Seattle has stopped charging people for personal drug possession - <AUTHOR> https://www.washingtonpost.com/local/public-safety/no-charges-for-personal-drug-possession-seattles-bold-gamble-to-bring-peace-after-the-war-on-drugs/2019/06/11/69a7bb46-7285-11e9-9f06-5fc2ee80027a_story.html <comment><USER3> As someone living there right now the article really doesn't properly cover the discontent in the city.

There is an overwhelming sense that Seattle has done too much to encourage homelessness (particularly with the expansion of policies like this one). "Tent City" has spread so far that it's getting into the suburbs and from a residents perspective it's getting far worse not better. I have routinely seen people shooting up and smoking glass pipes (not marijuana) in broad daylight in the Downtown and Pioneer Square areas. There's shouting, theft, property crime at all hours of the night near my apartment (Though strangely compared to SF I know very few people who have had their cars broken into).

Regardless of the tone of this article, Seattle is not a model to follow, it's a cautionary tale.

<comment><USER4> Could someone please explain what it means to "encourage homelessness"? At a first glance, it looks like a passive aggressive implication that homeless people, if they just tried harder, wouldn't be homeless. Can anyone help me see what I'm missing?

<comment><USER5> We had a post here last week about soda taxes in Philadelphia and it seemed like common sense that by making sugary drinks more expensive, you are encouraging people to consume it less, which results in fewer people drinking it.

We can discuss this with no implication that there's a static amount of soda consumption in the world, or that people want to be obese from consuming it. We understand life is a series of choices, "when to consume sugary drinks" makes up some of them, and that by disincentivizing that choice, people are more likely to choose a different beverage.

Nobody "chooses" homelessness, but like anything else, becoming / staying homeless often is the result of numerous choices, some of which are easier than others for various reasons. When you artificially remove bad consequences from some of those choices, it is not surprising that those choices are made more often.

<comment><USER6> The big difference is, you can simply stop consuming soda drinks if the habit becomes too expensive, but if you are a homeless person, you cannot really just stop being homeless.

<comment><USER5> The claim isn't that you can "just stop being homeless."

> Nobody "chooses" homelessness, but like anything else, becoming / staying > homeless often is the result of numerous choices, some of which are easier > than others for various reasons. When you artificially remove bad > consequences from some of those choices, it is not surprising that those > choices are made more often.

Consuming soda is just one way people can become obese. The problem is obesity. If you are an obese person, you may not really be able to "just stop" being obese, but if policy leads to people choosing healthier beverages, it helps fight obesity.

...and the opposite is true, too. It would not be difficult to imagine what might happen if we subsidized soda until it was free, for example. Except we probably wouldn't have advocates claiming that because nobody wants to be obese, the incentives can't possibly be affecting the increase in soda consumption.

<comment><USER6> I see your point. I agree that we shouldn't incentivize drug consumption. However, the current way of de-incentivizing drug consumption through making it illegal doesn't seem to work well. Luckily, there is more than one way to de-incentivize something like that (look at the soda tax, for example!).

The issue with drugs (as opposed to soda) is that the illegality in itself a lot of times tends to make people homeless by heavily limiting their hosing/employment/etc. perspectives. De-incentivizing drug consumption by heavily taxing them and making the proceeds go towards rehabilitation for addicts and helping those people get on their feet and find employment? I am with you on that. But I cannot really support, in good conscience, punishing drug users to the point where they are pushed to become homeless.

<comment><USER5> > But I cannot really support, in good conscience, punishing drug users to the > point where they are pushed to become homeless.

To a large extent I agree with your point here, but these cities are well beyond simply not punishing drug users.

Mobile safe injection sites, needle exchange programs, cash handouts, unfettered defecation in streets, naloxone handouts, lack of enforcement of petty crimes like vehicle break-ins and theft. There are plenty of policy decisions being made here that affect the choices people make, and none of that even touches on actually enforcing drug laws.

Moral and financial cases can be made for any of the above, and we can debate that, but to me it's really drinking the Kool-Aid to claim these don't encourage homelessness. They certainly make it easier to make bad decisions that can start or keep you on the track of homelessness.

</comment></comment></comment></comment></comment></comment></comment><comment><USER7> I lean heavily towards giving people the freedom to do what they want, but in 'private' and without burdening public life of others. If people want to light up or shoot up, so be it. But I think a community must have ways to discourage or push people out of the public sphere who practice unwelcome and unsocial behavior. The gov't fully feeding, clothing, and sheltering large groups of addicts is impractical and unviable in most/all places.

<comment><USER8> I'm a transgender woman. Applying your thought process seems to me, inevitably, to mean I can't live in society.

I work downtown cooking for a bar (despite my deep involvement in tech as a child/teen and early work programming and some infrastructure stuff, life's challenges haven't enabled me access to significant wealth or appreciable social status). I've found survival, and I deal with drug addicts, mentally ill, the deeply traumatized and abandoned. The biggest thing anyone needs in these circumstances is love and acceptance.

Coming from a place of privilege, your leaning to exclude the suffering from society is wildly antisocial and a leading cause of the rise in "eat the rich" mentalities.

<comment><USER9> Their keyword is unwelcomed behavior, there was no mention of identity. Unless you're behavior is out of control, this doesn't apply.

<comment><USER10> For many, just being transgendered and not attempting to pass as cisgendered is unwelcomed behavior.

I think the issue is the choice of word 'unwelcomed'. Aggressive may be better in capturing (what I assume is) the author's intent, but I would still find it a bit lacking. Some homeless behavior isn't aggressive but is unpleasant enough to cause people to make changes to avoid it. How do you describe such behavior without also describing behavior that a different group may choose to avoid that they really shouldn't be avoiding?

Maybe we can define it as aggressive or unsanitary. Not perfect, but it is the closest I can get without shooting over the intent.

<comment><USER11> However we have to define it so that it can be an issue we can actually address.

</comment></comment></comment></comment></comment><comment><USER12> Seattle is a city that has made a lot of bad decisions. It is suffering from rampant drug abuse, property crime, and gross mismanagement under the current city council, which seems obsessed with following an ideologically-motivated progressive agenda instead of common-sense good governance.

The policy of not enforcing laws, not prosecuting (either certain crimes or certain cohorts of offenders) has caused the city's problems. There are two sets of laws - one is for law-abiding tax-paying residents who are just trying to live their lives without disruption, and the other is for everyone else, who somehow are seen as victims through a twisted social-justice lens, instead of malicious actors. The law-abiding tax-paying residents should not have to give up their public spaces, safety, property, or contribute more taxes in order to accommodate the huge rise of permanently-homeless service-refusing people that want nomadic or drug-centric lifestyles.

Those people do not contribute to society and are making society worse for those who do want to contribute. And yes, there has to be a consequence for that, in order to deter such behavior and lifestyles and not attract an influx of them into the city. This article does not make real the frustration experienced by most residents of Seattle, as it has deteriorated towards SF 2.0 in these last 4 years.

<comment><USER13> In response to the 'dead' reply, you make some points that stick. I'm curious what kind of solution could exist to address the issue(s) you describe. Hoping to hear more thoughts.

</comment></comment><comment><USER14> People are conflating 'drug decriminalization' with other policies. I'm agnostic on other homeless policies, but strongly support decriminalizing possession. You can be for more social services for the homeless, or, more law-and-order and advocate for more cops on the beat to stop car camping, burglary, etc. All while agreeing that spending thousands on incarceration just for possession is a poor use of societal resources.

I'd advocate for a) outlawing public drug _usage_ (the same way alcohol is legal but public consumption is not). And b) an officer on the scene can still confiscate illegal drugs- motivating addicts/homeless to be discreet and low- key. Both of these will help prevent public spaces from becoming a free-for- all, while not wasting valuable money on arresting an addict for the 20th time

<comment><USER8> public alcohol usage is very much legal. we manage it by providing regulations on dispensing/selling alcohol. in my city alcohol may be consumed in most parks and in the majority of municipalities it is legal to serve alcohol in public establishments meeting basic business regulations.

alcohol of course, is a deadly and addictive drug that increases incidences of violence, property crime, and other anti-social behavior.

<comment><USER15> I gotta ask, which city or even country? The United States has extensive and varied laws on public consumption and intoxication. Places like Las Vegas are the exception, not the norm.

<comment><USER8> denver

but most places do have bars and serve alcohol in restaurants, which counts as public consumption of alcohol

<comment><USER16> They let you walk around with an open beer in denver? They don't let you smoke weed openly on the sidewalk. The places you listed are all examples of private consumption of alcohol , and those places have liquor licenses as well. Even on Bourbon Street, the heart of hedonism, there are rules like your container can't be glass.

<comment><USER8> >in my city alcohol may be consumed in most parks

this is true

and it is my experience that most places consider restaurants and such a place where a member of the public can be charged with "public intoxication," though to my knowledge that's not a thing that's punished here

</comment></comment></comment></comment></comment></comment><comment><USER17> Just finished watching Seattle is Dying. I don't understand why so many American cities suffer so much from drug problems. Everywhere in the world you will find homeless people, but outside of the US I haven't seen anywhere so many drug addicts. Is it all those depressing suburbs with shitty education and people who are bored to death with their life? Is it lack of support from family? I don't get it.

I feel that's the root of the problem and where the US should invest heavily.

<comment><USER18> The US drug abuse problem is multiple things colliding over many decades.

Extraordinary wealth & extremely high disposable incomes (very large profit magnet), by far the largest pharma economy, a pharmaceutical culture you won't find anywhere else, a many decades long history of general persecution of drug addicts, and a healthcare system that doesn't take good care of the homeless or drug addicts.

That covers both the prescription abuse and blackmarket issues.

The wealth & income in the system acts as a huge magnet. If you're going to sell drugs somewhere (legal or illegal), you want to do it in the US. The US has nearly double the median personal disposable income of the EU, under one big roof. The culture encourages a drug-solution approach to everything. The doctors, nurses, admin, hospitals, pharma companies and healthcare system overall have been _very_ happy accomplices, feeding the problem for decades to great personal profit. A lot of prescription writers should be in prison for playing assist in murdering tens of thousands of Americans. The persecution of drug addicts makes everything worse on the back-end once a person has become an addict; it pushes them away from treatment, it isolates them from society. The poorly constructed healthcare safety net in combination with the cultural & legal / political persecution, then finishes them off, leaving them little to no proper safe recourse or way back out - ending far too often in death.

