most (those with
heavy exposure to relatively 'non extended' cognition services).

~~~
ethbro
When you're looking at effects, I think you need to dig down into what exactly
is being extended.

Are more data sources being made available? Is data being preprocessed? Is an
initial task being automated?

Because the truth of any worker (in less than a ruthlessly specialized huge
company) is that they may be an "extended cognition" worker, but still perform
many "non-extended cognition" activities as part of their job. Because there
was previously no alternative and work needs to get done.

Fast forward that, and you're never going to fully automate a goal. But you
will automate sections of the process that are amenable to machines.

Advice? Recognize which type of work you spend most of your time in, and don't
get caught being the "non-extended cognition" person...

------
quantgenius
AI arrived in Investing a long, long time ago. If you limit AI to deep
learning, as in deep neural networks, maybe only 3-5 years ago. Strategies
based on news have been around for decades. Figuring out what the news means
isn't necessarily as helpful as it seems because it's hard to put much size on
when there is limited time even if you are first. However, various patterns
around news is much easier and to do that all you needed to know was that some
important news had arrived, not necessarily whether it was good or bad, the
goodness or badness was plainly visible in how the price action. Figuring out
the magnitude but not the sign of the importance of a news item has not been
difficult for a long time. Yet somehow we keep getting articles about how AI
has arrived in investing.

As far as the return forecastability deniers out there, particularly the ones
who claim to be doing it on the basis of some sort of empirical thing, well,
if you can't be bothered to actually look at the data or even read academic
literature on the subject, I can't be bothered to educate you.

~~~
joncrane
If you can reliably predicts the magnitude, even without the sign you can
still trade very profitably on the volatility of a stock.

~~~
jnordwick
Not so sure about that.

I've literally missed the sign on a trade before, and it was 7-figure
disastrous. (I've missed the direction of movement on individual symbols a
number of times, but this one time I literally went the wrong way on
everything by accident.)

Markets adjust too quickly to flip your position and profit in any reliable
way. On planned or anticipated events, people are all locked and loaded
waiting for something to happen.

However, I'd much rather know the sign because at least I can put on some
position and guess a little at the magnitude.

~~~
perl4ever
I have no professional experience in finance, and I wouldn't try to go long
volatility because it's too expensive and risky, but why can't you buy puts
and calls at the same time? Or, I have read that there are options on the VIX.

------
rukittenme
Breaking news: robots and humans both equally unable to predict the next digit
in a random sequence. Obviously an incredible over simplification of whats
happening in finance and this article.

~~~
headmelted
Probably not that much of an oversimplification.

Side note: Why is it that we need something so physical to attach these
concepts to?

The photo of the monolithic POWER7 rig that houses Watson with it's
translucent logo is akin to all of the Bitcoin articles with shiny gold coins
with an icon. I understand the need to have some kind of image, but it's just
so detached from the reality of what's going on in practice.

Getting back on topic, I do wonder how much data they're feeding in - it's one
thing to pass masses of historical trades into the algorithm, quite another to
have it watch for relevant news events that affect the asset prices.

~~~
mevile
> Side note: Why is it that we need something so physical to attach these
> concepts to?

Posts with images get more clicks.

------
cik
I run a similar experiment, with real money and allow my robot to trade on my
behalf. For long-term investments, I continue to follow the indexed-only ETF-
based couch potato model, but I'm happy to let this run. I view it as a risky
investment, akin to investing in any startup, and have invested accordingly.

The other reality is that over the long-term it's highly unlikely to beat the
market. Realistically (almost) nothing beats the market over a long-enough
period. At the same time in my testbed, with real data, real 'money where your
mouth is' it worked. It's no crazier than any other idea.

Ultimately whether humans or AI drive investment is immaterial if you believe
in an indexed portfolio. Should those investment approaches succeed, they'll
join the indexes in some way. Similarly, should they fail, they won't

~~~
mikevm
I'd also really love to create a trader bot for part of my money. Any chance
you could give a few pointers on how to get started in this field? (good
resources to read, frameworks to use, etc...)

~~~
cik
Sure. I use a variety of free datasources - including Alphavantage, and the
nightly Nasdaq dumps, to collect a bunch of data nightly, in addition to real-
time. My robot is based on errbot - which I integrate with a private slack
organization/channel so that I can interact, and have all the logging
infrastructure I need.

