[deleted]
Jeff Dean explains TensorFlow [video]
41–50 of 71 posts
Re: Jeff Dean explains TensorFlow [video]
#42Earlier quoted context omitted.
That's not really a fundamental differentiator. Torch/Theano are definitely production ready. I think the portability is definitely an advantage, though.
I think you would not use Theano in an end-user product. It's made for developers to run on developer machines. It's very fragile. It has a very long start-up time, might be in the order of several minutes at the first start. Maybe it would work good enough in a service backend. But even there it would not scale that well. For example, it doesn't support multi-threading (running a theano.function from multiple thread…
Good point. Torch, then.
Re: Jeff Dean explains TensorFlow [video]
#43TensorFlow looks amazing, and the Google team deserves huge kudos for open-sourcing it. It may well become one of the best supported OS DL frameworks out there.
People have been asking about its fundamental differentiators. I'm not sure there are any. Theano and Torch already set a pretty high standard.
We know what good tools look like, and those tools exist even if they're getting incremental improvements.
Now it's just a matter of building really cool things with them.
Re: Jeff Dean explains TensorFlow [video]
#44FYI, Jeff Dean is the inventor of most of Google's distributed computing infrastructure including MapReduce. Definitely up there with the likes of John Carmack and Fabrice Bellard as one of the great software engineers of all time.
This is the MapReduce white paper, from Jeffrey Dean and Sanjay Ghemawat, 2004, if people are interested. http://research.google.com/archive/mapreduce.html
Re: Jeff Dean explains TensorFlow [video]
#45FYI, Jeff Dean is the inventor of most of Google's distributed computing infrastructure including MapReduce. Definitely up there with the likes of John Carmack and Fabrice Bellard as one of the great software engineers of all time.
The Jeff Dean Facts are worth reading: https://www.quora.com/What-are-all-the-Jeff-Dean-facts Personal favorite: "Jeff Dean once shifted a bit so hard, it ended up on another computer."
"Jeff Dean's resume lists the things he hasn't done; it's shorter that way."
Re: Jeff Dean explains TensorFlow [video]
#46This is from ~22nd of October, and he is being asked whether it is an internal thing or going to be released - his answer is that it is internal and there are no plans to release it. Did they change their mind in a couple of days (not likely)? Was he not in the loop (also unlikely)? What else?
Maybe touching to lips gesture is a body language sign of not telling the exact truth:
https://youtu.be/90-S1M7Ny_o?t=2043
He says "I don't have anything to announce" so technically not lying.
Re: Jeff Dean explains TensorFlow [video]
#47Yay!! An open sourced voice engine in the future? That would really shake things up.
No. a) Stuff similar to this has been available for ages and there are no (good) open source voice recognition packages. b) It requires absolute mountains of training data which we don't have. c) It requires designing a suitable network, which I'm not sure if we have, but I would doubt it. d) It requires training a network on the mountains of training data using an immense computing cluster, which we requires money t…
Can anyone explain why was this downvoted?
Re: Jeff Dean explains TensorFlow [video]
#48Just wanted to repost this from the other thread on TensorFlow, since I joined the party a bit late: I think some of the raving that's going on is unwarranted. This is a very nice , very well put together library with a great landing page. It might eventually displace Torch and Theano as the standard toolkits for deep learning. It looks like it might offer performance / portability improvements. But it does not do an…
I think the fundamental differentiator might be how "production ready" TensorFlow is - the promise of simply declaring an ML pipeline and have that run in very heterogeneous compute environments from mobile phones to GPU blades to plain-old clusters, if fulfilled, can indeed be a huge game changer. The promise is that you literally do not have to write any new code when you are done with a research project / a series…
Torch is used in production by Facebook , deepmind and possibly baidu, amongst others. Facebook especially have released code to make torch run much faster on AWS with GPU cards. Also no startup time. The design is done with a high level language (lua) while computation done mostly in C. I'd be very surprised if tensorflow is actually faster than torch on a single machine
Re: Jeff Dean explains TensorFlow [video]
#49Earlier quoted context omitted.
I'd wager that way more people know who Jeff Dean is than know who Fabrice Bellard is.
Maybe some people do, personally I'm more familiar with the works of Fabrice Bellard, and that's probably fair enough since I expect I have more pieces of software derived from Bellard projects installed on my machine than I do software derived from Jeff Dean projects (not to criticise Jeff Dean, who I'm sure is very inspirational).
I just wanted to do a +1 here, but as it is not very HN-worthy, I'll provide a little bit more of work, and just say that a search in HNSearch for "Fabrice Bellard" produced 3 pages of results for tha last year, whereas "Jeff Dean" only produced 2.
Personally, I feel I've been more exposed to Fabrice Bellard's work, which might be not true, but I first learned of Jeff Dean's existence yesterday.
Re: Jeff Dean explains TensorFlow [video]
#50Yay!! An open sourced voice engine in the future? That would really shake things up.
No. a) Stuff similar to this has been available for ages and there are no (good) open source voice recognition packages. b) It requires absolute mountains of training data which we don't have. c) It requires designing a suitable network, which I'm not sure if we have, but I would doubt it. d) It requires training a network on the mountains of training data using an immense computing cluster, which we requires money t…
I agree there. Plenty to be done still.