vrv
No user record in our sample, but vrv has activity below (stories or comments). Likely we have partial data — the full bulk-load will fill profiles in.
No user record in our sample, but vrv has activity below (stories or comments). Likely we have partial data — the full bulk-load will fill profiles in.
MintMCP | Founding Engineer / Founding GTM | SF Bay Area (ONSITE) MintMCP helps enterprises safely roll out agents to the entire organization (e.g, governance around MCP tools and agents like Claude Code / Codex /…
MintMCP | Founding Engineer / Founding GTM | SF Bay Area (ONSITE) MintMCP helps enterprises safely do more with Agents (e.g, governance around MCP tools and agents like Claude Code / Cowork, and others). We're building…
Agreed, OAuth is certainly preferred for many reasons, but replace "API keys" with "OAuth access tokens" and you have the same fundamental challenge of ensuring an LLM or untrusted code never has access to the user's…
If the output schema specifies an id field, the LLM can write a code snippet that references it based on the context of the subsequent request, but the LLM doesn't need to observe the underlying value unless necessary.…
bfloat16 was first in DistBelief, so it actually predates TensorFlow and TPUs (I worked on both systems). IIRC the motivation was more about minimizing parameter exchange bandwidth for large-scale CPU clusters rather…
Thanks for mentioning that Sam, I appreciate it. Speaking for just myself: I personally don't care what tools or frameworks people use to get work done and have repeatedly suggested people use whatever works best for…
I'm sorry to hear of that experience, and it's certainly not intentional. We should (and I will) always try to be better (I know some will forever view Google as an antagonistic behemoth but usually the engineers on…
The codebase in GitHub is pretty much exactly the same as the internal, the main exceptions being things like having to rewrite include paths for files, filesystem plugins for internal cluster filesystems, etc; and…
(I made this change anyway).
wrt GPU memory: If we made InteractiveSession by default grow memory, would that work for you? Seems sensible to change the default for InteractiveSession (e.g., for use in notebooks), but not the default for Session…
TensorFlow doesn't yet do loop fusion (though I believe the specific example shown in that article may already be done via constant folding). But if you have a bunch of elementwise operations, JIT-techniques can reduce…
Windows support is definitely being worked on and lots of progress has been made, so it will eventually arrive -- just lots of little details to work out, but we're optimistic it'll come soon.
For what it's worth, we're hoping to integrate these APIs into our iOS version of the TensorFlow runtime, so you can maintain graph portability but still get the benefits of the optimized implementation on the platform.…
FYI, TF now supports: 1) dynamic RNNs, 2) bidirectional RNNs and will soon have 3D convolution -- that comparison is a little out of date.
The arxiv paper is just a repost of the preliminary paper, which is really more a design outline and rationale -- we may work on a more substantial paper later, we've been busy building the software.
I believe our published wheels now include the code for cuda compute 3.0, so it should work out of the box now. (as long as the images have cudnn v4 and cuda 7.5 installed, I think :)
It's on the roadmap: https://www.tensorflow.org/versions/r0.8/resources/roadmap.h...
(Do you have an example link that doesn't work? I clicked a bunch of links there and they were all working. Feel free to file a bug at github.com/tensorflow/tensorflow)
And even those numbers on the front page are out of date :) (we're even faster now: https://github.com/soumith/convnet-benchmarks/pull/96, which is from a few weeks ago.) The field is moving quickly enough that many…
In our issues template, we start it with: "GitHub issues are for bugs / installation problems / feature requests. For general support from the community, see [StackOverflow](link)" However, we still get plenty of issues…
Can you point me to "current memory utilization" numbers you're referring to?
Indeed we are. Here's a recent commit from today https://github.com/tensorflow/tensorflow/commit/d6f3ebfdfc1d... :)
Keeping that up-to-date and useful is as hard as keeping benchmarks in Deep Learning up to date ;)
Yeah, those are just cards we know that work: we don't have all possible GPUs to test our 20+ changes a day on, so we can't formally guarantee it will work on older cards, but in general we try our best to keep it all…
Feel free to ping us (TensorFlow) on github issues to get installation issues resolved -- on cudnn r4 we're doing much better, and we're soon to check in a series of changes to get us roughly on par with Torch on cudnn…