Great talk from Andrej Karpathy about the challenges of building the Software 2.0 stack.
https://goo.gl/XxyZm1
https://t.iss.one/ArtificialIntelligenceArticles
https://goo.gl/XxyZm1
https://t.iss.one/ArtificialIntelligenceArticles
Figure Eight
Building the Software 2.0 Stack by Andrej Karpathy from Tesla
Figure Eight's Artificial Intelligence Resources Center has been created and curated for data science and machine learning teams
Machine Learning Top 10 Articles for the Past Month (v.June 2018)
❄️💦10 مقاله برتر یادگیری ماشین به انتخاب Mybridge در ماه گذشته
https://goo.gl/yTVtv1 @ArtificialIntelligenceArticles
❄️💦10 مقاله برتر یادگیری ماشین به انتخاب Mybridge در ماه گذشته
https://goo.gl/yTVtv1 @ArtificialIntelligenceArticles
Improving Language Understanding with Unsupervised Learning
Unsupervised pre-training + fine-tuning (NLP)
By Alec Radford : https://blog.openai.com/language-unsupervised/
https://t.iss.one/ArtificialIntelligenceArticles
Unsupervised pre-training + fine-tuning (NLP)
By Alec Radford : https://blog.openai.com/language-unsupervised/
https://t.iss.one/ArtificialIntelligenceArticles
Yann LeCun :
ConvNet outperforms human dermatologists for melanoma detection.
Dermatologists in level-II protocol:
- sensitivity: 88.9% (±9.6%, P = 0.19)
- specificity: 75.7% (±11.7%, P < 0.05).
ConvNet:
- sensitivity: 88.9%
- specificity: 82.5%
"Conclusions: For the first time we compared a CNN’s diagnostic performance with a large international group of 58 dermatologists, including 30 experts. Most dermatologists were outperformed by the CNN. Irrespective of any physicians’ experience, they may benefit from assistance by a CNN’s image classification"
paper : https://goo.gl/oybrZj
https://t.iss.one/ArtificialIntelligenceArticles
ConvNet outperforms human dermatologists for melanoma detection.
Dermatologists in level-II protocol:
- sensitivity: 88.9% (±9.6%, P = 0.19)
- specificity: 75.7% (±11.7%, P < 0.05).
ConvNet:
- sensitivity: 88.9%
- specificity: 82.5%
"Conclusions: For the first time we compared a CNN’s diagnostic performance with a large international group of 58 dermatologists, including 30 experts. Most dermatologists were outperformed by the CNN. Irrespective of any physicians’ experience, they may benefit from assistance by a CNN’s image classification"
paper : https://goo.gl/oybrZj
https://t.iss.one/ArtificialIntelligenceArticles
OUP Academic
Man against machine: diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition…
AbstractBackground. Deep learning convolutional neural networks (CNN) may facilitate melanoma detection, but data comparing a CNN’s diagnostic performance to l
پژوهشگران دانشگاه امآیتی موفق شدهاند با استفاده از هوش مصنوعی و امواج فرکانس رادیویی حرکات فیزیکی انسان رو از پشت دیوار تشخیص دهند
Artificial intelligence senses people through walls
Wireless smart-home system from the Computer Science and Artificial Intelligence Laboratory could monitor diseases and help the elderly “age in place.”
https://news.mit.edu/2018/artificial-intelligence-senses-people-through-walls-0612
paper: https://openaccess.thecvf.com/content_cvpr_2018/CameraReady/2406.pdf
https://t.iss.one/ArtificialIntelligenceArticles
Artificial intelligence senses people through walls
Wireless smart-home system from the Computer Science and Artificial Intelligence Laboratory could monitor diseases and help the elderly “age in place.”
https://news.mit.edu/2018/artificial-intelligence-senses-people-through-walls-0612
paper: https://openaccess.thecvf.com/content_cvpr_2018/CameraReady/2406.pdf
https://t.iss.one/ArtificialIntelligenceArticles
MIT News
Artificial intelligence senses people through walls
RF-Pose, a wireless smart-home system from the MIT Computer Science and Artificial Intelligence Laboratory, could monitor diseases and help the elderly “age in place.”
