chimtim

8 ms·

31.
by chimtim 10y ago
In terms of number of neurons, human brain is around 10^11. Current image classification deep networks are around 10^7. However, its not just the number of neurons, the connections per neurons also matter. The connections per neuron in a hu
32.
Intel acquires Nervanasys for 400M USD(newsroom.intel.com)
1 points by chimtim 10y ago|0 comments
33.
by chimtim 10y ago
PCM -- coming soon next year since last 7 years.
34.
by chimtim 10y ago
It is a dataflow language and deals with tensors (multi dim arrays), so tensor + dataflow = tensorflow.
35.
by chimtim 11y ago
Interesting to see the speech, vision API among others. I wonder what this means for metamind, clarifai and many other startups offering an API for doing something close?
36.
by chimtim 11y ago
This is a great experiment for computer vs computer simulations. When I played FIFA, I tried to buy cheap players with properties that worked well with my playing abilities. For me, at least until FIFA14 (did not try beyond that), a player&
37.
by chimtim 11y ago
AlphaGo can be beaten. It uses reinforcement learning so it will perform the set of moves that in the past led to its win. So predictable. Sedol just needs to take control and make it play in a predictable fashion. Also, perhaps play obscur
38.
by chimtim 11y ago
Another way to look at it would be that best-paper awards deserve much LESS credit than they are given. E.g. MapReduce did not get a best paper award but has been more influential than other best paper award winners.
39.
by chimtim 11y ago
"This year, I'll teach my simple AI to recognize patterns. I'll train it to recognize my voice so I can control my home through speaking. I'll train it to recognize my face so it can open the door when I'm approachi
40.
by chimtim 11y ago
I believe the Chess/Go engines are not really AI. They are operating on a set of rules written in code. It can compute and search the moves faster than a human. It can also remember a longer chain of moves better than a human can. But
41.
by chimtim 11y ago
what fault tolerance does spark give you in this scheme? It cannot look into TF progress and checkpoint all state. Using Spark with TF, seems like an overkill -- you need to manage and install two framework what should ideally be a 200 line
42.
by chimtim 11y ago
A good measure of any of the techniques are the results. We see record object recognition and speech recognition results. How many of these results are from Numenta or IBM neomorphic chips? Most successes have been on deep learning architec
43.
by chimtim 11y ago
This is not really true. ML applications in general do not scale linearly. There is the systems (scaling) overhead, and then there are the algorithm payoffs, which start to diminish depending on the algorithm. If they went from 4 to 8 GPUs,
44.
by chimtim 11y ago
Is this a machine with GPUs? You can order a similar looking design from acmemicro since last 4 years atleast?
45.
by chimtim 11y ago
Thanks a lot for your hard work! This is amazing work. I was wondering if you had any sense of which one of the models works best (or when one is better than another) -- Stanford, Toronto (Show, attend, tell), and Google (Show and tell) ?
46.
by chimtim 11y ago
IMHO, Google released Tensorflow because AI is currently being driven by research, and researchers were mostly writing code for Torch that is used at Facebook. So FB folks were enjoying lots of new algorithms, benchmarked against their syst
47.
by chimtim 11y ago
Appears to be only CUDA from the code. Also no distributed systems support released. Also, I cannot get it to work since this morning.
48.
by chimtim 11y ago
Do 10% speedups really matter for its success, if both libraries are ultimately calling into CUDNN? I do not think so. Right now, Torch/Caffe adoption is really good with lots of research code being released for it (even from within Go
49.
by chimtim 11y ago
My comment and the article are about AI research specifically, where there is lots of exciting new research due to the success of deep learning. And since the area is new, there is lot of low hanging fruit and challenging problems, which re
50.
by chimtim 11y ago
This is not how research works or a new fundamental technique is discovered. Any result needs to stand the rigor of peer-review before the said breakthrough can be conclusively proven (more unbiased minds trying to find the limitations of t
51.
by chimtim 11y ago
My guess is RankBrain is the personalization piece that operates on user data (location, history, etc.) while PageRank is the search index piece that operates on web data (web-pages, trends, etc.).
52.
by chimtim 11y ago
MSR has published lots of great papers but it has not yet replicated the success of PARC or Bell Labs by any means. I am not sure why this has happened, but it has been pretty obvious to everyone in the research community. Google, which cam
53.
by chimtim 11y ago
Hand-selecting a bunch of famous folks results in IAS Princeton effect which has the criticism of producing nothing significant. Usually the approach of hiring a towering/inspiring figure with an emerging research view works well (like
54.
by chimtim 11y ago
This was a fascinating read. I found the initial bit interesting that other models were ahead because they simply had more raw computational power, though it later adds that there may be other subtle differences.
55.
by chimtim 11y ago
VLDB accepts 150 papers and SIGMOD perhaps another 150. This is just top tier. I am pretty sure science can live without about more than 50% of those papers. I disagree with the tone of the original comment. But I do not disagree with the s
56.
by chimtim 11y ago
Static analysis tools are great for simple bugs. However, most compiler tools already fix these simple bugs. If there is a class of bugs not addressed by a compiler, most developers have a script to catch these. It may not find the harder t
57.
by chimtim 11y ago
This looks cool but I'm somewhat skeptical. I would be more interested in seeing what problem the system solves better or decently (say even MNIST) rather than how it was built using memristors. There is a lesson from IBM trying to mim
58.
by chimtim 12y ago
There is another paper, XStream from SOSP 2013, which ran a facebook sized graph on a single machine. I wonder what is "hot" in this HotOS submission?
59.
by chimtim 12y ago
If the dataset and/or computation fits in your laptop, why would you use a cluster framework? If you want to use multi-core, why would you not use the pthread library instead of using Spark, GraphX etc. The authors never show a pthread
60.
by chimtim 12y ago
O(N^2) is not exponential but just polynomial. O(2^N) is still exponential. O(N!) and O(N^N) are faster than exponential but not that much; O(N^N) grows slower than O(N!)[1]. Hyper-exponential is most likely double exponential O(a^b^N). The

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