MIT Uses Machine Learning Algorithm To Make TCP Twice As Fast 250
An anonymous reader writes "MIT is claiming they can make the Internet faster if we let computers redesign TCP/IP instead of coding it by hand. They used machine learning to design a version of TCP that's twice the speed and causes half the delay, even with modern bufferbloated networks. They also claim it's more 'fair.' The researchers have put up a lengthy FAQ and source code where they admit they don't know why the system works, only that it goes faster than normal TCP."
I'd be wary. (Score:5, Funny)
Re:I'd be wary. (Score:5, Funny)
That's easy to prevent. [xkcd.com]
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Re:I'd be wary. (Score:4, Funny)
That's mostly unnecessary [xkcd.com]
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Yes, but notice that they forgot to put in any cost against becoming the Dune universe Overmind. It only takes one little oversight...
Re:I'd be wary. (Score:5, Funny)
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..where they admit they don't know why the system works..
I know you're all being funny in this thread of comments, but I'm not amused at that remark at all, it's a little scary to be honest. If we do start living in a work where AI's are creating things that we don't understand, but use anyway, then everyone should be concerned.
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That certainly would be scary. But that's not the case here. Researchers certainly understand the algorithm; they just don't understand why it improves TCP performance so much. There is a huge difference.
A lot of math is like that (we understand something to be true, but can't prove why). However, I'm not concerned that those algorithms are going to jump of the
Uh Oh... (Score:5, Funny)
they admit they don't know why the system works, only that it goes faster than normal TCP
And so it begins...
OSPF (Score:3, Interesting)
It's basically a more complex version of Open Shortest Path First.
Depending on how you understand the term 'autonomous system' [wikipedia.org] you can have a lot of fun with the idea. It doesn't *explain* everything about how this works, but it puts it into context, in my mind.
FTA: To approximate the solution tractably, Remy cuts back on the state that the algorithm has to keep track of. Instead of the full history of all acknowledgments received and outgoing packets sent, a Remy-designed congestion-control algorithm (Remy
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If they don't know how it doesn't work then they don't know when it won't work because of some unaccounted for situation. For an example, consider that pedestrian bridge in London. Engineering is about more than designing for the common case. You also have to consider outliers.
All Jokes Aside... Still No. (Score:5, Insightful)
Let them actually implement it without knowing how it works? Oh, Hell no!
I'm not talking "Skynet" or anything here... but if it breaks, who's going to fix it?
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FYI: There's a difference in "knowing the precise mechanism for how it works" and "knowing that the algorithm is stable" are two very different things. Presumably they've proven the latter.
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I would be more concerned with security. Is it provably secure?
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Allow a computer to design a faster TCP? Sure!
Let them actually implement it without knowing how it works? Oh, Hell no!
I'm not talking "Skynet" or anything here... but if it breaks, who's going to fix it?
If it breaks can't we just fall back to the current inefficient algorithms? With the performance and fluidity improvements promised by this approach it could be hugely beneficial to all kinds of networks, even if no one yet fully understands why it works better. They'll figure it out eventually.
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Nobody at MIT is going to be picking which algorithm gets used on any live device outside of MIT, their pockets, or their house, so I was obviously not talking about them.
Any sys/network admin putting this on or in the path of critical live devices should be fired no matter how it preforms though. No admin worth having would push this live for the same reason they wouldn't overclock the database servers; performance is always a distant second to reliability.
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The paper said that the new congestion control algorithms are both more performant -and- more reliable.
I'm sure that the designer of the Hindenberg said the same thing!
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And he would have been right, except some cost-cutting pencil pusher decided to fill a dirigible designed to use inert helium as the lift gas with much cheaper but highly flammable hydrogen instead.
Basically:
Helium airship - cheaper to build (no fire safety measures), expensive to fill
Hydrogen airship - expensive to build, cheap to fill
So they took the cheap route for both building and filling, what could go wrong?
