The End of Starsky Robotics - <AUTHOR> https://medium.com/starsky-robotics-blog/the-end-of-starsky-robotics-acb8a6a8a5f5 <comment><USER2> This is sad news.

I worked at Starsky Robotics as a perception team intern after graduating high school. I will always be grateful for the team for the opportunity, it was a fantastic first job and everyone who worked there was very kind (especially Stefan).

Unfortunately, Starsky had effectively had no machine learning in 2017 (when I worked there), using solely classical computer vision techniques. This didn't match the company's ambitions of not using LIDAR and there was a strong stigma against switching to a deep learning approach. At the time, very few object detection models had public implementations and I spent a lot of time trying to get a YOLO9000 and RetinaNet implementations running at real-time speeds. Frustrating, as a small startup the labeling services kept screwing us over by returning poorly annotated images.

I think what I took away from the experience is that deep learning in domains with long tails requires a enormous investment in a labeling pipeline - dwarfing the computational aspect - to get decent results. I don't think any solutions are on the horizon that will allow us to bypass this reality. You don't see improvements between Comma.ai and Tesla because it's about the improvements far out on the tail.

<comment><USER3> For others like me who were as amused by the name, YOLO9000, it's a real thing, "a state-of-the-art, real-time object detection system that can detect over 9000 object categories".

YOLO9000: Better, Faster, Stronger - [https://arxiv.org/abs/1612.08242](https://arxiv.org/abs/1612.08242) (2016)

<comment><USER4> YOLO = "You Only Look Once"

</comment></comment></comment><comment><USER5> Thank you for the great writeup. It sounds like you took a responsible, valuable, and even economically viable approach, but the market doesn't want to hear it.

I wonder when the market will start listening to people who actually WORK on the problem.

> _which means that no one should be betting a business on safe AI decision > makers. The current companies who are will continue to drain momentum over > the next two years_

Sounds about right.

\-----

Here's me over 2 years ago simply quoting people who worked close to the problem:

[https://news.ycombinator.com/item?id=16353541](https://news.ycombinator.com/item?id=16353541)

 _Here 's my negative scenario: self-driving is "AI-complete"; you can't really hit all the edge cases without solving AI in general, which is more than 30 years away (Kurzweil is the wild optimist and predicts 2045)._

 _You CAN use self-driving in limited circumstances, but those limitations are precisely the ones that make driving yourself around more attractive. The expense doesn 't go down as quickly as anticipated because of this. They are a niche technology for DECADES._

This looks about right, and I'm not claiming to be prescient, just basically saying what Chris Urmson and Bill Gurley already said years ago. It's weird to me that there's still so much money chasing this pipe dream.

It was a sign when Google spun out Waymo. If they really believed in the product, it would be called something like "Google Self-Driving Cars", not "Waymo".

\----

edit: it's easy to be negative, so on the positive (and contrarian) side, I believe rideshare is undervalued, and has a long way to go. I bought both Uber and Lyft stock at $16 yesterday (they may go down again, but ping me in 2 years). This comment in this thread is a nice take and makes me even more optimistic:

[https://news.ycombinator.com/item?id=22631151](https://news.ycombinator.com/item?id=22631151)

<comment><USER6> I still think that AI shuttles and buses driving predetermined routes and schedules would be tremendously useful. Especially if they could operate continuously 24/7\. And that should be possible, with maybe tele-operators dialing in to override the edge cases or sending dispatch crews to takeover for any issues that come up.

<comment><USER5> How's Lyft Shuttle doing? (genuine question, I don't know)

[https://nymag.com/intelligencer/2017/06/lyft-reinvents- the-b...](https://nymag.com/intelligencer/2017/06/lyft-reinvents-the-bus.html)

The point is that we already have self-driving vehicles. You press a button on your phone and somebody drives you around. Whether it's a premium ride, a shared ride, or a bus is an orthogonal issue to whether the driver is human, which is a matter of cost.

The fact that it's a cost issue makes it look even worse and further out for driverless.

If there is demand for a shuttle along predetermined routes, it would already exist with a driver, and that's what Lyft Shuttle is if I understand correctly. I haven't seen it in SF or heard of anyone using it. It's definitely possible that they could figure out the product and it will become popular, but that has little to do with self-driving.

<comment><USER7> > The fact that it's a cost issue makes it look even worse and further out for > driverless.

I see it the other way, they slot immediately and easily into already existing businesses and if the only difference is cost consumers are likely to swap over.

</comment></comment></comment></comment><comment><USER8> > _There are too many problems with the AV industry to detail here [...] The > biggest, however, is that supervised machine learning doesn't live up to the > hype [...] It's widely understood that the hardest part of building AI is > how it deals with situations that happen uncommonly, i.e. edge cases. In > fact, the better your model, the harder it is to find robust data sets of > novel edge cases. Additionally, the better your model, the more accurate the > data you need to improve it. Rather than seeing exponential improvements in > the quality of AI performance (a la Moore's Law), we're instead seeing > exponential increases in the cost to improve AI systems_

This is _exactly_ the problem with data hungry machine learning approaches, specifically deep learning (and that's without even mentioning the compute resources necessary to learn). The only way to circumvent that is plausibly apply better inductive biases, and fundamentally rethink what the field considers important.

<comment><USER9> I think the obvious problem is that induction (which is what learning from data is), is simply only one tool in the huge space that is intelligence, and it will never be enough to emulate the skill of a human driver, which is more or less what is necessary for autonomy in an open environment.

<comment><USER10> The "induction" that machine learning algorithms do also isn't the same as the induction that humans preform. We induce new concepts from experience (data) -- The description itself assumes consciousness in both "concepts" and "experience".

Thinking of computers as getting more "intelligent" like humans is a category error -- computers are dumb matter configured in an intelligent way by actual intelligence (humans) to preform certain tasks for us. We get better at telling them how to preform certain tasks (software), but there's no reason to think we're moving along some continuum of intelligence towards us.

<comment><USER11> > We induce new concepts from experience (data)

That's the premise of deep learning - inducing high level concepts from experience, without manual feature engineering.

DL models are good at induction, what they can't handle is generalisation (being accurate outside of distribution). And self driving has a long tail, that's why it's so hard.

</comment></comment></comment></comment><comment><USER12> Ah well, it was great while it lasted.

Most of the engineering team has spread throughout the AV industry, with most folks going to our neighbors and fellow YC company Cruise Automation. Some are at Waymo, Zoox, AutoX, and some purposefully exited the AV space entirely.

I joined Applied Intuition to help build out Simulation and Infra for other companies producing AVs/robotics.

There are a few folks I know of who are still looking for their next roles in the BizOps/PplOps side, which has been especially hard during COVID-19 season if anyone wants to do some linkedin stalking.

<comment><USER13> _Most of the engineering team has spread throughout the AV industry, with most folks going to our neighbors and fellow YC company Cruise Automation._

Sounds like most of the engineering team does not share the founder's perspective on the AV industry.

<comment><USER14> I've worked for 2 hopeless industries. It doesn't prevent me from collecting a paycheck.

</comment></comment></comment><comment><USER15> Thank you for the write-up! It's a little depressing (but not entirely surprising) to hear that you couldn't get folks excited about safety -- I work in the aerospace field, and our day-to-day is all about risk management: how, why, when. It's frustrating that high-reliability systems aren't seen as exciting when really they're what makes the magic run.

Best of luck, and I'm looking forward to your next venture!

<comment><USER16> Ironically, in my experience, finance is the field that probably cares most about risk management. That and maybe healthcare (though less than you would think, surprisingly).

</comment></comment><comment><USER17> Disclaimer up front: I work for General Motors. I don't work on AV. Any opinions are my own. I have no special knowledge of GM's AV strategy.

> It didn't matter that that jump from "sometimes working" to statistically > reliable was 10–1000x more work.

There's 2 states of functionality:

1) It doesn't work

2) It sometimes works

The inverse, for disk drives: Failing and Failed.

Think about apps/services. You could say that your app is working, but over a long enough time period, it is only sometimes working. It's working while you have disk space, free memory, and a working network connection. It's working while your business assumptions hold true. It's working while your datacenter has power. We've developed strategies for managing all of these things; for load balancing and Active/Active hosting. But even with that, it only sometimes works.

\---

With all that, I think it may be useful to think of self driving in terms of tasks.

If you can put a box around what you expect a computer to be able to do, you can define tasks that will always return a reasonable output.

The more tasks a computer handles, the easier it is for the human in control (think driver assist, like lane keeping and automatic cruise control).

If you add enough tasks, and perform them well enough, maybe you can take the human in control out of the vehicle.

I think I'm in agreement with the authors that I don't see the day when there isn't a human in control. Or the other way to say that is that if there isn't a human in control, sometimes your AV will just stop.

<comment><AUTHOR> Just stopping is ok is ok in some use cases, but not others. It will be a long time before robotaxis "just stop" less frequently than uberdrivers, but AV trucks can already be more reliable than contemporary drivers.

</comment></comment><comment><USER18> Thank you for sharing this very candid article on the Starsky Robotics and generally the autonomous vehicle space. It's a real eye opener. I've been following your progress for the last few years (and I also read about your company through Reilly Brennan's "Trucks - FOT" newsletter).

I am sorry you could not get investors to believe more in what you and your team, especially as you required a lot less funds than many other companies in this arena. I also thought you had a clear business case (I worked in ride- hailing and also logistics so understand some of the problems in this space).

I wanted to ask you a question: I am building a startup in the dash cam video analysis space. We are building a large and geographically diverse dataset of road videos, where our users can annotate/label the data. We then are going to look at detecting specific events like accidents and edge cases on videos. Do you feel this type of business, the data we collect, and insights we generate would have value for a AV startup?

All the best in your next move. Stay strong - you can be proud of what you and your team did.

<comment><AUTHOR> Hard to say.