AI can now generate memes
Abel L Peirson V & E Meltem Tolunay:
Dank Learning. Generating Memes Using Deep Neural Networks
https://arxiv.org/abs/1806.04510 @ArtificialIntelligenceArticles
Abel L Peirson V & E Meltem Tolunay:
Dank Learning. Generating Memes Using Deep Neural Networks
https://arxiv.org/abs/1806.04510 @ArtificialIntelligenceArticles
Self-supervisory Signals for Object Discovery and Detection. https://arxiv.org/abs/1806.03370 @ArtificialIntelligenceArticles
Altered Fingerprints: Detection and Localization
Achieves a True Detection Rate (TDR) of 99.24% at a False Detection Rate (FDR) of 2%, outperforming published results
https://arxiv.org/abs/1805.0091
Achieves a True Detection Rate (TDR) of 99.24% at a False Detection Rate (FDR) of 2%, outperforming published results
https://arxiv.org/abs/1805.0091
AI could get 100 times more energy-efficient with IBM’s new artificial synapses
Copying the features of a neural network in silicon might make machine learning more usable on small devices like smartphones.
https://goo.gl/hFfg69
paper : https://goo.gl/xyXbWo
https://t.iss.one/ArtificialIntelligenceArticles
Copying the features of a neural network in silicon might make machine learning more usable on small devices like smartphones.
https://goo.gl/hFfg69
paper : https://goo.gl/xyXbWo
https://t.iss.one/ArtificialIntelligenceArticles
MIT Technology Review
AI could get 100 times more energy-efficient with IBM’s new artificial synapses
Copying the features of a neural network in silicon might make machine learning more usable on small devices like smartphones.
مقاله جدیدی از پروفسور Li Fei-Fei
new paper : Li Fei-Fei
Learning to Decompose and Disentangle Representations for Video Prediction. https://arxiv.org/abs/1806.04166 @ArtificialIntelligenceArticles
new paper : Li Fei-Fei
Learning to Decompose and Disentangle Representations for Video Prediction. https://arxiv.org/abs/1806.04166 @ArtificialIntelligenceArticles
vulnerabilities in #deeplearning could lead to new kinds of healthcare fraud and other issues https://goo.gl/JBktiY @ArtificialIntelligenceArticles
Generating NES music using deep learning
Code : https://github.com/chrisdonahue/nesmdb
Paper: https://arxiv.org/abs/1806.04278 @ArtificialIntelligenceArticles
Code : https://github.com/chrisdonahue/nesmdb
Paper: https://arxiv.org/abs/1806.04278 @ArtificialIntelligenceArticles
A nice review article about relational reasoning, relational inductive biases in typical deep learning building blocks, and graph networks. https://arxiv.org/abs/1806.01261 @ArtificialIntelligenceA
Theoretical Impediments to Machine Learning With Seven Sparks from the Causal Revolution": Judea Pearl presents seven tasks which he claims are beyond reach of current machine learning systems but have been accomplished using the tools of causal modeling.
https://arxiv.org/abs/1801.04016
https://t.iss.one/ArtificialIntelligenceArticles
https://arxiv.org/abs/1801.04016
https://t.iss.one/ArtificialIntelligenceArticles
Telegram
ArtificialIntelligenceArticles
for who have a passion for -
1. #ArtificialIntelligence
2. Machine Learning
3. Deep Learning
4. #DataScience
5. #Neuroscience
6. #ResearchPapers
7. Related Courses and Ebooks
1. #ArtificialIntelligence
2. Machine Learning
3. Deep Learning
4. #DataScience
5. #Neuroscience
6. #ResearchPapers
7. Related Courses and Ebooks
مقاله ی از دکتر علی اسلامی محقق Google DeepMind
https://deepmind.com/blog/neural-scene-representation-and-rendering/
paper :https://science.sciencemag.org/content/360/6394/1204
https://deepmind.com/blog/neural-scene-representation-and-rendering/
paper :https://science.sciencemag.org/content/360/6394/1204
Instant 3D Photography
Hedman et al.: https://visual.cs.ucl.ac.uk/pubs/instant3d/ @ArtificialIntelligenceArticles
Hedman et al.: https://visual.cs.ucl.ac.uk/pubs/instant3d/ @ArtificialIntelligenceArticles
🚀 100 Times Faster Natural Language Processing in Python
https://goo.gl/vX9zea
https://t.iss.one/ArtificialIntelligenceArticles
https://goo.gl/vX9zea
https://t.iss.one/ArtificialIntelligenceArticles
Medium
🚀 100 Times Faster Natural Language Processing in Python
How to take advantage of spaCy & a bit of Cython for blazing fast NLP
IBM researchers use analog memory to train deep NeuralNetworks faster than with GPUs, using hundreds of times less energy: https://goo.gl/jB4BWW paper : https://goo.gl/u1EE6C
NCRF++: An Open-source Neural Sequence Labeling Toolkit
GitHub : https://github.com/jiesutd/NCRFpp
paper : https://arxiv.org/abs/1806.05626 @ArtificialIntelligenceArticles
GitHub : https://github.com/jiesutd/NCRFpp
paper : https://arxiv.org/abs/1806.05626 @ArtificialIntelligenceArticles
End-to-End Parkinson Disease Diagnosis using Brain MR-Images by 3D-CNN. https://arxiv.org/abs/1806.05233 @ArtificialIntelligenceArticles