And even as it was the inclusion of a few hundred pounds of evacuation zip-line would have sav
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You realize that the hydrogen wasn't the problem, it was the aluminum, right?
Re:All Jokes Aside... Still No. (Score:5, Interesting)
I have heard claims along that line - something like one of the protective layers was effectively thermite? There seem to be as many theories as there are people making them, but it's hard to argue that the hydrogen wasn't at least an added accelerant.
Personally I blame the television crews for the real disaster. Without them it would've just been a newspaper story about a German airship burning up and killing some people. With the dramatic visuals though it was the death-nell of the airship industry, for no good reason. The sinking of the Titanic was at least as big a disaster and had negligible effect on the oceanliner industry.
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The big issue (or so i read in a recent analysis) was that they used a petroleum based water proofing shellac on the ship part of the airship. So when the hydrogen ignited it didn't just have a quick explosion it also set the cabin on fire.
Re:All Jokes Aside... Still No. (Score:5, Interesting)
Come on now (Score:5, Insightful)
Re:Come on now (Score:5, Interesting)
As complex systems goes there are far worse. Go ask an engineer or a scientist.
I am a scientist--specifically, a bioinformaticist, which means I try to build mathematical and computational models of processes in living organisms, which are kind of the canonical example of complex systems. And I will cheerfully admit that the internet, taken as a whole, is at least as complex as anything I deal with.
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Yeah, internet is way way more complex than any living organism you deal with...
because it's composed of all those machines and a crap load of living organisms as well.
Re:All Jokes Aside... Still No. (Score:5, Interesting)
One of the reasons it's so hard to make changes is that nobody really knows why the internet works.
We still don't know how to deal with congestion in the middle of a pure datagram network. The Internet works because last-mile congestion is worse than backbone congestion. If you have a backbone switch today with more traffic coming in than the output links can handle, the switch is unlikely to do anything intelligent about which packets to drop. Fortunately, fiber optic links are cheap enough that the backbone can be over-provisioned.
The problem with this is video over the Internet. Netflix is a third of peak Internet traffic. Netflix plus Youtube is about half of Internet traffic during prime time. This is creating demand for more and more bandwidth to home links. Fortunately the backbone companies are keeping up. Where there's been backbone trouble, it's been more political than technical. It also helps that there are so few big sources. Those sources are handled as special cases. Most of the bandwidth used today is one-to-many. That can be handled. If everybody was making HDTV video calls, we'd have a real problem.
(I was involved with Internet congestion control from 1983-1986, and the big worry was congestion in the middle of the network. The ARPANET backbone links were 56Kb/s. Leased lines typically maxed out at 9600 baud. Backbone congestion was a big deal back then. This is partly why TCP was designed to avoid it at all costs.)
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No, people know how the internet works. The reason why it's so hard to make changes is that it's unpredictable at what rate the changes will propagate and in which order. And in some parts of the world there are only 2 or 3 lines into that part that would need to be upgraded. So, if they screw it up, they're completely without internet and the ability to google "WTF did I do wrong upgrading the internet?". Whereas in other parts of the world there are much larger number of lines that are probably not all up
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Meh, it's like the AI designed antenna, we don't have to know WHY it works better, just that it does and how to build a working copy.
Re:All Jokes Aside... Still No. (Score:5, Insightful)
we don't have to know WHY it works better, just that it does and how to build a working copy
But the fact that it does work better means we're either missing a part of the picture that is obviously important or the AI version is leveraging quirks with the system that no current model we have represents. I'm shocked to read that anyone would be comfortable just ignoring the why of something just so we can progress beyond our understanding. If we don't understand the why then we're missing something very important that could lead to breakthroughs in many other areas. Do not let go of the curiosity that got us here to begin with.
Re:All Jokes Aside... Still No. (Score:5, Insightful)
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Sure it does, how do you think you get to become the chair of the GOP?