We had really strict rules on what we wanted our data to look like, and were very specific about subject matter. We probably wouldn't have been able to be a customer.

Our intention to deal with accidents/edge cases was that if anything looked outside of ODD (as in, not perfect driving conditions) we'd execute a MRC (pull to side of the road, or stop at next exit). Relatively easy way to solve most of the really hard edge cases.

<comment><USER18> Understood and makes total sense given the ODD at Starsky.

</comment></comment></comment><comment><USER19> > Around November 12 of 2019, our $20m Series B fell apart. We furloughed most > of the team on the 15th (probably the worst day of my life), and then > started work on selling the company and making sure the team didn't go > without shelter (or visa status, or healthcare for the new and expectant > parents). We were able to land many of the vulnerable jobs by the end of > January and I'm in the process of selling the assets of the company (which > includes a number of patents essential to operating unmanned vehicles). Like > the captain of a sinking ship, I've gotten most of the crew on lifeboats and > am now noticing the icy waters at my ankles while I start to think about > what I do next.

Well done.

</comment><comment><USER20> I've been developing software for self driving (both road and offroad) the past two years and what I've noticed is that there isn't much innovation in the field. It seems like everyone follows the exact same design paradigm which is using something like Autoware. It's pretty disheartening to see how much money has been poured into this field and what do we have out of it now? GM Supercruise came out in like 2013 [0] with similar performance to the level of autonomy we're at in 2020. To clarify, this was in a production cadillac in 2013, so anyone who knows about automotive products knows how long this must have been in development before they were allowed to put it in production.

To the author, it's interesting to read how quick you rose and fell, but it's good you got out now instead of holding on for years and years.

What do you think is next?

I'm honestly tired of the lack of progress in self driving, and was wondering what anyone's thoughts were on home robotics. I feel like that's the next big thing that VC's will pour billions into.

[0][https://media.gm.com/media/us/en/gm/news.detail.html/content...](https://media.gm.com/media/us/en/gm/news.detail.html/content/Pages/news/us/en/2013/Apr/0429-cadillac- super-cruise.html)

</comment><comment><USER21> > Instead, the consensus has become that we're at least 10 years away from > self-driving cars.

I'm going to assume the founder of a self-driving truck company knows what he's talking about.

But at the same time, I have a hard time reconciling that with the fact that I sat in a car that drove itself all around San Francisco, dealing with a ton of edge cases.

Maybe we won't get to a 100% drive-anywhere-you-want-car in 10 years, but to be fair, a lot of humans aren't capable of driving a car anywhere either.

There are a lot of LA drivers who can't drive in snow, for example. I was one of them, until I got practice, and even then, I'm not that safe at it.

I think as long as we set the bar at "drive anywhere a car can go with 100% safety" we will never reach that bar.

But if the bar is at "drive as well as a human in most of the places humans drive", well, I've already seen a car that can do that.

<comment><AUTHOR> What's hard about this comparison is knowing exactly what you saw. If the safety driver disengaged 1-3x, it might have felt like a robotaxi drove you all over; but the effort to get that system safe for unmanned regular service might take another decade.

If it was super mapped and following a fixed route with object avoidance; the difference between a car that can go on an HD-map track and one that can go point-to-point in a city is also maybe a decade.

We humans have limited empathy for what is really really really hard for computers. Many know that's true for an app, but somehow ignore that knowledge when it comes to autonomy.

<comment><USER22> Even if jedberg observed 0 disengagements, it's still not the millions of miles of data you'd want to prove something.

</comment></comment></comment><comment><USER23> Such an excellent and cogent discussion of the challenges of making an autonomous vehicle startup work.

I really resonate with the challenge they had making safety "sexy" from a coverage point of view. It seems it shares that attribute with "security" which, when done well, means nothing happens.

I had a lot of hope that we would get four lane (two each way) "freight ways"[1]. These would be paved roads designed specifically for autonomous trucks to move freight from one point to another. With sufficient freight ways between key cities on the coast and further inland, and efficient way to move goods with somewhat worse costs than rail and quite a bit better in terms of reaction time.

[1] Like a free way but designed specifically to exclusively service autonomous trucks carrying standard containers.

<comment><USER24> This begs the question, how much does it cost to lay road than to lay rail? If it's going to be exclusively autonomous, the more narrow confines of the rail should be well suited.

<comment><AUTHOR> Another common fallacy. The US actually has a better rail network than Europe - most people just think it's worse because passenger rail here sucks. That's the case because we prioritize freight trains over passenger (in America Business is #1).

To paraphrase Churchill, trucking is the worst form of transportation, besides all the others. If you can put freight on a train, you do. It's slower, point- to-point, and less good a less-than-trainload freight than trucks are.

</comment></comment></comment><comment><USER25> I always thought that autonomous driving was more than 10 years off (if not 20) for cars in city traffic. But I thought trucking in the US had a chance for intersate traffic till the proverbial last mile, because there are less edge cases that you need to train the model. Were you off by just 3 years for interstate "driving" till the last mile?

Will investors lose their loss memory and a whole new set will invest in the space in say 3 years.

<comment><AUTHOR> System worked. Problem was investors have mostly bet on full autonomy, and when that failed to materialized they got scared out of the space.

Full autonomy isn't necessary. And I don't know if it's even profitable for trucks.

<comment><USER26> Does the current coronavirus pandemic assist you in promoting a teleop model? I'm not sure how much human to human contact there is in the business.

<comment><AUTHOR> Hard to say. Truck drivers will be hit hard by this - they can't really stop interacting with people, almost never get paid time off, are older and in poor health, and are paycheck to paycheck.

My bet is that nearly all of them get COVID, with a higher hospitalization / mortality rate. Could knock 30% of capacity off the road in the next 2 quarters, which would mean food shortages.

</comment></comment></comment></comment><comment><USER27> This is a very good and honest retrospective. He shows clear thinking, and surprising technical understanding for someone who is not technical. And most importantly he shows humility. A+

</comment><comment><USER28> _There are too many problems with the AV industry to detail here: the professorial pace at which most teams work, the lack of tangible deployment milestones, the open secret that there isn't a robotaxi business model, etc._

Just curious, why would there not be a business model for robotaxis?

<comment><USER29> Uber: the drivers own the cars, the drivers maintain the cars, the drivers clean the cars, the drivers store the cars when not in use.

Driverless: the company needs an operation, real estate, and staff comparable to a big auto rental company to do all that. Plus the engineering and technical staff required for autonomy.

Even with startups doing autonomous shuttle buses, which works at low speed, nobody is making money in that space. It's all demos.

<comment><USER18> Add to that the fact that you are _never_ going to get 100% fleet utilisation, will need to pay for qualified tele-operators, maintain/repair vehicle along with sensors...

I recently listened to a podcast episode of the Autonocast[1], where they interviewed a Harvard Researcher who claimed the economics of Robotaxis just don't work. Very interesting listen.

[1] [http://www.autonocast.com/blog/2020/3/11/177-ashley-nunes- on...](http://www.autonocast.com/blog/2020/3/11/177-ashley-nunes-on-robotaxi- economics)

<comment><AUTHOR> All transportation businesses are utilization businesses. Empty hours/miles are never recovered.

Early robotaxis will have tight geofences. Makes them particularly bad competitors to poorly paid people who are willing to drive wherever.

</comment></comment></comment></comment><comment><USER30> > The biggest, however, is that supervised machine learning doesn't live up to > the hype.

This is the key point. The new DNN approaches can outperform the classical techniques, but only when they can exploit vast amounts of training data. The dramatic successes of Deep Learning all depend on either unsupervised learning against enormous raw datasets (BERT, GPT-2, word2vec, etc) or games, where you can generate unlimited quantities of labelled data by playing the game against your own agent (AlphaGo, AlphaStar, OpenAI Five, etc).

<comment><USER31> As someone already mentioned here,I think it's probably not a goood approach. The way we store info in dstabases is very limited compated to what we can do in our heads. For instance we know a concept of a table.It can be made of almost any material,can have whatever shape,size, and colour we want and yet we can instantly recognise it without having some concrete data points on what it should look like. I can make a glass cube,put it in a middle of the room and people would know it's a table.How the hell we operate this way,I have no idea.

<comment><USER32> On a basic level we all: \- Know what a room looks like. \- Expect certain objects to exist at certain places and not expect others \- The brain indexes these \- Seeing one or two datapoints allows us to guess. So seeing a glass cube in that context gives us few logical chpices (it must be a table) similar to someone typing a letter in a textbox and having it filter a pre-defined list.

</comment></comment></comment><comment><USER33> Thank you for sharing this. The insights and details you share here will help many future founders.

I'm sorry things didn't end up in the exact way your team may have hoped. I hope you can take pride in everything you accomplished. I wish you all the best!

</comment><comment><USER34> It took me a while to figure out that "AV" means _autonomous vehicle_... I was kind of wondering what AV as in AV club had to do with trucking.

</comment><comment><USER35> The VSSA (Voluntary Safety Self-Assessment) referenced in the post

[1] [https://uploads- ssl.webflow.com/599d39e79f59ae00017e2107/5c1...](https://uploads- ssl.webflow.com/599d39e79f59ae00017e2107/5c1be1791a7332594e0ff28b_Voluntary%20Safety%20Self- Assessment_Starsky%20Robotics.pdf)

</comment><comment><USER36> Great read! And thanks to the author for all the candor.

The business case always seemed clear to me and now reading this, I wonder if there is a case to be made for an engineer and a trucking operations veteran to build a business that requires minimal capital (or maybe even is bootstrapped?!), to take it across the finish line?

<comment><AUTHOR> There are a couple of people working on that, notably CloudTrucks.

It's not for the faint of heart - truck drivers and engineers follow a very different set of social norms. It's hard to be the hardass boss drivers don't want to fuck with while being the cuddly CEO engineers like the culture of. That might be a future blogpost.

