skysight-inc/HackerNews huggingface dataset:
I think everyone agrees that ANN are a useful abstraction of what happens in real neural networks. A "closer" abstraction in some sense, as you mention, is what is being called Spiking Neural Networks, so you may want to read up on that if you're interested. I don't think they are strictly more powerful in any way, for what it's worth, as they more or less just trade continuous-domain discrete-time computations for digital-domain continuous-time computations; although there's some interesting hardware work being done to implement them.

That said, don't underestimate the complexity of what is happening in real neurons. It's true that an individual neuron is fairly simple (more or less! some may perform very complex encodings of sensory data!), but the complexity of the "computations" they perform goes up very quickly, and you have a _lot_ of them that are highly connected, so it may be that ANN are a good abstraction in the sense that they reduce the complexity of spike trains to a more abstract but more powerful representation.

It's true though that they probably don't perform back-propagation, at least in the mathematical sense; I don't know the literature but I think an inhibitory mechanism is probably a better biological model for how "error detectors" can be used to suppress useless or noisy output.
3 votes 4 Colon Power, 1 vote 4 Faith Spotted Eagle, 8 votes 4 Hillary Clinton
Agreed. The most important lesson I took away from my ML class is that I have to learn more of optimization theory.
I think in stories like these the human tendency is to let rage from any number of personal experiences or perspectives blind us to real lessons that could be gleaned.

One lesson, we inherit complex worlds -- we work at corporations with dark histories, attend institutions built by slaves, use devices and wear clothes made by people who live their lives in horrid conditions.

Maybe we can't change that, but maybe we owe ourselves the human responsibility to grapple with those questions.
Sort of off topic. I have been planning to do the same course(CS 231n), and was wondering, is it okay if I do the Andrew Ng Machine Learning (Coursera) in parallel, or is it more of a prerequisite ?
This was deterministic (cooperative).

And yes, you can absolutely handle it by throwing an exception. But cancellation is such a common mechanism that you'd want to have 1) a standard exception type that can be used to indicate it, and that other async operations can handle in a composable fashion, and 2) a standard mechanism to request cancellation cooperatively, again, so that various layers can collaborate on handling a high-level cancellation request all the way to the lowest level like an I/O read.

And that's what this proposal was all about.
Warren Buffett on the David Rubenstein Show
Edit: hmm not sure why this comment is getting downvoted.

Backprop isn't just a leaky abstraction. There's not really any evidence yet that biological neural networks use anything like backprop. So its important that students be taught the low-level aspects of the current state of the art so that better architectures can be invented in the future.

(Note: at the very end of this comment, I am leaving a link to one hypothesis about how something like backprop may happen at the dendritic level.)

I've been doing a deep dive on ML and bio neurons in the last week or so to try and get up to speed. The feedforward networks with backprop that are doing such awesome work right now share almost nothing in common with actual neurons.

Just some differences: (neuron == bio, node == artificial)

Terms: Neuron resting potential is about -70mV. Action potential (threshold) is about -55mV.

1) Neurons are spikey and don't have weights. A neuron sums all of its inputs to reach a threshold. When that threshold is reached, an electric current (action potential) is spread equally to all synaptic terminals. A node has a weight value for each input node that it multiplies by the value received from the input node. All of these values are then summed and passed to the connected nodes in the next layer.

2) There are multiple types of neurons, but for simplification there are 2 types that called "excitatory" and "inhibatory". A neuron can mostly only emit "positive" or "negative" signals via the synapse. There are different neurotransmitters that either add or subtract to the voltage potential for each dendritic input. The total sums work together to cross the threshold voltage. I say mostly because there is some evidence for a minority of neurons to be able to release neurotransmitters from both groups.

3) Artificial networks are generally summation based with no inclusion of time. Bio networks use summation and summation over time together to determine if they should fire or not. If I recall correctly, a neuron can repeatedly fire about 300 times per second. A dendritic input can last for up to 1.5 milliseconds. So if a neuron gets enough positive inputs at the same time, or collects enough over time, it will fire.

