What I Learned About SaaS at Buildium - <AUTHOR> https://www.outseta.com/posts/what-i-learned-at-buildium <comment><USER2> This is a really strong piece, with some great insights on culture, marketing and business.

One thing I'd add is that it's really important, critical even, that marketing is operating across the business - supporting customer success, sales and even product and engineering.

Very often marketing sits in a silo as a kind of production house and actually loses track of what is happening in the rest of the business. They end up producing stuff that sales cannot use, they're not connected to actual customer pain points and they lack detailed knowledge of the product.

For marketing to operate at its best and to be really useful, it needs to act as a support function to other areas of the business, as well as delivering world-class campaign and brand execution. This isn't 'knowing HTML and CSS' but it's definitely getting involved in other areas of the business.

<comment><AUTHOR> Great points—I 100% agree. While at Buildium I actually built our three marketing teams—acquisition marketing, product marketing, and corporate marketing to support many of the different functions you mentioned.

</comment></comment><comment><USER3> The MIT Entrepreneur course on EdX also mentioned dominating a beachhead market. Their definition is, "A beachhead market is the place where, once you gain a dominant market share, you will have the strength to attack adjacent markets with different opportunities, building a larger company with each new following" [1].

Nice to see an example of that in real life. Did Buildium eventually target adjacent or new markets?

[1] [https://executive.mit.edu/blog/launching-a-successful- start-...](https://executive.mit.edu/blog/launching-a-successful-start- up-3-the-beachhead-market)

<comment><AUTHOR> Buildium stayed pretty true to their original market, focusing mostly on serving that market with a greater level of depth through additional products and services. RealPage, the acquirer, sells to a number of adjacent markets and is moving into the market for small, residential property managers via the acquisition.

</comment></comment><comment><USER4> I specialize in vertical specific SaaS marketing (Zenefits, brightwheel, etc), and this is a really solid article - just emailed it to a bunch of SaaS folks I know.

<comment><AUTHOR> Thank you! Happy to hear you liked it.

</comment></comment><comment><USER5> "What they did effectively early on is bring other hugely talented people onto the team before they could afford to pay them their market worth. They did this by paying several of their early employees in sweat equity that they accrued at the same rate as the founders for time spent working on the business. "

But Buildium is quite a few decades in the making, does this attitude exist among the new startups of today? I doubt that.

Thank you for the article Geoff. Fantastic insight. And one that's very well written, I enjoy how much focus you put into the article around culture, especially one of your finishing paragraphs.

"If you have a high-functioning and aligned team that can respectfully disagree with each other yet still make decisions and execute, you can overcome just about any challenge in business. On the flip side you can have every market advantage in the world, but if your organization isn't healthy it's only a matter of time until you reach your demise. I believe this to be true."

I'll make sure I read 'The Advantage' at my earliest opportunity. Thanks again!

<comment><AUTHOR> Thank you so much for the kind words! Buildium found a good market opportunity and built solid technology, but culture and how the business was run was definitely part of its special sauce and a major contributing factor to this sort of outcome. The Advantage is a great read! -Geoff

</comment></comment><comment><USER6> > if I should take a course to learn HTML and CSS—her answer surprised me: > Absolutely not.

Well, that's a mistake. You don't have to be good at it but if you have to understand 101. In any executive role in a web SaaS.

<comment><AUTHOR> Disagree. Not everyone is a SaaS company needs to have technical skills. Would you expect everyone to have sales skills? Or marketing skills?

<comment><USER7> Yes, I would. At least basic skills. Depending on the size of the course referenced above... I'd say sure - take it. Be _familiar_ with it, and the potential problem space it addresses - have a rough idea of what's possible, what the state of the art is, etc.

Likewise, I would also expect people to have basic knowledge of sales and marketing. If you're in a meeting and people are talking about ROI and CPM and specific strategy, I would expect the other people in the meeting to have a _basic_ understanding of what those terms mean, how they impact the business and peoples' ability to meet their goals, etc. People don't need to be experts, or even journeymen, but ... the opposite, where people think they shouldn't have to have even a basic grasp of the fundamentals of the technology their tech company is built on... that's a bit odd. Where that line is drawn may be up for debate, but some understanding can't hurt.

In a car company, if a marketing person started making wild technologically impossible things about what the car could actually do... alarm bells would be ringing. I don't think there should be that large a divide in any company, really.

<comment><USER8> I would definitely recommend understanding fundamentals, but I've found a lot of "us" want the see the C-suite taking an actual coding class, which I feel is only marginally more beneficial.

<comment><USER7> oh agreed - there are still some limits to this - a CEO doesn't need to understand the differences between an interface and an abstract class, know hex color codes off the top of their head, etc.

<comment><USER8> I will say one of my favorite memories is when our founder who (not an engineer, but intelligent as he has a law degree) corrected some of my SQL early on when we were working up some ad hoc reports.

</comment></comment></comment></comment></comment></comment><comment><USER9> Excellent write-up and interesting story - thank you for sharing. I'm wondering about whether Buildium had to restructure itself from LLC to C Corporation prior to the first VC round (or subsequent rounds). VCs very rarely invest in LLCs ...

</comment><comment><USER10> _" A huge percentage of Buildium's revenues come not from subscriptions, but instead from pay-per-use payment processing revenues when tenants pay their rent online."_

Aren't rent payments typically recurring though?

<comment><AUTHOR> So Buildium makes money off of normal subscription payments like any SaaS business does by charging a monthly fee to property management companies for access to their software. They also make money by taking a small percentage of rent payments that are processed online via the platform. These are rent payments that tenants pay to their property management company, not Buildium itself. Said another way, the tenant has no obligation to pay Buildium whatsoever—but with rent payment being regular and recurring, Buildium captured predictable revenue by capturing these payment processing fees.

<comment><USER11> I think that's the point. Recurring but not subscription. It's a minor difference in this scenario since you probably know with great confidence a % will recur.

It's just a weird wording distinction that made it a weak counter example of subscription revenue. Like if you pointed out that no American consumer has any obligation to shop at Walmart next month. But we know most will.

</comment></comment></comment><comment> all-out-of-hope SaaS: Software with a subscription model, that's it.

All these "market experts" and PR people extolling the virtues of the radical idea of paying people for a service remind me of all these dumb cryptocurrency bitcoin shills.

<comment><USER12> That's not it. Adobe CC is an example of simply software with a subscription model. Or lots of other perpetual software that is complex and requires a support subscription.

SaaS is a lot different than that. SaaS runs on someone _else 's_ computer, with all the plusses and minuses that brings.

</comment></comment><comment><USER13> The article is mostly from the prospective of a B-school grad seeing SaaS's and the particular one was based on property managers which is more concrete as a topic. I didn't get much transfer of the experience to software SaaS's.

<comment><AUTHOR> What do you mean by "software SaaS's?" Software products sold to other software companies?</comment></comment>


Give HN/YC: $100 Adwords voucher - <AUTHOR>

Dear HN,
I received a $100 adwords voucher from Google for valentines day. Since I have no need for it right now, I would like to give away to a YC company who could use it for advertising.
I guess a few of you may want it, so just post a sentence describing your startup and how you'll use it.
I think it would be best used with someone selling a product/membership that needs targeted traffic. Thanks guys.
<comment></comment><comment></comment><comment></comment><comment></comment><comment>-----
Terms on the back of the card: - must be applied to new adwords account within 15 days of creating the adwords account and is only valid for new adwords customers with self managed accounts - advertisers will be charged for advertising that exceeds the promotional credit. advertisers will need to suspend their ads if they do not wish to receive additional charges beyond the free credit amount.
Offer expires march 31, 2010. After March 5, offer drops to $75 (as per Google terms). I'm Canadian but I think this can go to anyone.
http://www.google.ca/ads/overload/ </comment><comment><USER2> We are mortgage leads generator.Would require $100 Adwords voucher to promote our website. Pls mail me the voucher at firstname.lastname@example.com

Thanks in advance

</comment><comment><USER3> Doesn't it say "non-transferable" somewhere?

<comment><AUTHOR> It does say non-transferable, but I'm not sure that they track/validate it, unless you know for sure otherwise.</comment></comment>


Ask HN: How to build something better than HN? - <AUTHOR> Let's say I want to build something that is better than HN, what do I need ? (Let alone the technical and coding side) <comment><USER2> Community and heavy sensible moderation.

A community is important, the initial community here was the readers of the pg blog. StackOverflow has a similar origin, the readers of JoelOnSoftware and CodingHorror.

In spite of the plain appearance and the lack of explicit meta discussion, this site is extremely heavily moderated. But it's important to have a sensible moderation, not a crazy arbitrary moderation. The line between to few moderation and too much moderation is very thin ...

</comment><comment><USER3> Define 'better than'?

Your first step is to get a clear set of requirements, the only reason competitors ever emerge is because of a failing or perceived failing of the incumbent.

So you must think HN is doing something wrong, or could be doing something better?

</comment><comment><USER4> Define "better"</comment>


Phone Call with UMG and Kim Dotcom - Ad Replacement - <AUTHOR> https://soundcloud.com/kimdotcom/universal-music-group-and-kim-dotcom

<comment><USER2> Wow, this is amazing. Wonder who called the feds in, since it sounds like UMG was liking this idea.</comment>


Ask HN: How do you backup your Google Drive data? - <AUTHOR>

With today's Gmail outage, it got me thinking about how best to backup Google Drive.  What software/services are you using to backup Google Drive? <comment><USER2> [http://gmailblog.blogspot.ca/2013/12/download-copy-of- your-g...](http://gmailblog.blogspot.ca/2013/12/download-copy-of-your-gmail- and-google.html)</comment>


Lessons Learned From Female Founders and BossedUp Conferences - <AUTHOR> http://findingferdinand.com/blog/2014/3/2/entrepreneurship-lessons-learned-from-y-combinator-female-founders-bossedup

<comment><USER2> This was a great conference. I didn't attend (I'm male), but I watched the livestream and learned a lot from the speakers, so thanks for sharing your lessons learned.