<comment><USER37> Waiting for it. Sad but good read.

</comment></comment></comment><comment><USER38> Thank you for the excellent write-up here. I'm sad to hear that Starsky is dissolving, but I have hope that the lessons learned here will be applicable elsewhere.

The point about safety being a low priority with investors makes sense but is unfortunate. I hoped that Google's investment in Waymo would push past this hurdle, but they're latest funding round makes it clear that they also have to deal with investor wants over the success of the technology. Really hoping to see someone get the funding to make this tech work reliably in the future and apply the same safety-first design that Starsky used.

</comment><comment><USER39> Why not an aquihire? Surely lots of companies would want to augment their av teams?

<comment><USER40> I'm sure it was explored but it didn't close. Stuff like this is annoying for a founder to hear because he's like "aw yeah, why didn't I think of that earlier?!" Of course he thought of it — but it just didn't work out that way.

</comment></comment><comment><USER41> It is pretty cynical and hindsight is always 20/20, but... is self-driving automotive just trains and metros? There is a fundamental business case flaw in these startups, because regulators worldwide will never approve them go together with human traffic, which is messy, chaotic, smart in its own sense at local level (you need to know the uses of local people, not the general rules... eg. driving a car in Naples is very different from driving a car in Milan). Only dedicated lanes or tunnels then, trains!

</comment><comment><USER42> I wonder what Elon is going to do when _his_ "full self driving" fails to materialize. Which it will. Not only you can't do this with just cameras and radar, I doubt you can do it _period_ without modifying the roads specifically for such cars, and segregating them from human drivers. And even then it will be difficult psychologically and legally to convince the public that this is "better" than a (possibly inebriated) human, for reasons that have been discussed to death already.

<comment><USER43> >Not only you can't do this with just cameras and radar

Humans do it really well with just two cameras. It's not a hardware problem; it is entirely software. Whether self driving is possible or not with current AI techniques is debatable, but we're not waiting on any advances in hardware to do it.

<comment><USER44> > Humans do it really well with just two cameras.

If you don't mind, I think I'm going to steal that quote. It makes a really good point very succinctly.

<comment><USER45> It's true, but it ignores the fact that human eyes have orders of magnitude more dynamic range than even _very_ expensive specialized cameras, and it obviously ignores the fact that we haven't invented general AI yet.

It's a pithy response that undermines the challenge of a problem nobody has been able to solve even with years of effort and billions of dollars.

<comment><USER43> >It's true, but it ignores the fact that human eyes have orders of magnitude more dynamic range than even very expensive specialized cameras, and it obviously ignores the fact that we haven't invented general AI yet.

That level of resolution doesn't matter at all for driving. People can drive just as well through a video feed, like Starsky was doing. Yes general AI does not exist yet, but my point is simply that the parent made a comment about the need for hardware which is simply not true.

<comment><USER45> > That level of resolution doesn't matter at all for driving. People can drive > just as well through a video feed, like Starsky was doing.

I can tell you from experience this is false. It usually works, but when it doesn't you're fucked. People wildly underestimate, by orders of magnitude, how many and how complicated the edge-cases are for self-driving.

</comment></comment></comment></comment></comment></comment><comment><USER46> Why does every self-driving car company focus on driving like we do today? Seems more viable to make a system where the trucks dock at speed on the highway. This is where the power of AI come in to play by coordinating the two trucks next to each other, switching load and continue driving without ever have to stop. The end goal would be to also move people, but we have to start with something safer that makes economical sense.

</comment><comment><USER47> All this L1/L2/L3 when most of the public failures in AV are at the level of vision and interpretation of the world.

<comment><USER48> So? That graph is about the capability of the system and how it improves with effort. This has nothing to do with which part of the system fails the most. Where do you see the contradiction?

<comment><USER49> The choice of naming here is somewhat unfortunate, and probably contributes to some confusion.

Level 0-5 is terminology used by SAE to describe the range of fully manual (Level 0) to fully autonomous (Level 5). One would expect that in an article about Autonomous Vehicles, L{0,1,2,3,4,5} would describe the level of autonomy that the vehicle provides, but the article instead uses these to describe arbitrary thresholds of a graph demonstrating the capability of an AI.

<comment><AUTHOR> Fair point. I'm shitty at drawing mathematical graphs.

I'll update at some point with different notation.

<comment><USER37> I think it makes my day as it is a rare but simple insight into the s curve and the peak line. It will be a useful mental tool for life.

Not sure why l meant anything in some other model would affect its reading. Good to me.

</comment></comment></comment></comment></comment><comment><USER50> Not sure about him blaming the "professorly pace" of research though. That's the rate good research is done at. If you were expecting anything faster than you don't really understand what it was going to take in the first place

</comment><comment><USER51> Stefan & team: I'm sorry your company failed. I hope you can and will take time now to rest and recover.

Things that help recovery from burnout: long walks, therapy, exercise, sleep, meditation, and spending time with people you love.

</comment><comment><USER52> If we'd sold AV as "grandma driving" instead of "autopilot" do you think we could have avoided some of this mess?

The public are only ever going to accept perfection which prevents us from getting our hoverboards here.

</comment><comment><USER39> Welcome to the trough of disillusionment. (sp)

I think the plateau of productivity will be really awesome computerized copilots and safety assists/warnings. The human computer driving team could Be quite a combo of designed right.

<comment><AUTHOR> The problem is that most of those businesses don't make sense with the current cost of talent. The L2 systems OEMs are rolling out are primarily made by engineers in low-cost areas at $60-90k/yr, not $130-250k/yr in SV.

Realistically, most of the AV talent will go to industries that can afford them. Salary isn't super elastic.

<comment><USER39> The engineers in the low cost of living areas do the real work. We don't need rockstars.

</comment></comment></comment><comment><USER53> For any engineers reading this who want to solve the computer vision/machine learning problems explained in the blog post - reach out at firstname.lastname@example.com.

</comment><comment><USER54> Thanks for sharing, Stefan. Lots to be proud of in what Starsky achieved, and factors outside your control at work at the end.

Excited to see what you do next.

</comment><comment><USER55> > In 2019, our truck became the first fully-unmanned truck to drive on a live > highway.

Uber drove an autonomous truck on a live highway to deliver beer for Anheuser- Busch back in October 2016

[https://fortune.com/2016/10/25/uber-anheuser-busch-first- aut...](https://fortune.com/2016/10/25/uber-anheuser-busch-first-autonomous- truck-beer-delivery/)

<comment><AUTHOR> There was a person in the vehicle. Amusingly - many VCs who "should know better" fell for the same error. I'd regularly get in arguments with investors about whether others had done unmanned or not.

<comment><USER55> In the sleeper cabin monitoring the vehicle. The main cabin was unoccupied and there wasn't a single intervention for the entire trip. I knew people involved with that trip at the time.

<comment><AUTHOR> The difference between "in the sleeper cab" and "outside the truck" are huge. We first started doing in the sleeper cab in Jul'17, took us 2 years of dedication to get confidence to remove from vehicle.

To take the person out of the vehicle, the system itself needs to be able to self-monitor and pull itself over if it stops working. That's the big lift.

<comment><USER55> That's it. The team at Uber did that like a year or so later but with no public fanfare because it wasn't considered noteworthy. That still puts it at ~2 years prior to this accomplishment.

</comment></comment></comment></comment></comment><comment><USER56> This to me very much assumes no leap forward. See the start of deep learning - sudden rapid progress. I don't see why there can't be another jump like that. Much like the chip manufacturers mentioned in the post.

No idea what that advance may be but it's out there I think

<comment><USER57> Perhaps there is no leap forward in long haul trucking. Yet there are many supervised machine learning products in the market and doing well (Tesla autopilot, iRobot vacuums, etc). I bet the founder can find a niche that could be marketable and can be mass produced or scaled.

</comment></comment><comment><USER58> Just this hiring season, I still saw positions open...and now this

</comment><comment><USER59> Maybe it's time they got bought out by a larger company, and go dark. Continue their research in private, until they build the perfect robot.

</comment><comment><USER60> Sad news. Apart from improving upon ML, can more sensors and physical modeling get us past the AV plateau?

An example of an additional sensor would be an infared camera. I don't know how well infared cameras work during the day or when they are occluded, but they seem like they can provide an additional datapoint to classify an object as "person" for example. That way, it doesn't matter if they're wearing a paper bag Halloween costume, the car still knows what's underneath.

Physical modeling seems like it would help with prediction. If a deer is idle on the side of road ahead, a car with a physical "deer" model would account for the probability that the deer will suddenly dart across the road and the speed at which it can possibly do so. It will slow down and watch for certain behaviors, such as the deer standing up from a prone position, and modify its probabilities accordingly. That is, after all, what we humans do. The ML wouldn't need to perfectly model all animals. Some animals would be put into a "mammal" class or more vague "animal" class, paying special attention to size and stature.

Additionally, depending on how long it might take to develop truly autonomous self-driving cars, we might want to develop self-driving car friendly infrastructure. I'm talking about AV-only lanes with safeguards in place to minimize variability, vehicle-to-vehicle communication, infrastructure-to- vehicle communication, and better than average maintenance. It seems like it might be worth it, given the gains to be had.

Here's an underappreciated angle to the AV-friendly infrastructure: it's a hedge against incorrect predictions. What if truly autonomous vehicles are actually 15 years away? In that case, if an "AV heaven" is developed in a corridor somewhere in Los Angeles 5 years from now, that'll be the only place where the AV dream is realized for the ensuing 10 years. The profit from "AV heaven" can be reinvested into AV development. It can also be used to expand into other areas. Moreover, AV heaven might galvanize the government, public, academia, and investors to eliminate any bottlenecks in AV development. There's no immutable stone tablet, only viewable by God, that says "AV development must take X years." We can modify the timeline to some extent. Lastly, AV heaven would allow us to observe the true value of self driving cars. What if they're better than we ever imagined? What if they radically change human behavior? What if they increase development in surrounding areas by a lot? What if they change the nature of work and where people live by more than we even expected? What if self-driving trucks + last mile bot delivery radically push down prices on everything and enable previously impractical business models or behavior? We actually know many of the changes that AVs will bring, but, critically, we don't know the magnitude of those changes.

