Yannic Kilcher Videos (Audio Only)

#mlnews #cedille #wmt Only the greatest of news from the world of Machine Learning. OUTLINE: 0:00 - Sponsor: Weights & Biases 1:50 - Cedille - French Language Model 3:55 - Facebook AI Multilingual model wins WMT 5:50 - YOU private search engine 10:35 - DeepMind's Open-Source Arnheim 12:10 - Company sued for using AI to make website more accessible 18:05 - Alibaba DAMO Academy creates 10 Trillion M6 model 21:15 - AMD MI200 Family 22:30 - State of AI report 2021 24:15 - Andrew Ng's Landing AI raises 57M 25:40 - Cerebras raises 250M 26:45 - Microsoft's Varuna: Scalable Training of Huge Models 28:15 - Laura Ruis reproduces Extrapolation Paper 29:05 - Ian Charnas' Real-Life Punchout 30:00 - Helpful Things 33:10 - AI finds profitable Meme-Tokens 34:55 - This Sneaker Does Not Exist Sponsor: Weights & Biases https://wandb.com References: Cedille - French Language Model https://en.cedille.ai/ https://github.com/coteries/cedille-ai https://app.cedille.ai/ https://en.wikipedia.org/wiki/Cedilla Facebook AI Multilingual model wins WMT https://ai.facebook.com/blog/the-firs... YOU private search engine https://you.com/ https://youdotcom.notion.site/FAQ-8c8... DeepMind's Open-Source Arnheim https://deepmind.com/research/open-so... https://twitter.com/OriolVinyalsML/st... https://github.com/deepmind/arnheim https://colab.research.google.com/git... Company sued for using AI to make website more accessible https://www.wired.com/story/company-t... https://archive.ph/kdvOM Alibaba DAMO Academy creates 10 Trillion M6 model https://pandaily.com/alibaba-damo-aca... https://www.infoq.cn/article/xIX9leku... AMD MI200 Family https://www.anandtech.com/show/17054/... State of AI report 2021 https://www.stateof.ai/?utm_source=po... Andrew Ng's Landing AI raises 57M https://techcrunch.com/2021/11/08/lan... https://www.forbes.com/sites/bernardm... https://landing.ai/platform/ Cerebras raises 250M https://cerebras.net/news/cerebras-sy... https://cerebras.net/news/cerebras-sy... Microsoft's Varuna: Scalable Training of Huge Models https://syncedreview.com/2021/11/10/d... Laura Ruis reproduces Extrapolation Paper https://lauraruis.github.io/2021/11/0... https://github.com/LauraRuis Ian Charnas' Real-Life Punchout https://www.reddit.com/r/MachineLearn... https://www.youtube.com/watch?v=07Jib... Helpful Things https://www.marktechpost.com/2021/11/... https://pair-code.github.io/lit/demos/ https://github.com/pair-code/lit https://www.reddit.com/r/MachineLearn... https://twitter.com/yeemachine/status... https://github.com/yeemachine/kalidokit AI finds profitable Meme-Tokens https://finance.yahoo.com/news/artifi... https://finu.co/ This Sneaker Does Not Exist https://thissneakerdoesnotexist.com/ Links: TabNine Code Completion (Referral): http://bit.ly/tabnine-yannick YouTube: https://www.youtube.com/c/yannickilcher Twitter: https://twitter.com/ykilcher Discord: https://discord.gg/4H8xxDF BitChute: https://www.bitchute.com/channel/yann... LinkedIn: https://www.linkedin.com/in/ykilcher BiliBili: https://space.bilibili.com/2017636191 If you want to support me, the best thing to do is to share out the content :)

#deeplearning #backpropagation #simulation More and more systems are made differentiable, which means that accurate gradients of these systems' dynamics can be computed exactly. While this development has led to a lot of advances, there are also distinct situations where backpropagation can be a very bad idea. This paper characterizes a few such systems in the domain of iterated dynamical systems, often including some source of stochasticity, resulting in chaotic behavior. In these systems, it is often better to use black-box estimators for gradients than computing them exactly. OUTLINE: 0:00 - Foreword 1:15 - Intro & Overview 3:40 - Backpropagation through iterated systems 12:10 - Connection to the spectrum of the Jacobian 15:35 - The Reparameterization Trick 21:30 - Problems of reparameterization 26:35 - Example 1: Policy Learning in Simulation 33:05 - Example 2: Meta-Learning Optimizers 36:15 - Example 3: Disk packing 37:45 - Analysis of Jacobians 40:20 - What can be done? 45:40 - Just use Black-Box methods Paper: https://arxiv.org/abs/2111.05803 Abstract: Differentiable programming techniques