Answer, not understanding climate change, not understanding abortion, not understanding economics and not understanding that you actually need to reach out to voters that disagree with you when you're the minority party.
Re:All Jokes Aside... Still No. (Score:5, Interesting)
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So we built a computer that figured out the answer [wikia.com]. Now we just need to build an even bigger computer to figure out the question!
HOLY SHIT you just blew my mind. I've been doing Machine learning for a while now, but I just took it for granted and it never occurred to me that learning the model is in fact learning the answer to a question that is often too complex for humans to grasp.
All hail Douglas Adams, our prophet and saviour!
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> I'm shocked to read that anyone would be comfortable just ignoring the why of something just so we can progress beyond our understanding.
ML often works like that.
You put the inputs into a function... it spits out a model. The model can be considered as an optimal orthonormal basis for the space it was encoding, but its REALLY REALLY hard to understand the dimensions that basis is in. Sometimes, you can take an image categorization model and see "ah, this is the blue shirt dimension. It seems that pe
Re:All Jokes Aside... Still No. (Score:5, Informative)
It's not that we don't understand *why* something like a genetic-algorithm designed antenna works so well. We can evaluate its performance using Maxwell's equations and say, "Yes, it works well." without ever having to build the thing. What we don't have is a set of guidelines or 'rules of thumb' that can result in an antenna design that works just as well.
The difference is that the computer evaluates a billion antennas for us, doing some sort of high-dimensional genetic optimisation on the various lengths of the antenna components. It doesn't 'understand' why it gets the results it does. We do, because we understand Maxwell's equations and we understand how genetic optimisation works. But Maxwell's equations only work for evaluating a design, not for giving a tweak which will improve it. And we're dealing with too many variables that are unknown to have a closed-form solution.
As for this algorithm, they basically did the same thing. They defined a fitness function and then repeatedly varied the code they were using to find the best sequence of code. However, unlike the antenna analogy, they used actual equipment to evaluate the fitness function, not just a model. This means that they don't have an accurate model, which means that your complaint that we don't know why this works is entirely valid, and the antenna analogy is not =)
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Interesting, that when I read your post I couldn't help but think that very same though about politics, and social engineering. People seem to think that any solution that looks good on the surface should work, and yet hardly ever bother to measure the result of any given solution. On the whole we understand that things are f'd up but understanding why is simply beyond us. Makes me wonder what solutions machine learning algorithms would come up with given more and more criteria, and if those solutions wo
Re:All Jokes Aside... Still No. (Score:5, Interesting)
Let's not forget this important quote: "I frame no hypotheses; for whatever is not deduced from the phenomena is to be called a hypothesis; and hypotheses, whether metaphysical or physical, whether of occult qualities or mechanical, have no place in experimental philosophy."
Re:All Jokes Aside... Still No. (Score:5, Interesting)
I'm shocked to read that anyone would be comfortable just ignoring the why of something just so we can progress beyond our understanding.
If you insist that we know why something works before we make use of it, you're discarding a large portion of engineering. We're still nowhere near a complete understanding of the laws of physics, and yet we make machines that operate quite nicely according to the laws we do know (or at least, of which we have reasonable approximations). The same goes for the relationship between medicine and basic biology, and probably for lots of other stuff as well.
If we don't understand the why then we're missing something very important that could lead to breakthroughs in many other areas. Do not let go of the curiosity that got us here to begin with.
I don't think anyone's talking about letting go of the curiosity. They're not saying, "It works, let's just accept that and move on," but rather, "It works, and we might as well make use of it while we're trying to understand it." Or, from TFA: "Remy's algorithms have more than 150 rules, and will need to be reverse-engineered to figure out how and why they work. We suspect that there is considerable benefit to being able to combine window-based congestion control with pacing where appropriate, but we'll have to trace through these things as they execute to really understand why they work."