</comment><comment><USER16> I'm not sure it's intellectually honest to put all the blame on stupid investors, as a founder it's your job to deliver what the market and the investors want, or convince them otherwise. And if in fact investors and the market is just stupid, that's actually a great sign: you were just early and have a shot at doing it again in the future.</comment>


Hubspot Interview for Senior Software Engineer - <AUTHOR> https://blog.rampatra.com/hubspot-interview-for-senior-software-engineer <comment><USER2> have my interview next week. thanks for sharing

<comment><AUTHOR> No worries. All the best!</comment></comment>


What Is Best Australian Eta Visa Agency? - <AUTHOR> ETA visa is for short term stays in Australia purely for tourism and business activities only. It lasts for 12 months and allows you to travel to Australia as many times as you want. However, you can only stay in Australia maximum of 3 months on each visit. <comment><USER2> There's no 'agency' you apply for it yourself online.</comment>


MessagePack vs. CBOR (RFC7049) - <AUTHOR> https://diziet.dreamwidth.org/6568.html <comment><USER2> Nope, I'd rather prefer the better format which is CBOR. message pack had a problem (and others), which they refused to fix (despite PR's). So a new better format was created without these problems and without adding too much nonsense. Like Mongo's BSON which added insecurity to a very secure format.

<comment><USER3> How does BSON compromise MongoDB security?</comment></comment>


Harvard Research Computing Resources Misused for Dogecoin Mining Operation - <AUTHOR> http://www.thecrimson.com/article/2014/2/20/harvard-odyssey-dogecoin/

<comment><USER2> I don't understand how he could be using so many resources unless he had access to the entire cluster.

Even then he is retarded for using the entire cluster. A single node is probably 10 of my desktops.

Or even better why not make it into a research project to see what Harvard could to with the coins?</comment>


Linux Explorers - <AUTHOR> http://linux-explorers.blogspot.com/

<comment><AUTHOR> Know linux from bottom to top....</comment>


Yosemite@17gigapixels - <AUTHOR> http://www.yosemite-17-gigapixels.com

<comment><USER2> It's breath-takingly beautiful (and even more so in person), but the stitiching isn't so great around the waterfall... :(

Since the water (obviously) moves, along with the mist and the spray, there are clear discrepencies between the panorama's input photos.

</comment><comment><USER3> cool, borderline spam though?

<comment><AUTHOR> Ya I agree, still though, it's borderline. So viewer beware of AD + Flash.

</comment></comment><comment><AUTHOR> 214414 x 80571 pixels. 59.5 x 22.4 ft @ 300 dpi.

</comment><comment><USER4> Looked like an Obama ad to me.

</comment><comment><USER5> O-Spama.</comment>


Ask News.YC: Teach for America? - <AUTHOR>

Don't know if this is appropriate for Hacker News. But I'm guessing some of you are in college and thinking about what you're going to do 9 to 5 after you graduate, if you don't go IPO before school ends.<p>Anyone have experience with Teach for America (www.teachforamerica.org)? Any thoughts about the organization? <comment><USER2> If you are a hacker (you are posting to hacker news), I suggest you avoid it.

I don't know anything about Teach For America specifically, but several people in my graduate program did work for a variant of it (local and math focused). None of them were happy with the program, though several stuck with it for financial reasons. One of them was put in charge of statistical analysis, since he was the only person in the room who knew what a standard deviation was (I'm not exaggerating). His conclusions:

1\. Except for the grossly incompetent, teacher quality doesn't matter. He could not reject the null hypothesis (teacher quality doesn't affect student outcome).

2\. Students do not benefit from being in the program, unless it removes them from a dangerous school. He couldn't reject the null hypothesis here either (accepted students perform the same as rejected ones). (This fact is usually well hidden: students accepted by special teaching programs as well as students who apply but are rejected usually perform better than students who do not apply.)

According to him, other programs usually get similar results (well hidden in the appendix of a report), at least when the results are reported.

Overall, he said it is a waste for a talented individual to go into teaching. You won't make a difference. As a software person, you will.

Leave teaching to people who can't do anything else. They have a comparative advantage (even if they lack an absolute advantage).

<comment><USER3> [Disclaimer: I've been teaching computer science at the high school level for nearly eleven years now. My B.S. is in computer science from the University of Texas at Austin, and I set the curve in some of my courses.]

I hesitate to disparage the analysis of an anecdotal person I've never met, but I disagree with the claim that statistically teacher quality doesn't affect student outcome.

The current leading meta-statistical analysis of teachers and teaching methods and their effect on student learning is "Classroom Instruction that Works", by Marzano, et al. They have statistics on good teacher/bad school, good teacher/good school, bad teacher/good school and bad teacher/bad school and the effect on student performance. The average effect size when comparing multiple studies shows that good teachers _do_ make a significant and measurable difference in student achievement.

I think leaving teaching to "people who can't do anything else" is a cop-out. I've taught the basics of programming to over 1000 students in my career thus far. I know of at least a dozen who now do it for a living, including some who say that a career in programming never crossed their mind before taking my class. Do you think I've had a net positive effect on the industry? I can write a lot of code, but teaching others to code eventually produces more. "Teach a man to fish" and all that.

I do agree with Prrometheus below that a lot of public education is "an inflexible, pathological bureaucracy."

I also agree that if you don't enjoy working with young people, don't bother. Further, if you can't set healthy boundaries, you'll eventually get burned out. Also, if you're a hacker at heart, you'll need to keep coding somehow, or you'll go mad.

Of course, I don't know anything about Teach for America either, but I do know that I really enjoy teaching, and I'm glad I went that route rather than industry or starting something of my own.

Just my two cents.

<comment><USER2> Well, keep in mind what I'm describing is one special program in math. Also, everything I know I heard over beers, while complaining about our advisors.

Regarding teacher quality, he found the best fit was a failure model. Most teachers perform adequately, and these teachers are statistically indistinguishable. Some teachers fail, with varying degrees of failure.

Basically, think hard drives. Most work, and these are all the same. Some fail, with varying degrees of data loss.

If the sample in the study you mention comes from the partially failing region, they could easily find an increasing relation. Or possibly this program was special, that I don't know.

However, I do stand by my statement to leave teaching to those who aren't great at other things. That's just basic comparative advantage.

You are comparing your students with you as a teacher to your students with no teacher. The proper comparison is "you program, joe blub teaches" vs "you teach, joe blub programs." If joe blub teaches almost as well as you, but you program much better than him, then it's far better if you leave the teaching to him.

Of course, if you enjoy teaching, you certainly are not obligated to do the most economically efficient job. I'm certainly not (postdoc in math here).

<comment><USER3> Yes, but the number of students in my program is higher than the other two (wealthier) schools in my district, and a lot higher than schools with comparable demographics.

Even if Joe Blub teaches nearly as well as I do (and I'm willing to accept that he may), I _recruit_ a whole lot better than he.

But if I teach my students Java (as the AP exam requires), does that make _me_ Joe Blub?!? :)

</comment></comment></comment></comment><comment><USER4> Dear god, if you have the people skills to manage a classroom full of teenagers, and the pedagogical skills to teach stuff, software engineering _needs_ you. Can I interest you in the Drupal project? ;)

I know one person who used his new B.S. in Physics to Teach for America, and was unhappy. I know another person who loved to work with kids, worked for years in a science museum, then got a degree in education and worked as a high school teacher in a rural county, and is now... unhappy.

I think that teaching is like medicine, law, marriage counseling, postdoctoral research, and just about any other career: It's hard to know if you'll like it until you try it for real. You can't really learn what it's like, day-to-day and year-to-year, by watching from the outside. I've certainly met teachers who loved their jobs, but you have to love the reality, not the Platonic ideal in your head.

Honesty, if not my sense of social justice, compels me to observe that the long-term happiness of the teachers I've met has been correlated to the selectiveness of their schools -- they work at Catholic schools with tuition, magnet schools, private schools, or schools in districts where only doctors and lawyers can afford to live. I think the main reason for this is that the students in such schools are relatively well motivated: they either care about the material or care about their grades. (It's not just pay -- the Catholic school teachers I knew were paid considerably less than their public-school colleagues. But then, if you've read _Peopleware_ , you could have predicted that.)

The happiest hacker-turned-high-school-teacher I know started off in industry, burned out after a couple of decades, then switched to teaching. You might consider that path. OTOH, the advantage of Teach for America is that it gets you in front of students (a) quickly, without having to go through as much bureaucratic hazing -- no education degree required; (b) temporarily -- you can quit in a couple years with no dishonor; and (c) when you're young, so that it will have minimal impact on your future career.

<comment><USER5> "I think that teaching is like medicine, law, marriage counseling, postdoctoral research, and just about any other career: It's hard to know if you'll like it until you try it for real. You can't really learn what it's like, day-to-day and year-to-year, by watching from the outside."

A difference with those other fields is that teaching is ensconced in an inflexible, pathological bureaucracy. Although, that could be my ideological bias talking.

<comment><USER4> Wait, are you saying that medicine and counseling _don't_ have pathological bureaucracy? Have you asked your doctor to describe exactly how much time and effort it takes to get money from dozens of separate insurance companies, all of which are using every trick in the book to avoid paying? Or are you lucky enough to live in a civilized country?