are widely used in the community and are responsible for the machine learning renaissance of the past several decades. While these methods are powerful, they have limits. In this short report, we discuss a common chaos based failure mode which appears in a variety of differentiable circumstances, ranging from recurrent neural networks and numerical physics simulation to training learned optimizers. We trace this failure to the spectrum of the Jacobian of the system under study, and provide criteria for when a practitioner might expect this failure to spoil their differentiation based optimization algorithms. Authors: Luke Metz, C. Daniel Freeman, Samuel S. Schoenholz, Tal Kachman Links: TabNine Code Completion (Referral): http://bit.ly/tabnine-yannick YouTube: https://www.youtube.com/c/yannickilcher Twitter: https://twitter.com/ykilcher Discord: https://discord.gg/4H8xxDF BitChute: https://www.bitchute.com/channel/yann... LinkedIn: https://www.linkedin.com/in/ykilcher BiliBili: https://space.bilibili.com/2017636191 If you want to support me, the best thing to do is to share out the content :) If you want to support me financially (completely optional and voluntary, but a lot of people have asked for this): SubscribeStar: https://www.subscribestar.com/yannick... Patreon: https://www.patreon.com/yannickilcher Bitcoin (BTC): bc1q49lsw3q325tr58ygf8sudx2dqfguclvngvy2cq Ethereum (ETH): 0x7ad3513E3B8f66799f507Aa7874b1B0eBC7F85e2 Litecoin (LTC): LQW2TRyKYetVC8WjFkhpPhtpbDM4Vw7r9m Monero (XMR): 4ACL8AGrEo5hAir8A9CeVrW8pEauWvnp1WnSDZxW7tziCDLhZAGsgzhRQABDnFy8yuM9fWJDviJPHKRjV4FWt19CJZN9D4n

#mlnews #turing #reskin The latest and greatest from the Machine Learning world Sponsor: Weights & Biases https://wandb.com References: Microsoft Turing Bletchley: Universal Image Language Representation Model https://www.microsoft.com/en-us/resea... https://turing.microsoft.com/bletchley Meta AI Tactile Sensing https://ai.facebook.com/blog/teaching... https://ai.facebook.com/blog/reskin-a... https://twitter.com/AIatMeta/status/1... AnimeGANv2 https://huggingface.co/spaces/akhaliq... https://github.com/bryandlee/animegan... https://github.com/TachibanaYoshino/A... https://tachibanayoshino.github.io/An... General In-Hand Object Re-Orientation https://taochenshh.github.io/projects... https://arxiv.org/abs/2111.03043 Does Facebook score the "Anger" Emoji too high? https://www.washingtonpost.com/techno... IsomorphicLabs: New Alphabet Company for Drug Discovery https://twitter.com/demishassabis/sta... https://www.isomorphiclabs.com/blog ruDALL-E: Russian DALL-E https://github.com/sberbank-ai/ru-dalle https://huggingface.co/spaces/anton-l... https://colab.research.google.com/git... https://huggingface.co/sberbank-ai/ru... https://rudalle.ru/ https://habr.com/ru/company/sberbank/... https://habr-com.translate.goog/ru/co... Image Scaling Attacks https://twitter.com/AlexTamkin/status... https://twitter.com/rzhang88/status/1... https://arxiv.org/abs/2104.11222 https://twitter.com/arxiv_org/status/... https://bifold.berlin/preventing-imag... https://embracethered.com/blog/posts/... Azure OpenAI Service https://blogs.microsoft.com/ai/new-az... https://azure.microsoft.com/en-us/ser... Neural MMO https://openai.com/blog/neural-mmo/?u... https://github.com/jsuarez5341/neural... https://github.com/jsuarez5341/neural... https://jsuarez5341.github.io/neural-... https://jsuarez5341.github.io/neural-... https://arxiv.org/abs/2110.07594 ArxivDOOM https://sniklaus.com/arxivdoom?utm_so... ARC Game https://github.com/volotat/ARC-Game https://volotat.github.io/ARC-Game/? ResNeXtGuesser https://twitter.com/resnextguesser/st... Zillow loses money based on AI home price estimation https://www.reddit.com/r/MachineLearn... https://www.cbsnews.com/news/zillow-l... https://www.businessinsider.com/zillo... https://archive.ph/qEITQ Helpful Things https://github.com/PyTorchLightning/p... https://www.reddit.com/r/MachineLearn... https://devpost.com/software/iris-7s3yna https://github.com/prabhuomkar/iris https://araffin.github.io/post/rliable/ https://github.com/google-research/rl... https://paperswithcode.com/dataset/me... AI will make your company great! Promise, Human! https://fortune.com/2021/11/05/ai-art... https://sloanreview.mit.edu/projects/...