I haven't found any hypotheses or experiments that try to explain how reinforcement learning takes place in neurons yet in the absence of back propagation. Pretty sure that information is out there but I haven't run across it.

Overall I think that there will be multiple engineering approaches to AI, just like there are to construction and flight. We understand how birds and bees fly, but we don't build planes the same way.

Its important to remember than cognition is based in physics just like any other physical system. When the principles are well understood, there are multiple avenues to using them.

Here is a short collection of links that I've been finding helpful.

https://en.wikipedia.org/wiki/Neurotransmission

http://neuroscience.uth.tmc.edu/s1/introduction.html

https://www.quora.com/Can-a-synapse-change-from-being-inhibi...

https://en.wikipedia.org/wiki/Dale's_principle

https://en.wikipedia.org/wiki/Neural_backpropagation
I think you're doing something wrong, or you just don't like vegetables.
No, I mean real AWD. The systems used in smaller crossovers are such afterthoughts that they are only able to handle a tiny fraction of the drivetrain's torque continuously. They may be able to handle up to 50% for a period of time but the tiny little clutches would fry themselves if they weren't protected, thus neutered, by software. They exist to fill out the highly marketable checkbox of "AWD" and to provide some assistance once the vehicle is in motion but they cannot be depended on to deliver the performance of a more traditional AWD system.

See the Honda CR-V for an example: https://www.youtube.com/watch?v=jkiv-bWbLIo

The same "trick" has been applied to the Focus RS. It's "AWD" but the system is so weak that it can never live up to the expectations of those who think the AWD system will perform like that of a Subaru WRX or a Mitsubishi Evo. Source: http://www.vorshlag.com/forums/showthread.php?p=58372
Please don't introduce snark into an already divisive topic.
"Fixed in Java 8" means "You were right but that has been addressed".

I agree with the author in this case and it should be obvious that I do. It's a completely sensable point. I'm not arguing for Java X version I don't like. I'm arguing for Java as an evolving standard. No one in their right mind would think that many of the other languages the author loves are perfect in older stages.

Python 2? Who the hell represents strings as byte arrays? This was a mistake back in the Bell Labs day. It's the "vintage" of computer science.

Does that mean python "sucks"? No, quite the contrary. It means python is good because it will evolve with the times and fix it's issues as it runs into them.
Prank Gone Wrong Ruins $2000
Having never had to lose weight, I also feel happy talking about this. You are conflating healthy with boring, which is an opinion but not a helpful one; I happen to disagree with it.

A more useful discussion revolves around time. In order to eat cheap and healthy food you must cook everything yourself! Preferably in larger batches; things like slow cooking a whole chicken in water to not only prepare meat but to make chicken broth as well, then using that meat and broth later in other dishes and soups. All of this takes planning and time.

Buying frozen meals or going to McDonalds is vastly more expensive, dollar wise, than preparing your own food. But they also require zero planning and minimal effort -- those are the real "savings" provided by junk food.
"Arcadia is still in pre-alpha and highly experimental. We are working towards a coherent first release, but we’re not quite there yet."

http://arcadia-unity.github.io/

Looks like lots of fun to play with though.
Can you go into detail on using LISP for text MUDS? I have an appreciation for text based games. I find the simplicity to be elegant.
How to Increase Chances of Getting a Second Plus Size Dating
knowing what can be substituted boils down to google and in lieu of an answer, making a guess and bullshitting your way through it. Most of my favourite meals are those made from bullshit because we were missing ingredients.
Guide to Technical Development
Apologies, but to me your argument sounds like "but nobody has implemented a REAL capitalism yet!" -- ideal definitions will always exist and conversely, will never be implemented.

Maybe the fact that most developers never really see well-implemented Scrum process says something extremely important about Scrum and the human nature. Namely that they don't click well together.