The database is MySQL, and communicated with via SQLAlchemy (through errbot of
course), with a series of commands and crons (errcron) set up, in order to
both notify myself and execute on various data gathering activities. The rest
of the processing code is likewise - in python. I don't rely on scipy, numpy,
or anything else, given that I don't see the need.

The reality is that there are a series of activities that are profitable at
the micro) level in the geography in which I trade, which is why my robot
currently integrates with Questrade - specifically so that I can execute from
Slack, while I work at my 'regular' job. All passwords and reusable tokens are
stored in an ansible-vault, so that I can commit and push my repository
around.

I'm running two different experiments actively: one that does an arbitrage
based on data I'm looking into, the other than specifically tries to eke out a
$0.10 gain per share, closed daily. Going into Jan 1 2018, I'd made ~57% from
August 31 (first day of trading). This year, I'm down ~8% overall so far.
Passively, the return has been great.

Now, I'm changing my focus - enough people I know are generally interested and
willing to light the same amount of money that I am on fire. So, I'll keep
experimenting, but I'm taking 1% of the overall return for the 'bank' (i.e. my
corp).

This will all clearly catch fire.

------
_delirium
> the E.T.F. runs most of its calculations on I.B.M.’s Watson supercomputer

Every time I read an article that mentions Watson, it's sprouted a new thing
the name is applied to. Previously it was a question-answering system, which
famously won Jeopardy. Then it became a general NLP platform. Then it became a
brand name for basically all IBM machine learning offerings. Now it's also a
supercomputer?

If what this really means is that they built a bot that plugs a bunch of data
into IBM's cloud ML platform and trades on that basis, I'm not really
surprised it's not beating the market. Building an auto-trading bot using off
the shelf ML techniques is actually a pretty popular university project that's
worth trying if you're curious, though (at least with simulated money, or
money you can afford to lose). They can probably do better than a typical
university project, because I assume they have more extensive financial data
feeds. But everyone else serious about automated trading (which lots of people
are) also has those data feeds plus the same off-the-shelf ML, so unless they
have something else...

~~~
ardit33
Watson is a marketing term, and a division of IBM.

Think of it similar as "Amazon Cloud", which really consists of over 100
different type of services/products, some of them very different, and build by
different teams, but the "Amazon Cloud" is more of an umbrella.

~~~
zaphod12
and one that hasn't been terribly successful in a lot of areas! It's often
sold as almost a software/business consulting effort, which requires a ton of
money and time to get up and running

MD Anderson Cancer Center wasted $62 million on it:
[https://www.healthnewsreview.org/2017/02/md-anderson-
cancer-...](https://www.healthnewsreview.org/2017/02/md-anderson-cancer-
centers-ibm-watson-project-fails-journalism-related/)

------
jedberg
It's amazing how a little bit of light insider trading can trump all the
algorithms...

~~~
darethas
To take your comment a little deeper despite me knowing you are being
facetious, I think that's exactly it: the algorithms cannot communicate to
facilitate these types of advantages. They cannot, in essence, be human.

In a world ran and dominated by humans, there will always be an inherent
advantage to being part of the race that creates the game. If algorithms
perfect a system in such a way that there stands no gain to be made by those
at the top, people will simply create a new game to play.

~~~
ChuckMcM
until they can. And at that point it gets really weird. I have heard reports
(but cannot confirm them obviously) that machine learning techniques are
already creating trading strategies that exploit weaknesses in other trading
system algorithms. At what point does the algorithm correlate what it can see
in email inboxes on a connected cloud service with advantageous stock trades
...

~~~
danieltillett
This is where the real money is to be made in AI trading. Of course this sets
of a very interesting series of countermeasure/measure battles.

~~~
perilunar
Is money being made? Seems to me that all trading does is just redistribute
existing money, and no wealth is created.

What a waste to have all these computational resources engaging in a continual
'series of countermeasure/measure battles' instead of calculating something
useful.

~~~
aianus
Trading results in price discovery. Accurate prices allow more informed
investment decisions and the development of more real wealth. The alternative
is something like a centrally planned economy which have generally been
unsuccessful.

------
apetresc
My impression was that humans are still routinely bested by indexes in the
long run, so being "dominated" by humans sounds downright scathing.

> Those programs may be useful, but they are not A.I. because they are static;
> they do the same thing over and over until someone changes them.

Oh, I see. It's better because it's AI. My mistake, then.