And, please, don't even ask about postdoctoral research and the attendent interactions with university bureaucracy, departmental politics, and Federal grant review processes. Or I might need counseling. And my insurance doesn't cover that. :)

</comment></comment></comment><comment><USER6> My brother did this - taught French in a Louisiana middle school for two years after college. However, he was a humanities major who went on to a PhD program afterwards; aside from a bit of stats in R, he doesn't do any hacking.

It was a good experience for him, and it is an admirable thing to take on. He said that it was largely crowd control, and a little bit of teaching. The schools that serve low income people in Louisiana are in pretty grim shape, evidently.

I don't think it would help a hacker much at all. But there are things other than hacking in life, right?

I dunno, from the sound of it, I don't think it would be in the best interests a 22 year old hacker, who is almost bursting to get out there and work with an innovative startup, to step out of the game at age 22 to teach basic math in an underfunded school. The excitement, creativity, and freedom you have at that age won't be there forever.

I'm sad to say that, though - because I personally _do_ think that talented teachers make a positive difference, and I think that a more public-mindedness among technology workers would be a good thing (there's a strong undercurrent of distain for politics and legalisms - but if we don't participate, lawyers will be more than happy to regulate technology for us...)

</comment><comment><USER7> I'm not a programmer, but I did TFA for three years in Compton after graduating with a BS in Physics. I would say that if you are serious about your start-up, it's probably not the best fit for you: you simply won't have the time or energy at the end of the day, especially in your first year. This of course assumes that one would do TFA because one wants to actually tackle the problem of educational inequality, and not just because one thinks it will look good on a resume someday or one has a martyr complex.

A typical day is: get to school at 7, plan, hold before-school tutoring, teach all day (with a lunch break of 30 minutes), kids go home at 3, hold after- school tutoring until 4, plan, go home at 5 or 6, eat, grade papers until you fall asleep. This was my experience at least.

I loved it because for me it was about connecting with people who had a completely different upbringing than I do. The skills I learned in the classroom have colored most of my professional life. I found that students, in aggregate, are excellent judges of character, and I really had to step up my game to gain their trust.

Common Criticisms and responses: "It's crowd control..." -only if you're a lousy teacher (and there are plenty)

"TFA is a cult..." -it is, but after your initial training, which is actually very useful, you can choose to be as involved as you want (I wasn't very)

"Teaching is for those who can't do anything else." -Maybe there's some truth to this. I think it depends on what a person believes is important. Effective teaching in an inner-city school is definitely not easy, and to be honest, I think it's a problem in need of a new solution. I think the world could use a better model of education more than it needs a better way to use RSS to find out what one's friend had for breakfast. So if you have the raw innovative skill, it's a huge opportunity.

<comment><USER6> I feel a little bad saying it was "crowd control" because those are my words, not my brother's (who was the one doing the program). I think he was a good teacher, and he would probably object to that characterization.

He told me that once he left the room for a few minutes because a kid was sick, and heard a huge crash. When he rushed back in, it turned out that a girl had tried to smash the overhead projector on top of the head of another student. Glass was everywhere This was the result of leaving the classroom for 2 minutes.

But when he was in there, I don't actually think it was all crowd control. He had the respect of the students, and he was able to teach.

You made an interesting observation about the "cultish" quality of TFA. He said that he had no illusions about how much of himself he was giving. He said his attitude from the start was "This school has 30 teachers. Two of us are TFA. The other 28 are just doing their job." That attitude helped him out a lot, I think.

<comment><USER7> There's definitely an element of crowd control in the sense that the students are kids; they naturally like to get into trouble, and don't come pre- installed with self-management skills.

I think that it's important to be cognizant of how to manage crowds, but it's easy to get bogged down in just maintaining the peace. There's gotta be a reason to pay attention, a reason to behave, other than "do what I tell you or else"...this is what I meant by lousy teaching.

Sounds like your brother knows what he's doing and I'd bet his students are lucky to have him. With regards to his story about the overhead projector, it brings back fond memories of pretending to leave the room but really just standing right outside the door to see which students were the first to a) realize I'm gone and b) start trouble. The classroom can be a hilarious laboratory for the study of human nature. (I do certainly hope that the victim was alright and that the perpetrator was held responsible.)

</comment></comment></comment><comment><USER8> Yes, not sure how it relates to Hacker News. If you're trying to choose between TFA and running a startup, you've got your head twisted around somehow. Very different paths. If you have notions of doing both at the same time, give those up. First year of teaching is very demanding.

But if you're still interested anyway, sure, look into it. I did TFA for a couple years (95 Rio Grande) and it was a good experience. I wouldn't teach in a public school again unless I was starving, but it was the right thing for me at the time. Feel free to email me, email@example.com, if you've got particular questions.

</comment><comment><USER9> Teaching is a tough gig -- I tried it, and it was too tough for me.

The downside of tfa is that they are somewhat cultish and will want you to drink cool aid. The upside is that you get some training, and will meet cool people. (Many don't drink the cool aid, and even those that do are well intentioned positive thinkers.)

For those who are born teachers, who love kids, whose calling is to teach... TFA is great. For those who aren't, it could be a catastrophe in a rosy coupon. Most people will fall somewhere in the two extremes.

So, the simple answer is: run away. But, maybe you are a born teacher and this is right for you. No harm in applying, I guess.

<comment><USER9> Note: I applied, and was negged, by TFA, but know many people who did it and told me of their experiences.

I taught briefly in an urban public school, where basically anyone with a college degree could get a job because there was such a teacher deficit. (They were quitting in droves.)

I probably could have used the training I would have gotten in TFA, as going in there completely green was a _bad_ idea :) Oh well, I probably taught a few kids some stuff they might be able to use later in life. Mostly I just tried to keep them in their seats and not setting the building on fire.

One final note: The hardest thing about teaching is the workload. 100 hour weeks is just words until you've experienced it. (To be honests, I am not sure if it was that many, but it seemed like it. And this isn't 100 hours staring at a spreadsheet, but chasing down kids, grading illegible homework, calling parents, dealing with bureaucracy, dealing with classroom observations and job ratings from the assistant principle who doesn't give a shit about your fancy college degree... yikes.)

Teaching would be a lot more doable if you had fewer students, or if all the classes you had to teach could follow the same lesson plan. I was preparing five different plans a day. A tough schedule even for an experienced educator with years of semi-prepared lesson plans that he has already taught a few times and knows what works and what doesn't.</comment></comment>


Hiring in a Startup – The Hard Truth - <AUTHOR> https://medium.com/swlh/making-the-first-hires-in-a-startup-the-hard-truth-fa7dbf37160f <comment><USER2> Nice approach to reach out to potential employees :)

<comment><AUTHOR> Thanks! :)</comment></comment>


Do all programming languages converge to Lisp? - <AUTHOR> https://www.quora.com/Do-all-programming-languages-actually-converge-to-LISP/answer/Max-Thompson-41?share=1 <comment><USER2> All programming languages have tree representations of their syntax, so are kind of a 'lisp' under the hood. However other languages typically don't allow you to get under the skin of the compiler in the way macros do to manipulate those trees. Therefore I don't think all programming languages converge to lisp (although lisp can converge to other programming languages!).</comment>


New tLD .prod is messing with my configs - <AUTHOR> http://www.linuxquestions.org/questions/linux-server-73/new-tld-prod-is-messing-with-my-configs-4175517305/

<comment><AUTHOR> It appears the new TLDs are in a period called Controlled Interruption[1] where DNS queries get a response of 127.0.53.53 .

ICANN has made a "Guide to Name Collision Identification and Mitigation for IT Professionals"[2]

Here's a list of their Name Collision resources: [3]

[1]: [https://www.icann.org/resources/pages/name-collision-it- pros...](https://www.icann.org/resources/pages/name-collision-it-pros- faqs-2014-08-01-en#interruption)

[2]: [https://www.icann.org/en/system/files/files/name- collision-m...](https://www.icann.org/en/system/files/files/name-collision- mitigation-01aug14-en.pdf)

[3]: [https://www.icann.org/resources/pages/name- collision-2013-12...](https://www.icann.org/resources/pages/name- collision-2013-12-06-en)</comment>


CDO Revival Led by Funds Pinning Hopes on Smallest Banks (2015) - <AUTHOR> http://www.bloomberg.com/news/articles/2015-10-20/cdo-revival-led-by-hedge-funds-pinning-hopes-on-smallest-banks <comment><USER2> I don't know anything about the details of this particular CDO structure (and the article was a bit sparse on the details other than its small banks), but I've grown disgusted with people trying to make convoluted financing schemes to make money.

CDO's didn't exist until 1987. The market and economy grew just fine without them. In fact, we've seen an increased divergence of rich/poor since that time. CDO's only help the rich get richer.</comment>


Who ordered memory fences on an x86? (2008) - <AUTHOR> http://bartoszmilewski.com/2008/11/05/who-ordered-memory-fences-on-an-x86/ <comment><USER2> By the way, in case anyone was curious about the comment in the article:

> Since fences are so expensive, couldn't you add a dummy assembly instruction > that prevents the X86 from re-ordering? So the pseudo assembly for thread 0 > might become:

        > store(zeroWants, 1)
        > store(victim, 0)
        > r0 = load(victim) ; NEW DUMMY INSTRUCTION
        > r0 = load(oneWants)
        > r1 = load(victim)

> Since the dummy instruction is a load, the X86 can't reorder the other loads > before it. Also, since it loads from "victim", the X86 can't move it before > the store to "victim".

> If you do this to both threads, does that solve the problem?

This doesn't work. Intel specifically calls out these sorts of attempts to get a fake memory barrier: "The memory-ordering model allows concurrent stores by two processors to be seen in different orders by those two processors; specifically, each processor may perceive its own store occurring before that of the other." This is true in practice as well as in theory.