<comment><USER17> These make sense. I've experienced it myself in the US when I felt the medical stuff is pushing me towards the most money making for them option than the option that made the most sense for me.

</comment></comment></comment><comment><USER19> What a depressing thread.

In one corner, we have people that are absolutely exhausted of the current state of affairs. The trash, the needles in parks, human feces, the tents ... etc. They want _someone_ to do _something_ about it, but it's not clear at all what that _something_ really is or who would do it. If it were clear, we wouldn't be arguing about it. There are real costs to a draconian reversion to hardcore enforcement. People will get hurt, unnecessarily.

In the other, we have people that seem completely convinced that enforcing any kind of norms against anti-social behavior - indeed, outright dangerous behavior - is simply an extension of the War on Drugs, and further criminalizes marginalized people by cycling them through a prison system that seems equally uninterested in actually solving the problem. And there are real costs here, too. People are getting hurt continually by repeat offenders, and by the other social costs of living where parts of the city are unclean or unsafe, or both.

I've lived in Seattle since 2011 (with a 29 month cumulative absence for a deployment and then for school), and I think it's just absolutely nuts to think that decriminalizing usage has done anything but make this problem worse. I understand the impulse behind it. I really do. But we can't keep trying to convince ourselves that this is "working", unless "working" is really "condition people to think that this is the new norm". Obviously, I guess I sit in the first corner. There's no real middle ground between these two cohorts, as far as I can tell. One group sees the other's concerns as reactionary or uncompassionate, and the other see's the first group's compassion as naive and even a deep enabling of the problem.

For me, I don't want to live in a city like this. That's maybe the only middle ground that exists between the two groups - neither want this. But my sense is that we're at a true impasse here, and that, and I'm just being realistic given the political arrangement here in Seattle, we're going to keep doing "more of this", whatever "this" is. The second camp has clearly captured city leadership, and decriminalization, lax or no enforcement of existing laws, and a general apathy (or maybe it's faith) about the situation will guide policy. We'll become the next SF, and then wake up one day wondering "how did this happen"?

<comment><USER20> > They want someone to do something about it, but it's not clear at all what > that something really is or who would do it

> it's just absolutely nuts to think that decriminalizing usage has done > anything but make this problem worse

From reading these two statements and others in this thread, it's hard for me to see how you're the one arguing _against_ criminalizing people, and yet that's how you're describing yourself. What does "enforcing norms against anti-social behavior" mean in this context, if not putting people in prison or issuing citations (which eventually lead to prison)? I'm genuinely unsure if there's some third option I'm not thinking of.

The thesis seems to be that if you just do that enough, those people will go somewhere else or decide to stop being homeless. The problem is, _that 's what we used to do_ and _it didn 't work_. Those people are from here, and they're not homeless by choice. Even if some do move on, they'll just end up homeless somewhere else.

The frustrating thing is that there is a solution to this, which is called housing first. The basic idea is that you give people housing they can live in, and then provide services like addiction counseling and job training to get them into a better place. But you start with the housing, because without stability in your life, it's hard to tackle challenges like this, and not having housing results in all kinds of other social problems. The problem with housing first of course is that it's expensive, which requires taxation.

To me the real problem is that the council has insisted on sticking to ineffective half-measures. We had the beginnings of a tax for affordable housing last year, although it was still too small, but the council backed down when Amazon and other large companies raised hell. What this ended up doing is making it clear that the council has no solution to this that they're willing to pursue, which has lead to this impasse.

<comment><USER19> I guess I don't really disagree with what you said.

>What does "enforcing norms against anti-social behavior" mean in this context, if not putting people in prison or issuing citations (which eventually lead to prison)?

Not being okay with it, which implies that we'd so something about it. Which does mean things like citations, at a minimum. Right now it's totally normal.

>The frustrating thing is that there is a solution to this, which is called housing first...

Broadly, I agree with this paragraph. I think we should take the billion we spend in this city on homelessness (not sure that stat is actually true since I've never seen the line item in the budget but people say it a lot) and build these places ... and then make them mandatory, or at least semi-mandatory. That might sound extreme, but frankly many of these people clearly don't have agency anymore given their addiction and they've become a danger to themselves and others. So that's my "out there" suggestion. Build the housing, fund the medical and job-training services, and deliberately - not passively - <USER2> people into them.

Of course, this presupposes that lack of housing is the first incident problem. Maybe it is, maybe drug use is in some cases. I don't particularly care for drug use, so my personal preference is that we repeal the decriminalization rules and reverse some of the cultural acceptance that's taken hold here of this behavior. We've probably missed the boat on that one, since most here seem to take the libertarian approach that what someone does with their body is "their business", despite the fact that it often becomes someone else's very quickly.

>...backed down when Amazon and other large companies raised hell.

If the city council wanted to just tax Amazon then they could've done that, but instead that cast such a wide net that medium sized low-margin businesses that don't have enormous capital behind them were wrapped up in it too - so I understand why they backed down. There wasn't any real self reflection from them after that happened, so I tend to agree that we're stuck in an infinite loop of "more of this".

<comment><USER21> > Of course, this presupposes that lack of housing is the first incident > problem.

Not at all. Even if a person's drug abuse is what led them to lose their job and housing, the drug abuse can't be the issue you fix first. The lack of housing makes solving any other "first incident problem" massively more difficult.

> I don't particularly care for drug use, so my personal preference is that we > repeal the decriminalization rules and reverse some of the cultural > acceptance that's taken hold here of this behavior.

The problem is that criminalization of drug use and homelessness has absolutely failed to have a positive impact on either issue and quite arguably has made both problems worse.

</comment></comment></comment></comment><comment><USER22> These experiments tend to work at reducing secondary crimes etc.

However, they also are usually unpopular at the same time, leading to a backlash and a drug clampdown again. It's the drug policy circle of life.

<comment><USER23> These conditions are exactly what prompted the drug war's start in the first place. Neighborhoods were tired of the addicts and petty (and sometimes not so petty) crime which plagued their day-to-day lives.

I wouldn't be shocked if 10 years from now, these coastal cities are leading the charge on a tough on drugs reversal.

<comment><USER24> Well, not quite. The reason why the drug wars got started wasn't because of addicts or petty crimes. It was a form of class warfare because they wanted the dirty poors and minorities to stop using their poor drugs.

The history behind the War on Drugs is very explicitly a one divided on racial grounds and a cursory look at things like the legality of marijuana or mandatory minimums tells the full tale.

<comment><USER23> If this were true, how did the drug laws passed in the 70's hang around for so long? If there was no reason but racism, why didn't Obama, who in his first term had super majorities in Congress, simply wipe them away? You take away the agency and voices of people who live in crime ridden poor neighborhoods which suffer the consequences of high levels of addiction.

In the capital of my state, in just the last few weeks, we've had people high on pcp attack cops (after strangling his girlfriend), shoot at traffic, and pick up a child out of a stroller and slam them on the ground, all unprovoked. Those victims aren't racist in wanting to not have to deal with people high out of their minds.

<comment><USER24> You're essentially asking why Obama, a fairly centrist liberal by many accounts, didn't end racism forever.

There's a very good reason why black people are disproportionately arrested for drug-related crimes, especially Marijuana, despite having similar usage rates as others.

There's also the fact that members of the Nixon administration outright admitted this fact.

<comment><USER23> The reason Obama didn't do anything isn't that he's not that worked up over racism, it's just not as simple as waving your hand and saying everything would be great if it only for those racist laws. Drugs reduce inhibitions. People with reduced inhibitions do crazy things, often hurting other people. Families are often willing to support draconian measures so that their kids aren't endangered by some random stranger in some drug induced state of manic paranoia.

Victims of drug crime should have a voice too.

</comment></comment></comment></comment></comment></comment><comment><USER25> No matter the merits of the case to be made for this specific policy, the state of Seattle isn't one of the highlights.

To clarify: there are all sorts of factors at play in Seattle's troubles, my point is that if you believe a the policy "we should stop charging people for personal drug use", "just look at Seattle!" isn't going to be convincing to most of the country.

</comment><comment><USER26> All those comments to the tune of "those bums are bums because they are addicted" ... they make me so sad.

Can anyone not see it's the other way around? Really?</comment>


Claude Shannon: The Bit Player - <AUTHOR> https://thebitplayer.com/ <comment><USER2> Shannon was certainly one of the great scientists. His paper "The Mathematical Theory of Communication" [1] is on the one hand accessible but profound. His derivation of entropy and the the limits of communication over a noisy channel are almost simple but I believe this is true only because of hindsight and is, in my opinion, the hallmark of a deep idea.

We've only recently been able to get close to the Shannon limit with Turbo Codes [2] and Low Parity Density Checks (LPDC) [3].

For anyone interested, I wrote a short post on deriving entropy and channel capacity [4].

[1] [http://math.harvard.edu/~ctm/home/text/others/shannon/entrop...](http://math.harvard.edu/~ctm/home/text/others/shannon/entropy/entropy.pdf)

[2] [https://en.wikipedia.org/wiki/Turbo_code](https://en.wikipedia.org/wiki/Turbo_code)

[3] [https://en.wikipedia.org/wiki/Low-density_parity- check_code](https://en.wikipedia.org/wiki/Low-density_parity-check_code)

[4] [https://mechaelephant.com/dev/Shannon- Entropy/](https://mechaelephant.com/dev/Shannon-Entropy/)

</comment><comment><USER3> The Idea Factory was a pretty enlightening book. I never realized how important Bell Labs was in our technological history. They purposely sought out the best minds and gave them freedom to find the next great tech.

<comment> cbm-vic-20 Now we deport them when their visa expires.

<comment><USER4> I'm pretty sure Visas expired back then too..

<comment><USER5> And when the prospect of losing the cold war is breathing down your neck you go right ahead and renew visas of those making an important contribution..?