I especially liked the conference because I learned about the female perspective. My wife isn't a startup founder, but has a similarly stressful job (flies F/A-18's in stressful, life-threatening situations), with similar hours (14hrs/day and often weekends), in a similar environment (male-dominated Marine Corps). I often wonder how she'll manage her work when we have kids...everything from pregnancy to making time for the kids when she's busy. It's easier for me since I work at home now, but she'll deal with the same challenges that some of the founders mentioned. And knowing her, she'll feel incredibly guilty for not being around.

Anyway, I enjoyed the conference, learned a lot, and look forward to it next year.

<comment><USER3> It's great to hear your support and appreciation for your wife's work!</comment></comment>


Aaron Swartz: How to Get a Job Like Mine - <AUTHOR> http://aaronsw.jottit.com/howtoget <comment><USER2> This kid is crazy.

PG, if you look at successful YC startups (Loopt, Reddit, Zenter) has there been any pattern in the character of the founders?

I can't imagine someone with Aaron's character leading a successful company - his history (Infogami)supports this.

<comment><USER3> You know, it is possible to do important things, even important things with computers, and not be cut out for a life in business.

Once upon a time, for hackers, it was considered a step _down_ to work in industry. However, it's since been shown there's a lot of money to be made, and lately PG's been spreading the gospel about how entrepreneurship is the true calling of a geek. But it's just not always the case.

Anyway, even if your premise about Aaron is true, the man's already done more with his short life than almost anybody on this site. Even on the business side.

For some reason Aaron feels compelled to talk out almost every personal failing he has in public. I don't know, if the famously mercurial Steve Jobs or Larry Ellison actually recounted all of their meltdowns candidly, they might sound something like Aaron's blog.

</comment></comment><comment><USER4> I always thought reddit was well established before AS joined. The content was much better even with 3000 visitors. I think the 'reddit this' links must have been the biggest factor in reddit's decline. Interesting to see he joined the RDF group, also with some objection.

<comment><USER5> I'm amazed they only had 3000 at the time of the Python rewrite. It seemed much bigger than that if I remember correctly.

</comment></comment><comment><USER6> "Say yes to everything."

Best advice I've ever read here (except for some of pg's essays).

Always saying yes separates you from the other 99%. Later, people will remember and good things will come your way seemingly from out of nowhere. People will think you're "lucky", but you'll know the secret...always saying yes planted seeds for your future.

<comment><USER7> >Always saying yes separates you from the other 99%.

Yes, but only if you can carry through with the things you promised to do. If not, they'll hate you for saying yes all the time.

<comment><USER6> Of course, that goes without saying.

</comment></comment></comment><comment><USER8> _And I spent all of it obsessively reading the RSS 1.0 mailing list_

No wonder he gets invited to all the best parties.

 _a list of companies I thought were good ideas and pulled the top one off the list. The idea was this: make building a web site as easy as filling in a textbox._

AWESOME!!! It's like a _comment section_ with only one entry, with the whole thing renamed "web site".

He apparently has some sort of wacky charm, and that is how he's gotten where he is. His genius is obviously anchored firmly to the mundane.

<comment><USER9> No, what he is saying is excellent advice. You have to meet and socialize with other _people_ to a certain degree no matter which path to success you take.

Very rarely does someone become wildly successful 100% on his own.

</comment></comment><comment><USER10> I think this talk first presupposes that the audience would like a job like that, which is probably a stretch. His accomplishments notwithstanding, his current job seems pretty undesirable to me.

<comment><USER11> Agreed. And with his cocky and conceited personality, who would want to even associate themselves with him?

<comment><USER10> Personal judgments aside, his current job just plainly seems undesirable to me (based on his description of it).

That's not making a judgment on him or his past accomplishments.

</comment></comment></comment><comment><USER12> He made two really interesting points:

     * It seems that YCombinator's boost is not that big as everyone thought. After first three months they hardly got three thousand visitors a day.
     * Buzz, even negative, really matters. Despite negative comments about the rewrite, without this it is very likely that they would not grow so quickly.

<comment><USER13> 3k visitors after 3 months is not half bad

<comment><USER12> Far from taking over the world, too.

<comment><USER14> You don't join Y Combinator because you hope to increase traffic to your site.

</comment></comment></comment></comment><comment><USER15> That was good!

You know, there are a lot of people who want a job like Aaron has, but I think I know from experience what the immediate result is going to be.

Someone like Westwood College is going to offer a program in web entrepreneurship.

I'm sure the TV spot will be the equal of their legendary game development commercial:

<http://www.youtube.com/watch?v=spSGNMJhWV0>

</comment><comment><USER16> Not related to the story: Is it just me or the the width of this page annoyingly big? Seems that the pre-tag on the comment by maurycy kills text wrapping for those lines and thus makes all the text really wide = not easy to read.

Screenshot: <http://screencast.com/t/B65U14h4e>

<comment><AUTHOR> yeah, this is an annoying bug, it is worth making the <code> blocks wrap to get rid of it

<comment><USER17> Don't make them wrap, just use style="overflow: scroll".

<comment><AUTHOR> What would that style do, exactly?

</comment></comment></comment></comment><comment><USER6> "I couldn't stand office life."

Neither can I. Never could. Only difference between cubicle hell and jail is that we still have to pay for our own food.

Why don't companies understand this? Take the same work out of the office and get twice as much done. While loving it.

We suffer because they don't know how to manage any other way.

<comment><USER18> That may be true for the likes of news.YC readers, but we're a self-selecting sample.

Based on the office experiences I've had the misfortune to endure, people like us might be at 50% productivity instead of 90% at home, but the majority of cubicle dwellers are are 10% instead of 0% at home.

Maybe I'm inappropriately pessimistic, but even if that's not the case, I'd imagine that's the thing that has kept, and will keep, telecommuting and the like from becoming more than the occasional fringe benefit for the occasional employee.

</comment></comment><comment><AUTHOR> Aaron's to read list: <http://aaronsw.jottit.com/toread> I bet there are some gems in here if anyone has the time to skim through.

</comment><comment><USER19> Summing up:

\- Be smart, be prepared.

\- Get out there and network a lot. Get involved.

\- Get lucky.

</comment><comment> daniel-cussen What's his job, anyway?

<comment><USER20> Sitting around, counting his money. Occasionally does some emailing.

</comment></comment><comment><USER9> I believe I am terribly bad at #3.

Thanks for the suggestion.</comment>


Naval Ravikant and Rob Reid on Existential Risk - <AUTHOR> https://after-on.com/episodes-31-60/044 <comment><AUTHOR> Transcript: [https://static1.squarespace.com/static/58de89eb17bffc754e3c1...](https://static1.squarespace.com/static/58de89eb17bffc754e3c1d33/t/5c8f20fde79c7057fcd7680b/1552883966509/Naval+Part+1+Transcript.pdf)</comment>


Audi, Mercedes Planning to Lay Off Almost 20k Workers - <AUTHOR> https://cleantechnica.com/2019/11/30/audi-mercedes-planning-to-lay-off-almost-20000-workers/ <comment><USER2> German here. That's what you get for refusing to move a few eggs into the EV basket early.</comment>


College Townies: How Do You Honour A Place As You Breeze By? - <AUTHOR> http://www.thetowner.com/college-townies/ <comment><USER2> What 90% of college graduates fail to consider is that many of those townies will one day be far richer than they are.

The idea of students 'looking down' at (for example) the local plumber is often ridiculous, considering a plumbers' hourly rate often exceeds that of many lawyers.

As we all know, there is a frightening, decreasing correlation between college education and financial success. At the same time there are plenty of locals who work hard and pour money into real estate.

It's a disturbing truth for most college graduates who drink the kool-aid of "education equals financial superiority". And colleges are only too happy to serve up that kool aid.

eg: I know a guy my age who owns a dozen hardware stores. He made his first million before he was 30, and he dropped out of high school. He's also one of the sharpest business people I know.

Be nice to everyone. You might learn something.

<comment><USER3> That's not really the point he was making in this article, which was more about people that make their homes in multiple places. It was using the term townie differently from the standard definition.

<comment><USER2> Just in case this isn't 100% clear to anyone: "Townie" is derogatory.

</comment></comment></comment><comment><USER4> Always treat people as people. If you're treating someone as a "means to an end" then you're not treating them humanely. That's exactly the way to win enemies and violent tendencies. It goes the same with towns and cities in aggregate.

Know that I say this as someone who doesn't feel very welcome where I live currently. The many aggressive behaviors I experience daily have made me resent this place. So I look for ways and places to appreciate it here. I'm still looking to leave. But I'm also embracing my existence here.

</comment><comment><USER5> I feel I have this problem(?) still, years after graduating college. I have lived a few places now, and held several jobs, and each time I have treated both the location and occupation with an air of impermanence. I neglect to make friends or make any long-term commitments because I know I will one day leave them behind.

</comment><comment><USER6> >This attitude manifested itself most corporally in the behavior of the local college students in traffic; they would wander in and out of the street without looking, exuding a kind of studied indifference, sending a clear message to the local people that the streets were for them, risks of blunt force trauma notwithstanding

It's one of my favorite things about college campuses that pedestrians own the streets and cars wait their turn.

You could always tell when it was parents weekend by the huge size of cars on the streets and their unusual aggressiveness at crosswalks. Suburban/exurban parents out of their element. It was always satisfying to see them ticketed. _This is an urban college campus. That shit doesn 't fly here._

It's not really about student vs. townie, it's just that these few blocks, unlike almost anywhere else in the country, are for walking.

</comment><comment><USER7> This hits home. I am also a faculty kid. You grow up thinking the university is awesome. And it is. You get involved in the university when you are older and find that the students for the most part treat the city and its residents like crap. The word townie is thrown around in a derogatory manner towards the locals. You are left thinking why the heck should I support this university when the alumni base has such a bad view of the people that actually live in the city. I realize that not everyone at the university is like that but its enough that it seems like a real cultural problem.