I wonder why are people so stubborn when it comes to having to take a step back and re-evaluate their process?
I had the same thought. I'm curious if anyone will sue him. :)
As someone who has followed Warren Buffett very closely for over ten years (as well as being a shareholder in Berkshire), this interview had some new tidbits of information about him and Berkshire that I hadn't heard before, which is honestly pretty rare these days.

Edit: I posted the wrong URL. Here's the right one: https://www.youtube.com/watch?v=u8ANHNU0Fng
What is the point of this?
Not very, according to it's website http://arcadia-unity.github.io/

Also looks like the last commit was 2 months ago, FWIW.
Thanks! Sounds like a lot of fun, but a gamble to bet a commercial project on.
>Real neurons don't use calculus and activation functions, nor back-propagation, etc in order to learn.

This sounds like a (common) failure to understand how abstractions work. Bridges don't do calculus, but the bridge builder uses calculus to understand what bridges do use (the laws of nature), and thus the calculus abstraction is used to encode the behavior of bridges. Thus you can model bridges using calculus.

Similarly, neurons are modeled by calculus. Abstractions are abstract precisely because they are not the concrete thing they model: they are necessarily approximations. They give us the power to simplify at the cost of gaining the capacity to be wrong.

The point being this: you can literally use any abstraction you desire to model anything you like. Some will work better than others, and the better they work, the more closely the structure of your abstraction matches the structure of the concretion being modeled.
I'd say that the "minivan == unit-body/transverse engine/FWD" taxonomy is the correct one.

I mean, what are the counterexamples?

-the body-on-frame/rwd/solid axle Aerostar/Safari/Expo were...slightly smaller than the domestic quarter ton vans. not really mini, plus all the drawbacks of high floor height, bad fuel economy, truck handling etc. of the full size vans.

...which is why they aren't sold anymore.

-the VW Type 2/Vanagon:

Customers didn't like rear-engine handling. Or two-digit hp in a 5000lb gvw vehicle. Plus it's hard to make forward control layouts pass front-impact tests. So, a design dead-end.

-Mid-engined Japan-vans

High floor height, weird service position, once again, crash safety became an issue.

Of course, I'm happy that all these vehicles existed, and surely many customers felt their advantages outweighed their deficiencies...but on the whole, the Chrysler model ended up defining the market as it exists today, in the same way the Mercedes W124 defined "luxury car".
If you don't care about the electric drive, there are MUCH nicer cars available at the same price as a Tesla. It doesn't even compare. This is why I don't have a Tesla. I could afford one, but I have spent a lot of time in them, and they do not feel like a car in the price range that they are. The interior is fine, but not premium. The touch screen makes it feel like you're driving a computer, not a vehicle (not in a good way). The styling is obviously entirely subjective, but I think that most cars in the Model S's price range look nicer, and the Model X is downright ugly.

While it may sound like I'm anti-Tesla, I'm really not. I'm glad they're pushing this market forward, and I have many friends who have one and are very happy with it. I'm just saying that I don't buy the argument that it's a great car for the price if you ignore the fact that they "happen to be electric."
Very interesting.
I would like to see something in the future with support for approximate times, like launching something about five minutes.

Why? Because sometimes you don't want all your jobs to start at once. Just moving one job some miliseconds ahead of time will make a whole server to handle load better
You're not alone, I think there's a slowly growing awareness amongst the general public after the Snowden events. I have totally non-techy friends asking how they can get their TV to stop listening to them, etc.

On the other hand, a very large segment of the population subscribes to 'if you have nothing to hide, don't hide it', which I attribute to ignorance of how these things are misused, and subtle propaganda telling consumers not to worry about it.
I don't think that's a fair statement. They shipped the Volt when Tesla was mostly vapor.

The Bolt isn't like the electric Fiat they they just shoved a battery into.
I use the xps 15, you can buy the cheapest version then pop it open (unlike the xps13) and switch out the internal ram and ssd for something better.