~~~
hodl
Indeed! how could all humans beat the index?

------
WalterBright
In college in the 70's, a fellow student was developing a stock trading
program on the institute's PDP-11. He figured it was going to make him rich. I
asked him what the algorithm was, but he was very secretive about it.

It was likely some form of technical analysis.

I wonder sometimes if it ever worked out for him.

------
WalterBright
> artificial intelligence has an edge over the natural kind because of the
> inherent emotional and psychological weaknesses that encumber human
> reasoning.

It's Mr Spock's problem. He always produced inferior decisions because he
failed to take into account the emotions of others.

~~~
PeterisP
The Mr Spock's problem is fictional, designed to make for an interesting plot,
not to reflect reality.

For example, in humans, an innate lack of empathy (the ability to feel the
emotions of others) and being unemotional yourself are factors correlated with
being a _better_ , more effective detector of emotions and manipulator of
emotions; taking into account the emotions of others can be done better if its
done in an analytical way (however, it requires attention, it's not an "always
active" skill then), and lack of emotionality allows you to express the
emotion that's most beneficial for your goals in current situation instead of
whatever you actually think.

If anything, a realistic advanced AI / Spock should be expected to have the
communication skills of a good hostage negotiator combined with a charismatic
politician combined with a wise psychotherapist combined with a sleazy car
salesman. Having and feeling emotions is not required to understand them in
others and show them yourself. For _normal humans_ (excepting e.g. some cases
of sociopathy) it's hard to fake emotions because we're evolved to have
emotional expressions as a somewhat trustworthy, hard to fake signal; it's a
limitation built in homo sapiens, not an inherent limitation.

~~~
WalterBright
> not to reflect reality.

Oh, I know that well. I just find it amusing. Spock is actually the most
illogical character in the show, and the most emotional.

I'm not convinced this is intentional on the part of the scriptwriters. For
example, how does a scriptwriter write a character who is more intelligent
than the writer is? Most "advanced intellects" in scifi seem remarkably
average in their intelligence, reflecting the intelligence of the writer.

~~~
FeepingCreature
This is in the context of a certain work of _Harry Potter_ fanfiction, but you
may find this set of notes for how to write intelligent characters
interesting. I specifically direct your attention towards the section "Level 2
intelligent characters", which goes into how to write a character that appears
smarter than the author.

[http://yudkowsky.tumblr.com/writing](http://yudkowsky.tumblr.com/writing)

Also on Spock in particular, there's a good talk by Julia Galef, The Straw
Vulcan, about how irrational Spock really is and what a rational Vulcan
_should_ look like.
[https://www.youtube.com/watch?v=Fv1nMc-k0N4](https://www.youtube.com/watch?v=Fv1nMc-k0N4)

~~~
WalterBright
It seems that both of my observations are well-trod territory!

Anyhow, the book "Brainwave" by Poul Anderson has the best description of what
more intelligent characters would be like - they spoke with fewer words, as
the rest of the information was more obvious from context.

------
zitterbewegung
AI and humans have arrived in investing. S&P is dominating for now.

I just pulled out of my "intelligent" portfolio from a 401k rollover into the
S&P. Using that portfolio tool was unintelligent for me :(

~~~
hyprCoin
The more people that follow index funds, the larger my portfolio grows.
Definitely follow this advice, nothing can go wrong and the price can only go
up. Unless of course, there is a large withdrawal event looming around the
corner that will incredibly impacts the current market price of every stock.

When were baby boomers set to retire again?

~~~
sigstoat
> When were baby boomers set to retire again?

they've been retiring for years. 1945 births are 73 now, well into retirement
age. boomers will start retiring over the span of 2007 to 2034, depending on
when they were born and the age they choose to retire at. they'll then be
drawing down their retirement funds for decades.

are you trying to suggest that this ongoing multidecadal process will
constitute a large "withdrawl event"?

~~~
hyprCoin
What does it look like when a large group of people start selling a large
amounts of stock directly into a buy wall?

Fear of an insolvent retirement can trigger this behaviour which then can
compound on itself as other retirement plans are jeopardized. An entire new
generation of wealth giving up on prior security and stock distributions in
favor of new markets can also trigger this, such as what almost happened in
South Korea with crypto currencies.

Hope none of this happens of course, but please be aware of the risks you are
implicitly taking.