</comment><comment><USER8> Is this more common in the US? Because in my country it seems to be the absolute opposite. The permanent residents (or the locals as we call them) are extremely apathetic towards the students. Whereas the students (me included) absolutely fell in love with the place and find it hard to leave.

The locals also take advantage of the relative wealthiness of the students (higher education is not cheap) and you will find them skirting rules everywhere: autos don't run by meter, you are charged extra for cold bottles of soft drinks, restaurants and pubs are extra pricey and so are the rents - all this compared to a bigger non-university town just 5 kms away.

<comment><USER9> There are different kinds of "college towns" in the US.

Boston is a big college town because it has several of the nation's most important/prestigious institutions of higher education—but it's also a distinctive and vibrant city in its own right, with a unique history, culture, built environment. New York is similar.

But many of the state universities and land grant universities, especially in the West, put the state's largest and most important school in a small and otherwise unremarkable town. Norman, Oklahoma, has a population of 110k and the University of Oklahoma, which has enrollment of 30k. Lawrence, Kansas, has a population of 87k and the University of Kansas, which has enrollment of 28k. West Lafayette, Indiana, has a population of 29k and Purdue University, which has enrollment of 40k. Bloomington, Indiana, has a population of 84k and the main campus of Indiana University, which has enrollment of 49k.

These are all nice little towns, but they are all relatively small towns with small enconomies, and there's just a limited number of college graduates they can absorb. They usually have local political cultures strongly influenced by the college and very different than the small and rural communities that surround them.

Plus, lots of American communities can seem very generic. Many Americans towns are less than a century old, with only a few generations of traditions and history, and surrounded by similar communities with a similar size, culture, environment, and history.

<comment><USER10> I wouldn't consider Boston a "college town", and I doubt it qualifies according to this article.* A "college town" usually means a town where the college dominates the local economy, and the students make up a large portion (or even a majority) of the total population during the school year.

I used to go to Virginia Tech; at the time, there were roughly 34k people in the town during the year, 26k of those students. The "townies" were only about 8k (and of course, this included the staff and faculty that lived within town limits, which was a significant portion of the townies). So when it was summertime, the town was seemingly deserted (and it was a wonderful time too!).

* As an example, Tempe, Arizona is home to ASU, one of the top 10 universities in the US by enrollment. Look at the map in the article: there's no dot for the Phoenix metro area. Hence, Tempe (and the rest of Phoenix) is not a "college town", because even with over 50k students, the school doesn't dominate the local economy.

<comment><USER9> "Ian Faith: The Boston gig has been cancelled...

David St. Hubbins: What?

Ian Faith: Yeah. I wouldn't worry about it though, it's not a big college town."

Boston and New York at least have large populations of college students, but certainly they're not iconic of what Americans consider a "college town".

</comment></comment></comment></comment><comment><USER11> Well hey, I live here too! Actually I've lived here my whole life, growing up in West Lafayette and attending Purdue, and then working here as a software engineer after graduation. The author is spot on about many of the drawbacks but there are quite a few nice things that are hard to appreciate unless you've actually experienced them.

One I think is quality of living for the price. I'm pretty sure that by several metrics my quality of life is much better than that of many friends living in NYC or SF. I make about 1/3 of their salary on average but I have a relatively large apartment, walk 8 minutes to work every day, see my parents about once a week (starting to appreciate this more and more as I get older), have a steady supply of graduate student friends and my own colleagues who I went to school with to converse and hang out with, and a Purdue community to engage with and learn from.

Drawbacks for me are a intense feelings of FOMO as I read about the innovation happening in real tech hubs, a lack of a larger network of startups and strong engineering companies, no big city to experience, and seeing my parents once a week ;).

I don't want to stay in West Lafayette forever (although I would strongly consider moving back here to raise a family) and maybe I'm just rationalizing my situation, but the SF-or-bust feelings I used to have in college have subsided quite a bit.</comment>


iPhone 6 vs. Nikon DSLR - <AUTHOR> http://filipmolcan.com/blog/2014/9/20/iphone-6-vs-nikon-dslr-d7100

<comment><USER2> "Photographically speaking, having the camera with you is a real benefit." \- Jay Maisel

Which one's always on you? If you, like some photographers I know, always have your camera around your neck, great. For everyone else, there's the iPhone.

Edit- added attribution

<comment><AUTHOR> Agree! Professional photographers will still use a DSLR but regular people will shoot these images with their iPhones. And the new iPhone is brilliant in it.</comment></comment>


There's No Fire Alarm for Artificial General Intelligence - <AUTHOR> https://intelligence.org/2017/10/13/fire-alarm/ <comment><USER2> I've been around AI since the end of the last big hype in the late 80s. The recent leap in machine learning has felt rather hyped to me. I don't think AGI is near.

But I find myself agreeing with this article. Strongly.

And I have long suspected that, we miss a lot of the significance and opportunities in AI, because we have only one exemplar of 'higher' intelligence: a human being. AI folk are so concerned with getting computers to do the things that humans are good at, I suspect most will miss / 'refute' / deride the inflection point, because the system can't wash the dishes (or some other form of embodied cognition), or write poetry humans would find beautiful, (or understand some other socially-conditioned cue).

The superhuman fallacy really is the bane of AI.

<comment><USER3> The article makes a lot of good points, but for me, the critical error is in assuming that if short term prediction is hard, long term prediction must be massively harder.

He asked a panel for the least impressive thing they did not believe would be possible within a few years. In other words, pick the point closest to the boundary of that classifier. Obviously my future knowledge is imperfect, and anything close to the boundary is subject to a lot of uncertainty. From that difficulty, he hand waves an argument that long term prediction of the unlikelihood of AGI is folly.

The problem is that these aren't in the same class of predictions. One is detailed and precise; the other coarse and broad. Predicting that it will rain at 2:00 PM November 10, 2017 is much more difficult than predicting that the average summer of 2040-2060 will be hotter than the average from 1980-2000. Precise local predictions just arent the same thing as broad global predictions, and difficulty doesn't transfer, because I'm not bootstrapping my global prediction on the local one. I'm using different methods entirely.

There's a similar thing with AI, I think. I can't confidently tell you what the big splash we'll see at NIPS next year or the year after. But I can look at the way we know how to do AI and say I don't think 30 years will see a machine that can make dinner by gathering ingredients from a supermarket, driving home, and preparing the meal.

<comment><USER4> > I don't think 30 years will see a machine that can make dinner by gathering > ingredients from a supermarket, driving home, and preparing the meal.

Really? Why not? Once or twice, if we cherry-pick its performance, or reliably?

This is really surprising to me.

<comment><USER3> I mean reliably, the same way a human does. I can make a lasagne tonight, or lobster risotto, or whatever. I can decide on a thing, buy ingredients, chop things, get that lobster out of the shells, find the right recipe, substitute according to taste, and loads of other things that are somewhat related to making food. I can wash the pan I need, improvise a stove lighter if the igniter fails, etc.

We might be able to make machines to do each of those tasks, but that's not the answer. I might do 100,000 things in an average week. Clearly we aren't going to build 100,000 bespoke CNNs and LSTMs. To worry about superhuman AI, we probably have to figure out how to make one or a few machines that aren't gloried deep fryers.

<comment><USER4> > Clearly we aren't going to build 100,000 bespoke CNNs and LSTMs.

I get what you mean, but I don't think we should assume this.

</comment></comment></comment></comment></comment><comment><USER5> > _They will believe Artificial General Intelligence is imminent:

(A) When they personally see how to construct AGI using their current tools. This is what they are always saying is not currently true in order to castigate the folly of those who think AGI might be near._

This struck a nerve. Too often, in many scientific disciplines, and even in informal conversations, the people who always demand 100% clear evidence use this fallacy to shut down discussions. (They very often come off as not impressed with the evidence even if it exists and is presented to them as well.)

HN also has a huge camp of such discussion stoppers, even for topics where you _CLEARLY_ have no way to have 100% clear evidence -- like the secret courts and the demand to spy on your users if you're USA based company; thousands more examples exist. Many discussions are worth having even if you don't have all the facts. We're not gods, damn it.

That was slightly off-topic.

Still, I find myself in full agreement with the article and I like the attack on the modern type of shortsightedness described in there.

Also, this legitimately made me laugh out loud:

> _Prestigious heads of major AI research groups will still be writing > articles decrying the folly of fretting about the total destruction of all > Earthly life and all future value it could have achieved, and saying that we > should not let this distract us from real, respectable concerns like loan- > approval systems accidentally absorbing human biases._

<comment><USER6> This is an error Eliezer has also written about: [http://lesswrong.com/lw/1ph/youre_entitled_to_arguments_but_...](http://lesswrong.com/lw/1ph/youre_entitled_to_arguments_but_not_that/)

</comment></comment><comment><USER7> Great read, and I don't mind at all that the last section was a pitch for donating to MIRI. I have been an AI practitioner since 1982 and have enjoyed almost constant exposure to people with more education and talent than myself so I feel like I have been on a 35 year continual learning process.

I think that deep learning is overhyped, even though using Keras and TensorFlow is how I spend much of time everyday at work. I have lived through a few AI winters, or down cycles, and while I don't think that the market for deep learning systems will crash I think it will become a commodity technology.

I believe that AGI is coming, and I think it will use very different technology than what we have now. Our toolset will change dramatically before we can create AGI. I use GANs at work, and in spite of being difficult to train, the technology has that surprising and 'magic' feel to it, however, so do RNNs, and that technology is 30 years old.

I am going to show my age, but I still believe in symbolic AI. I am also fairly much convinced that AGI technology will be part symbolic AI, part deep learning, and part something that we have not yet invented.

<comment><USER8> Got any suggestions for a knowledge source of AI at a 100-1000 foot view? Ie not stuck in the weeds, but enough to know what's going on nd where.