I like the thunderbolt 3 port which allows me to connect to up to 3 external displays and my usb peripherals, something that I cannot find with any of this generations laptops since docks stopped being a thing
Not close to true. If you don't like using IB, that's fine and your choice. But many of us prefer using visual tools to lay out our UIs, so that we can see how it's going to look without having to compile and run the app every time and then navigate to the screen.
To be fair, he has a point. The indyhackers Submit hub article is sub-titled:

"Jason Grishkoff built a $55,000/mo SaaS business helping musicians promote their music, and he did it in under a year. Here's how."
Thanks for inspiration, I'm in! Will try and put something out by 8 Jan!!
Shiny by RStudio: Web application framework for R
I'm (oddly) glad someone else finds the name offensive. I know the history from the chess playing machine, but I found it felt more strongly tied to the meaning behind that in Turkish people. I just worried I was being overly sensitive and no one else would see it that way.

But I'd also say having a stated minimum wage, and having a relevant minimum wage are two different things. I come from a country on that list with a stated minimum wage of 1.70$ a day or about 22 cents an hour.

Not only is that incredibly low, I assure you no one is touring villages looking for hawkers with young helpers that aren't getting paid 1.79 a day, when the hawkers themselves can't ensure they're getting 1.79 every single day.

Ironically, it looks like mechanical Turk would actually meet the minimum wage in the country. And I'm sure the country is not alone there. So for someone who has no better source of income, I'm sure even after paying for an Internet cafe they'd come out making income that's livable.

I don't think that it's a bad thing that those wages aren't livable in a country where our hourly minimum wage exceeds the daily minimum wage.

That's why I'd say treat it like a hobby if you're in a country that's like the US.

I'm definitely not calling the work described as fun, but treat it as a hobby in the sense of treating it as something you do because you want to make a few dollars from the comfort of your computer (and for some reason don't want to try something that pays better in the long run like learning a skill, say... programming), not because you have to pay rent next month (again, situation permitting).

You have to remember, even in the US at minimum wage people still struggle with rent, so even if mechanical Turk did pay minimum wage per country, it'd still wouldn't guarantee financial security in many parts of the US
I understood the article, and I'm not a physicist or anything like that. And I suspect almost everyone else here who read it understood it too. It's not uncommon for HN readers to be interested in how the Universe works, and therefore this wouldn't be the first physics article they've ever read.
How much lithium batteries degrade depends on their type. High current cells have different characteristics from high capacity cells, for instance. Tesla puts them in groups of 75 cells in parallel so they draw a minimal amount of current from each cell, thereby prolonging the life of the battery. They also monitor the health of the battery cells so they degrade as evenly as possible.

100,000 miles at 265 per charge (85kWh) is 377 charges. During typical behavior (commuting) the car will remain above 70% charged at all times. That by itself cuts the degradation roughly in 3rds. So we're looking at a 125 full charge cycle equivalent after 100,000 miles. So about 8% capacity loss sounds about right. No additional trickery required.

Apparently there is significant room for improvement here too:

> CEO Elon Musk once referred to a battery pack Tesla was testing in the lab. He said that the company had simulated over 500,000 miles on it and that it was still operating at over 80% of its original capacity.

https://electrek.co/2016/06/06/tesla-model-s-battery-pack-da...
I think you are assuming the human brain is significantly simpler and better than it is. To start with: the number of neurons in the brain is ~100 billion, which is roughly 10,000 times more than in a large ANN, we train the human brain for years before it does anything remotely intelligent (as opposed the the expectation that neural nets will get somewhere useful in hours or days) and most importantly: our brains probably have strong priors due to millions of years of evolution encoded in our DNA. On top of this, not all brains are as good as each other, especially when you think about animals who do not have a real system of speech.
Your figures are way wrong.

I have an original Tesla Roadster, bought in 2010, with a battery that is basically the first thing they figured out how to do in order to put a car together. (The Model S battery is much more advanced). I drove the Roadster daily for 6 years, and I had about 12% capacity loss after those 6 years. This was a much better situation than Tesla projected (I don't remember what they said at the time, but it was something like 30-40% loss at 7 years, and for a relatively low price they sold an optional battery replacement plan that kicks in at 7 years).