</comment></comment></comment></comment><comment><USER6> Haven't read this yet but it's on my list:

[https://www.amazon.com/Mind-Play-Shannon-Invented- Informatio...](https://www.amazon.com/Mind-Play-Shannon-Invented- Information/dp/1476766681)

This is also a good read:

[http://nautil.us/issue/50/emergence/claude-shannon-the- las-v...](http://nautil.us/issue/50/emergence/claude-shannon-the-las-vegas- cheat)

<comment><USER7> It's a good book. The Nautilus article is an excerpt from it.

</comment></comment><comment><USER8> Why do all video players these days start with volume on full blast? Even worse, on this player i cant find the volume button.

<comment><USER9> Had to open the link out of curiosity just to confirm this. It's a Vimeo embed, but it doesn't show a volume button! Pressing [?] shows the up/down arrow keys control volume, but I can't confirm it does because my computer doesn't have sound.

</comment></comment><comment><USER10> How can someone be so good at the age of 21? It depresses me.

<comment><USER11> That early 1900's generation was overflowing with wunderkinds, Fermi, Feynman, Pauli

<comment><USER10> Why don't we have that anymore?</comment></comment></comment>


NHTSA's full investigation into Tesla's Autopilot shows 40% crash rate reduction - <AUTHOR> https://techcrunch.com/2017/01/19/nhtsas-full-final-investigation-into-teslas-autopilot-shows-40-crash-rate-reduction/?ncid=rss <comment><USER2> It's interesting how vague this is. There's an NTSB investigation still pending into a specific Tesla crash.[1] The goals are different. NHTSA asks "do we need to do a recall?" NTSB asks "exactly what, in detail, happened here?" NTSB mostly does air crashes, but occasionally they do an auto crash with unusual properties. Here's the NTSB report for the Midland, TX crash between a train and a parade float.[2] That has detailed measurements of everything. They even brought in a train and a truck to reconstruct the accident positions.

It took a combination of problems to cause that crash. The police lieutenant who had informed the railroad of the parade in previous years had retired, and his replacement didn't do it. The police marshalling the parade let it go through red lights. They were unaware that the traffic light near the railroad crossing was tied in to the crossing gates and signals. That's done to clear traffic from the tracks when a train is approaching before the gates go down. So ignoring the traffic signal took away 10 seconds of warning time. The driver thought the police had taken care of safety issues and was looking backwards at the trailer he was pulling, not sideways along the track. People at the parade were using air horns which sounded like a train horn, so the driver didn't notice the real train horn. That's what an NTSB investigation digs up. Those are worth reading to see how to analyze a failure.

[1] [https://www.ntsb.gov/investigations/AccidentReports/Pages/HW...](https://www.ntsb.gov/investigations/AccidentReports/Pages/HWY16FH018-preliminary.aspx)

[2] [https://www.ntsb.gov/investigations/AccidentReports/Pages/HA...](https://www.ntsb.gov/investigations/AccidentReports/Pages/HAR1302.aspx)

<comment><USER3> The only thing that matters is "NHTSA notes that crash rates involving Tesla cars have dropped by almost 40 percent since the wide introduction of Autopilot"

Even if autopilot was faulty in some way, if more people were living than dying - does it matter?

<comment><USER4> Well, yeah. Imagine there's heart surgery which has only 20% success rate. So every time 100 people go in for that surgery, only 20 survive.

Now, someone makes a robot that has 100% success rate, but every 100 operations, it has a glitch in the sofware, where it stabs and kills the patient instead. It has been calculated that on average, using the robot only kills 1-2 out of 100 people going in for surgery, compared to the old method of 80 people out of 100. The robot is clearly 80 times better than manual procedure, so why not keep using it?

The answer seems to be - because robot killing people is not an unavoidable outcome. It can be fixed. It's a software problem, a mistake that costs someone their lives. Similarily, an auto-driving Tesla may be killing less people on average than manual drivers, but that doesn't mean that any software problems that lead to it don't matter.

<comment> loup-vaillant Step 1: _don 't_ recall the robot surgeon. While it does have a fatal bug, recalling eat would kill 79% more patients. Oops.

Step 2: Correct the bug, so the robot stops killing patients.

The Tesla autopilot may be in a similar situation. Even if there is a number of fatality inducing bugs, disabling it would be even worse. That said, 40% crash reduction is not enough. I want to see 75%, 90%, and more.

<comment><USER5> You are omitting the PR angle: "I DON'T CARE THAT FAR MORE PEOPLE WOULD DIE OTHERWISE - BAN KILLER ROBOTS NOW!!!!"

<comment> loup-vaillant That one is easily dealt with: "Our robot surgeon reduces the fatality rate by 98.5%. Our study of the remaining fatalities suggest we can reduce them further. We hope to reach near-zero fatality rate within the year.

Don't even speak of the bug. Just state what matters: this stuff is better than what we had before, and it can (and will) be even better. This may prevent talks about killer robots.

</comment></comment></comment></comment></comment></comment><comment><USER6> After looking at the report it looks like Tesla ran into the same issue we did in the 2007 DARPA Urban Challenge. The trailer was higher than the front facing sensors. We and most other teams had all assumed 'Ground Based Obstacles' meant that any obstacles on the test track would make contact with the ground in the lane of travel. DARPA decided to put a railroad bar across the street and expected cars to back up and do a U-Turn when they encountered it. The bar was too high off the ground for our forward LIDAR to see it so we collided with the bar at nearly full speed.[1] The sad part about this is that when we were drinking after dropping out of the challenge our team leader said something along the lines of 'At least we know no one will ever die now from the mistake we just made.'

[1] [https://www.wired.com/2007/10/safety-last- for/](https://www.wired.com/2007/10/safety-last-for/)

<comment><USER7> Predictions like that only work out if the lesson is sufficiently broadcast. Clearly, since this is still newsworthy here, that is not the case. (However this back channel is helping.)

<comment><USER8> If there isn't some compilation or review article along the lines of "all serious failure modes encountered in autonomous vehicles since 2005-ish," there should be.

<comment><USER9> That's an excellent idea and should be managed centrally (by the NHTSA or similar). Basically a communal regression test suite that all self-driving vehicles have to pass.

</comment></comment></comment></comment><comment><USER10> Tesla comes off extremely well in this report. For one thing, the 40% statistic cited in the headline appears to be well supported by the NHTSA report (section 5.4) and actually manages to frame the incident in a very positive light:

 _ODI analyzed mileage and airbag deployment data supplied by Tesla for all MY 2014 through 2016 Model S and 2016 Model X vehicles equipped with the Autopilot Technology Package, either installed in the vehicle when sold or through an OTA update, to calculate crash rates by miles travelled prior to and after Autopilot installation. Figure 11 shows the rates calculated by ODI for airbag deployment crashes in the subject Tesla vehicles before and after Autosteer installation. The data show that the Tesla vehicles crash rate dropped by almost 40 percent after Autosteer installation._

I had hoped to see more information about this specific incident. For instance, any data on whether the driver had his hands on the wheel, what steps the car had taken to prompt his attention, etc. But that doesn't seem to be included.

<comment><USER11> I really would like to know the absolute numbers for this reduction. It's really questionable if this would hold up with millions of Teslas on the road in the hands of less wealthy(probably better educated) drivers.

<comment><USER12> > wealthy (probably better educated) drivers.

You mean drivers like the ones behind the wheel of all the BMWs and Audis that cut me off with no turn signals, speed, make aggressive lane changes, tailgate, and generally act like giant douches because a simple traffic ticket is nothing to their pocketbook while their time == money?

Those people are going to be a hell of a lot safer behind the wheel of an autonomous (level 4) vehicle where they can be on the phone and their laptop as the vehicle obeys the speed limits and safe following distance.

<comment><USER13> Anecdotally I have a lot more near-incidents with 4WDs and little hatchback getabouts. In my experience the 4WDs have been distracted or drifting outside their lane, and the little getabouts have been tailgating and driving aggressively. Having "P" plates (1) also raises the chances _massively_.

Could just be the numbers of those kinds of cars in my area though.

Generally I feel that a douche can drive any type of car, and I try to drive in fear like everyone else on the road is a drunk prison escapee.

(1) provisional licence holders - new drivers (and also people who have lost their licence) have to display "P" plates for a year here (Australia).

<comment><USER7> I find that drivers who fail to keep right except when passing are the leading cause of 'aggressive' and 'unusual' passing conditions.

<comment><USER12> Because the aggressive drivers behind them aren't responsible for their own actions in rage passing left lane hogs?

Somehow I manage to consistently undertake people who are going slow in the left lane safely. Its not that hard.

</comment></comment></comment></comment></comment></comment><comment><USER14> For those who don't want to signup to Scribd just to download a publicly available PDF: [https://static.nhtsa.gov/odi/inv/2016/INCLA- PE16007-7876.PDF](https://static.nhtsa.gov/odi/inv/2016/INCLA- PE16007-7876.PDF)

<comment><USER15> Thank you! I'm completely unwilling to register for that site just to download a pdf

</comment></comment><comment><USER16> Oh, hey, will you look at that.

The imperfect, incomplete, beta, level 2 self driving cars that were supposed to be the "dangerous" area of self driving are ALREADY better than human drivers.

Can we stop the politics and deploy all the real self driving cars to the road immediately, since the government has proven that even the shitty variety is safer than humans?

<comment><USER17> Level 3 is the real danger area. That's the level where the driver is able to do other things, but must be prepared to retake control at any time. Those two ideas are basically contradictory: if you're not already involved with driving, it takes too long to get back into it to do anything useful.

Tesla's system is level 2, meaning that the driver must (as in, is supposed to) remain engaged and aware of the driving task at all times, although the car will handle common cases on its own.

I believe the plan for everybody is to go straight from level 2 to level 4, since it looks like level 3 is just not going to work.

In any case, we can't stop the politics and deploy all the real self driving cars to the road immediately, because there aren't any real self driving cars to deploy yet. The technology is advancing extremely quickly and it's getting close, but politics is _not_ the only obstacle.