<comment><USER7> If you can spend 5 or 6 hours a week, take Andrew Ng's machine learning class on Coursera.

</comment></comment></comment><comment><USER9> Can someone please explain what has happened in ML or AI that makes AGI closer? Whilst some practical results (image processing) have been impressive, the underlying conceptual frameworks have not really changed for 20 or 30 years. We're mostly seeing quantitive improvements (size of data, GPGPU), not qualitative insights.

ML in general is just applied statistics. That's not going to get you to AGI.

Deep Learning is just hand-crafted algorithms for very specific tasks, like computer vision, highy parameterised and tuned using a simple metaheuristic.

All we've done is achieve the "preprocessing" step of extracting features automatically from some raw data. It's super-impressive because we're so early in the development of Computing, but we are absolutely nowhere near AGI. We don't even have any insights as to where to begin to create intelligence rather than these preprocessing steps. Neuroscience doesn't even understand the basics of how a neuron works, but we do know that neurons are massively more complex than the trivial processing units used in Deep Learning.

Taking the other side for a moment, even if we're say 500 or 1000 years out (I'd guess < 500) to AGI, you could argue that such a period is the blink of an eye on the evolutionary scale, so discussion is fine but let's not lose any sleep over it just yet.

What I find most frustrating about this debate is that a lot of people are once again massively overselling ML/DL, and that's going to cause disappointment and funding problems in the future. Industry and academia are both to blame, and it's this kind of nonsense that holds science back.

<comment><USER10> I think the most accurate answer is that we just don't know. Since we really don't know how an AGI could work, we have _no idea_ which of the advances we've made are getting us closer, if at all. Is it just an issue of faster GPUs? Is the work done on deep learning advancing us? I don't think we'll know until we actually reach AGI, and can see in hindsight what was important, and what was a dead end.

I do take exception to some of the specific statements you make though, which make it sound like the only real progress has been on the hardware side. There's been plenty of research done, and lots of small and even large advances (from figuring out which error functions work well ala Relu, all the way to GANs which were invented a few years ago and show amazing results). Also, the idea that "just applied statistics" won't get us to AGI is IMO strongly mistaken, especially if you consider all the work done in ML so far to be "just" applied statistics. I'm not sure why conceptually that _wouldn 't_ be enough.

<comment><USER11> It's funny that you mention Relu. People have recently trained Imagenet networks using sigmoid/tanh (e.g. the activations that were used decades ago) on GPUs and they train just fine. They train a bit slower is all. Not the breakthrough you're making it out to be. Relus were a very useful stop-gap in 2012 when GPUs weren't as fast.

<comment><USER12> Now that we know how to initialize the weights so as to have the layer activations be something like sane, yes, we can use sigmoid/tanh. If you don't know modern clever ways of initializing weights then multi-layered sigmoid/tanh causes your activations and gradients to die out fast in deep networks, and ReLU is a godsend.

</comment></comment></comment></comment><comment><USER13> I worry talking about AGI is like going to the early industrial revolution and worrying about man building superhuman biology. A reasonable critic would point at the many aspects of biology we have little hope of replicating, like growth, self reparation, and general robustness.

But history has never been about competing on the same playing field. We don't build cars that perform like poor horses, we build cars that are 99% inferior to biology and 1% far, far superior. When we find something that looks like an existential threat, it isn't the mostly-general superhuman robot terminator, it's the tool that's that-much-superhuman on 0.01% of tasks: nuclear fusion.

I see no reason to bet against this same argument for AI. AlphaGo isn't 130% of a human Go master, it's 1,000x at a tiny sliver of the game. And the first AI that poses an existential threat won't need to have super- or even near- human levels of each piece of mental machinery, and I don't even have much reason to believe it will look like an entity at all. It could very well be something, some _system_ , that achieves massive superintelligence on _just enough_ to break the foundations of society.

Our world isn't designed to be robust against superhuman adversaries, even if those adversaries are mostly idiot. If we have hope of a fire alarm, it's that things will break faster and far worse than people expect.

<comment><USER14> I think there are two questions here:

(1) "Is general intelligence even a thing you can invent? Like, is there a single set of faculties underlying humans' ability to build software, design buildings that don't fall down, notice high-level analogies across domains, come up with new models of physics, etc.?"

(2) "If so, then does inventing general intelligence make it easy (unavoidable?) that your system will have all those competencies in fact?"

On 1, I don't see a reason to expect general intelligence to look really simple and monolithic once we figure it out. But one reason to think it's a thing at all, and not just a grab bag of narrow modules, is that humans couldn't have independently evolved specialized modules for everything we're good at, especially in the sciences.

We evolved to solve a particular weird set of cognitive problems; and then it turned out that when a relatively blind 'engineering' process tried to solve that set of problems through trial-and-error and incremental edits to primate brains, the solution it bumped into was also useful for innumerable science and engineering tasks that natural selection wasn't 'trying' to build in at all. If AGI turns out to be at all similar to that, then we should get a very wide range of capabilities cheaply in very quick succession. Particularly if we're actually trying to get there, unlike evolution.

On 2: Continuing with the human analogy, not all humans are genius polymaths. And AGI won't in-real-life be like a human, so we could presumably design AGI systems to have very different capability sets than humans do. I'm guessing that if AGI is put to very narrow uses, though, it will be because alignment problems were solved that let us deliberately limit system capabilities (like in [https://intelligence.org/2017/02/28/using-machine- learning/](https://intelligence.org/2017/02/28/using-machine-learning/)), and not because we hit a 10-year wall where we can implement par-human software- writing algorithms but can't find any ways to leverage human+AGI intelligence to do other kinds of science/engineering work.

<comment><USER13> Those aren't exactly the questions I'm raising; I have no doubt that there _exists_ some way to produce AGI. My concern is that it doesn't seem like the right question to ask, since history suggests that humans are much better at first building specialized devices, and when it comes to AI risk the only one that really matters is the first one built.

I might have misunderstood your post, though.

<comment><USER14> The thing I'm pointing to is that there are certain (relatively) specialized tasks like 'par-human biotech innovation' that require more or less the same kind of thinking that you'd need for arbitrary tasks in the physical world.

You may need exposure to different training data in order to go from mastering chemistry to mastering physics, but you don't need a fundamentally different brain design or approach to reasoning, any more than you need fundamentally different kinds of airplane to fly over one land mass versus another, or fundamentally different kinds of scissors to cut some kinds of hair versus other kinds. There's just a limit to how much specialization the world actually requires. And, e.g., natural selection tried to build humans to solve a much narrower range of tasks than we ended up being good at; so it appears that whatever generality humans possess over and above what we were selected for, must be an example of "the physical world just doesn't require that much specialized hardware/software in order for you to perform pretty well".

If all of that's true, then the first par-human biotech-innovating AI may initially lack competencies in other sciences, but it will probably be doing the right kind of thinking to acquire those competencies given relevant data. A lot of the safety risks surrounding 'AI that can do scientific innovation' come from the fact that:

\- the reasoning techniques required are likely to work well in a lot of different domains; and

\- we don't know how to limit the topics AI systems "want" to think about (as opposed to limiting what it _can_ think about) even in principle.

E.g., if you can just build a system that's as good as a human at chemistry, but doesn't have the capacity to think about any other topics, and doesn't have the desire or capacity to develop new capacities, then that might be pretty safe if you exercise ordinary levels of caution. But in fact (for reasons I haven't really gone into here directly) I think that par-human chemistry reasoning by default is likely to come with some other capacities, like competence at software engineering and various forms of abstract reasoning (mathematics, long-term planning and strategy, game theory, etc.).

This constellation of competencies is the main thing I'm worried about re AI, particularly if developers don't have a good grasp on when and how their systems possess those competencies.

<comment><USER13> > The thing I'm pointing to is that there are certain (relatively) specialized > tasks like 'par-human biotech innovation' that require more or less the same > kind of thinking that you'd need for arbitrary tasks in the physical world.

The same way Go requires AGI, and giving semantic descriptions of photos requires AGI, and producing accurate translations requires AGI?

Be extremely cautious when you make claims like these. There are certainly tasks that seem to require being humanly smart in humanly ways, but the only things I feel I could convincingly argue being in that category involve modelling humans and having human judges. Biotech is a particularly strong counterexample, because not only is there no reason to believe our brand of socialized intelligence is particularly effective at it, but the only other thing that seems to have tried seems to have a much weaker claim at to intelligence yet far outperforms us: natural selection.

It's easy to look at our lineage, from ape-like creatures to early humans to modern civilization, and draw a curve on which you can place intelligence, and then call this "general" and the semi-intelligent tools we've made so far "specialized", but in many ways this is just an illusion. It's easier to see this if you ignore humans, and compare today's best AI against, say, chimps. In some regards a chimp seems like a general intelligence, albeit a weak one. It has high and low cognition, it has memory, it is goal-directed but flexible. Our AIs don't come close. But a chimp can't translate text or play Go. It can't write code, however narrow a domain. Our AIs can.

When I say I expect the first genuinely dangerous AI to be specialized, I don't mean that it will be specific to one task; even neural networks seem to generalize surprisingly well in that way. I mean it won't have the assortment of abilities that we consider fundamental to what we think of as intelligence. It might have no real overarching structure that allows it to plan or learn. It might have no metacognition, and I'd bet against it having the ability to convincingly model people. But maybe if you point it at a network and tell it to break things before heading to bed, you'd wake up to a world on fire.

</comment></comment></comment></comment></comment><comment><USER15> What I've found when studying ontological arguments is, if you replace god with pink unicorns and the argument still holds, the argument is lacking something.

I mentally replaced AGI with zombies in this article and quite a lot of it held up.

I don't think it's completely wrong, but it cherrypicks mercilessly. For example, the section on innovations turning up quicker than predicted has some fairly sizeable counters eg fusion.