#machinelearning #ardm #generativemodels Diffusion models have made large advances in recent months as a new type of generative models. This paper introduces Autoregressive Diffusion Models (ARDMs), which are a mix between autoregressive generative models and diffusion models. ARDMs are trained to be agnostic to the order of autoregressive decoding and give the user a dynamic tradeoff between speed and performance at decoding time. This paper applies ARDMs to both text and image data, and as an extension, the models can also be used to perform lossless compression. OUTLINE: 0:00 - Intro & Overview 3:15 - Decoding Order in Autoregressive Models 6:15 - Autoregressive Diffusion Models 8:35 - Dependent and Independent Sampling 14:25 - Application to Character-Level Language Models 18:15 - How Sampling & Training Works 26:05 - Extension 1: Parallel Sampling 29:20 - Extension 2: Depth Upscaling 33:10 - Conclusion & Comments Paper: https://arxiv.org/abs/2110.02037 Abstract: We introduce Autoregressive Diffusion Models (ARDMs), a model class encompassing and generalizing order-agnostic autoregressive models (Uria et al., 2014) and absorbing discrete diffusion (Austin et al., 2021), which we show are special cases of ARDMs under mild assumptions. ARDMs are simple to implement and easy to train. Unlike standard ARMs, they do not require causal masking of model representations, and can be trained using an efficient objective similar to modern probabilistic diffusion models that scales favourably to highly-dimensional data. At test time, ARDMs support parallel generation which can be adapted to fit any given generation budget. We find that ARDMs require significantly fewer steps than discrete diffusion models to attain the same performance. Finally, we apply ARDMs to lossless compression, and show that they are uniquely suited to this task. Contrary to existing approaches based on bits-back coding, ARDMs obtain compelling results not only on complete datasets, but also on compressing single data points. Moreover, this can be done using a modest number of network calls for (de)compression due to the model's adaptable parallel generation. Authors: Emiel Hoogeboom, Alexey A. Gritsenko, Jasmijn Bastings, Ben Poole, Rianne van den Berg, Tim Salimans Links: TabNine Code Completion (Referral): http://bit.ly/tabnine-yannick YouTube: https://www.youtube.com/c/yannickilcher Twitter: https://twitter.com/ykilcher Discord: https://discord.gg/4H8xxDF BitChute: https://www.bitchute.com/channel/yann... Minds: https://www.minds.com/ykilcher Parler: https://parler.com/profile/YannicKilcher LinkedIn: https://www.linkedin.com/in/ykilcher BiliBili: https://space.bilibili.com/1824646584 If you want to support me, the best thing to do is to share out the content :) If you want to support me financially (completely optional and voluntary, but a lot of people have asked for this): SubscribeStar: https://www.subscribestar.com/yannick... Patreon: https://www.patreon.com/yannickilcher Bitcoin (BTC): bc1q49lsw3q325tr58ygf8sudx2dqfguclvngvy2cq Ethereum (ETH): 0x7ad3513E3B8f66799f507Aa7874b1B0eBC7F85e2 Litecoin (LTC): LQW2TRyKYetVC8WjFkhpPhtpbDM4Vw7r9m