If and when we have a real, production-worthy self-driving system that's being blocked by politics for no good reason, we can revisit this. I get the sense that, at least in most places, the politics will be pretty easy once the technology gets there. Getting a lot fewer registered voters killed has a way of swaying legislators. Especially in the US, where it's a state-by-state decision, a few states will want to get a jump on it and then the rest will face immense pressure to follow.

<comment><USER18> There is zero chance I'd stay awake behind the wheel of a level 2 or 3 vehicle.

<comment><USER19> I'm in the same boat as you here. Level 2 and 3 are unsafe for me as an individual. When I drive, actively focusing on the road and driving keeps me awake. When I'm a passenger, the lack of mental concentration plus the gentle rocking motion of a moving car knocks me out within ten minutes.

The current Tesla autopilot is obviously working well for many people, but for myself I have to wait until level 4. Anything more hands on than that is inherently unsafe because of my habits.

<comment><USER20> What kind of "CARTCHA" challenges and games might be fun to play, to prove to your car that you were paying attention to the road and traffic, yet not distract you from being ready to take over driving?

Computer vision and speech recognition could be useful for proving the driver's awake, as well as driving the car itself.

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

<comment><USER21> The challenge of driving the car manually, without any hyped autopilot.

<comment><USER22> This. There's nothing else because any other task requires diverting mental focus away from the act of constantly assessing the changing environment around your car. That by definition leads to slower reaction times.

</comment></comment></comment></comment></comment></comment></comment><comment><USER23> The 40% number isn't very informative. The report has multiple notes about it:

 _ODI analyzed data from crashes of Tesla Model S and Model X vehicles involving airbag deployments that occurred while operating in, or within 15 seconds of transitioning from, Autopilot mode. Some crashes involved impacts from other vehicles striking the Tesla from various directions with little to no warning to the Tesla driver._

 _ODI analyzed mileage and airbag deployment data supplied by Tesla for all MY 2014 through 2016 Model S and 2016 Model X vehicles equipped with the Autopilot Technology Package, either installed in the vehicle when sold or through an OTA update, to calculate crash rates by miles travelled prior to[21] and after Autopilot installation.[22] Figure 11 shows the rates calculated by ODI for airbag deployment crashes in the subject Tesla vehicles before and after Autosteer installation. The data show that the Tesla vehicles crash rate dropped by almost 40 percent after Autosteer installation._

 _21 Approximately one-third of the subject vehicles accumulated mileage prior to Autopilot installation._

 _22 The crash rates are for all miles travelled before and after Autopilot installation and are not limited to actual Autopilot use._

So the actual rates of crashes for Teslas using Autopilot vs Teslas not using Autopilot aren't reported.

<comment><USER24> Reading it, I think it is essentially a 'before October 2015' vs 'after October 2015' comparison of overall accident rates, given the caveats there. So the -40% here should be a lower bound, since it includes a time period with 0% Autopilot usage (before October 2015) and a time period with an unknown but <100% Autopilot usage (after October 2015). If people after October 2015 used Autopilot for 50% of their mileage, then you'd expect the true effect of Autopilot to be more like -80%.

This strikes me as suspiciously high: what fraction of airbag-worth accidents are supposed to happen on the highways where one can use Autopilot at all? So maybe there's some other trend going on which is driving this decrease.

<comment><USER25> This accident reduction is driven not by the auto-driving part of the package, but the emergency response part. The autonomous breaking and evasive steering that occurs when an accident is imminent is what is preventing accidents.

<comment><USER26> Also, airbag activation isn't a perfect proxy for accident rate. Passenger safety is only a subset of vehicle safety.

</comment></comment></comment></comment><comment><USER27> Waiting for the headline: "Human Fails to Prevent Accident, Outraged Public Calls for Banning of all Human Drivers"

The obsession with perfection in self-driving cars is misplaced, they just need to be demonstrably better than humans.

This is obviously the future.

<comment><USER22> At the very least in a legal standpoint that's not true, because with a human driver it's far easier to define fault (which in turn allows for the issue to be resolved) than if two autopilots happen to collide. Who pays for what then?

From a safety point of view, I'm more inclined to agree however I'm not entirely convinced that we've passed the novelty stage of it yet where drivers will remain vigilant because it's a new and exciting feature and that mentally primes them to keep focused. It wouldn't suprise me that as it becomes more mainstream, drivers begin to be less vigilant on staying focused as society as a whole begins to trust it more. That's when everything could go bad.

Nevertheless, you're absolutely right that this is the future no matter what so we need to design it as best we can to resolve all of the issues it may give rise to.

<comment><USER28> There's all sorts of cases in real life now when defining fault is not at all easy. Children and animals are two examples of 'autonomous' individuals who's liability _may_ lie with another party (parent/owner), buy also may not, depending on the circumstances.

Additionally, who's at 'fault' really doesn't matter when in most cases the damages are fully outsourced to insurance providers. In the case of autonomous driving, this insurance burden is shifted up a level to the automaker, but this cost will be passed on to the car's owner in some way, either in the cost of the car or a subscription to autonomous driving.

However if autonomous driving is safer than non-autonomous driving, premiums will go down, probably dramatically. Insurance companies can much more easily monitor the quality of autonomous driving for various automakers / cars either by the testing specification that they meet or the real-world statistics. Are autonomous Tesla's in less accidents than autonomous Volvo's? Cheaper premiums for Tesla.

This is exactly the situation you want to be in. Premiums for individuals are blunt instrument... it's hard to change many individuals behavior, the rewards may be low for the individual (save $3 on your premium!), and the penalties can be pretty random (you sped that one time so you're a high risk driver... or are there just more police in your city?). It's way better to incentivize at a higher level, like the automaker.

The only case where automakers would truly be at risk is something they _should_ control, and that is if they pulled a VW and committed fraud on their autonomous driving tests, or were negligent in overlooking scenarios or providing updates.

</comment></comment></comment><comment><USER29> Can anyone who is in the industry comment on how Autopilot performs in poor weather (ie. flash floods, thunderstorms, snowstorms etc...)

All I can find from the article about weather was in section 3.1:

> The manual includes several additional warnings related to system > limitations, use near pedestrians and cyclists, and use on winding roads > with sharp curves or with slippery surfaces or poor weather conditions. The > system does not prevent operation on any road types.

<comment><USER30> Not sure about Tesla's, but many others are completely disabled or say specifically not to use them in poor weather conditions.

You have to look at what they're using for this, it's cameras with computer vision and radar. Radar has reflection problems like all hell at ground level and computer vision using cameras is generally piss poor (hence why you see videos of the Tesla hitting reflective objects).

It's a miracle that they can do this well using it IMO, even without adverse weather.

</comment></comment><comment><USER31> This is really good news. A major worry with driverless cars has been that companies would be harshly punished for accidents, even if there was a dramatic reduction in crashes overall.

<comment><USER32> They managed to weasel themselves out of similar problem when they rebranded vehicular manaslaughter to jaywalking shifting the blame to the victim. I'm sure there's no problem here that a bit of marketing and societal engineering can't solve.

</comment></comment><comment><USER33> I think there's sometimes a lot of marketing and hand waving in this type of argument "crashes go down with autopilot". Most car accidents are caused by drunk or old people, and they drag the average up. if you tell me a Tesla autopilot beats a drunk guy it won't surprise anyone. Now as a non-drunk, young(ish) driver but experienced and careful, my statistics don't look anything like the average, they look at lot better. You have to convince this demographic, not beat the averages otherwise it's not rational for me to buy the feature. I'm guessing this goal post is a lot harder.

<comment><USER34> I'm confused. You think young(ish) people need to be convinced to buy semi- autonomous vehicles? If they can afford it, why wouldn't they buy it? People love things that make their life more convenient.

In my experience, its the older people that are somehow scared of the concept of a self-driving car and would need to be convinced.

<comment><USER33> Because of security. I wouldn't buy an autonomous car that has an accident rate worse than my demographic. A car that has an accident rate better than average is not good enough. I hope that explains my point.

</comment></comment></comment><comment><USER35> For your reference, a level 4 automated car will look something like this:

[https://www.youtube.com/watch?v=jhUX8qWFGc4](https://www.youtube.com/watch?v=jhUX8qWFGc4)

Imagine you are too fucked up to drive. Your car will be able to pick you up. Do you need Pepto Bismol too? Your car will pick it up from a drive through billed through your license plate. I'd give roughly 15~20 years for this to take place.

</comment><comment><USER36> So I'm far less likely to crash if I use this, and I have something to blame if I do. Everybody wins! (Except the engineers).

</comment><comment><USER37> The truck was visible for at least 7 seconds prior to the crash in the full report - another article here:

[http://arstechnica.com/cars/2017/01/after-fatal-tesla- crash-...](http://arstechnica.com/cars/2017/01/after-fatal-tesla-crash-probe- us-regulators-conclude-theres-no-need-for-recall/)

Strangely enough, giving more people autopilot would probably be better than letting people drive. I think Tesla's picked the right time to enable it, since the cross-over point between autopilots being better than humans in general use cases has been reached.

Call it a beta if you want, but it's a pretty damn promising beta.

</comment><comment><USER38> I don't always like Gladwell, but his piece on the Ford Pinto and the NHTSA philosophy towards auto safety more generally is quite worth the read [1]. I hadn't considered the intersection of this and self-driving car tech, but I wonder if NHTSA will basically take the position that as long as self-driving tech saves lives overall, a few "bugs" where the car kills the driver are an acceptable trade-off.

[1] [http://www.newyorker.com/magazine/2015/05/04/the- engineers-l...](http://www.newyorker.com/magazine/2015/05/04/the-engineers- lament)

</comment><comment><USER39> 40% figure is meaningless unless the absolute numbers are reported. How do we know if this difference is statistically significant ?

<comment><USER40> was 1.3 crashes / million miles. Is now 0.8 crashes / million miles.

Tesla's have driven >= 3 billion miles

<comment><USER41> So 3000X the difference of 0.5, or 1500 crashes avoided.

:O

</comment></comment></comment><comment><USER42> What other car company can even recover the airbag deployment rate per mile?

<comment><USER43> I believe that GM's OnStar also collects that data.