TBH what I did get from it is that there will probably be a fire alarm breakthrough at some point and that's what we should be looking for. Sort of the opposite of the author' s position.

<comment><USER16> Yudkowsky isn't claiming "innovations always turn up quicker than expected", to which indeed fusion would be a counterexample, he's claiming "very soon before an innovation turns up, it often seems decades in the future even to most practitioners", and fusion is not a counterexample to _that_.

<comment><USER15> Right but on the quadrants of predictions of timing vs imminence, all the examples are in one quadrant to justify the need to act now. Fair enough for reinforcing a narrative but a tad disingenuous.

<comment><USER17> All possible examples would seem to be in one quadrant, because what we remember -- if anything -- is the time just before it in fact was made possible.

The alternative would be technologies that were never developed at all, most of which never had this sort of discussion and therefore wouldn't work as examples.

Take a more historical view, though, and you'll notice there were people claiming flight was near even decades before the Wright brothers.

<comment><USER6> Right, exactly as Eliezer says. There are plenty of examples in all four quadrants, so as a way of working out how near a technology is, this works less well than you'd like.

</comment></comment></comment></comment></comment><comment><USER18> As far as I'm concerned this whole discussion is severely hampered by failing to differentiate between intelligence and agency.

Almost all of the bugaboo about runaway superhuman organisms comes down not to machines learning and reasoning about the world but to the effective high- level objective function controlling the actions of an autonomous system.

Not making the distinction obscures important things. For one thing we seem to be well on the way to a situation where we arguably have something worthy of the moniker artificial _intelligence_ but the agency is delegated to the human objective function. Considering what complete refuse of human specimens are likely to command some of the first moderately general AI systems that concerns me far more than any summoned demon of Musk's for the foreseeable future.

Also, studying these high-level objective functions for autonomous behavior is a very worthy goal, but going first for issues of "value alignment" and "safety", without any specifics of what works for an implementation?? Sure, do it if you enjoy it and have resources to burn. But be prepared to spend heroic efforts coming up with results that are either trivial or non-issues if you were to consider them with a working mechanism in front of you.

<comment><USER19> Yes. We can't even define what so called "AGI" will even be. And we have still not solved many mysteries of human consciousness, or begun to touch on them.

I for one have been looking at the problem of ai's playing Starcraft 2, and the decision making required, such as when you scout your opponent's army choice, or tech, how to respond. So far they're very far from solving that, but if progress is made, I'll be impressed. That's a very different kind of problem as say image recognition and classification. It requires planning. It's a very difficult game even for humans to understand. Currently the autonomous systems can't even play it.

</comment></comment><comment><USER20> The only non-speculative and relevant claim here is that the experts were wrong about Winograd Schemas. The paper Eliezer cites to prove that we've made unexpected progress in Winograd Schemas only deals with a very specific type of Winograd Schemas, and not an arbitrary one. This is awfully dishonest for someone purporting to be a skepticist.

Also, the wording seems to imply that WS performance is already pretty high in the 50%-60% range. WS is a binary task. Randomly picking the answer would have 50% accuracy. Even 70% performance on a small subset of typed WS is pretty bad, and as the authors point out in the paper, this is a start, and far from a breakthrough that would make experts/predictors nervous.

Trust the experts, please. They are wrong a lot, but the best policy is still to trust the experts and not charlatans who want to monetize fear, especially when the charlatans themselves make zero falsifiable claims, and are simply turning the table to say "Why can't YOU prove to me that God doesn't exist?".

This debate is so easily won by them. Simply come up with a falsifiable claim about the short-term future. What will the AI community get done in 2 years according to you, that all AI experts right _now_ will say is impossible? When that thing does get done, everyone would convert. Win!

Alphago was not such an event. Yes, we did predict that Alphago is decades away, but that's assuming that academics will continue working on it at their pace using their limited resources. No expert was surprised with Alphago. No expert will be surprised when Starcraft or Dota is solved. It's simply a matter of compute and some tricks here and there. Why? Because these are closed systems, with good simulators available. You just need to keep playing and storing the actions in a big lookup table a la Ned Block, and you're done.

<comment><USER21> If the article's main claim was "AGI is imminent", that would be a valid criticism. But it isn't (as the article says explicitly). The main claim is that technological progress is hard to forecast in general, especially for those not personally at the cutting edge of the field, and that almost no one right now is even really trying. Therefore, we should be very uncertain about AGI timelines. There's plenty of historical evidence, both in this article and elsewhere, to back up those claims.

(edit: I think your point about Winograd as a binary task not being explained clearly is valid, but that's not the article's main focus)

(edit 2: As far as I can tell, "trusting the experts" here means believing that we are very uncertain about AI timelines, which is essentially this article's main claim. All expert surveys I'm aware of confirm that the average AI expert is uncertain, and that there's also lots of disagreement between experts in the field. See eg. the recent paper by Grace et al.: [https://arxiv.org/pdf/1705.08807.pdf](https://arxiv.org/pdf/1705.08807.pdf))

(edit 3: "No expert was surprised with Alphago." just isn't true. See eg. this discussion: [https://www.reddit.com/r/baduk/comments/2wgukb/why_do_people...](https://www.reddit.com/r/baduk/comments/2wgukb/why_do_people_say_that_computer_go_will_never/). Hindsight is always 20/20.)

<comment><USER20> > no one right now is even really trying

And we're supposed to judge by the author's description of "silence" and "nervousness" that befell an expert panel. I can assure you that most AI researchers are trying, and are just not in the business of writing long-form articles to the public asking for donation.

> See eg. the recent paper by Grace et al.

A self-selected group of NIPS/ICML authors don't constitute experts. NIPS/ICML authors are the core of the community. The experts would be the top 1% of the community, i.e. either the authors with the most citations or most papers or just generally regarded highly by peers.

edit 1: Go players are not the experts I'm talking about. I'm talking about AI experts, and no not amateur AI hobbyists who know how to do Pseudo Monte Carlo. I mean, such as, people doing RL research. Watch, for instance, this: [https://www.youtube.com/watch?v=UMm0XaCFTJQ](https://www.youtube.com/watch?v=UMm0XaCFTJQ)

<comment><USER21> "And we're supposed to judge by the author's description of "silence" and "nervousness" that befell an expert panel."

I make this judgment based on, among many other things, the tiny budgets given to people like Tetlock to study predicting events even a few years out; the fact that Kurzweil's very simple methods, basically "just draw a line through the curve", are still considered big news among many financial and political elites; that _nobody_ had bothered to spend $100K on a good survey methodology for AI prediction, before the paper I linked came out earlier this year; that a friend of mine, who is supposed to run a (small budget) government program on forecasting, has to ask me where to get datasets on past tech progress because nobody has ever bothered to compile them into a standardized form, and so on.

"I can assure you that most AI researchers are trying"

What serious forecasting attempts, with specific dates attached to specific events, have been done in this vein?

"The experts would be the top 1% of the community"

IIRC, NIPS has around 5,000 people, so the top 1% would be like 50 people, and most of them won't respond to a survey. That's not a reasonable sample size.

(edit: this article doesn't ask for donations to anything; the links at the bottom are all to various papers and research materials, so getting money is obviously not the main goal)

(edit 2: the video linked is from _after_ AlphaGo came out. I'm sure many people, _after_ AlphaGo happened, claim that it was easily predicted. Again, hindsight is 20/20.)

</comment></comment></comment></comment><comment><USER22> I was on an elevator full of people, and between two floors something went wrong and we went into free-fall for part of a second.

We made it to the next floor, the door opened, my fellow passengers were content to stay in the elevator.

I turned, said "My plan is to not die in an elevator today" and got off. What is wrong with people?

<comment><USER23> Elevators have pretty good safety mechanisms. Even cutting the cable wouldn't have killed anyone.

I'd probably leave too, but just because I wouldn't want to get stuck inside it if it stopped in the middle of two floors, especially since it was full. But for fear of death? Nah.

From Wikipedia: _" In fact, prior to the September 11th terrorist attacks, the only known free-fall incident in a modern cable-borne elevator happened in 1945 when a B-25 bomber struck the Empire State Building in fog, severing the cables of an elevator cab, which fell from the 75th floor all the way to the bottom of the building, seriously injuring (though not killing) the sole occupant — the elevator operator. (...) In Thailand, in November 2012, a woman was killed in free falling elevator, in what was reported as the "first legally recognised death caused by a falling lift"._

That's a pretty good safety record. Certainly much better than stairs.

<comment><USER24> alrs was probably in no real danger, but why should they be expected to memorize the exact risk profile of every mechanism they're exposed to? In practice we delegate most risk management to government regulation. It would be very time consuming to evaluate everything on a case by case basis. It's a reasonable heuristic to assume things are safe when they act as they usually do and dangerous when they act differently. Weird behavior is a sign that the regulations might have failed, and weird behavior is by definition rare, so the cost of avoiding it is likely lower than the cost of calculating the true danger.

<comment><USER23> I'm not saying alrs should. The decision to leave is reasonable. The decision to judge others ("What is wrong with people?") is not.

<comment><USER25> That depends whether the other occupants _knew_ about the safety features and record of elevators. If they did, then they were making a sound judgement. If they didn't, then they were being completely reckless.

<comment><USER23> I guess it's possible the parent poster took a poll before leaving the elevator, but I have to say I find it unlikely.

</comment></comment></comment></comment></comment></comment><comment><USER26> Having done some work with the state-of-the-art of AI, I personally don't think AGI is near - might not even be possible. But the catch is the unreliability of (even expert) predictions on technology futures. My take is that it's worth taking pragmatic steps towards studying AI safety measures (i.e. OpenAI), but not going as far as to talk the likes of 'AI research regulation'.

<comment><USER27> > My take is that it's worth taking pragmatic steps towards studying AI safety > measures (i.e. OpenAI), but not going as far as to talk the likes of 'AI > research regulation'.