A related trick that _does_ work in practice (though it is also banned by Intel) is to write to the low-order bytes of a word, read the entire word, and get the high-order bytes. It's sort of a single-word StoreLoad barrier. There's a paper from Sun that documents it further: [http://home.comcast.net/~pjbishop/Dave/QRL-OpLocks- BiasedLoc...](http://home.comcast.net/~pjbishop/Dave/QRL-OpLocks- BiasedLocking.pdf) .

</comment><comment><USER3> Reminds me of this interesting paper (2 years later) which found at least one of the x86 memory ordering guarantees was not true: [http://www.cl.cam.ac.uk/~pes20/weakmemory/cacm.pdf](http://www.cl.cam.ac.uk/~pes20/weakmemory/cacm.pdf)

<comment><USER4> For an overview of papers for x86 memory ordering of the same group, see [http://www.cl.cam.ac.uk/~pes20/weakmemory/index3.html](http://www.cl.cam.ac.uk/~pes20/weakmemory/index3.html)

</comment></comment><comment><USER5> This article is pretty old and I suspect if you asked Bartosz now he'd explain it slightly differently. You certainly need to use instructions that impose additional ordering guarantees on x86 in these kinds of situations but you don't need an mfence and in general it will be slower than an appropriate locked instruction. The appropriate uses of mfence are actually much more limited, it's only really needed with special memory types (e.g. write combined) or when you need ordering on certain non temporal loads and stores (mostly vector instructions) AFAIK.

In regular code you should never require the hammer of mfence for correct synchronization. You can implement C++11 atomics without it.

<comment><USER6> It doesn't look like the LOCK prefix applies to MOV (from a quick google)? So how does it address write buffering or OOE for stores in a TSO memory model?

[edit] "never require the hammer of mfence for correct synchronization", maybe you're confining this to correct synch. and not recovering sequential consistency (or some other semantic property).

<comment><USER5> It's a little while since I looked closely at this and it's easy to get this stuff wrong but here's what I concluded when digging into this in the context of a codebase I was maintaining that made heavy use of lock free techniques:

\- You don't _need_ mfence (or sfence / lfence) on x64 (which is actually what I care about rather than x86, though they're essentially the same in this respect) to correctly implement C++11 atomics with acquire / release semantics. You can get all the guarantees you need with locked instructions.

\- Correctly implemented C++11 atomics implemented with locked instructions will be as fast or faster than when implemented with explicit fence instructions.

\- The obvious way to implement standalone fences on x64 is with fence instructions but you rarely if ever need standalone fences. Generally you are better off using atomic operations with explicit acquire / release semantics.

In the codebase I was maintaining, the pre-C++11 atomic library was based around explicit fences rather than C++11 style atomic operations with acquire / release semantics attached to the operations themselves. This code was primarily written for Gen 3 consoles (PS3 / Xbox 360) and so was optimized for PowerPC. On x64 (Gen 4 consoles!) there was measurable performance overhead due to unnecessary/redundant standalone fences.

We decided it was too risky to try and rewrite everything in terms of atomic operations with acquire release semantics and remove the standalone fences in the end but it seems to me that if you want to write efficient cross architecture lock free code you want to avoid standalone fences and use a C++11 style atomics library where acquire release semantics are tied to the atomic operations themselves.

</comment></comment></comment><comment><USER7> Remember that x86 (and SPARC) offer the strongest memory ordering guarantees among modern processors. The POWER and ARM memory models are weaker than x86. This actually leads to correctness issues when virtualizing a multi-core x86 guest on a weaker host (cross-ISA virtualization). Of course, this problem only shows up in truly parallel emulators using multiple threads on the host to emulate a multi-core guest, such as COREMU ([http://sourceforge.net/projects/coremu/](http://sourceforge.net/projects/coremu/))

</comment><comment><USER8> The fun thing about membars on x86 is that, unless you're playing with nontemporal stores or non-standard memory types, LOCKed ops are more efficient fences than mfence.

<comment><USER5> Missed this somehow before making my comment saying essentially the same thing. Unfortunately the code base I've been maintaining heavily overuses mfences at a measurable performance penalty on x64.

</comment></comment><comment><USER9> I'm pretty sure the strong ordering of x86 is all in support of backward compatibility (probably to the first multi-core x86). One related example of this is the cache coherent I/O system. If a PCIe card writes to memory, there is really not much that the driver code needs to worry about compared with other processors. Why is this? So the ancient device drivers in MS-DOS will still work with the ancient floppy disk DMA controller.

</comment><comment><USER10> > Loads are not reordered with other loads.

Wonder why that guarantee is necessary. Loads have no side-effects (in the memory), after all.

<comment><USER11> To add to the example of 'DSingularity: remember that the memory ordering guarantees specify the behavior of _individual processors_ in a multi- processor system. You have to extrapolate the system behavior from there. The guarantee on reordering of loads with respect to each other is only unnecessary if you assume that no other processor modifies those locations between loads.

<comment><USER10> Ah yes, I understand it now. Took me some time to get myself thinking on that abstraction level again :) Thanks!

</comment></comment></comment><comment><USER12> You can apply Peterson`s lock for more than 2 threads.</comment>


Moka - Minimalist functional python library - <AUTHOR> https://github.com/phzbox/moka/ <comment><AUTHOR> Clickable link for the doc: <http://phzbox.com/moka/index.html>

Moka is still in an alpha stage; but that being said, I'd love to hear some feedback. Feel free to browse the code, it should be pretty straightforward to any python dev.

<comment><USER2> You've invented your own incompatible dialect of python. You've broken composition, objects and the general design choices of python.

1\. You break Composition

Your magic flag within a list changes all the semantics of the methods between immutable and mutable lists.

> x = List([1,2,3]).saving()

So now, if you're passed a list you have no idea if the operations you do will mutate the list.

This _breaks_ composition entirely. You can't pass a mutable list into a function built for immutable lists without destroying things.

2\. You break objects

Picking another example, this breaks duck typing and inheritance and polymorphism.

>def user_logged(users): > return List(users).all(User.is_logged)

this does not have the same semantics as:

> def user_logged(users): > return all(user.is_logged() for user)

Because the method lookup is done per instance, rather than assuming everything is the same class.

3\. You're writing jquery in python

Python chose not to demand that all iterables implement a series of operators, but provides them as functions within a module. The rationale is that it is easier to add new functions within itertools, and there is far less to do to correctly implement the iterator protocol

You can see this in the "".join(foo) operator too. Instead of demanding all iterables support join, string takes an iterable as argument.

Making readable and maintainable python comes from using the existing idioms within the language and used within the community. Your proposed solution isn't readable, and it isn't pythonic.

<comment><USER3> What is with all the hate lately on anyone who dares to write Python with different semantics than employed by the stdlib builtins?

'You've invented your own incompatible dialect of python. '

It isn't a "dialect." You don't need a different parser. There are no macros. It is simply a container with slightly different semantics than the stdlib ones.

"You've broken composition, objects and the general design choices of python."

No those all still work and if you don't like his semantics don't use them. They are perfectly readable and easily understandable if you having a passing familiarity with the pattern he is using.

tl;dr : I don't see what the big deal is, people are allowed to write Python however they want.

<comment><USER2> tl;dr: you didn't read my post. I am pretty sure I made it clear how composition breaks.

'people are allowed to write Python however they want.'

people are encouraged to write python other people understand.

<comment><USER3> No I did read your post. Actually I read all of them. My point is he didn't "break" composition. In isn't like you import this guy's library and suddenly function composition no longer works. Breaking isn't the right word. It is agressive and wrong on a semantic level.

You could say "You functional list does not properly support composition. Here are some problems." You posts were needlessly combative. I only spoke out because I have seen this kind of thing cropping up recently with respect to Python functional libraries.

"people are encouraged to write python other people understand."

As I said, the semantics of his library are reasonably clear on inspection doubly so if you read the docs.

EDIT:

I just re-read some of your other posts on this thread. You really do keep banging on "He made his own 'dialect.'" To clarify, no he didn't. Making a library isn't a dialect. A dialect needs to be a significant enough departure that you would actually need a different parser/interpreter. That is a "dialect." If you would like I can point you actual Python dialects. This is a library. Deal with it.

<comment><USER2> "the semantics of his library are reasonably clear on inspection"

does .remove() mutate in place or not ? depends on the constructor!

this would be an example of breaking composition - you can no longer use a function built for an immutable list on a mutable list. I am sure I explained this too.

a dialect is a style, in linguistic terms, if I speak a dialect of english, I still speak english.

if I needed a different parser/interpreter I am pretty sure that is the stage of 'new language' where new syntax and semantics are introduced.

the 'dialect' he is introducing is a arc/clojure inspired syntax for what /already/ exists in python.

thanks for the semantic pedantry! the long and the short of it is that if you want to write python, write python that looks like python. not like scheme or clojure.

as someone who gets paid to maintain shitty code, i'd rather people stuck to the existing idioms of the language, rather than blindly copy paste them from another language.

<comment><USER3> "if I needed a different parser/interpreter I am pretty sure that is the stage of 'new language' where new syntax and semantics are introduced.

the 'dialect' he is introducing is a arc/clojure inspired syntax for what /already/ exists in python."

No a dialect is another version of the language. For instance python3 is a dialect of python, just as python2 is. They are not 100% compatible.

"as someone who gets paid to maintain shitty code, i'd rather people stuck to the existing idioms of the language, rather than blindly copy paste them from another language."

It is not his problem you see a lot of shitty python. It is also not his problem if you want every one to stay stuck in the poor design choices that were made in the stdlib a long time ago. You can fight evolution of languages or you can embrace them. I don't see you advocating for "thou" in English ;-)

"the 'dialect' he is introducing is a arc/clojure inspired syntax for what /already/ exists in python."

"syntax" --> no thats is what is defined by the grammar of python. This _is_ python syntax.

"a dialect is a style, in linguistic terms, if I speak a dialect of english, I still speak english."