</comment></comment><comment><USER44> I only want to use open-source code for something that my life depends on. That way it can be open to any one to inspect some can independently determine if the code is behaving as desired.

</comment><comment><USER45> That is a pretty remarkable report. It essentially holds Tesla up as an exemplar of the standard other car makers will be expected to achieve.

</comment><comment><USER46> This means that autopilot must be engaged at least 40% of the time (Amdahl's law!). Tesla owners, is that realistic?

</comment><comment><USER47> Does anybody know what the "Population" field indicates at the top of the report?

</comment><comment><USER48> Impressive. 2/5 reduction is a lot of lives saved.

</comment><comment><USER22> I've railed on about the safety issues of autopilot before and how I'm not entirely comfortable with the pace they've developed compared to the considerations of human-machine interfaces and driver attentiveness, particularly given my (moderate) exposure to these sort of problems in other industries. Thus I'm particularly interested in that section of the article.

What I found interesting is that figure 10 shows that as you jack up the independence of the machine, the level of driver distraction accordingly increases. Adaptave Cruise Control (ACC) shows a significantly higher percentage of shorter-duration off-road glances than Limited-Ability Autonomous Driving Systems (LAADS). Additionally, countermeasures help to alleviate _some_ but not _all_ of that increase in distraction. Importantly, this is coupled with the point that the duration in which drivers have to react to most impending is under 3 seconds. This may seem obvious but it's a critical set of data to help objectively demonstrate the risks involved with losing or even reducing alertness.

It goes on to say that Tesla has addressed the risks of mode confusion, distraction, etc. and has implemented solutions to address this unreasonable risk, which they in turn define as abuse that is reasonably forseeable. In this, they're talking about the reasonably forseeable risk of eg: the driver not understanding if they're in autopilot or not. It goes on to mention that Tesla has also changed its driver monitoring strategy to promote driver attention, which I take to mean detecting hands on the steering wheel.

Either way, Telsa's main approach to dealing with driver alertness by testing for hands on the steering wheel. My concern is that this doesn't consider the alertness of the driver to their surroundings, particularly other vehicles that may be approaching them or the process of anticipating hazards (approaching an intersecion where there's a blind corner and adjusting focus to pay more attention to what may come from it, for example). I don't see how Tesla's countermeasures address this.

The physical act of manually driving causes drivers to maintain alertness not only to where they're going, but also the situational alertness of what's around their vehicle. Specifically, it's the process of _random_ actions that requires an taking input, making a decision and executing the appropriate action that maintains this alertness. If the driver isn't having to make those random decisions and take action then their alertness drops. Autopilot, even with hands on the wheel, eliminates much of that random decision-making and reacting.

When you drive, you mentally note the vehicle over your shoulder that is in the lane next to you, and subconsciously consider that they may do something insane. You consider those blind corners as you approach them and that vehicles may spontaneously appear out from them. You see a truck on the road which is approaching a bend and give it a wider berth because its centre throw may cause it to cut the corner into your lane slightly. These are all tasks that you do, that you may not do as well or at all when autopilot is steering, because you are not as engaged with the driving process.

Critically, I don't see how ensuring hands are on the steering wheel causes these alertness tasks to continue as frequently as manual steering. The driver may be in the physical location to quickly take over, but they may not be in the _mental_ location to do so. This is the major issue I have with the rapid autopilot development based on my experience in related areas where maintaining situational alertness proved to be very difficult when the person was engaged with only a limited scope of requirements to prove their conscious presence.

I feel like the report doesn't really drill in to this as much as it needs to. It begins to touch on it around Figure 10 but sort of hand-waves it away saying 'Telsa considered it discharged their responsibility to make sure drivers stay focused by implementing countermeasures', but I believe it's more nuanced than that. It investigates the extent to which Tesla's system is good at ensuring drivers are physically present (that is, their hands aren't on the passenger seat making breakfast) but it doesn't really look at the _mental_ presence that delivers situational alertness.

That mental alertness is the major sticking point for me. I don't really have a solution beyond "drive manually" which isn't reasonable, because this technology is here to stay and will continue to grow, but it's why I've always been bearish about the rapid pace of rollout of these driverless technologies, particuarly when advertised as 'beta'. As I've said before, no amount of disclaimer and 'hey, you _should_ do this' really changes how drivers behave once the equipment is placed in their hands.

</comment><comment><USER49> Great. There is no doubt that driver assists cut down on crashes. But what tesla has on the road is far from a total eyes-closed autopilot. That is an inflection point with this tech that nobody has dared to test on the public road. I remain unconvinced pending those trials.

Also, still havent seen any autodrive handle off-road driving such as boarding a carferry or navigate a construction zone manned by an inattentive flag person.

<comment><USER17> Haven't there been a lot of tests of self-driving technology on public roads? Tesla has released a couple of videos of theirs, and Google has put a couple million miles on theirs. What hasn't happened yet is a production-ready, customer-owned vehicle on public roads.

<comment><USER49> Not unsupervised. Unleashing a robot into school zones without a human in the loop is still considered too dangerous legally if not physically.

<comment><USER32> That's pretty much the rule about all robots operating in proximity to humans (except perhaps elevators, escalators, automatic doors and toy robots).

</comment></comment></comment></comment><comment><USER50> I don't completely trust the NTSA and I'm skeptical about auto-piloting cars but accept that more and more of those will be on the roads. I will _never_ ride in a vehicle that lacks an override mechanism.

In general, I think we are moving way too fast towards these self-driving vehicles because certain factions want to try and replace long and short haul truckers with robotic systems that are cheaper and damn the consequences.

</comment><comment><USER51> I don't really know why this is surprising. Computers are already better than humans at most tasks that involve a limited set of behaviors and they have infinitely better response time than humans (and continue to get better). How could anyone think that a report like this was going to end up any differently?

<comment><USER52> The history of self driving cars shows that it is not an easy task. We've been working on this for over 15 years. I was on a self driving car team during 2008-2010. We won multiple intercollegiate competitions. At that time I was certain it would be 20+ years before we had something that could drive on the roads. The progress has been spectacular.

<comment><USER51> No, programming the self-driving car is not an easy task. A car that's already been programmed, though, is definitely going to be safer than a human driver and driving for the computer _is_ an easy task.

<comment><USER53> > definitely going to be safer than a human driver

That's just ridiculous. It is going to be safer in some cases and less safe in others, and obviously it depends on the system and the driving conditions. To say that a computer is necessarily a better driver is just science fiction until we have solid data showing that to be the case.</comment></comment></comment></comment>


Show HN: Use Google Spreadsheet as a Database - <AUTHOR> https://github.com/sheetsu/sheetsu-web-client <comment><USER2> Love the idea. Clearly, a ton of effort put into this, congrats on shipping. But if you're going to abstract away Google Sheets, you might as well make a thicker abstraction. I want to use Google Sheets like a key-value store or some Mongo-like API, without thinking about worksheet names, column names, or underlying worksheet-specific implementation details. Your custom designed API is too much of a leaky abstraction, seems that it's not too far from me learning and using the Google Sheets API directly. Consider how other libraries like diskDB abstracted away the filesystem behind a Mongo-like API.

<comment><USER3> That's a very good insight! We treat spreadsheet more like a database with a schema. What you propose is a schema-less approach. I like this idea, and I think we will try to implement it, as we see that in such solutions schema is needless and is adding more complexity for the end user, which, in most cases, don't care if there is any schema or not - she is just a spreadsheets user.

From the other hand, it's hard to map JSON to a spreadsheet, because - what to do with the nested keys. Any ideas?

<comment><USER4> Don't hesitate to stick to enhancing the low-level non opinionated api. Having one is great because that enables all users to do what they want.

Then you can have other apis on top of it for opinionated usage like a kv store or other stuff.

For representing a nested key the first implementation that springs in mind is to use the indent (number of empty colums on the left) as indicator of parent- child relationship.

</comment></comment></comment><comment><USER5> You list Code for America, imgur, Berkeley, Stanford, and others under partners on your website. How are they using this? And do you have some links to blog posts of them talking about it or something?

<comment><USER3> Students from Stanford, Berkley and other universities (Notre Dame, Illinois, Columbia, Yale, Texas Woman's Uni, Alaska, Colorado Boulder, Minnesota, UCLA, Michigan, Chicago, Georgetown), as well as students from Boston, Harvard college, are using Sheetsu to learn how to talk with APIs and use them on the front-end.

Folks from Code for America were using it for very simple CMS to show dates of some events.

Guys from GeneralUI are using this for a quick solution for prototyping and have forms up and ready without setting up middlewares, servers, etc.

A customer from imgur is using this for some user research process (getting feedback).

Basically, most of them are using this in places where marketing or UX meets IT. Or there's no budget for IT to be involved, and they need to setup something on their own. We are trying to get all of those awesome use cases and make stories and blog posts from there. We are really amazed by some of them, what people can build if they need to.

</comment></comment><comment><USER6> Using google spreadsheets is a favorite of mine for prototypes. Especially without building out an admin app.

<comment><USER3> It is indeed. Much faster, because of almost no setup. You can also use Google Spreadsheets for your Sketch prototypes [https://medium.com/@Fif/create-your- own-api-for-craft-data-p...](https://medium.com/@Fif/create-your-own-api-for- craft-data-plugin-no-code-required-c5ef58da61b0)

</comment></comment><comment><USER7> Who said we're all just putting spreadsheets on the Internet?

This at least makes that easier...

</comment><comment><USER8> Don't do that. Please.

<comment><USER3> Why?

<comment><USER9> Because Google Speadsheet isn't designed to be a database. For example there are no datatypes.

It's maybe good enough for protoyping, but that's all.

<comment><USER10> maybe prototyping is all it's needed for. It doesn't need to fit every single use case to be useful.</comment></comment></comment></comment>


Ask HN: What would do to increase conversion on this page? - <AUTHOR> http://www.mydailystartup.com/?2 <comment><USER2> Do you have a lot of traffic to optimize for? It looks pretty new, if it's just a trickle you need to solve that problem first.