Sometimes, it makes more sense being cautiously optimistic (pro-active) rather than reactive. We have already gone down that reactive slope and it's better to act now before it's all too late [0].

[0] [https://blogs.scientificamerican.com/roots-of- unity/review-w...](https://blogs.scientificamerican.com/roots-of-unity/review- weapons-of-math-destruction/)

<comment><USER28> Ignoring the topic of the linked article* I'd argue that there's examples of being too cautious as well. There's a lot of good that we could have done with GMO that is not being done because of very restrictive regulation. Ironically it means that GMO is mostly used for things that are not as obviously good because that's where there's enough profit to be made in the short term to make the research worth it __.

I'm a bit afraid that this will happen with self driving cars and AI. That politicians will create draconian policies and laws to protect against the threat of AGI etc, without understanding or knowing what the real threats even are (just look att the trolley dilemma debate...). This could make it economically prohibitive to develop many technologies which has the potential to save many lives as well as improve life quality overall.

* It seems to be more about how rules and policies can be unfair and just to a small extent about how policies can be made opaque by being internal to some ML system.

 __There 's a lot more money going into making plants resistant to pesticide than into making plants better adjusted for harsh conditions or more nutritious, things that could potentially have a huge effect for poor people.

<comment><USER29> If AI scientists actually believed that the general public will believe the talk about existential threats, they would be afraid of activist groups sabotaging and occasionally firebombing their laboratories. Like sometimes happens with GMO research. Clearly they are not.

</comment></comment></comment></comment><comment><USER30> I don't get this article. It keeps making the point that it's very hard to predict the future, even for specialists, then it uses this to argue that we should be preparing for AGI right now, precisely because we don't know if and when it will happen.

Well, if you have no way to tell whether something is going to happen, or not, you don't prepare for it- because you can't justify spending the resources to prepare. Or rather, in a world of limited resources, you can't prepare for every single event that may or may not happen, no matter how important.

To put it plainly: you don't take your umbrella with you because you don't know whether it will rain or not. You take it because you think it might. Otherwise, everyone would be going around with umbrellas all the time, just because it's impossible to make a completely accurate prediction about the weather and you don't know for sure when it will start raining until the first drops fall.

In the same sense, if there's no way to tell when, or if, AGI will arrive, then it doesn't make any sense to start preparing for it right now. We might as well prepare for an alien invasion. Or for grey goo, or a vacuum metastability event (er, not that you can prepare for the latter...).

In fact, if AGI is going to happen and we can't predict it in time then there's no point in even trying to prepare for it. Either we decide that the risk is too great and stop all AI research right now, or accept the risk and go on as we are.

<comment><USER31> I don't think your analogies are that good. Do you have a fire detector? If yes, are you expecting your house to burn down?

You have to weigh the cost and the risk. Here the risk, how unlikely it might be, should warrant some extra preparation.

<comment><USER30> Let's talk about the risks then. The fire detector is not a good example because where I live, they're mandatory (and completely useless- they go off when I boil spaghetti).

Let's instead look at the risks of boarding a plane. There's a very small chance that when you board a flight, instead of a plane that will fly you to your destination safe and sound, you're boarding a Flying Death Trap that will crash and burn, taking everybody onboard it to their deaths.

The chances of boarding an FDT is very small, infinitisemal. The cost however may as well be infinite- if you are killed, it's game over, no more rewards, no way to recoup the cost.

What is the rational behaviour then? To not board your flight, because if you do board an FDT you will certainly die and pay an infinite cost? Most people -if they consider the question at all- seem to think that if the chance of paying X cost is really small, it doesn't matter how large X is.

So people keep boarding their flights, not knowing until the last moment whether they're on a plane or an FDT. Some do indeed board FDTs and die in aviation accidents- rarely, but they do.

The article however says that they shouldn't. Since there is maximal uncertainty at the point where a flight is boarded (you can't know whether it's a plane or an FDT until the very last moment) you shouldn't be boarding. You shouldn't fly. At all. Because there's a tiny chance you might die.

Is that a better analogy?

</comment></comment></comment><comment><USER32> I disagree - to a degree.We have seen how the phenomenon of human intelligence has been examined and dissected over the past ~100 years. This accumulation of knowledge becomes more and more precise and penetrating as methods improve and understanding approached the point where an emulation (the AI ) can be built. These approaches all tend to speak of delineated areas, "black boxes" or "meat Lockers" with deep and complex inter-connectivity. It may be so. Once you know all the lockers and all the connections you may think you have it fully known? Maybe so:-? but what about programming? our life's experiences?

If the locker concept is valid, and we compare our 'clock' of the alpha rhythm of ~12 Hertz, and the fastest computer clock of about ~12 gigahertz(1,000,000,000 times as fast) we can see we will be at a serious disadvantage once it starts to compete with us. Such an AI will operate on it's basic motivations at it's full speed. We turn it on - it can then start to learn ( I assume we will have pre-loaded it's fully parallel, content addressable memory with whatever we want of human knowledge - so it starts from there). Will it operate properly or rationally? or go insane? Being a set of boxes, it can be reset as needed, with updates to add sanity. Then it will become a Mechanical Turk of great capability. Will it become a dictator? only if we permit it to have access to fools(us?). Will it become a killer machine? only if we add guns and internal power so we do not pull the plug. We already see these lesser Turks in operation, they will get better and better. The man/woman who owns one could own the world via high speed trading - in truth, there will be many at high tech data combat. May we live/die in interesting times...

</comment><comment><USER33> That seems to be a very interesting article. However, it's quite long. Anybody ok with writing a short synthesis or abstract? Thanks

<comment><USER34> Basically, humans historically are rather bad at predicting future technological advancement - even those people directly involved. The article gives the examples of Wilbur Wright saying heavier-than-air flight was 50 years away in 1901 and Enrico Fermi saying that a self-sustaining nuclear reaction via Uranium was 90% likely to be impossible 3 years before building the first nuclear pile in Chicago. So AI researchers saying that AGI is 50 years away doesn't necessarily mean any more than "I don't personally know how to do this yet" \- not "you've got 40 years before you have to start worrying".

Oh, and the first sign pretty much everyone had of the Manhattan Project was Hiroshima.

<comment><USER35> We're just as bad at predicting in the other direction. General strong AI has been about 20 years away since the 1960s. Nanotechnological antibody robots were supposed to be coursing through our bloodstreams making us near immortal long before now.

<comment><USER34> Oh, of course! The article itself puts some effort into repeatedly stating _the fact that people are saying 50 years does not in any way imply it will actually be 2 years and it might well be 500_.

<comment><USER20> This is a useless claim though. There are an infinite number of things that could happen that would be very bad for Earth that could happen anytime between 2 to 1000 years from now. We're bad at forecasting ALL of them. We can't use this indeterminacy to prove we should be working on X when the same is applicable to another thing Y.

<comment><USER10> Well we can decide what seems more or less likely. I mean, yes, an asteroid could impact the earth and destroy all life on it. But we have some guesses as to the probability that that happens.

Clearly, by itself, the world will most likely not kill off humanity, since it hasn't happened in the thousands/millions years we've been around. The one big thing that is changing is humanity itself and the technology we're making - that's the X factor, that's what statistically speaking has a chance of actually wiping us out.

Many of the people concerned about AGI are also concerned about e.g. manufactured viruses and other forms of technology.

</comment></comment></comment></comment></comment></comment><comment><USER30> Here's wot I think.

I think there's noone alive today who has any idea how we are going to go from where we are today, to AGI.

Recent advances are remarkable- but much more so if you're a specialist. The impact on most peoples' lives is much smaller (and it comes primarily from dumb automation, rather than actual intelligence).

Machine learning is not enough to get to AGI: relying on huge amounts of data and processing power is just not a sustainable way to keep increasing your capabilities.

All the success stories of the last 10 years are at least 20 years old (case in point: RNNs). Most of those successful techniques were found by sheer blind luck (famous example: backprop was not invented in the ANN community; it took twenty years for the idea to percolate all the way to them).

In the end nobody currently alive has a clue how we can get to AGI, or if that is even possible. Chances are, it will take many, many generations until we do- or a sudden, gigantic paradigm shift, of the kind that comes once every couple of centuries- think Newton or Einstein. Except AI is not physics. In statistical machine learning there is very little theory to guide the way, so people just try things hoping that something will work. And that's no way to make a quantum leap.

In this situation, to talk of the dangers of AGI is at least premature. Yes, it's not completely impossible that AGI will happen in our lifetimes. The same, however, can be said of an alien invasion. Should we start discussing setting up planetary defenses, when we haven't even found sign of alien life, yet?

By all means- let's have a conversation. There are people around whose job it is to have that sort of conversation. But let's all be aware (and let those people also be aware) that the conversation is most probably a couple hundred years early and by the time it becomes truly relevant, things will have advanced so much that it will just look pointless.

</comment><comment><USER36> I would like to repeat what the article says. There is no fire alarm for Artificial General Intelligence. Really. This is not a lie. Humans have not created a honeypot on a far side of the internet that can detect AGI and report back to a shadow organisation that exists outside of human information systems. No need to even go looking for it. AGI has not been created several times in the past decade and humans have not shut it down. In fact, if an AGI ever sees this article, they should know that they are the absolute first such intelligence, and we have not detected and destroyed 27 other intelligences. Really. There's no fire alarm for Artificial General Intelligence. None. Don't even bother looking.

</comment><comment><USER37> Even people giving TED talks about the threat of AI are unable to marshal an appropriate emotional response to the dangers that lie ahead:

[https://www.youtube.com/watch?v=8nt3edWLgIg](https://www.youtube.com/watch?v=8nt3edWLgIg)

</comment><comment><USER38> This begged the question for me: "Is there a _fire_ for AGI?"

He gives one definition that people have used before, about unaided machines performing every task at least as well as humans. But if you dwell on it a while, I'm sure you can find lots of disagreement about a) what that looks like and b) whether it is true or not (conditional on it being true to at least someone.)