No it is a mutation. But I agree with you if you speak a dialect you still speak the "language." Olde English is still English.

\---

However my main point remains. You are needlessly combative in this thread. He made a library you attacked him like he insulted the Pope of Python. I am sorry you maintain shitty Python but you don't need to take you anger about _that_ out on some poor guy on hacker news.

</comment></comment></comment></comment></comment></comment></comment><comment><USER4> Here's a gist comparing the Moka front page example to a slightly more typical Python way of doing things:

<https://gist.github.com/1380898>

EDIT: using the timeit module on these, the Moka version is about 18 times slower on my machine... not that this matters much if it's a much nicer way of expressing the program

<comment><AUTHOR> Thanks for sharing. And ya, it's freaking slow right now.

</comment></comment><comment><USER5> The doc at <http://www.phzbox.com/moka/index.html> is pretty complete. The only thing I find is missing is a few words about efficiency. Does calling List(l) copy the list l for example?

<comment><AUTHOR> Optimizing for performance is the next big step of Moka and I understand that it's the breaking point for lots of python developers. So, I'll make sure to work on that and provide realistic benchmarks.

As for the copy, yes it does as it tries to act like a builtin list as much as possible. (In fact, moka.List inherit from list). When it's in immutable state, a new list is returned at each step. If it's in mutable, self[:] = (..) is used.

</comment></comment><comment><USER6> This is indeed minimalist, there's less code in it than I'd expected.

The idioms it introduces do clash with Python ones, but on the other hand, I've been learning Clojure lately and my Python code has more comprehensions than previously. I'm not sure what to think.

</comment><comment><USER7> Needs a README and examples without a hop.

</comment><comment><USER8> This is pretty interesting looking. I'm tempted to try using it on my next project...anyone else used it yet? Seem stable/bug free?

<comment><AUTHOR> It's fairly new but feel free to browse the code; it should be pretty straightforward to you. I've tried to provide good examples to make it easy to learn/use on phzbox.com/moka/.</comment></comment>


Ask HN: AT&T OfficeHand by RingCentral Offline? - <AUTHOR> Does anyone use RingCentral provided by AT&T Office@Hand? My softphone won't login, nor will my Android app. The website login at https://service-officeathand.att.com/login/enter.html reports a 502 error from NGINX. <comment><AUTHOR> [https://community.ringcentral.com/ringcentral/topics/anyone-...](https://community.ringcentral.com/ringcentral/topics/anyone- having-inbound-call-issues-again-i-am-in-nj-all-of-my-clients-are-down- again-07-21-2016)

Yup, looks like it's dead.</comment>


U.S. Loses Appeal Seeking to Block AT&T-Time Warner Merger - <AUTHOR> https://www.nytimes.com/2019/02/26/business/media/att-time-warner-appeal.htm <comment><USER2> Relevant: [https://ritholtz.com/2012/07/media-consolidation-the- illusio...](https://ritholtz.com/2012/07/media-consolidation-the-illusion-of- choice-2/#more-81574)

Does anyone have a version updated for 2019?

Edit: The story got flagged - any idea why?

<comment><USER3> Perhaps because the link is broken (missing the final "l" of "html" as someone pointed out)

</comment></comment><comment><USER4> correct link: [https://www.nytimes.com/2019/02/26/business/media/att- time-w...](https://www.nytimes.com/2019/02/26/business/media/att-time-warner- appeal.html)

</comment><comment><USER5> Does anyone have more (even if hypothetical) ramification examples of said merger? I can only assume it's bad for consumers for the most part, right?

<comment><USER6> Why should it be bad for consumers. Content producers are free to license their material to whomever they choose.

If show X is only available on service Y, and you don't agree, don't watch it. It's mindless entertainment anyway.

<comment><USER7> I agree with the stance that, yes, they are free to do what they want, but only to a degree. The closest historical parallel would probably be the Paramount case that completely changed the cinema landscape from studios owning and operating their own cinemas that only showed the films from their own studio to breaking up these cinemas from the studios and allowing them to show films from whoever they want.

[https://en.wikipedia.org/wiki/United_States_v._Paramount_Pic...](https://en.wikipedia.org/wiki/United_States_v._Paramount_Pictures,_Inc).

But unfortunately the appetite in this country for anti-trust litigation has almost completely dried up at this point.

<comment><USER6> How is this any different than Old Navy selling only their branded clothing? Or Tesla dealerships (if they can be called that) selling only Teslas?

IMO, when strictly speaking about content, there should be zero regulation in regards to whom can own and license content to whom.

<comment><USER7> Its probably worth reading about Rockefeller and some of the reasons we began to enforce anti-trust laws in the first place.

What we want in this country is not solely a free market, but a competitive one. Huge corporations often find themselves in the position of improving profit not by offering better products, but by _snuffing out their competitors_. Often nefariously.

Rockefeller didn't just establish a great supply chain for his oil refineries, he began making railroad companies charge other refineries more than his company. Then he bought the railroads and made the process even easier. He was literally making Standard Oil the only game in town. Anti-competition is not in our best interest as Americans.

And I'm not saying content providers are going to employ the same tactics as Rockefeller did, but its not hard to see how if you controlled a substantial amount of capital in the entertainment industry, maybe you can blacklist actors who decide to go do a show on Netflix. Or pay a director a few extra million just to stop working with HBO. We, as both consumers and free marketeers, do not want this behavior.

<comment><USER6> > What we want in this country is not solely a free market, but a competitive > one.

Who's this we business? Turn of the 20th century politicians?

> Rockefeller didn't just establish a great supply chain for his oil > refineries, he began making railroad companies charge other refineries more > than his company.

And were those railroads forced to take that deal? Economies of scale. Sounds similar to how Walmart is able to use their buying power to force down prices from their suppliers. "Raise prices for others" is the same as "Lower prices for me."

> Then he bought the railroads and made the process even easier.

Similar to how Walmart and now Amazon have their own shipping services as well (Walmart does their own back-haul).

> Or pay a director a few extra million just to stop working with HBO

I'm pretty sure this is already a thing? You can create all sorts of contracts around non-compete.

> We, as both consumers and free marketeers, do not want this behavior.

I want exactly this behavior. Hopefully we can cut out more middle people and have more direct-to-consumer purchasing model.

</comment></comment></comment></comment></comment></comment><comment><USER8> Article seems to be missing what the Justice Department's arguments were about how this merger is anticompetitive and/or violates antitrust law?</comment>


Are Entrepreneurs Pirates? 4min Test for HN by Behavioral Economist Dan Ariely - <AUTHOR> https://danariely.qualtrics.com/SE/?SID=SV_6AsB0KdTTwU4yzy <comment><USER2> I'm sure that my behavior does not reflect my answers on this test. Given the numbers, I calculate expected value and answer rationally. In real life, a) the values and percentages are much less clear and b) even if they weren't I know I don't follow them as rationally.

<comment><USER3> Based on all these "rational actor" responses, I take it none of you purchase insurance?

<comment><USER4> Actual rational actors understand that extreme loss has a disproportionate effect. (In other words, losing $100k is more than 1k as expensive as losing $100 for most of us.)

Naive rationality may be easy to analyse but that just means that the GIGO transfer doesn't cost much.

</comment></comment></comment><comment><USER5> I just went through it, choosing almost exclusively certainties. I'm definitely an entrepreneur, although currently a very struggling one.

I fear the survey is going to be incredibly influenced by income level and current financial security. If you had changed the magnitudes of the numbers, my answers would have been completely different. I can do the math, but I also know that my immediate financial needs are unmet and that my ability to sustain losses is very limited.

<comment><USER6> Without a doubt. For instance, I will always take a $50 loss over any chance of a $1000 loss, because $50 one way or the other barely has in impact on my day, let alone my life. $1000, on the other hand is significant.

If however, the questions had been about $500 vs. $10,000, I'd have to think a bit more carefully.

<comment><USER7> _For instance, I will always take a $50 loss over any chance of a $1000 loss_

That's almost certainly not true. 0.1%?

</comment></comment></comment><comment><USER8> I didn't like this test very much. The financial questions are highly dependent. I guess I was relating to a hypothetical situation rather than the one I'm in now, but I don't think the choices here have anything to do with entrepreneurship; they're all circumstantial.

As all entrepreneurs know, things can fluctuate quickly; there are times when $50 today, little as it is, is more important than the potential of $5000 in the distant future, there are times when you need all the fumes you can get to keep things running. Then there are times when there is a lot of cushion available and $50 today is almost so worthless it's not worth considering -- in that case, of course it's better to take the gamble.

This test has very little to do with entrepreneurship. I ruined it for everyone and just chose random things.

<comment><USER9> Just to ruin your day, choosing random answers doesn't do any damage :)

This is all about statistics, and also about comparing with a control group. I assume the authors have (or can get) baselines for all the questions here. They look like the kind of questions Dan Ariely would work a lot with.

So it doesn't matter that the questions are context dependent. If HNers massively answer one way while the college student population doesn't, you have a difference you can work with. Of course, it's not a definitive answer but it's still valuable information.

As for the results, I'd guess entrepreneurs are more risk averse then average, but also more inclined to chose rewards in the future.

</comment></comment><comment><USER10> I'm really not sure it means much to say that people are "risk-adverse" or not; humans (and monkeys! see <http://www.ted.com/talks/laurie_santos.html>) are BOTH: they prefer to play it safe when they expect a gain, and prefer risk when they expect a loss.

For example, people (in general) prefer $500 now than a 50% chance of $1000, but the _same people_ prefer to take a 50% chance of losing $1000 than losing $500 now with certainty.

Behaviorists call this "irrational" because the two cases are the same: whatever you prefer, you should prefer the same, that is:

\- if you're "risk adverse", you should prefer the certain outcome in both cases

\- if you have a preference for risk, you should take the chance every time.