It also gives me the impression this is just for startup founders to share their startup with other founders. That's not very good or important traffic for most companies so if you're reaching a wider demographic you could elaborate on that.

<comment><AUTHOR> No not a lot of traffic right now. I figure the higher i can get the conversion rate with low traffic, that should only save me money ramping up the traffic. It is for startup founders - more precisely B2B startup founders. I think a lot of B2B startups could stand to benefit from using each others products. But you're right - that traffic would not apply to most companies outside of that niche. Thanks for the input. :)

<comment><USER2> If a handful of registrations is enough to skew your results you won't be able to accurately conclude anything from your experiments.

This is a good read, the stuff about "busy work" \- even a bad conversion rate will outperform your best effort at scale, it's very easy to distract yourself with the wrong work when the hard stuff is so much harder.

[http://blog.samaltman.com/the-post-yc-slump](http://blog.samaltman.com/the- post-yc-slump)</comment></comment></comment>


Ask HN: What's the best way to sell a domain name? - <AUTHOR>

I recently decided to call it quits on a Web application that I was pretty excited about at the time: I was planning on adding restaurant menus to a database so that users could add their feedback about the menu items themselves, rather than the restaurant as a whole. Each menu item had the same price and description as the physical menu, but also showed which percentage of users liked the item.
The domain that I was using for this project was menuvoice.com
Just looking through the current offerings on GoDaddy's site, I see that MenuAssistant.com is selling for $2700, and other domains that lead off with menu are priced similarly. I'm interested in selling this domain for roughly $2000-$2500 - since both words are easily pronounced and spelled, and the domain is only nine letters long. I also own the Twitter account name for it, which I would be offering as well.
My question to the HN community is: what is the best way to expedite this process? Is this a domain that should theoretically be valuable?
I don't want to have to spend years sitting on this before anyone bites, but I understand that patience here is probably important.
One strategy that I thought about was to contact start-ups with a similar focus, and send them e-mails explaining that I'm looking for a buyer. <comment><USER2> I would be amazed if you could get that price for that domain. It's 2 words, but they don't really 'speak' to me. I think you are overvaluing it based on your idea. What you must realize about domain selling (passive domain selling that is) is that it is a probability game. Big portfolios passively sell maybe 2% of their portfolio per year. They also charge much higher price than the liquid rate.

If you wanted to sell that domain right now, I would say $50-100 if you were to offer it to resellers.

However, if you go into active selling mode and contact potentially interested parties... the price can go higher. This depends entirely on your ability to sell and your network. I have no idea who you are, perhaps you are wolfgang puck and know every restaurateur and can sell it for a few grand no problem. However, based on where this is, I am going to say you're a programmer and probably don't have a deep network of restaurateurs.

So the question you have to ask yourself... how much time are you willing to spend on selling it and what is the price you would be satisfied at? If I am looking to liquidate generally I would find maybe 10-20 businesses and contact them, my reply rate is 5-10% on average. I take what I can get, I am dumping it anyways. Emotional attachment to domains lowers your chance of making a sale.

</comment><comment><USER3> During SXSW this year, I had a discussion with someone about domain reselling. They said that rather than try and resell just the bare domain, they went to an inexpensive logo design service and had the domain branded first, with the landing page showing the logo and a simple layout saying the domain _and brand_ were for sale. You'd be offering the logo you just bought, plus the Twitter account, and maybe even the details of the project.

He said that the branded ones always sold quickly and for much more than the bare domains did, although I don't recall the figures. It was worth his time and money to have the additional work done on them, apparently.

</comment><comment><USER4> I'll give you $100 for it right now via PayPal if you go with ohashi's advice.

<comment><AUTHOR> I'm willing to do this, but have no way of getting in touch with you. My e-mail address is in my info if you're still interested in this domain.

</comment></comment><comment><USER5> I've used sedo.com with success. They seem to have a wide international audience of domain pros. It is good for when you don't have the time to execute your plan of contacting biz's directly. They handle the transaction process via concealed identity offer and counter-offers. The con is they charge 10% of the selling price to the seller.</comment>


Amazon's pricing tactic is a trap for buyers and sellers alike - <AUTHOR> https://www.ft.com/content/86426be2-ad1f-11e8-94bd-cba20d67390c <comment><USER2> [http://archive.is/PYB4g](http://archive.is/PYB4g)

<comment><USER3> Thanks.

</comment></comment><comment><USER4> most shocking part is the NDAs with cities for the HQ2 bids require local governments adherence to dynamic pricing contracts. For one CA school district, that system would make them pay 12% more. So on top of the big and extended tax breaks cities have to give to win over Amazon, along with the exceptions to zoning restrictions that most builders have to adhere to, that's not enough. They also have to buy from amazon at inflated prices. Not a bad deal, if you're Amazon.

<comment><USER5> My general thought on this: why allow tax reductions for giants like Amazon at all?

<comment><USER6> Because how else can a city compete? Look at the number of Caribbean islands which are known to be "tax havens". Besides offering virgin beaches and piña coladas (which other places can also offer), they can also advertise favorable taxes and rule of law to lure foreign capital in.

tldr: "better to have a smaller % of something than 100% of nothing".

<comment><USER5> Would Amazon really risk offshoring HQ2 to the Caribbean? I doubt it. And if tax reductions are disallowed, the cities have to "compete" on other metrics. Otherwise we'll soon hear that cities pay Amazon to pick them up.

<comment><USER6> I never said Amazon would be considering a Caribbean island as a potential candidate. I think you missed my general point.

What does a company do when trying to gain your business? They can compete on price or quality/service. In this case the local city governments are competing in price, especially those that cannot offer the education like that of Boston for example.

</comment></comment></comment></comment></comment><comment><USER7> This article is dumb.

1\. mentions it being a trap for sellers - doesn't even mention sellers at all throughout the article or ever elaborate

2\. never even says what the "pricing tactic" is

3\. somehow shoehorns Sanders complaining about worker wages into it

There's no coherent narrative, analogies that aren't compelling or fleshed out.

Should have been a tweet, not an article.</comment>


Thalmic's (YC W13) MYO draws 10,000 preorders in 2 days - <AUTHOR> https://www.communitech.ca/thalmics-myo-draws-10000-pre-orders-in-first-2-days/

<comment><USER3> Here's some amusing trivia: the source on this article, Communitech, rejected Thalmic from their "Hyperdrive" accelerator program shortly before the company was accepted by YC. Something about "we don't think people will like it".

Suffice is to say they've been kicking themselves ever since.

<comment><USER4> We did get rejected from Hyperdrive. It was pretty early on, however - <USER2> Spring.

<comment><USER5> Aw! That sucks! Woulda been awesome to play with the MYO.

</comment></comment></comment><comment><USER6> I want two of these and Google glass. Seems like a match made in heaven.

Should be able to get Silent Messaging going, straight out of Vernor Vinge's "Rainbows End"

<http://en.wikipedia.org/wiki/Rainbows_End#Augmented_reality>

<comment><USER7> Throw in this thing for good measure: <http://www.theaudeo.com/>

<comment><USER8> Wow. What a frustrating website to learn about a product. It took forever to try and figure out what this does and how it works.

The homepage should have a description and a demonstration video.

Instead, it has a vague explanation and the only video that worked (the YouTube videos were set to private) was a video presentation at a conference which took forever to get to an actual demo.

For those that are wondering, apparently you can speak very silently (or not at all) and the computer will pick up what you're trying to say and repeat it louder in a synthesized voice. I think??

<comment><USER7> Sorry about that :P If you're curious about the technology, it's called subvocalization and they aren't the only people working on it: <http://en.wikipedia.org/wiki/Subvocal_recognition>

</comment></comment></comment></comment><comment><USER9> I'm not sure how I missed this earlier, but this is the first YC company in a long time I'm _genuinely_ excited about. This is as close to telekinesis as I'm likely to get, and I want it, dammit.

</comment><comment><USER10> Does anyone know if the API can/will provide the raw EMG measurements? (I work in a lab that does this kind of recording with wired electrodes. A robust wireless interface that spits out the full bandwidth signal would be quite a useful research tool).

Anyway, even if it doesn't, I think this will still be awesome.

<comment><USER4> We're evaluating this - haven't announced either way yet. There are a few reason we wouldn't - namely power usage if we have to transmit that data over BT.

<comment><USER11> Will there be an optional wired connection or at least the ability to use MYO while charging?

</comment></comment></comment><comment><USER12> Genuine question - have preorders always been this popular? Or are they a relatively new thing? It seems that Kickstarter has really changed people's perceptions of purchasing a product. People seem much more willing to pre-buy something like this.

Either way - this thing looks great. Can't wait to try it myself!

<comment><USER4> This is also a bit different from Kickstarter - we're not actually taking any money up front. But it's a tool to show and estimate demand, and get potential user feedback before a product is fully manufactured and ready to ship. This way we'll be able to work with thousands of developers early on before the units ship.

</comment></comment><comment><USER13> I wonder if it would work for amputees. I.e. do you need an actual hand in order for the signals to be processed correctly, or would imagining your hand's movements be enough?

<comment><USER14> "A myoelectric prosthesis uses electromyography signals or potentials from voluntarily contracted muscles within a person's residual limb on the surface of the skin to control the movements of the prosthesis..."

<https://en.wikipedia.org/wiki/Prosthesis#Myoelectric>

</comment></comment><comment><USER15> Wow, looks like a great product. If it works as seamlessly as the concept video suggests this could be a huge hit. I find this product more interesting to me than Google glass. I'd consider preordering but there are too many unknowns at this point and the website is kind of vague.

I wonder if the rumored apple "watch" is similar tech.

</comment><comment><USER16> I've seen their [EDIT: concept] video (below) and it was wildly successful in getting me excited about the product. The video combined with the tagline "UNLEASH YOUR INNER JEDI" definitely gave me goosebumps.

<http://youtu.be/oWu9TFJjHaM>

 _The MYO, its name derived from the Greek myos, for muscle, instantly measures electrical activity in muscles and connects wirelessly to computers, smartphones and other electronics, enabling users to control these devices with a simple wave of the hand._

Some of my engineer friends have serious doubts as to how well this technology will actually work (haters gon' hate?) but nonetheless I will be rooting for the guys at Thalmic. Good stuff.

