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Listen "49. Nvidia A100, Training Game AI, Neural Networks | AI Developer Interview"
Episode Synopsis
Hot off the heels of the announcement of Nvidia A100, we have an AI Developer on to talk about what these massive GPU’s are actually used for – AI & ML applications.
SPONSOR: https://www.cdkoffers.com
25% Windows Code discount: brokensilicon
3% off all software: dieshrink
Win10 pro oem key 13$: https://bit.ly/2Wdfghh
Win10 Home oem key 10$: https://bit.ly/3dsbSFi
Office 2016 key 27$: https://bit.ly/2Wb3sMx
Office 2019 key 44$: https://bit.ly/2WdfBAz
Win10 pro oem+Office 2016 35$: https://bit.ly/3bkJeVb
1:21 AI Buzzwords & Introductions (some sound issues)
6:03 What is a Neural Network?
12:53 Challenges in Training Neural Networks
16:21 Sparsity and Pruning
24:03 How will AI Improve our Lives?
35:42 Bottlenecks to AI Research
42:03 AI & ML in Gaming
47:38 CUDA Intrenchment, AMD’s ability to enter the market
50:58 Cerebras & Graphcore
55:53 AMD vs Nvidia Graphics
1:03:13 Comparing Synthetic AI to Biological Brains
https://www.thispersondoesnotexist.com/
https://devblogs.nvidia.com/nvidia-ampere-architecture-in-depth/
https://www.cerebras.net/cerebras-wafer-scale-engine-why-we-need-big-chips-for-deep-learning/
https://cirrascale.com/graphcore-cloud.php?utm_term=graphcore&utm_source=adwords&utm_medium=ppc&utm_campaign=Graphcore&hsa_net=adwords&hsa_grp=86815837387&hsa_mt=p&hsa_tgt=kwd-606839681642&hsa_kw=graphcore&hsa_src=g&hsa_acc=2793442874&hsa_cam=8112712212&hsa_ver=3&hsa_ad=397149594120&gclid=CjwKCAjwwYP2BRBGEiwAkoBpAuc9L_R5wt9rbYuJ7jeopg5W5YdYxaFBkNVpQz336TjcNJYg9jyZ2BoCX0MQAvD_BwE
https://arxiv.org/pdf/1803.03635.pdf
https://arxiv.org/pdf/1807.01281.pdf
https://podcasts.google.com/feed/aHR0cHM6Ly9jaGFuZ2Vsb2cuY29tL3ByYWN0aWNhbGFpL2ZlZWQ/episode/Y2hhbmdlbG9nLmNvbS83LzcwNA?hl=en&ved=2ahUKEwiuzYfG_7jpAhUIHs0KHSavAhAQjrkEegQIBxAE&ep=6
https://twimlai.com/upside-down-reinforcement-learning/?fbclid=IwAR18e99xWPGUN0_SVG84IKUaT5KYSKVhzwMdq37goiOdDwRuUf8s9Z_8GSI
https://en.wikipedia.org/wiki/Reinforcement_learning
https://en.wikipedia.org/wiki/Concept_learning
https://en.wikipedia.org/wiki/Unsupervised_learning#cite_note-2
https://arxiv.org/abs/1912.02875
https://arxiv.org/pdf/1912.02877.pdf
https://www.alexirpan.com/2018/02/14/rl-hard.html
https://www.microsoft.com/en-us/research/blog/turing-nlg-a-17-billion-parameter-language-model-by-microsoft/
https://ai.facebook.com/blog/state-of-the-art-open-source-chatbot/
https://openai.com/blog/jukebox/
https://www.pnas.org/content/pnas/116/43/21854.full.pdf Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
SPONSOR: https://www.cdkoffers.com
25% Windows Code discount: brokensilicon
3% off all software: dieshrink
Win10 pro oem key 13$: https://bit.ly/2Wdfghh
Win10 Home oem key 10$: https://bit.ly/3dsbSFi
Office 2016 key 27$: https://bit.ly/2Wb3sMx
Office 2019 key 44$: https://bit.ly/2WdfBAz
Win10 pro oem+Office 2016 35$: https://bit.ly/3bkJeVb
1:21 AI Buzzwords & Introductions (some sound issues)
6:03 What is a Neural Network?
12:53 Challenges in Training Neural Networks
16:21 Sparsity and Pruning
24:03 How will AI Improve our Lives?
35:42 Bottlenecks to AI Research
42:03 AI & ML in Gaming
47:38 CUDA Intrenchment, AMD’s ability to enter the market
50:58 Cerebras & Graphcore
55:53 AMD vs Nvidia Graphics
1:03:13 Comparing Synthetic AI to Biological Brains
https://www.thispersondoesnotexist.com/
https://devblogs.nvidia.com/nvidia-ampere-architecture-in-depth/
https://www.cerebras.net/cerebras-wafer-scale-engine-why-we-need-big-chips-for-deep-learning/
https://cirrascale.com/graphcore-cloud.php?utm_term=graphcore&utm_source=adwords&utm_medium=ppc&utm_campaign=Graphcore&hsa_net=adwords&hsa_grp=86815837387&hsa_mt=p&hsa_tgt=kwd-606839681642&hsa_kw=graphcore&hsa_src=g&hsa_acc=2793442874&hsa_cam=8112712212&hsa_ver=3&hsa_ad=397149594120&gclid=CjwKCAjwwYP2BRBGEiwAkoBpAuc9L_R5wt9rbYuJ7jeopg5W5YdYxaFBkNVpQz336TjcNJYg9jyZ2BoCX0MQAvD_BwE
https://arxiv.org/pdf/1803.03635.pdf
https://arxiv.org/pdf/1807.01281.pdf
https://podcasts.google.com/feed/aHR0cHM6Ly9jaGFuZ2Vsb2cuY29tL3ByYWN0aWNhbGFpL2ZlZWQ/episode/Y2hhbmdlbG9nLmNvbS83LzcwNA?hl=en&ved=2ahUKEwiuzYfG_7jpAhUIHs0KHSavAhAQjrkEegQIBxAE&ep=6
https://twimlai.com/upside-down-reinforcement-learning/?fbclid=IwAR18e99xWPGUN0_SVG84IKUaT5KYSKVhzwMdq37goiOdDwRuUf8s9Z_8GSI
https://en.wikipedia.org/wiki/Reinforcement_learning
https://en.wikipedia.org/wiki/Concept_learning
https://en.wikipedia.org/wiki/Unsupervised_learning#cite_note-2
https://arxiv.org/abs/1912.02875
https://arxiv.org/pdf/1912.02877.pdf
https://www.alexirpan.com/2018/02/14/rl-hard.html
https://www.microsoft.com/en-us/research/blog/turing-nlg-a-17-billion-parameter-language-model-by-microsoft/
https://ai.facebook.com/blog/state-of-the-art-open-source-chatbot/
https://openai.com/blog/jukebox/
https://www.pnas.org/content/pnas/116/43/21854.full.pdf Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
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