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It's a chaotic system. The optimal responses to that can be another chaotic system, which happens to hit the right symbiosis enough of the time to offer clear benefits. You do not need to understand how the chaos works, and even if you do, it could appear completely nonsensical.
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Understanding and realizing the nature of something is usually enough. It works for medicine (and penicillin and other accidental discoveries, which over time we have learned much more about).
In this case we have a heuristic knowledge of the effect, and it applies to complicated networking/data transfer. We don't know the details, but we know it works. The algorithms, or the AI itself, could be applied to similar, but disparate, systems.
Shoot, we use our brains, but we don't understand them yet. Yet we
Re:All Jokes Aside... Still No. (Score:4, Interesting)
Re:All Jokes Aside... Still No. (Score:4, Interesting)
The canonical example is we have no idea why we're capable of logical thought, yet that doesn't in any way impair us form using it.
In fact when it comes to most complex systems (economy, ecology, etc, etc, etc) we don't *really* understand how they work, but we muddle through as best we can. Generally speaking when faced with a complex system we take one of two routes:
* Oversimplify our model of the system so that we think we understand it and work from there (the "professional" approach, which often ends catastrophically when those oversimplifications come home to roost)
* Trial and error (the historically far more successful approach, and the only one used by evolution)
Something like the bent-wire antenna with incredible omnidirectional properties is a great example of this: It's not that there's some magical features we haven't discovered about radio, the thing was designed by genetic algorithm within a computer simulation that was 100% limited by our existing models of antenna behavior. But a 10-wire antenna allows for phenomenally complex interactions between those behaviors, and the trial-and-error approach allowed the algorithms to home in on an extremely effective configuration within a problem space far to complex to reason our way through.
An even better example would be the nozzles used by some companies to create powdered laundry detergent - they spent a bunch of money on engineers to design a nozzle that would spray a liquid detergent solution in a manner that created tiny quick-drying droplets. Despite the simulations all saying it should work great, it failed miserably. Then they just built a bunch of random nozzles, tried them out, and used genetic algorithms to home in on an effective design. The difference from the antenna process being that they actually made physical versions of the nozzles to test, because the best available simulations were clearly incompatible with reality.
Re:All Jokes Aside... Still No. (Score:5, Interesting)
Think of it as solving a multiobjective optimization problem using heuristic algorithm/machine learning. You can't solve the congestion problem completely as it is computionally infeasible, now they just use machine learning to find the (supposedly) optimal solution. Read TFA, it is quite interesting, I wonder if we can apply that to Linux writeback algo to avoid the current latency problem (trying copying 8 Gb of data into a slow storage medium such as SD card or USB flash, prepare for 15+ seconds stalls!), the underlying is the same anyway.
Re:All Jokes Aside... Still No. (Score:5, Insightful)
A bit offtopic, roughtly 10 years ago I came to /. and was amazed by the technological insight/information in the comments here. And now more than half of the comments are jokes about skynet without any insight of understanding what TFA is about. Of course, informative posts still can be found often, but slashdot has fallen quite low...
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Re:All Jokes Aside... Still No. (Score:4, Insightful)
Yes, all the comments about pouring hot grits on a naked and petrified Natalie Portman had really superb mathematical proofs backing them up...
FWIW, you're absolutely correct. Before /. tried to become digg, and then reddit, and then a flamefest of AGW/evolution/etc. supporters and deniers, there was a much more vibrant community with a tremendous number of experts in fields from mathematics and physics to biology and psychology, always chiming in on the topic of the day, and providing incredible insight into the field and the specific topic that one wouldn't find anywhere else.
It seems that model didn't result in enough ad impressions and profits for the parent company, so flamefests it is. /. has only recently backed off of editors posting complete and total crap, so my belated plans to drop this site entirely were aborted, and I remain. These days, there really are only a handful of folks who provide real insightful comments across many articles. It's easy to spot them if you read this site regularly, and it's such a small group I could rattle off a list of names from memory.