<comment><USER17> Is this a demo video or is this a concept video? I can't find anything on the site to say one way or the other.

<comment><USER18> Appears to be a concept video to me.

</comment></comment></comment><comment><USER19> I haven't heard about it before and oh boy I'm so excited now as I wasn't in a long time about a piece of hardware. If it really will work as good as advertised, and I think it's very possible it will, this will be huge.

</comment><comment><USER20> I don't see how it can distinguish between normal use of your hand/arm and a control gesture. Perhaps in the midst of a video game, you are gesturing full- time, but the other examples seem more dubious to me.

<comment><USER21> That's a good point. Maybe you would have to do a particular gesture to get it "live"? But I'm just speculating here

<comment><USER22> I remember reading that they've selected a gesture that isn't likely to happen naturally to enable or disable the device.

</comment></comment></comment><comment><USER23> Have they given any indication of what stage in development they are in? Do we know this thing works yet? I couldn't find any mention on their site.

<comment><USER24> I've tried it. It's really friggin cool. (My team's desks are right next to their's)

</comment></comment><comment><USER25> You will be hiring 200 RIM engineers next year if there aren't delays and problems.

<comment><USER4> With 200 RIM engineers we'll be sure to have delays and problems ;)

Joking, of course...

</comment></comment><comment><USER26> Are there any more specific release timelines outside of 'by the end of 2013'?

</comment><comment><USER27> Their concept video was definitely interesting, but is there any video of an actual demo? (Or, since the company seems to be answering questions here, is one planned?)

</comment><comment><USER28> For the record, a friend of mine ordered one and was told he was roughly number 9500. (Basically 10,000, but I thought I would put in my 2 cents)

</comment><comment><USER29> FAQ says MacOS and Windows are fully supported + iOS and Android API support.

What are the plans for Linux down the line?

<comment><USER30> They say "under consideration". Some of us are taking matters into our own hands, as much as we can. #MyoForLinux on Twitter.

</comment></comment><comment><USER31> That's great that they are a YC company. I hope they do something together with boosted boards, that would be incredible.

<comment><USER32> That would be amazing, even though the boosted boards remote seems kind of awesome on it's own.

</comment></comment><comment><USER33> Would anyone like to guess as to how long I would have to wait to receive one if I were to pre-order it now?

</comment><comment><USER34> [http://gascash.co/mercedes-benz-tells-the-history-of- the-f1-...](http://gascash.co/mercedes-benz-tells-the-history-of- the-f1-safety-car-video)</comment>


The Supreme Court's Cultural Winners - <AUTHOR> http://www.wsj.com/articles/the-supreme-courts-cultural-winners-1467068464 <comment><AUTHOR> <(Justice Thomas) said the majority's reasoning is an acknowledgement that "we have passed the point where 'law,' properly speaking, has any further application."></comment>


How Google Translate squeezes deep learning onto a phone - <AUTHOR> http://googleresearch.blogspot.com/2015/07/how-google-translate-squeezes-deep.html <comment><USER3> This is great. I particularly like that they also automatically generated dirty versions for their training set, because that's exactly what I ended up doing for my dissertation project (a computer vision system [1] that automatically referees Scrabble boards). I also used dictionary analysis and the classifier's own confusion matrix to boost its accuracy.

If you're also interested in real time OCR like this, I did a write up [2] of the approach that worked well for my project. It only needed to recognize Scrabble fonts, but it could be extended to more fonts by using more training examples.

[1] [http://brm.io/kwyjibo/](http://brm.io/kwyjibo/)

[2] [http://brm.io/real-time-ocr/](http://brm.io/real-time-ocr/)

<comment><USER4> It seems your dissertation paper is behind something password protected [1]. It would be nice to see that too.

Can't get [1][https://www.dcs.shef.ac.uk/intranet/teaching/campus/projects...](https://www.dcs.shef.ac.uk/intranet/teaching/campus/projects/archive/l31011/pdf/LBrummitt_aca08lb_com3021.pdf)

<comment><USER3> Hmm looks like they have, well here's another link to it: [https://dl.dropboxusercontent.com/u/1672291/scrabble- referee...](https://dl.dropboxusercontent.com/u/1672291/scrabble-referee.pdf)

</comment></comment></comment><comment><USER5> I am 15 years into this computers thing and this blog post made me feel like "those guys are doing black magic".

Neural networks and deep learning are truly awesome technologies.

<comment><USER6> They are, but once you start learning about them, you realize the "black magic" part comes mostly from their mathematical nature and very little from them being "inteligent computers".

A neural net is a graph, in which a subset of nodes are "inputs" (that's where the net gets information), some are outputs, and there are other nodes which are called "hidden neurons".

The nodes are interconnected between each other in a fashion, which is called the "topology" or sometimes "architecture" of the net. For example I-H-O is a tipical feed forward net, in which I (inputs) is the input layer, H is the hidden layer and O the output layer. All the hidden neurons connect with all the input neurons "output", and all the output neurons connect to the hidden neurons "output". The connections are called "weights", and the training adjusts the weights of all the neuron with lots of cases until the desired output is achieved. There are also algorithms and criteria to stop before the net "learns too much" and looses the ability to generalize (this is called overfitting). In particular, a net with one hidden layer and one output layer is a universal function estimator -- that is, an estimator that can model any mathematical function of the form f(x1, x2, x3, ..., xn) = y.

Deep learning means you're using a feedforward net with lots of hidden layers (I think it's usually between 5 to 15 now), which apply convolution operators (hence the "convolutional" in the name), and lots of neurons (in the order of thousands). All this was nearly impossible until the GPGPUs came along, because of the time it took to train a modest network (minutes to hours for a net with a between 50 to 150 neurons in one hidden layer).

This is a very shortened explanation -- if you want to read more I recommend this link[1] which gives some simple Python code to illustrate and implement the innards of a basic neural network and you can learn from the inside. Once you get that you should move to more mature implementations, like Theano or Torch to get the full potential of neutral nets without worrying about implementation.

[1] [http://iamtrask.github.io/2015/07/12/basic-python- network/](http://iamtrask.github.io/2015/07/12/basic-python-network/)

<comment><USER7> You could say very much the same about the brain...

> [...] the "black magic" part comes mostly from their mathematical nature and > very little from them being "inteligent computers". A brain is a graph, in > which a subset of neurons are "inputs", some are outputs, and others are > "hidden". The nodes are interconnected between each other in a fashion, > which is called the "topology" or sometimes "architecture" of the net.

The deep question about deep learning is "Why is it so bloody effective?"

<comment><USER8> If there is magic to be found, it may be in that question. Why about graphs (namely the subset that are deep neural networks) allow them to not only contain such powerful heuristics, but also allow them to be created from scratch with barely any knowledge of the problem domain.

As a side note, I was playing a board game last night (Terra Mystica I believe) and wondering if you could get 5 different neural networks to play the game and then train them against each other (and once they are good enough, against players). I wonder how quickly one could train a network that is unbeatable by humans? Maybe even scale it up to training it to play multiple board games til it is really good at all of them before setting it lose on a brand new one (with a similar genre). Maybe Google could use this to make a Go bot.

But what happens if this is used for evil instead? Say a neural network that reads a person's body language and determines how easily they can be intimidated by either a criminal or the government. Or one that is used to hunt down political dissidents. Imagine the first warrant to be signed by a judge for no reason other than a neural network saying the target is probably committing a crime...

<comment><USER9> The best Go bot approach (as of some years ago, but it's not like neural networks are a new idea) uses a very different strategy. Specifically, the strategy of "identify a few possible moves, simulate the game for several steps after each move _using a very stupid move-making heuristic instead of using this actual strategy recursively_ , and then pick the move that yielded the best simulated board state".

<comment><USER10> Monte Carlo Tree Search ( Random playout ) is currently the best computer strategy for evaluating a Go position.

This is likely due to the way Go works , random playout provides a rough estimate of who controls what territory ( this is how Go is scored ).

Recently two deep-learning papers showed very impressive results.

[http://arxiv.org/abs/1412.3409](http://arxiv.org/abs/1412.3409)

[http://arxiv.org/abs/1412.6564](http://arxiv.org/abs/1412.6564)

The neural networks were tasked with predicting what move an expert would make given a position.

The MCTS takes a long time 100,000 playouts are typical - once trained the neural nets are orders of magnitude faster.

The neural nets output a probability for each move ( that an expert would make that move ) - all positions are evauluated in a single forward pass.

Current work centers around combining the two approaches, MCTS evaluates the best suggestions from the neural net.

Expert Human players are still unbeatable by computer Go.

<comment><USER10> For Chess see David Silver's work on TreeStrap

It learns to master level from self-play.

[http://www0.cs.ucl.ac.uk/staff/D.Silver/web/Applications_fil...](http://www0.cs.ucl.ac.uk/staff/D.Silver/web/Applications_files/bootstrapping.pdf)

also his lecture bootstrapping from tree based search

[http://www.cse.unsw.edu.au/~cs9414/15s1/lect/1page/TreeStrap...](http://www.cse.unsw.edu.au/~cs9414/15s1/lect/1page/TreeStrap.pdf)

and Silver's overview on board game learning

[http://www0.cs.ucl.ac.uk/staff/D.Silver/web/Teaching_files/g...](http://www0.cs.ucl.ac.uk/staff/D.Silver/web/Teaching_files/games.pdf)

</comment></comment></comment></comment></comment></comment></comment><comment><USER11> The most awesome and surprising thing about this is that the whole thing runs _locally_ on your smartphone! You don't need network connection. All dictionaries, grammar processing, image processing, DNN - the whole stack runs on phone. I used this on my trip to Moscow and it was truely god send because it didn't need expensive international data plans (assuming you have connectivity!). English usage is fairly rare in Russia and it was just fun to learn Russian this way by pointing at interesting things.

</comment><comment><USER12> I used this in Brazil this last March to read menus. It works extremely well. The mistranslations make it even more fun. Much faster than learning Portuguese!