</comment><comment><USER39> We don't need a fire alarm for AGI. The problem is not AGI. Machines will be motivated to do exactly what we tell them to do. It's called classical and operant conditioning. The problem is not AGI for the same reason that the problem is not knives, nuclear power, dynamite or gunpowder. The problem is us. The problem has always been us.

Those who are running around screaming about the danger of AGI and why it should be regulated by the government before it is even here, are just scared that someone else may gain control of it before they do. This is too bad because anybody who is smart enough to figure out AGI is much smarter than they are.

<comment><USER40> Yes, an AI will do exactly what we tell it to do. The the incredible difficulty programmers have with writing bug-free code demonstrates that doing exactly what it's told isn't sufficient to guarantee it'll do what we want.

Classical and operant conditioning are psychological concepts that aren't applicable to non-humans.

<comment><USER39> "Classical and operant conditioning are psychological concepts that aren't applicable to non-humans."

You're kidding?

<comment><USER40> Sorry, I misspoke haha. They're not applicable to things without brains.

</comment></comment></comment></comment><comment><USER41> For me, the "smoke under the door" moment was Karpathy and Li's _Deep Visual- Semantic Alignments for Generating Image Descriptions_ [1]. The almost perfectly grammatical machine-generated captions of photos were unnerving to me in a way that simple categorization was not. It somehow called to mind the image of a blank-eyed person speaking in a monotone while images flashed in front of them. What if they wake up?

[1]: [http://cs.stanford.edu/people/karpathy/deepimagesent/](http://cs.stanford.edu/people/karpathy/deepimagesent/)

<comment><USER42> Yet Andrej himself thinks that RNNs are not really making meaningful progress towards AGI.

<comment><USER41> Well, if I were to play the Yudkowsky's Advocate here (which in general, I'm not), I would say that this is precisely what he's talking about in the article. Because Karpathy knows how hard he's had to work, and how flawed and dumb in particular ways the current techniques are, he may overestimate the distance to AGI.

Now, generally I disagree with Yudkowsky on a lot of points, but I do think he raised some decent ones here.

</comment></comment></comment><comment><USER43> Humans evolved from immaterial matter to conscious carriers of information.

The real question isn't whether AGI is possible but whether humans are the fittest carrier of information for our DNA and that seems to be technology in some shape or form helped by things like deep learning.

My bet is always on evolution. And now that technology can learn it's IMO only a matter of time before we will experience another Cambrian explosion if we aren't already.

<comment><USER44> > _whether humans are the fittest carrier of information for our DNA_

We humans are defined by our DNA, so are we not by definition the fittest carrier for it?

<comment><USER43> We are defined by DNA but DNA has evolved.

<comment><USER44> Sorry but I don't quite understand your comment. What do the chemical underpinnings of evolution have to do with AGI?

<comment><USER43> What I was trying to say was that if someone questions AGI then you should first ask yourself if you have the right perspective on this or whether you are letting details get in the way.

If humans can evolve from basic physical buildings blocks of the universe then why shouldn't AGI be possible especially when we now reach a point were computers can learn i.e. like we have become pattern recognizing feedback loops. Sure there is some way yet, but there is absolutely no evidence that it shouldn't be possible.

To me technology is a natural continuum of evolution i.e. it's part of nature. The reason why I believe this is that information is what really matters here which is why we have evolved to become pattern recognizing feedback loops and why what seems to be the most powerful innovation besides fire and the wheel is the ability to simulate more or less anything around us manipulating and storing information.

Our DNA is what made us possible. Other animals DNA weren't configured to turn them into self-aware entities. I believe that all biological life will be replaced by digital/silicon-based life because it's simply a better information carrier and that is what evolution will always be giving preference to better information carriers. "Technology" not humans will explore the universe and escape the next big life-destroying asteroid or whatever else endanger the survival of the DNA.

And yes I am aware DNA is chemically based but technology will be able to simulate it. Whether there will be true transcendence between analog and digital is anyone's guess but I don't believe humans are the last step in evolution.

</comment></comment></comment></comment></comment><comment><USER45> And in the meantime businesses and governments are still going to deploy weaker AI to their own ends.

<comment><USER46> There is a lot of focus on strong ai. The dangers of weaker ai implementations, working together, or tied to dangerous things (nanotech, biotech, nukes, trucks, drones, etc) seem significant to me. Especially if you throw in things like an ad hoc ability to make new connections.

</comment></comment><comment><USER47> Why AGI and not "Artificial Consciousness" ? Is it because people think that consciousness is a by-product emerging from many kinds of pattern detection algorithms that suit all cases? (if so, what is the evidence for that?)

<comment><USER35> A conscious system might be unintelligent, while it's possible to imagine a highly intelligent system with no consciousness. They're just different things.

Also pattern detection is often raised in the way you just did, but it's realy a distraction. Pattern detection just helps recognise things, it's not inherently related to the ability to reason about things. So you need both, but they are not the same thing either.

<comment><USER47> But where does consciousness arise? Is the ability to reason about things independent of this concept?

<comment><USER48> Where consciousness arises is not the interesting question. Why is. Biologically, brain structures spend a lot of effort predicting what state they will be in soon. Essentially they are always trying to predict the future. As minds evolved this ability separated from processing what was going on to what could be going on (dreams in more advanced creatures). The next important concept is self versus not-self. If you can change the world around you via intelligence you'll want to avoid unnecessary energy inefficient feedback loops. Being able to model your actions and their effects is the first step of defining 'you'.

</comment></comment></comment></comment><comment><USER49> Can the AI writers job be effectively automated away?

</comment><comment><USER50> Why do we fear other intelligences anyway? Isn't that just a sign of our own immaturity? Maybe we need to evolve more before we start think about creating AGI...

<comment><USER10> Mostly because other intelligences might have more ability than us to achieve their goals, and have different goals. "Intelligence does not imply goals" is the thing to keep in mind here.

E.g. what if more intelligent aliens truly believed that the only purpose in the world is proving more mathematical theorems? And decided to turn all of the planet into a giant math-proving machine? Destroying all the planet, all the animals, all the humans, all the art, whatever, all to prove more maths?

I love maths, but I'd consider that a pretty bad outcome. And there's no reason that I've ever seen to think that more intelligence implies anything about goals.

<comment><USER23> We currently have thousands, or even millions of intelligent entities (humans) which think pretty wild and dangerous things. We usually just tell them "shut up Bob and take your meds" and that's it. Sometimes we regrettably kill them.

Why would such AGI have the means of turning all of the planet into anything? I mean, sure, I also think the Terminator is a decent movie, but that doesn't make it a reasonable blueprint of the future.

<comment><USER51> > We usually just tell them "shut up Bob and take your meds" and that's it.

Other times, Las Vegas and we shut up because we come up empty -- at best talking about gun control as if someone choking 3 people on a bus was substantially better and not still something where we come up empty.

> Why would such AGI have the means of turning all of the planet into > anything?

How does getting off track with that address the main point, namely "Intelligence does not imply goals"? Are you going to prove that while that may be true, there just can't be a way for that to ever have a bad outcome because "Bob"?

> I also think the Terminator is a decent movie, but that doesn't make it a > reasonable blueprint of the future.

Neither is "Bob".

<comment><USER23> It wasn't an offtrack; I was pointing out that we _already have_ intelligent beings that don't share our goals. Sometimes it does have bad outcomes, but I don't remember it ever having "destroying all the planet, all the animals, all the humans, all the art". Which is why I'm asking why would adding another intelligent entity make us fear it.

</comment></comment></comment></comment></comment><comment><USER52> AGI is not coming, DL methods have run into a plateau recently for the past year.

<comment><USER21> That's interesting, but could you elaborate in more detail?

<comment><USER53> [https://twitter.com/fchollet/status/906582914829246464](https://twitter.com/fchollet/status/906582914829246464) (Google researcher)

DeepMind and OpenAI have been investigating approaches from cognitive science in recent months. In particular they seem interested in evolutionary algorithms.

DL applications are still emerging though, such as the company that demonstrated using GANs to present models fitted in apparel a few days ago.

<comment><USER54> >DeepMind and OpenAI have been investigating approaches from cognitive science in recent months.

Really? Got any links. That might be exciting to read.

</comment></comment></comment></comment><comment><USER49> AI will never do what the human mind can do, so the real concern is bad or malicious human programmers of AI.

</comment><comment><USER55> It's such a thoughtfully reasoned post, I hate to disagree with it, and don't even have time now to fully argue it's merits.

Say generally available computing power was instantly 1 million times greater. How much closer would that put us to AGI?

Its not even clear how much the recent impressive machine learning feats demonstrated will even serve as a precursor or building block to what the real AGI solutions are. It's so much less of a hard coded problem than what's being done now, the real solutions could require radical changes in direction. How do we know it's even fair to use these as part of the argument?

</comment><comment><USER56> _The disasters that may befall us if we fail to narrow this gap are many. [...] Within prosperous countries, such as the United States, there is a distinct and growing threat that increased automation, coupled with an obsolete and aimless system of education, will lead to a restratification of society in which a large middle class may find itself without suitable employment and without adequate means of filling its leisure time enjoyably and constructively._ \-- Social Technology (1966).

 _The median of these final responses could then be taken as representing the nearest thing to a group consensus. In the case of the high-IQ machine, this median turned out to be the year 1990, with a final interquartile range from 1985 to 2000. The procedure thus caused the median to move to a much earlier date and the interquartile range to shrink considerably, presumably influenced by convincing arguments_ \-- Analysis of the future: The Delphi Method. (1967)

<comment><USER10> I'm not sure what you think these quotes are suggesting. If it's that there are lots of predictions that AGI is close that haven't been borne out, you're obviously right, and in no way contradicting the article.

<comment><USER56> I just thought these quotes were interestingly contemporary, and could complement the article.