#pathways #mlnews #ego4d Your irregular dose of Machine Learning News. OUTLINE: 0:00 - Intro 0:20 - Sponsor: Weights & Biases 2:10 - Google Introduces Pathways AI Architecture 6:30 - OpenAI trains Language Models to do High School Math 8:25 - Sam Altman says Neural Networks truly learn 9:35 - Google AI researchers frustrated with lawyers 12:10 - DeepMind RL Lecture Series 2021 12:40 - Fashion Store sells Adversarial Patches 13:15 - A viable method to remove the GIL from CPython 15:05 - BigScience Workshop releases T0 17:40 - Huggingface Hub Dataset Viewer 18:10 - Scite classifies scientific citations 19:25 - Facebook AI Ego4D dataset & challenges 21:50 - Tesla Dojo Configurable Floating Point Spec 23:10 - Windows releases PyTorch-DirectML for Deep Learning on DirectX GPUs 23:50 - Helpful Things 33:00 - Traders use ML to analyze CEOs' language 34:20 - Cadbury creates DeepFake ads for local Indian businesses 35:25 - This Shoe Does Not Exist Sponsor: Weights & Biases https://wandb.com References: Google Introduces Pathways AI Architecture https://blog.google/technology/ai/int... OpenAI trains Language Models to do High School Math https://openai.com/blog/grade-school-... https://arxiv.org/abs/2110.14168 Sam Altman says Neural Networks truly learn https://twitter.com/sama/status/14508... Google AI researchers frustrated with lawyers https://archive.ph/lsQJJ#selection-28... DeepMind RL Lecture Series 2021 https://deepmind.com/learning-resourc... Fashion Store sells Adversarial Patches https://twitter.com/naotokui/status/1... A viable method to remove the GIL from CPython https://lwn.net/Articles/872869/ BigScience Workshop releases T0 https://bigscience.huggingface.co/ https://arxiv.org/abs/2110.08207 https://huggingface.co/bigscience/T0pp Huggingface Hub Dataset Viewer https://twitter.com/huggingface/statu... Scite classifies scientific citations https://scite.ai https://direct.mit.edu/qss/article/do... Facebook AI Ego4D dataset & challenges https://ai.facebook.com/blog/teaching... Tesla Dojo Configurable Floating Point Spec https://tesla-cdn.thron.com/static/SB... Windows releases PyTorch-DirectML for Deep Learning on DirectX GPUs https://devblogs.microsoft.com/window... Helpful Things https://github.com/achaiah/pywick?utm... https://github.com/orybkin/lexa-bench... https://orybkin.github.io/lexa/ https://twitter.com/danijarh/status/1... https://github.com/RobertTLange/mle-h... https://keras.io/examples/vision/mobi... https://twitter.com/osanseviero/statu... https://huggingface.co/spaces/flax-co... https://huggingface.co/transformers/m... https://github.com/facebookresearch/b... https://arxiv.org/abs/2110.11216 https://arxiv.org/pdf/2110.11216.pdf https://github.com/facebookresearch/x... https://superbbenchmark.org/ https://arxiv.org/abs/2110.07731 https://github.com/BaguaSys/bagua?utm... https://github.com/cgarciae/treex https://jax.readthedocs.io/en/latest/... Traders use ML to analyze CEOs' language https://www.reuters.com/technology/ai... Cadbury creates DeepFake ads for local Indian businesses https://www.bgr.in/entertainment/shah... This Shoe Does Not Exist https://www.thisshoedoesnotexist.com/

#efficientzero #muzero #atari Reinforcement Learning methods are notoriously data-hungry. Notably, MuZero learns a latent world model just from scalar feedback of reward- and policy-predictions, and therefore relies on scale to perform well. However, most RL algorithms fail when presented with very little data. EfficientZero makes several improvements over MuZero that allows it to learn from astonishingly small amounts of data and outperform other methods by a large margin in the low-sample setting. This could be a staple algorithm for future RL research. OUTLINE: 0:00 - Intro & Outline 2:30 - MuZero Recap 10:50 - EfficientZero improvements 14:15 - Self-Supervised consistency loss 17:50 - End-to-end prediction of the value prefix 20:40 - Model-based off-policy correction 25:45 - Experimental Results & Conclusion Paper: https://arxiv.org/abs/2111.00210 Code: https://github.com/YeWR/EfficientZero Note: code not there yet as of release of this video Abstract: Reinforcement learning has achieved great success in many applications. However, sample efficiency remains a key challenge, with prominent methods requiring millions (or even billions) of environment steps to train. Recently, there has been significant progress in sample efficient image-based RL algorithms; however, consistent human-level performance on the Atari game benchmark remains an elusive goal. We propose a sample efficient model-based visual RL algorithm built on MuZero, which we name EfficientZero. Our method achieves 190.4% mean human performance and 116.0% median performance on the Atari 100k benchmark with only two hours of real-time game experience and outperforms the state SAC in some tasks on the DMControl 100k benchmark. This is the first time an algorithm achieves super-human performance on Atari games with such little data. EfficientZero's performance is also close to DQN's performance at 200 million frames while we consume 500 times less data. EfficientZero's low sample complexity and high performance can bring RL closer to real-world applicability. We implement our algorithm in an easy-to-understand manner and it is available at this https URL. We hope it will accelerate the research of MCTS-based RL algorithms in the wider community. Authors: Weirui Ye, Shaohuai Liu, Thanard Kurutach, Pieter Abbeel, Yang Gao Links: TabNine Code Completion (Referral): http://bit.ly/tabnine-yannick YouTube: https://www.youtube.com/c/yannickilcher Twitter: https://twitter.com/ykilcher Discord: https://discord.gg/4H8xxDF BitChute: https://www.bitchute.com/channel/yann... Minds: https://www.minds.com/ykilcher Parler: https://parler.com/profile/YannicKilcher LinkedIn: https://www.linkedin.com/in/ykilcher BiliBili: https://space.bilibili.com/1824646584 If you want to support me, the best thing to do is to share out the content :) If you want to support me financially (completely optional and voluntary, but a lot of people have asked for this): SubscribeStar: https://www.subscribestar.com/yannick... Patreon: https://www.patreon.com/yannickilcher Bitcoin (BTC): bc1q49lsw3q325tr58ygf8sudx2dqfguclvngvy2cq Ethereum (ETH): 0x7ad3513E3B8f66799f507Aa7874b1B0eBC7F85e2 Litecoin (LTC): LQW2TRyKYetVC8WjFkhpPhtpbDM4Vw7r9m Monero (XMR): 4ACL8AGrEo5hAir8A9CeVrW8pEauWvnp1WnSDZxW7tziCDLhZAGsgzhRQABDnFy8yuM9fWJDviJPHKRjV4FWt19CJZN9D4n

#ytalks #siraj #plagiarism A conversation with Siraj Raval about his journey on YouTube, and the perils of fame. OUTLINE: 0:00 - Intro 1:30 - Welcome 3:15 - Starting out: From Economics to YouTube 13:00 - More Views: Plagiarizing Video Content 23:30 - One Step Up: Copying A Research Paper 29:15 - Was there another way? 39:00 - Clickbait Course: Make Money with Machine Learning 50:30 - Rock Bottom and the Way Forward 1:01:30 - Advice for Future Generations Siraj's Channel: https://www.youtube.com/c/SirajRaval Links: TabNine Code Completion (Referral): http://bit.ly/tabnine-yannick YouTube: https://www.youtube.com/c/yannickilcher Twitter: https://twitter.com/ykilcher Discord: https://discord.gg/4H8xxDF BitChute: https://www.bitchute.com/channel/yann... Minds: https://www.minds.com/ykilcher Parler: https://parler.com/profile/YannicKilcher LinkedIn: https://www.linkedin.com/in/ykilcher BiliBili: https://space.bilibili.com/1824646584 If you want to support me, the best thing to do is to share out the content :) If you want to support me financially (completely optional and voluntary, but a lot of people have asked for this): SubscribeStar: https://www.subscribestar.com/yannick... Patreon: https://www.patreon.com/yannickilcher Bitcoin (BTC): bc1q49lsw3q325tr58ygf8sudx2dqfguclvngvy2cq Ethereum (ETH): 0x7ad3513E3B8f66799f507Aa7874b1B0eBC7F85e2 Litecoin (LTC): LQW2TRyKYetVC8WjFkhpPhtpbDM4Vw7r9m Monero (XMR): 4ACL8AGrEo5hAir8A9CeVrW8pEauWvnp1WnSDZxW7tziCDLhZAGsgzhRQABDnFy8yuM9fWJDviJPHKRjV4FWt19CJZN9D4n

#gtc21 #mlnews #mujoco Registriere für GTC'21 und gewinne eine RTX 3090: https://nvda.ws/2Y2B5ni OUTLINE: 0:00 - Intro 0:15 - Sponsor: NVIDIA GTC'21 6:10 - DeepMind kauft & Open-Sourct MuJoCo 9:05 - PyTorch 1.10 Veröffentlicht 11:25 - Google Lernt Spreadsheet Formeln 14:15 - handtracking.io 15:25 - Zellinstanzsegmentierungswettbewerb 16:15 - Hilfreiche Bibliotheken 23:15 - Waymo autos verirren sich alle in der selben Sackgasse 24:50 - BlueRiver balanciert Traktoren References: DeepMind kauft & open-sourct MuJoCo https://deepmind.com/blog/announcemen... PyTorch 1.10 veröffentlicht https://pytorch.org/blog/pytorch-1.10... https://developer.nvidia.com/blog/cud... GoogleAI sagt Tabellen-Formeln voraus https://ai.googleblog.com/2021/10/pre... Handtracking im Browser https://handtracking.io/ https://handtracking.io/draw_demo/ Sartorius Zellinstanzsegmentierungswettbewerb https://www.kaggle.com/c/sartorius-ce... Hilfreiche Bibliotheken https://github.com/IntelLabs/control-... https://github.com/facebookresearch/s... https://github.com/facebookresearch/s... https://github.com/ydataai/ydata-synt... https://syntheticdata.community/ https://github.com/ydataai/ydata-synt... https://medium.com/aimstack/aim-3-0-0... https://github.com/aimhubio/aim https://robustbench.github.io/ Waymo Autos verirren sich in dieselbe Sackgasse wieder und wieder https://sanfrancisco.cbslocal.com/202... BlueRiver balanciert Traktoren https://www.linkedin.com/posts/lredde... https://bluerivertechnology.com/ourme... Links: TabNine Code Completion (Referral): http://bit.ly/tabnine-yannick YouTube: https://www.youtube.com/c/yannickilcher Twitter: https://twitter.com/ykilcher Discord: https://discord.gg/4H8xxDF BitChute: https://www.bitchute.com/channel/yann... Minds: https://www.minds.com/ykilcher Parler: https://parler.com/profile/YannicKilcher LinkedIn: https://www.linkedin.com/in/ykilcher BiliBili: https://space.bilibili.com/1824646584 If you want to support me, the best thing to do is to share out the content :) If you want to support me financially (completely optional and voluntary, but a lot of people have asked for this): SubscribeStar: https://www.subscribestar.com/yannick... Patreon: https://www.patreon.com/yannickilcher Bitcoin (BTC): bc1q49lsw3q325tr58ygf8sudx2dqfguclvngvy2cq Ethereum (ETH): 0x7ad3513E3B8f66799f507Aa7874b1B0eBC7F85e2 Litecoin (LTC): LQW2TRyKYetVC8WjFkhpPhtpbDM4Vw7r9m Monero (XMR): 4ACL8AGrEo5hAir8A9CeVrW8pEauWvnp1WnSDZxW7tziCDLhZAGsgzhRQABDnFy8yuM9fWJDviJPHKRjV4FWt19CJZN9D4n

