Facebook AI Research uses Torch7 for many projects, as do Deep Mind and several groups at Google.
Mostly true True in substance, wrong in a detail.
Factual: Statements about the present or the past, checked against the record: did they hold up?
The second judge said mixed; the verdict shown is the first judge's.
Said for an organisation they lead or work for; it counts on both records.
What would count as true or false
True if evidence from around May 2014 shows that Facebook AI Research used Torch7 for many projects and that DeepMind and several groups at Google also used Torch7. Mostly true if all three uses are confirmed but the extent differs a little (for example only a few FAIR projects, or one or two Google groups). Mixed if FAIR's use is confirmed but use by DeepMind or by Google groups is not, or the other way round. Mostly false if only one of the three uses can be confirmed and the others are contradicted. False if the evidence shows FAIR did not use Torch7 at that time.
Set before the research began.
Evidence (3)
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E1 DeepMind moves to TensorFlow Google Research blog · 29 April 2016
“For nearly four years, the open source Torch7 machine learning library has served as our primary research platform, combining excellent flexibility with very fast runtime execution, enabling rapid prototyping.”
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E2 FAIR open sources deep-learning modules for Torch Facebook Engineering (originally Facebook AI Research blog) · 16 January 2015 Own record
“Many research projects on machine learning and AI at FAIR use Torch, an open source development environment for numerics, machine learning, and computer vision, with a particular emphasis on deep learning and convolutional nets.”
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E3 FAIR open sources deep-learning modules for Torch Facebook Engineering (originally Facebook AI Research blog) · 16 January 2015 Own record
“Torch is widely used at a number of academic labs as well as at Google/DeepMind, Twitter, NVIDIA, AMD, Intel, and many other companies.”
Reasoning
E1, an independent Google Research post from April 2016, says Torch7 had been DeepMind's primary research platform for nearly four years. That covers May 2014. In E2, a January 2015 FAIR announcement, FAIR says many of its research projects use Torch, which supports FAIR's use around the time of the claim, though this source is FAIR's own. Use by several separate Google groups is backed only by FAIR's own mention of 'Google/DeepMind' in E3, which may not separate Google from DeepMind. FAIR's and DeepMind's use is supported, but the 'several groups at Google' part is only weakly confirmed, so the verdict is mostly true.
Cite this claim
Yann LeCun, “Facebook AI Research uses Torch7 for many projects, as do Deep Mind and several groups at Google.” (said 15 May 2014). Verdict: mostly true. Reliability API, claim c_ffe5c5de072c, method 0.1.0+c876030c, dataset release v1.1.2. https://epistacklabs.com/claims/c_ffe5c5de072c
This claim is in dataset release v1.1.2, with the same verdict.
Reply to this claim
More factual claims by Yann LeCun
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Mostly true
“This white-noise sounding signal with a flat spectrum is the pseudo-random bit sequence used to pre-train the adaptive equalizer that cleans up the mushy analog signal into clean bits.”
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Resolved true
“Opacus: a new PyTorch library for ML with differential privacy.”
Facebook AI released Opacus, a new PyTorch library for machine learning with differential privacy.
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Resolved true
“Announcing PyTorch Hub!”
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Resolved false
““Those agents are doing exactly what they’ve been asked to do,” LeCun said.”
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Resolved true
““It’s AI for the physical world, so it’s not language-related,” LeCun said.”
AMI Labs' work is AI for the physical world and is not language-related.
Verdicts are made automatically; how verdicts are made.