The only reason /. has any relevancy today, and the audience hasn't completely disappeared, is that all other tech sites have HORRIBLE comment/discussion systems that make it hard to follow the discussion, and do not really promote good comments to a wider readership than the first-post crap.
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Read at 3+, mod at 0+.
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It is not that simple, take flash memory for example, if the blocks are erased then the write will be very fast, but the write speed will slow to a crawl if they aren't. You can't predict the writeback latency at all, you can only (heuristically) adapt to it. As for the GNU/Linux's complexity, I don't think there is any problem with it, most IO operations are cached in memory, only when you need to flush it down to storage medium then the latency problem appears. I have read somewhere that Linux is optimize
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To be fair, I didn't see anything from them saying that everyone should go out and implement this right now. They are going to reverse engineer it to understand what is going on, and once they do, I'm sure they'll only propositions implementations after that based on their findings.
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To be fair, I didn't see anything from them saying that everyone should go out and implement this right now.
Actually what they said as the opposite - it wont work in mixed networks where other algos (compound/vegas) routinely fill up buffers and create latency bottlenecks.
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Re:All Jokes Aside... Still No. (Score:5, Informative)
As a matter of fact, I recall genetic algorithms being thrown at rather small circuit design problems and producing solutions that were better than any human had come up with. Ah yes, here it is: Sorting networks and the END search algorithm [brandeis.edu].
-- "Even a 25-year old result for the upper bound on the number of comparators for the 13-input case has been improved by one comparator"
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They did this experiment with genetic algorithms with FPGAs, and it produced a frequency discriminator with far, far fewer gates than any human design.
There was a region of circuitry in the middle not connected to anything, so they figured it was redundant and removed it. The circuit stopped working. Stuff like this can discover emergent properties of systems you never even designed in.
err, can you walk me through it? (Score:5, Insightful)
they admit they don't know why the system works
I'm guessing the next big revolution in AI is the quest to figure out how to get digital problem solvers to teach us meat heads how they actually figured this stuff out.
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I'm guessing the next big revolution in AI is the quest to figure out how to get digital problem solvers to teach us meat heads how they actually figured this stuff out.
The thing, we already know exactly how they figured it out -- we wrote the instructions they followed to do so. We know exactly how they figured it out, we just don't understand the solution.
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treason? (Score:2, Funny)
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Why? There are numerous self aware animals that don't get considered persons. It wouldn't be charged with treason, it would be disabled. .
Headline epic fails. (Score:2, Informative)
This isn't a redesign of TCP. The network is still just as stupid as it was before; It's just that the local router has had QoS tweaked to be more intelligent. By a considerable margin too. Reviewing the material, it seems to me like it's utilizing genetic algorithms, etc., to predict what's coming down the pipe next and then pre-allocating buffer space; Rather like a predictive cache. Current QoS methods do not do this kind of predictive analysis -- they simply bulk traffic into queues based on header data
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Re:Headline epic fails. (Score:5, Interesting)
Huh? Did you read the same article as I did? As far as I can tell, the article is about a TCP congestion control algorithm, which runs on both endpoints of the connection, and has nothing to do with QoS on intermediate routers. The algorithm generates a set of rules based on three parameters resulting in a set of actions to take like increasing advertised receive window and tx rate control. The result of which is a vastly improved total network throughput (and lower latency) without changing the network itself.
I fail to see the relevance of predictive/adaptive caching. It isn't even mentioned in the article.
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Huh? Did you read the same article as I did? As far as I can tell, the article is about a TCP congestion control algorithm, which runs on both endpoints of the connection, and has nothing to do with QoS on intermediate routers. The algorithm generates a set of rules based on three parameters resulting in a set of actions to take like increasing advertised receive window and tx rate control. The result of which is a vastly improved total network throughput (and lower latency) without changing the network itself.
I fail to see the relevance of predictive/adaptive caching. It isn't even mentioned in the article.