I took a few screen shots. Aligning the phone, focus, light, shadows on the small menu font was difficult. You must keep steady. Sadly, I ended up hitting the volume control on this best example. Tasty cockroaches! Ha! [http://imgur.com/j9iRaY0](http://imgur.com/j9iRaY0)

<comment><USER13> I had some Brazilian roomates who didn't speak english (and I don't speak portugues). We used a combination of my poor spanish and google translate off my phone to comunicate.

It worked ok (much better than nothing.) However there were a number of times when there were very large issues in the translations that created some pretty big misunderstandings. Luckily we had a friend who had fluent English and Portuguese who would translate when things got to confused.

To reduce errors, you do need to be really careful to use short, complete sentences with simple and correct grammar. It's also better to use and that contain words that aren't ambiguous. (Those two sentences would probably not translate well.)

e.g. Please write simple words, short phrases and simple phrases. Please write words with just one meaning. Those phrases and words are easier to translate.

<comment><USER9> > Please write words with just one meaning.

Those words are very rare and tend to only be useful in very technical contexts.

<comment><USER13> Fair enough. The idea that is intended to express is 'unambiguous'. I tend to try to avoid more obscure words when writing text for automatic translation, often at the expense of explicit accuracy.

</comment></comment></comment></comment><comment><USER14> Word Lens is impressive. It came from a small startup. Google didn't develop it; it was a product before Google bought it. I saw an early version being shown around TechShop years ago, before Google Glass, even. It was quite fast even then, translating signs and keeping the translation positioned over the sign as the phone was moved in real time. But the initial version was English/Spanish only.

</comment><comment><USER15> I see no mention of it, but I'd be surprised if they didn't use some form of knowledge distilling [1] (which Hinton came up with, so really no excuse), to condense a large neural network into a much smaller one.

[1] [http://arxiv.org/abs/1503.02531](http://arxiv.org/abs/1503.02531)

</comment><comment><USER16> WordLens/Google Translate is the most futuristic thing that my phone is able to do. It's specially useful in countries that don't use the latin alphabet.

</comment><comment><USER17> "Squeezes" is very relative. These phones are equal to or larger than most desktops 10-15 years ago, back when I was doing AI research with evolutionary computing and genetic algorithms. We did some pretty mean stuff on those machines, and now we have them in our pockets.

<comment><USER18> The main issue here is probably not squeezing memory but squeezing performance. Even using regular SIMD is not good enough if your network is medium sized. They apply linear quantization, lookups and special SIMD operations to make it speedy.

See here for what they did for offline speech recognition: [http://static.googleusercontent.com/media/research.google.co...](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/41176.pdf)

</comment></comment><comment><USER18> They did this even more impressively when squeezing their speech recognition engine to mobile devices.

[http://static.googleusercontent.com/media/research.google.co...](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/41176.pdf)

</comment><comment><USER19> A possibly relevant research paper that they didn't mention: "Distilling the Knowledge in a Neural Network" [http://arxiv.org/abs/1503.02531](http://arxiv.org/abs/1503.02531)

</comment><comment><USER20> International travel now has a new source of entertainment: On-the-spot generation of humorous mistranslations.

<comment><USER21> The oddest result I ever got from WordLens was when using it to translate a page of poetry on a plaque. The output was wonderful :)

WordLens was awesome for translating fragments of foreign languages - <USER2> like signs, menus and so on. But its offline translation seemed to be little more than a word->word translation, so there is a huge scope for improvement there. Very difficult when working offline!

</comment></comment><comment><USER22> What are the advantages of using a neural network over generating classification trees or using other machine learning methods? I'm not too familiar with how neural nets work, but it seems like they require more creator input than other methods, which could be good or bad I suppose.

<comment><USER23> Neural networks, and the plain old trusted logistic regression :) handles raw, continuous data better than the other learning algorithms. For example, if your inputs are images or audio recordings, it's really hard to do classification with decision trees or random forests as you'd need to construct the features manually. What would be a feature: color densities, color histograms, edges, corners, Haar-like, etc.? The promise of multilayer neural network is that given a lot of data, the right network structures, an appropriate learning strategy, and a huge farm of GPUs, the network can automatically learn the right features from raw data in the first layers, and utilizes the features in later layers. The big advantage of this approach is that you abstract away the domain problems (hopefully), and focus on picking the right network design, the right learning strategy, collecting a good data set etc. Neural network training is also easy to parallelize, so Google and the like can leverage their huge infrastructures.

Now if the features in the domain problem is more well defined, like credit ratings, and data is sparse, and domain expertise is available, decision trees are perfectly valid options.

<comment><USER24> _For example, if your inputs are images or audio recordings,_

Just wanted to add: and word/character/phrase embeddings.

</comment></comment></comment><comment><USER25> The article mentions algorithmically generating the training set. See here for some earlier research in this area: [http://bheisele.com/heisele_research.html#3D_models](http://bheisele.com/heisele_research.html#3D_models)

</comment><comment><USER26> Here's a short video about Google Translate just released.

[https://www.youtube.com/watch?v=0zKU7jDA2nc&index=1&list=PLe...](https://www.youtube.com/watch?v=0zKU7jDA2nc&index=1&list=PLeqAcoTy5741GXa8rccolGQaj_nVGw76g)

</comment><comment><USER27> This technology has been around since 2010 and was developed by Word Lens, which was acquired by google in 2014:

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

</comment><comment><USER28> For those unfamiliar with google's deep learning, this talk covers their recent efforts pretty well [https://youtu.be/kO-Iw9xlxy4](https://youtu.be/kO- Iw9xlxy4) (not technical)

</comment><comment><USER29> Would be great to see a more in depth article about this, and maybe even some open source code?

<comment><USER30> I would be interested in this as well. So far I found a similar app called Mitzuli which is based on open source tools:

[http://www.mitzuli.com/en/](http://www.mitzuli.com/en/)

</comment></comment><comment><USER31> Doesn't this article seem to say that the size of the training set is related to the size of the resulting network? It should be proportional to the number of nodes/layers that the network is configured for, not proportional to the number of training instances. Am I missing something?

<comment> alok-g The network is sized to be able to learn the training data reasonably well (e.g. via hyper-parameter optimization). If there is too much variation in data that is not seen in the real application (like rotation of letters mentioned in the article), an appropriately sized network will still learn it, but would be an overkill for the application at hand.

</comment></comment><comment><USER32> I generated training sets for an OCR project in JavaScript [1] a while ago using a modified version of a captcha generator [2] (practically the same technique mentioned in this article).

[1] [https://github.com/mateogianolio/mlp-character- recognition](https://github.com/mateogianolio/mlp-character-recognition)

[2] [https://github.com/mateogianolio/mlp-character- recognition/b...](https://github.com/mateogianolio/mlp-character- recognition/blob/master/captcha.js)

</comment><comment><USER33> I wonder if they use some kind of (neural) language model for their translations. Using only a dictionary (as in the text) would be about 60 years behind the state of the art...

</comment><comment><USER34> Anyone want to do a $1 bet on an over/under for how long until word lens can handle Chinese?

<comment><USER35> There is an app called Waygo that's already capable of handling Chinese, so I guess it's not too far.

</comment></comment><comment><USER36> Why do they need a deep learning model for this? They are obviously targeting signs, product names, menus and similar. Model will obviously fail in translating large texts.

Was there any advantage of using a deep learning model instead of something more computationally simple?

</comment><comment><USER37> I don't get it. They say they use a dictionary, and they say it works without an Internet connection. How can both things be true? I'm pretty sure there's not, say, a Quechua dictionary on my phone.

<comment><USER38> It doesn't come with all the languages, you have to download them.

<comment><USER39> You can download the language packs on Android and iOS, and each one is about 4 MB in size.

</comment></comment></comment><comment><USER40> Given the reliability of closed captions on YouTube and the frequency of errors in plaintext Google translate, I wouldn't be surprised if this service fails often, and often when you need it most.

</comment><comment><USER21> WordLens was an awesome app and it's good to see that Google is continuing the development.

The new fad for using the 'deep' learning buzzword annoys me though. It seems so meaningless. What makes one kind of neural net 'deep' and are all the other ones suddenly 'shallow' ?

<comment><USER19> > What makes one kind of neural net 'deep' and are all the other ones suddenly > 'shallow' ?

If this is a serious question, then googling "what is a deep neural network" would take you to any number of explanations. But to summarize very briefly, it's not a buzzword; it's a technical term referring to a network with multiple nonlinear layers that are chained together in sequence. Deep networks have been talked about for as long as neural networks have been a research subject, but it's only in the last few years that the mathematical techniques and computational power have been available to do really interesting things with them.

The "fad" (as you call it) is not mainly because the word "deep" sounds cool, but because companies like Google have been seeing breakthrough results that are being used in production as we speak. For example:

[http://papers.nips.cc/paper/4687-large-scale-distributed- dee...](http://papers.nips.cc/paper/4687-large-scale-distributed-deep- networks.pdf)

[http://static.googleusercontent.com/media/research.google.co...](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/43793.pdf)

[http://static.googleusercontent.com/media/research.google.co...](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/42538.pdf)

<comment><USER21> I honestly didn't realise that it had any definition - I see now that calling it a 'fad' is unfair. However, the boundary between deep learning and (representational) machine learning still seems murky.

<comment><USER41> Considering the very significant accuracy gains deep learning has achieved over previous approaches (and across a number of fields), it's certainly not a simple fad. Having worked in computer vision for a good 8+ years, deep learning is basically amazing.

Deep learning is a form of representation/feature learning.

</comment></comment></comment></comment><comment><USER42> Just waiting for the paper to come out that'll detail all the transformations that were done on the training data specifically for the phone and how did they arrive at deciding to use them.

> To achieve real-time, we also heavily optimized and hand-tuned the math > operations. That meant using the mobile processor's SIMD instructions and > tuning things like matrix multiplies to fit processing into all levels of > cache memory.

Let's see how this turns out to be. I'm still skeptical if other apps might crash because of this.

<comment><USER43> Not fitting into cache just means it will run slower. Why would it crash?

<comment><USER42> Other apps getting slow is also not a very good thing!</comment></comment></comment>