~~~
zitterbewegung
My retirement is primarly S&P at this time. Of course a 20% correction could
always be around the corner especially with the market being so high for so
long.

South Korea has a much different demographic than the United States. Samsung
plays a large part of the whole countries GDP.

Insolvent retirement is actually a fear of anyone. Primarily because you don't
know when you will die. So, how long do you accept the inherent risk and start
making your assets more liquid.

I really think that Baby boomers retiring isn't as big as an issue as the
consumer credit market and student loan credit. It seems right now that some
of the S&P's upside is the fact that its on the backs of people putting their
new toys on credit cards and finance plans. I don't think that this can last
forever and also the fact that the things they put on them keep on lasting
longer and longer.

But, for my retirement I'm pretty long on S&P (I'm only 30 years old). I am
not going to pull out at the moment and timing the market for things like that
is hard for me to fathom. Taking defensive positions is more for actually Baby
Boomers and people that are day trading. As you say that this correction will
be triggered by Baby boomers retiring the only thing that actually counters
that is medical science. I have a few coworkers in their 70s and they look and
act like 50 year olds.

~~~
hyprCoin
Here is my belief, may be different from yours:

There is a massive generational theft that's been happening over many
centuries. Property prices inflating along with the rising cost of education
and loans are further rigging the system towards the older, wealthy and
established.

Instead of this trend slowing, it's accelerating at the expense of class
mobility for the young, poor and intelligent. This disillusions these
individuals en masse.

Where have disillusioned intelligent people recently been life-changingly
rewarded for their efforts? Cryptocurrencies have done so, loudly. In fact,
there are developer celebrities in many of these communities.

The choice to the young and intelligent: Seemingly immediate power, prestige,
and potential class mobility versus an stressful period of self improvement
that causes extreme debt (college).

The game needs to be better for the young and intelligent or they are going to
play a different one. Many already are.

I'm extremely long on cryptocurrency for this (and other) reasons. For a sense
of time scale, I have an iota retirement plan that begins distribution in 10
years and lasts 35.

~~~
nl
Can I ask how old you are?

Why do you think that Cryto-currencies are fundamentally different to the
internet boom which made 20-somethings like Larry Page/Sergy Brin/Mark
Zuckerberg some of the richest people on earth in only 10 to 20 years?

I’m sure plenty will get rich on Cryto. I’m unconvinced that this time that
makes it different for some fundamental reason.

~~~
hyprCoin
Sure, I'm 35.

The ease of access to capital for good ideas without any of the bullshit
involved in startup fund raising is what has convinced me of this. It really
doesn't matter what ivy league school the CEO went to, it's outweighed by the
idea, the ability to execute and the ability to convince others to contribute
resources.

Crypto is like the internet boom if the boom was more distributed, as anyone
could take part in investment from the seed round.

------
indescions_2018
Market capitalization based weighting, the basis of the Nasdaq-100 index and
$QQQ ETF, probably constitutes a baseline for what can be considered
"unbiased". Any AI agent that measures market "sentiment" can only be
conditioned upon the quality of the data it is fed. Which will vary across
companies.

An example of one of the best algorithmic strategies I have seen is the
following. During secular bull market eras. Simply buy and hold for a period
of 24 months. Every IPO that comes down the pike. Regardless of sector.
Backtesting this strategy yields annualized 50% rates of return. Which beats
$FB performance the last four years :) No doubt, ML could further optimize
selectivity, weightings, hold duration, etc. The central thesis is that growth
in market cap is strongest during the growth phase of a company.

Of course, today is the day another great algorithmic trading idea: fading
volatility spikes. Unwinds in most violent and consequential fashion. Be
cautious out there!

Two Big Volatility Players May Be on the Loose as VIX Tops 15

[https://www.bloomberg.com/news/articles/2018-02-02/two-
big-v...](https://www.bloomberg.com/news/articles/2018-02-02/two-big-
volatility-players-may-be-on-the-loose-as-vix-tops-15)