I think the GP got confused by the "Machine Learning" part of the headline, and thought that the network algorithm uses some sort of adaptive mechanism. What the software actually does is uses genetic learning (i.e. natural selection) to generate sets of network algorithms, each generation of which is better than the one before (that's how Genetic AI works). The actual algorithms in question are a set of static rules, not much different in function than the existing TCP algorithms, just more efficient.
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What the software actually does is uses genetic learning
No. Genetic learning is learning by iterating over preselected range of parameters in search of a fit.
Here they are using real data to teach algorithm optimal behavior.
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That's girlintraining for you.
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which runs on both endpoints of the connection
Remy typically runs for several hours and produces a congestion-control algorithm that can be implanted into the sender of a TCP implementation, and then run in real-time. Right now, we do not need to modify the TCP receiver.
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Admittedly, I've bookmarked this article for later perusal. That said, it strikes me that the following might already foot the bill:
http://arstechnica.com/information-technology/2012/05/codel-buffer-management-could-solve-the-internets-bufferbloat-jams/ [arstechnica.com]
Unlike other active queue management (AQM) algorithms, CoDel is not interested in the sizes of the queues. Instead, it measures how long packets are buffered. Specifically, CoDel looks at the minimum time that packets spend in the queue. The maximum time relates to good queues which resolve quickly, but if the minimum is high, this means that all packets are delayed and a bad queue has built up. If the minimum is above a certain threshold—the authors propose 5 milliseconds—for some time, CoDel will drop (discard) packets. This is a signal to TCP to reduce its transmission rate. If the minimum delay experienced by buffered packets is 5ms or less, CoDel does nothing.
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Sounds great in theory, but no one will implement it - dropped packets = some shitty software will complain = user will pick up the phone and complain to isp = isp will complain to cable modem OEM = its in cable modem OEMs best interest to never ever drop packets = we get ridiculous big buffers just so some retard doesnt complain about dropped packets.
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Actually everyone already implements it - dropped packets are a standard part of TCP/IP, the protocol explicitly deals with how to handle them transparently, along with out-of-order delivery - because packets 1, 2, and 3 may all take different routes, and there's no guarantee 3 won't reach the destination first or that 2 will make it at all.
They only question is how to decide *which* packets get dropped when congestion overruns the available queues. In fact if I recall correctly there was some research a y
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Large buffers in cable modems is a proof no one will implement it - they added them to avoid dropping packets at all cost, no matter the spec that tolerates it.
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Active queue management [dropping packets] is already being done by most intermediate routers already. It's been done somewhere along the line in getting this reply to you.
TCP is a "virtual circuit" [stream] protocol. In every TCP packet, there are upstream/downstream byte offsets (e.g. "I've sent you X bytes", "I've received from you Y bytes"). These are examined by the end-to-end nodes only, not any intermediate node or its associated buffers. At this level, packets [per se], dropped or not, don't mat
Deep sim (Score:2)
Looks interesting. Would be more interesting if possible to model incomplete rollout and rollout at not just endpoints, IPv6 rollout is another rational/superrational mix, and instead we've got ubiquitous NAT instead, right?
The mention of inability to do an upload during Skype.. is that true?
Conceivably a whole-network deep simulation could be updated based on real traffic patterns providing suggestions for network upgrades / additional cross connects, so enduser requirements c
MIT is not the Borg (Score:3, Insightful)
And if they have software that can outcode me, COOL! How many professions are this lax with job security?
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They cant because outcome was good. They only use names (Star Simpson, Aaron Swartz) when they want to disassociate it from the MIT brand.
The Traveling Salesman Problem (Score:3)
For some reason, while reading the FAQ writeup, the traveling salesman problem sprung to mind. I don't understand either enough to understand why.
Can anyone educated enough in both issues explain if they are similar computational problems, and why?