#gtc21 #mlnews #mujoco Register to GTC'21 and Win a RTX 3090: https://nvda.ws/2Y2B5ni OUTLINE: 0:00 - Intro 0:15 - Sponsor: NVIDIA GTC'21 5:35 - DeepMind buys & Open-Sources MuJoCo 7:25 - PyTorch 1.10 Released 9:10 - Google Predicts Spreadsheet Formulas 11:25 - handtracking.io 12:25 - Cell Instance Segmentation Challenge 13:00 - Helpful Libraries 17:50 - Waymo cars keep turning into same dead-end 19:35 - BlueRiver balances tractors References: DeepMind buys & open-sources MuJoCo https://deepmind.com/blog/announcemen... PyTorch 1.10 released https://pytorch.org/blog/pytorch-1.10... https://developer.nvidia.com/blog/cud... GoogleAI predicts spreadsheet formulas https://ai.googleblog.com/2021/10/pre... Handtracking in Browser https://handtracking.io/ https://handtracking.io/draw_demo/ Sartorius Cell Instance Segmentation Competition https://www.kaggle.com/c/sartorius-ce... Helpful Libraries https://github.com/IntelLabs/control-... https://github.com/facebookresearch/s... https://github.com/facebookresearch/s... https://github.com/ydataai/ydata-synt... https://syntheticdata.community/ https://github.com/ydataai/ydata-synt... https://medium.com/aimstack/aim-3-0-0... https://github.com/aimhubio/aim https://robustbench.github.io/ Waymo cars keep coming to same dead-end over and over https://sanfrancisco.cbslocal.com/202... BlueRiver balances tractors https://www.linkedin.com/posts/lredde... https://bluerivertechnology.com/ourme... Links: TabNine Code Completion (Referral): http://bit.ly/tabnine-yannick YouTube: https://www.youtube.com/c/yannickilcher Twitter: https://twitter.com/ykilcher Discord: https://discord.gg/4H8xxDF BitChute: https://www.bitchute.com/channel/yann... Minds: https://www.minds.com/ykilcher Parler: https://parler.com/profile/YannicKilcher LinkedIn: https://www.linkedin.com/in/ykilcher BiliBili: https://space.bilibili.com/1824646584 If you want to support me, the best thing to do is to share out the content :) If you want to support me financially (completely optional and voluntary, but a lot of people have asked for this): SubscribeStar: https://www.subscribestar.com/yannick... Patreon: https://www.patreon.com/yannickilcher Bitcoin (BTC): bc1q49lsw3q325tr58ygf8sudx2dqfguclvngvy2cq Ethereum (ETH): 0x7ad3513E3B8f66799f507Aa7874b1B0eBC7F85e2 Litecoin (LTC): LQW2TRyKYetVC8WjFkhpPhtpbDM4Vw7r9m Monero (XMR): 4ACL8AGrEo5hAir8A9CeVrW8pEauWvnp1WnSDZxW7tziCDLhZAGsgzhRQABDnFy8yuM9fWJDviJPHKRjV4FWt19CJZN9D4n

#aiia #ai #art A trip report from the AiiA Festival in Geneva organized by the ImpactAI foundation. OUTLINE: 0:00 - Intro 1:50 - Laura Tocmacov: The Festival 4:10 - Timothy O'Hear: The Tech 6:50 - Jonathan O'Hear: The Robot 11:50 - Cléa Chopard: The Artist 17:45 - Final Words Website: https://aiiafestival.org/en/ Links: TabNine Code Completion (Referral): http://bit.ly/tabnine-yannick YouTube: https://www.youtube.com/c/yannickilcher Twitter: https://twitter.com/ykilcher Discord: https://discord.gg/4H8xxDF BitChute: https://www.bitchute.com/channel/yann... Minds: https://www.minds.com/ykilcher Parler: https://parler.com/profile/YannicKilcher LinkedIn: https://www.linkedin.com/in/ykilcher BiliBili: https://space.bilibili.com/1824646584 If you want to support me, the best thing to do is to share out the content :) If you want to support me financially (completely optional and voluntary, but a lot of people have asked for this): SubscribeStar: https://www.subscribestar.com/yannick... Patreon: https://www.patreon.com/yannickilcher Bitcoin (BTC): bc1q49lsw3q325tr58ygf8sudx2dqfguclvngvy2cq Ethereum (ETH): 0x7ad3513E3B8f66799f507Aa7874b1B0eBC7F85e2 Litecoin (LTC): LQW2TRyKYetVC8WjFkhpPhtpbDM4Vw7r9m Monero (XMR): 4ACL8AGrEo5hAir8A9CeVrW8pEauWvnp1WnSDZxW7tziCDLhZAGsgzhRQABDnFy8yuM9fWJDviJPHKRjV4FWt19CJZN9D4n