~~~
nradov
Most retail investors aren't able to participate in most IPOs. The majority of
IPO shares are allocated to institutional investors or high net worth
individuals. Your strategy doesn't work if you can't get a share allocation
and have to buy on the secondary market at higher prices.

~~~
perl4ever
The other problem is identifying "secular bull market eras". Well, identifying
them going forward, not retrospectively.

------
paulryanrogers
Ultimately markets serve humans, even if the number of beneficiaries is
shrinking. And living in a world of limited resources I doubt that AI will
have a long term future. It's so dependent on humans to provide: electricity,
computer hardware, maintenance, and even purpose.

Humans, at present, also seem better equipped to adapt to irrational markets;
especially when they are the source of irrational behavior.

------
frgtpsswrdlame
>Between Oct. 18, when it began trading, and the end of the year, the E.T.F.
rose 3.1 percent, compared with a 5.1 percent gain for the Standard & Poor’s
500-stock index.

A three month track record? "Dominating"? Come on. This article is either an
advertisement or a nothing-burger to get that clickbait headline although I
can't decide which.

------
LearnerHerzog
> _" It is to early to say whether the E.T.F., A.I. Powered Equity, will be a
> trendsetter or merely a curiosity."_

The New York Times are now hiring people who don't know the difference between
"to" and "too"? Well, that explains the sophomoric understanding of AI
showcased throughout the rest of the article!

------
jumpkickhit
You can see the unregulated AI in the cryptocurrency markets.

I wonder what the profits have been so far. People have invested in faster
internet trunks for trading ages ago, just for a few ms quicker trades.

[https://www.forbes.com/forbes/2010/0927/outfront-netscape-
ji...](https://www.forbes.com/forbes/2010/0927/outfront-netscape-jim-
barksdale-daniel-spivey-wall-street-speed-war.html#362f56f741ad)

[https://www.popularmechanics.com/technology/infrastructure/a...](https://www.popularmechanics.com/technology/infrastructure/a7274/a-transatlantic-
cable-to-shave-5-milliseconds-off-stock-trades/)

------
sandworm101
"Investing" is more than public stocks and other securities. Humans will
always be needed for investment in new tech or evaluation of a venture's
potential. Show me the machine capable of pickinv between vhs or betamax ...
before either hit the shelf.

------
gumby
Amazing they could write a whole article like this and not mention funds like
2Sigma which are entirely AI-focused. Those funds have been sucking cash out
of the rest of the managed fund sector at an astonishing rate (2S alone have
over $50Bn under mgmt).

No connection to these guys BTW

------
acd
The title is misleading that humans dominate investing.

Cats selecting stocks with its whiskers and monkey throwing darts on a
newspaper on average beats most human professional investors. Most amateur
investors are better of with low priced index funds tracking stock index than
buying more expensive managed products as those have higher fees.

Book A random down walk wall street.
[https://en.wikipedia.org/wiki/A_Random_Walk_Down_Wall_Street](https://en.wikipedia.org/wiki/A_Random_Walk_Down_Wall_Street)

~~~
narag
If machines are better than human investing, is there people that use machines
to select investments? I don't mean high frequency, but long-term.

~~~
zone411
Since it's a trade secret, it's hard to know exactly what they do and how much
human input there is - but a couple well-known quant hedge funds are
Renaissance Technologies and Two Sigma. They were both started by
mathematicians/computer scientists and they manage 10s of billions.

------
vadimberman
Considering that today the press can label any piece of software AI, one could
say it happened in 1990s.

------
harry8
Return over 10 years after fees as compared to a minimum expense index fund.

Everything that loses to that is a con (98-99% of actively managed funds).
Matters little if you were ripped off with a human picking the losers, an AI
or both or neither.

------
idrism
If humans are still dominating, AI has not arrived.

------
sirmoveon
A.I. doesn't have insider trading expertise.

------
sabujp
you don't buy on a dip, you buy after the dip is finished and it starts going
up again

------
SirLJ
Good morning NYT, i have been doing this for years with my stock trading
robots and my inspiration was not some obscure SV etf or other fin tech
gimmick, but the leaders on Wall Street period like RenTec, 2Sigma, etc...

------
superquest
Stopped reading after their first example of an investing model was "high
frequency trading" ...

------
blunte
"It is to early"... I know it's picky of me, but when the NYT can't edit their
work, what is the point of even trying to educate children on grammar. Surely
this was just a typo, but that is no excuse.

~~~
CodeCube
Let them who has never released a bug into production throw the first stone ;)