Supposedly the Model S's chemistry is much, much better. Just saying "they're lithium batteries" is kind of a red herring, because there are many many subclasses of lithium battery, and at least according to Musk the fact of lithium is not nearly the most important part, but what really matters is the composition of the cathode and anode:
https://chargedevs.com/features/tesla-tweaks-its-battery-che...

[Edit: And the theory that they would have preemptively hobbled the car's maximum range by (.85^6) is just crazy, because it means they could instead have advertised a car that had THREE TIMES THE RANGE on its initial launch, and "range anxiety" was one of the biggest issues they had to overcome. They could have said OUR CAR GOES SIX HUNDRED MILES ON ONE CHARGE, which would be way more important than hiding some degradation.]
Had they sold them they would have had to produce spare parts for 10 years. Maybe it was cheaper to crush them?

Offsets are nothing new. Ford used to sell Escorts near or below cost in order to sell Crown Vics.
It goes both ways, but most SaaS entrepreneurs tend toward code for obvious reasons. I run a SaaS company now (ZenMaid) where I've focused entirely on the things listed and my partner focused entirely on code. Not everyone is so lucky though and most neglect my part.

We've started "outsourcing" more (hiring help really) but I intend to talk to all of our customers personally for as long as I can.
I sure hope you're using an intermediate CA.
I already use android auto. I was referring to Amazon's system.
Maybe it requires human intelligence to be efficient like the matrix.
>25% discharges hit the same value after 2,000-2,500

This is exactly the point (and easy to miss)

The degredation per energy used is about the same.

1 cycle of 100% = 4 cycles of 25%

So the 300-500 cycle loss is equivalent to 500-625 when you divide the number of recharge cycles by 4. You _must_ do this for an apt comparison because what you should be interested in is how your capacity deacys with usage.

Artificially smaller capacities also means that using the supercharger is more common. Another feature of lithium battery chemistries is losing capacity faster at higher charge/discharge rates. Trickle charging overnight will cause significantly lower cycle decay than supercharging in an hour (or whatever period it is)
I don't. It's not that hard to talk with the other devs on your team to avoid those merge problems.
>I suspect the fact that it's ugly is a feature: it will hamper sales a bit and reduce the chance that they'll need to produce lots of this car.

I doubt that. I'm sure GM would be perfectly happy selling millions of these things if consumers were willing to buy. They're in the business of selling cars, after all.

But I also doubt they'll put much effort into it.
Yeah, I'm not totally against the idea, but I know a lot of people have concerns around privacy online and how data about them is collected. I agree that you should let your users know you're tracking them in this way if you use something like this.
http://www.lemmingsventurefund.com/

thanks!
Your point is valid but if you read my comment I'm not arguing why the author is better or worse than the people he criticizes.

My point is that the author is using questionable rhetoric and is not being honest with his audience at best (and manipulative at worst) in his article. He could have easily made his point while not being any of that.
Americans love hatchbacks when they are called crossovers, SUVs, or minivans. They just don't like the small ones.
Do you know this VC? I'm sure he'll fund your startup
Tesla has to do that because their product line isn't very diversified.

GM has the benefit of selling everything from heavy trucks to tiny cars. Tesla has to invest lots of capital in chargers and a direct sales model.

Personally, I think the ROI on any car is crap, and I don't buy fancy vehicles. The Bolt makes a lot more sense to me.
I'd still recommend running NGINX in front of Go or Node backends. NGINX gives you the flexibility to add things like gzip, caching, static asset expires headers, load balancing, health checks, etc.

(shamless plug)
In terms of the TLS, I wrote a short blog post (http://blog.commando.io/the-perfect-nginx-ssl-configuration/) on a setting up NGINX to get an A+ rating on Qualys SSL Labs. It is really only a few lines/directives.