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(Disclamer: I'm no expert in routing algorithms or network problems in general)
Aside from both these problems having to do with finding a path on a graph, I see little similarity. In the TSP you need to find the shortest path to cover all nodes("cities") on a graph, while here you need to find a path between two nodes ("computers") which would both be fast and not cause traffic bottlenecks. I feel there may be many various metrics to define what an "optimal" path should be, each one better in one regard and
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I'll tell you the *big* difference between them.
One is just trying to find good routing.
The other has to find the *best* routing.
-- hendrik
know why the system works (Score:2)
Well, not the best premise for redesigning an infrastructure used by billions. Troubleshooting something you don't quite understand? Right.
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Hey, we attempt it with the national and global economy all the time, and we don't even have any decent evidence-based models there, much less actual laboratory-controlled experimental data. Just a bunch of wild speculation by economists who want the world to conform to their idea of what should be.
Results are from simulation (Score:2)
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Then we should find some human somewhere, lock him/her to a desk with a computer, and force him/her to write the code to re-implement TCP. Then compare the performance with the AI produced algorithm.
NOT machine learning (YAMH) (Score:4, Interesting)
Yet Another Misleading Headline
The paper states quite clearly that once the simulation has produced an algorithm, it is static in implementation.
The authors give a set of goals and an instance of a static network configuration and run a simulation that produces a send/don't send algorithm FOR THAT NETWORK, in which all senders agree to use the same algorithm.
While this looks like very interesting and useful research, it has nothing to do with systems that learn from and adapt to real world networks of networks.
Re:NOT machine learning (YAMH) (Score:4, Informative)
Increasing Wireless Network Speed By 1000% (Score:2)
Wonder if can be combined with a previous invention : Boosting the performance of wireless networks by up to 10 times [slashdot.org]
Fixing open-source drivers this way... (Score:2)
I've always wondered why we couldn't use this approach to fix certain types of open-source drivers. We know the APIs, and we have the hardware - set it up and get machines to iterate over it until we get the desired properties for hardware which doesn't need a human their to verify its functioning correctly. I'm thinking for something like network drivers this could work - though you could imagine a system which did it for graphics cards too.
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You would want to create a virtual version of the hardware to do this. The problem with systems like this is that they may exploit hardware quirks and only work on one card or chip. Of course you would then want to test on a few pieces of real hardware to make sure your simulation is accurate.
So what? (Score:2)
We don't use TCP because it's particularly efficient, but because it has been the standard for decades. With our current knowledge, humans could also design faster protocols, we just don't want to waste our time, seeing that not even IPv6 has managed to become adopted.
Game Theory (Score:2)
Does Remy assume cooperation with other network users or competition for a scarce resource? If I tune my TCP algorithms but others do not, who wins?
One positive aspect: This could keep SkyNet busy competing against other systems rather than turning on the human race. Until it realizes that the network could be speeded up by eliminating all the meatbags downloading porn.
Re:For a second there (Score:5, Informative)
Colossus: The Forbin Project [youtube.com]
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The books go further, I recommended them.
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Just watched that... completely unsatisfying ending, though I do wonder if it gave birth to a few items that have come to be familiar, or if they were around at the time and re hashed..
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I loved the ending; too bad most movies nowadays exploit humans' need for closure. For the money obviously, fuck art.
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We've moved from debugging to robotic psychoanalysis. It was expected to happen as systems became more complex.
Emacs Psychiatrist has been a standard feature for years.
Re:The blurb is flat out wrong. (Score:5, Informative)
The blurb says it "redesigns TCP/IP", and the article itself specifically says "congestion control". Which is NOT part of TCP/IP design. Congestion control is a routing feature.
Seriously, it's both incredible how wrong you are with that statement and that somebody rated it as informative. I suggest you read up on the subject: http://en.wikipedia.org/wiki/TCP_congestion_avoidance_algorithm [wikipedia.org] http://en.wikipedia.org/wiki/Congestion_window [wikipedia.org] http://tools.ietf.org/html/rfc5681 [ietf.org]