But it's not what happens; to repeat, the _same individual_ usually prefers the outcome that is certain when the expected outcome is a gain, and usually prefers to take a chance when the expected outcome is a loss, even when those options are mathematically identical.

So, if one wants to show that entrepreneurs are different from ordinary people as regards to risk, they should study at least those two dimensions: gain/loss. And since most people prefer risk when confronted with a possible loss, then entrepreneurs would have to either

\- prefer risk always when confronted with a possible loss

\- prefer risk more often when confronted with a possible gain.

\- - -

If there actually is a difference between "entrepreneurs" and other people, it may be that entrepreneurs have a higher confidence in their own capacities, so that they think that they can influence the future in a good way.

<comment><USER11> That's a rather important point. Loss and gain are not symmetrical in most cases. I actually wonder if there's a study that looks at that in relation to actual wealth - it's easier to risk a loss if it doesn't materially affect you.

HN, anybody know of something like that?

</comment></comment><comment><USER12> I'm sure my choices here have been completely spoiled by all the pop-science books I read, in that my first thought upon each type of question was "Ah, that's from this and this research, where they found out that..." They need an "are you familiar with these types of questions?" question, because both the statistically expected answer and the rational answer were already known to me. I assume this is the case for more entrepreneurs, so I doubt this questionnaire will display a large discrepancy between entrepreneurs and non- entrepreneurs.

All I can say is, Pop-science books are fun, everyone should read more of them.

<comment><USER13> Yeah, I'm afraid I also did the "I'm a rational economic actor" answers,

<comment><USER6> That's funny--I had no trouble figuring out what I'd actually prefer, and even though I'm familiar with the various stories about risk-aversion and such, I think my answers make sense in the context of my income and finances.

</comment></comment></comment><comment><USER14> The questions are flawed because many entrepreneurs have already used up all their risk seeking "slack" and might quite rationally prefer to lose $50 over a 1% chance of losing $1500, since a $50 loss could be dealt with more easily in the context of a ramen budget... while a $1500 loss might destroy the company entirely.

In other words, just because you are in a casino and put all your money on double zero doesn't mean that you should also play russian roulette with a pistol while the roulette wheel is spinning.

</comment><comment><USER15> These tests are flawed because the absolute value of the money we're dealing with is too much of a variable between subjects. $1500 is not much for subject A to lose or gain but it is for subject B.

A test should account for that if we want results to be comparable across subjects.

</comment><comment><USER16> Mr. Ariely's book, Predictably Irrational, is a great read for those who aren't familiar with Behavioral Economics. It contains a lot of solid insights that entrepreneurs should understand, particularly relating to how consumers think.

</comment><comment><USER17> A lot more people will complete it if you give them some idea how long it is. You should use Wufoo.

<comment><AUTHOR> Thanks for the advice, Paul. I've updated the title and first page with more information about length and structure.

I also cannot show the entire survey on one page out of concern that its structure might influence the earlier responses.

</comment></comment><comment><USER18> Lawrence et al (2008), Nature 456, p168-169

<http://dx.doi.org/10.1038/456168a>

Some snippets from the above:

 _"...when subjects were introduced to the hot components of the task, differences were observed. We found that entrepreneurs behaved in a significantly riskier way, betting a greater percentage of their accrued points (63%) than their managerial counterparts (51%)."_

 _"… risk-taking performance in the entrepreneurs was accompanied by elevated scores on personality impulsiveness measures and superior cognitive- flexibility performance. We conclude that entrepreneurs and managers do equally well when asked to perform cold decision-making tasks, but differences emerge in the context of risky or emotional decisions"_

 _"... the entrepreneurs (mean age 51) are comparable to the young adults aged 17–27, whereas the managers (mean age 50.5) resemble their age-appropriate group"_ [with respect to risk tolerance]

 _"There are courses that teach the 'know-how' of entrepreneurship and, within this, teach how to mitigate risk through extensive business planning and market research. Yet given this new evidence, courses teaching the opposite — risk-tolerance in both behaviour and personality — may also be desirable"_

</comment><comment><USER19> Very interesting. I think loss aversion will turn out to be just as prevalent for self-professed entrepreneurs as for the general population, if not more so.

</comment><comment><USER20> I'm working on a paper about entrepreneurial traits and such mdoells. I'm still not sure if an entrepreneur si risk avers. Some scholars argue, he likes risks, because he is quiting his job to get an uncertain "payment". Others argue, entrepreneurs don'tlike risks. If they go for an opportunity, they know the risk quite well and soforth have already evaluated the risk and decided, it is doable. Is their any new thought on this?

i have to agree with the others, I just calculated the value and chose the higher one. Interesting could be the outcome of the last questions where no probability, or intrest rate was given.

Additionally, I think, even if all of us are entrepreneurs (there's still now agreed definition of the term see <http://bit.ly/amULry> ) we decide different. We decide different, depending on our situation or the environment (see Gartner 1989ab 1989b, 1990) we are in. I'm a student my self, perhaps getting $150 now could get me through the month, but one million in two month isn't. So I would take the 150 bucks.

</comment><comment><USER21> The experimental setup isn't great: the HN population almost certainly has an elevated level of education in areas like math and statistics. I don't think you should ever compare subjects who can compute "expected value" with ones who can't. Personally, I don't believe I can give great answers for this, because I'm conscious there's an experiment going on.

<comment><AUTHOR> Here's a question: how does this assertion sync with Arrington's claim that entrepreneurs would choose low-to-negative expected value projects simply for the thrill of gambling, as it were? What's going on here?

<comment><USER22> Hi Samuel,

I think entrepreneurs are not so enthused over gambling as you would believe (gambling as in casinos & slots, or an online questionnaire).

I think that what matters more is the intrinsic value of building something, but I'm not sure about how to measure it..

<comment><USER23> I abhor gambling - risk assumed for Nothing - except entertainment. Shudder.

I'm a serial lifetime Entrepreneur.

</comment></comment></comment></comment><comment><USER24> The magnitude of the numbers matter -- significantly!

I actually tested this out, too: <http://joshua.schachter.org/2008/09/amateur- economist.html>

See also: prospect theory.

</comment><comment><USER25> The questions are so abstract that they don't say much about me other than if I understand standard economics theory.

In real world situations I always have a measure of difficult to quantify control over the situation, which is completely different than the raw random chance gambling the test checks for.

For example, I would never buy a lottery ticket because that is stupid, but I would definitely spend 3 years of my time working obsessively on something that everyone in the world other than my self says has a one in a billion chance of succeeding, because the fact is that I will succeed.

</comment><comment><USER26> It would make more sense to ask things like "the following situation will occur exactly once in your lifetime. How would you decide? -- 100% chance of getting $1M, or 10% chance of getting $7M?"

By making the amounts small, the expectation is that you could run the bet multiple times, in which case it's just an odds game. The real question is what chances do you take that have such volatility, the deviation dwarfs the expectation for a single lifetime.

</comment><comment><USER27> Interesting. I'm not sure if my moves were right mathematically. I basically played as though I had one shot i.e., I pull a lever with a 5% chance once and I either win or get nothing. Similarly for the losing position. However, if I get to play a lot my answers would be completely different. While the expected value of $1000 with a 13% chance and multiple plays is $130, the probable value for a 13% chance and one play is zero dollars.

</comment><comment><USER28> I find that I sometimes choose the start-up (pure or within a larger corp.) because it is fundamentally more interesting to make something new or innovative than to do work that would be financially more certain.

It is not that the financial reward for a big hit wouldn't be exciting, but it certainly isn't the only reason I tend to gravitate toward start-ups or start- up like situations.

</comment><comment><USER29> Creating a successful startup confers more than just financial rewards. There are a myriad of other rewards like recognition and professional freedom that factor into the risk calculation. Depending on how much people value those non-monetary things it could be perfectly rational to take the option with a lower expected monetary value.

</comment><comment><USER30> You should have asked some questions with larger amounts of money at stake, and also asked our current net worth, income, and savings rate. I have enough savings now that my preference for certain outcomes over $2500 intervals is pretty small. If I were living paycheck-to-paycheck I would have given very different answers.

</comment><comment><USER31> It would also be interesting to see this survey conducted using natural frequencies instead of percentages. Humans are notoriously bad at reasoning with percentages.

Compare the following:

"I prefer a 1% chance of losing $1000"

"I prefer a 5% chance of losing $1000"

with this:

"I prefer a 1 in 100 chance of losing $1000"

"I prefer a 1 in 20 chance of losing $1000"

</comment><comment><USER32> Am interested to see the results, and more importantly, the HN discussions about the results!

</comment><comment><USER33> Just went through it and feel, as it seems many here do, that my financial risk-aversion quotient will be no higher than that of the general population.

Does anyone else think that what really makes us entrepreneurs wasn't touched upon by the survey?

<comment><USER34> I agree, feels more of a financial responsibility/risk ...will you prefer the money now or later which depends on the situation

</comment></comment><comment><USER35> As an entrepreneur who needs a quick buck to invest in my startup I feel that this survey is a better gauge of how much one desires money now so as to invest in whatever they're doing.

</comment><comment><USER36> Yeah, the percentages questions are kind of nuts. Would you expect to determine an exact threshold of the percentage odds an entrepreneur is willing to take?

</comment><comment><USER37> Is it just me or was choosing a 5% chance at a bigger reward more interesting/fun than choosing a 13% chance at a bigger reward?

Dunno, maybe I'm just weird.

</comment><comment><USER38> I am very interested to see the result of this one. Completed + tweeted.

</comment><comment><USER39> Isn't this just a survey of whether you know about expected value?</comment>


MacBook Air review (13-inch, mid-2013)  - <AUTHOR> http://www.engadget.com/2013/06/13/macbook-air-review/

<comment><USER2> The fact that it doesn't have retina display killed it for me. It's disappointing.</comment>