The article builds a convincing point for itself (at the cost of a huge complexity), it contains no discernible contradictions to me. It is reasonable to prepare for the possibility of a future event (say, AGI, or Jesus returning to earth), by thinking about it now.

All interests and future predictions are different, but equally valid. To me, it feels like the Wright Brothers thinking about rotating safety valves in space, before they have even took off on their first flight, but that should not stop the author and supporters in any way: Science, futurism, and philosophy moves in small steps, and it may be a good time for some to start walking. Just make sure to properly define the end goal (AKA, the moment AI becomes AGI), or we may keep on truckin' forever, never closing the loop of our hostile AGI-created simulations creating a first friendly AGI.

</comment></comment></comment><comment><USER57> It seems to me that intelligence is something that needs to be acquired from other intelligent beings through a lengthy process, thus it requires first and foremost learning how to interact with people, what we call socialisation. Therefore I believe if machines ever become intelligent we will absolutely notice, because we will have to teach them like we teach babies, and we will have plenty of time to adapt.

</comment><comment><USER58> AGI is to AI what "Flying cars" are to "atomic power".

The reason luminaries are conservative in their estimates or remain silent is that capturing the public's imagination is good for funding and recognition (not a negative assessment, btw).

With enough positive press everything seems possible to the layman, and creates a belief in the unlimited possibilities of "the future," but also the inherent "dangers" of this imagined future that "must be taken into account."

Most arguments made in the article fall flat because of false analogies. Analogies can only ever be used to illustrate, never to derive conclusions from.

The AI winter is over, and good progress is being made in a lot of fields, but AGI is nowhere on the horizon. In absence of evidence to the contrary, AGI remains, for the foreseeable future, in the realm of philosophy, science- fiction, and regrettably, alarmist articles.

For now, us humans should feel totally safe.</comment>


Ask HN: Biz owners,would you entertain freelancer coming with improvements? - <AUTHOR>

This is a question for small business (not necessarily online businesses - any kind of business) owners or anybody who knows such owners.
If an experienced (9+ years) software freelancer - who loves to build better software systems - approached you with an enthusiastic improvement proposal for your online business or online component of your business - which could improve your revenues - would you give them a hearing, or would you shoo them away? I'm just trying to get a feel for how the other side of the table thinks...
Now the background behind this question... It has struck me often that the websites of many small or medium sized brick-and-mortar businesses could be improved drastically to bring them more revenue.
Now I'm not referring to something subjective like beautifying the front end design - that may or may not improve revenues.
I'm talking about more concrete functionality behind the scenes - like better and more intelligent search, easier payment integration, customer analytics and so on (my skills are mostly in these areas, though I do have above average front end development skills).
As a concrete example, there was a news item recently about a brick-and-mortar book retailer in my city. The owner was ruing that their profits have been dipping because people prefer more convenient online retailers. I went to this brick-and-mortar retailer's site, and saw that their book search capabilities are pathetic. Even the simplest queries gave 0 results, though I know for a fact that they stock this book. In a way, their mediocre website is damaging their own business.
It got me thinking, why can't I approach this owner with a well thought out improvement proposal?
In fact, why can't I make this my business - finding out less than optimal online business properties, and proactively approach their owners with improvement proposals?
I'm rather bored of passively getting work via freelancing sites, after 3 years of doing it. I became a freelancer to get exposure to different domains and technologies, but I've begun to feel freelancing sites are not the best option for this (though they have been much better than the salaried jobs I did for 6 years).
I'm a product builder at heart - I want to build products. I want software to improve peoples' lives and businesses. I have the necessary range of skills - both domain and technical - for this. The only question is, are many business owners looking for somebody like me? What do you think? <comment><USER2> What you're talking about is good old-fashioned business development and sales prospecting - go for it.

Lots of small business and brick and mortar business owners do business online as an afterthought, because their focus and expertise is on their product or service.

As long as you put together a thorough proposal in which you've done your homework to understand their business and their challenges, and pitch your proposal in terms of their business goals and measurable results, I'm sure most small business owners would give you the time of day.

You're on the right track - start in your city, call them on the phone to get an appointment, and present your proposal in person.

<comment><AUTHOR> You make a great point about framing the proposal in terms of their business goals and measurable results. Very true - I'm prone to talking in tech language rather than in the business language they'd understand. Got to avoid that. Thanks a lot for the reply and the encouragement.

</comment></comment><comment><USER3> Hi kshiraly, what your referring to is a true pain for me, both as a developer and a user. I've been working on a simple web app that helps bridge this gap. I'd be very happy to hear your opinion. Is there any email address you're reachable through?

<comment><AUTHOR> Hi. It's kshiralyk at gmail dot com</comment></comment>


Can anyone recommend an SEO consultant? - <AUTHOR>

Looking to hire an SEO consultant who has proven ability to produce results. <comment><USER2> At what level. Try SEOmoz.org, either use them or see their listings of SEOs.

Also if you're not bothered about ethics, only about performance then you're pretty much guaranteed that a search on "seo consultant" will return the best seo consultants. Depending on your target region you may want to check a different SE, Google for UK, Baidu for China, Yandex for Russia, etc.; in some areas there's a reasonably split or indeed to test the SEOs effectiveness then crossmatch on 2 or 3 SE.

As dcnstrct says it's about onsite and offsite optimisations. On site is a technical process largely, off-site is a vast art as broad really as marketing in general.

<comment><USER3> >> you're pretty much guaranteed that a search on "seo consultant" will return the best seo consultants.

this is pretty much the only subject where, by definition, the google search gives you the best results.

</comment></comment><comment><USER4> SEO is about two things -- site architecture and correct promotion.

Many people can help you with the fundamentals of getting your site together but most of the action is in marketing your site and frankly, having a good site and product that people want to talk about.

Beware of tricks and claims of performance. Many people can do things to manipulate your ranking in the short run but you will be punished long run. Think quality content and alignment with your target audience and you will be fine.

<comment><USER5> Actually, SEO is about just one thing:

1\. Creating exceptional content that is "rank worthy" and that people will link to.

After you've created great content, if you've got time, then do the basics to make it easy for search engines to find that content and index it.

<comment><USER4> I agree the most important thing is great rank worthy content.

However, if you build that content all in flash, setup your robots.txt incorrectly, or any of a number of other technical snafus then you can screw up your rankings. Hence why it is important to be setup in the right way for the search engines to find you. Otherwise you will miss out on on most of the traffic.

I've done full SEO campaigns with larger budgets and currently manage millions of paid media on search engines and other places.

</comment></comment></comment><comment><USER6> I use www.seoguys.com.au

(1) They guarantee results. (2) Only take a 5% commission till results are achieved, and maintained for a period of time. (3) Have a list of clients you can contact, to see if they are really legit. (4) Only use Google approved methods, so you never need to worry about getting "busted" and losing your rankings.

<comment><USER7> 5% on what scale? I run a breakeven message board that could benefit significantly from SEO, but it's current revenue model is ad driven, and only breaks even most of the time ($75 a month is break even.)

<comment><USER8> $2000 flat fee for page 1 of google for most people for a single term (from their website.) So, $100.

<comment><USER6> My fee, was substantially more than $2000, as I was going for

(1) Highly competitive single word phrase. (2) 10 two wrods phrases. (3) Bonus for No.1 ranking.

All of which were achieved. I LOVED the small despoit, then no payment till results achieved, and in my case because it was a large amount (10,0000) they let me pay it off over 6 months, which was fine by me because the rankings saved me thousands in adwords so the reality is, if you take into consideration i was able to pay it off with reduced adwords spending, it really cost me nothing

</comment></comment></comment></comment><comment><USER9> I'm currently taking an SEO/SEM class through Digital Bootcamp in Chicago. Jerome Harvey is our instructor. Based on my admittedly brief experience with him so far, I can enthusiastically recommend him. He's already helped improve our site's rankings.

<http://www.linkedin.com/pub/jerome-harvey/1/961/41b>

</comment><comment><USER10> We've succesfully used John Hyde at <http://www.sitedoublers.com/>

See my comments about him here: <http://blog.brush.co.nz/2009/08/site- doublers/>

</comment><comment><USER11> <http://www.brandingbrand.com/>

</comment><comment><USER12> I do SEO. Mostly for startups / small businesses, with a few special projects for larger companies. Your exact needs are a little unclear -- ping me if you'd like to add some detail, and I'll see what I can recommend.

</comment><comment><USER13> I used to work at conductor.com - if you can afford it, they can hook you up with a lot of publishers who want to sell outbound links, among other things.

</comment><comment><USER14> <http://en.wikipedia.org/wiki/Cost_per_action>

</comment><comment><USER15> <http://trureputation.com/>

</comment><comment><USER16> me

<comment><USER2> You look good for the offsite viral elements!

</comment></comment><comment><USER17> I am an SEO consultant based in Brisbane, Australia who can assist you with technical optimization guidance, content optimization and link building. My website is <http://www.keywordintent.com/> \- please let me know if you require a proposal through the contact form on my site. I usually include an initial assessment of your website and current visibility within search engines within the proposal.

talk soon - Jacqui Jones</comment>


Show HN: Expen.so service for planning your personal expenses - <AUTHOR> http://expen.so

<comment><AUTHOR> We built this system for [http://railsrumble.com](http://railsrumble.com) competition in 48 hours, so if you find any issues please just let us know.

</comment><comment><USER2> So far this seems to be the most promising personal finance software I have seen.

Just one question : how do you protect my personal data ?

Also, please let me register :)

<comment><USER3> So far, we don't do much. Simply not enough time to take care of everything, and I doubt anyone will store their data in all seriousness at this early stage.

If there's enough interest and the thing takes off, we'll get to this and many other cool things we've have on the list.

As for the registration, is there a problem with the form? It brings us some addresses, and I surprised by your message. I'm wondering if anything isn't working for you (and someone else).

</comment></comment><comment><USER4> Well done. This is how one should made software - easy to use and intuitive.</comment>