![[ML News] Stable Diffusion Takes Over! (Open Source AI Art) @YannicKilcher](https://i.ytimg.com/vi/xbxe-x6wvRw/maxresdefault.jpg)
Uploaded September 2022 | Updated September 2026, 2 weeks ago
#stablediffusion #aiart #mlnews
Stable Diffusion has been released and is riding a wave of creativity and collaboration. But not everyone is happy about this...
Sponsor: NVIDIA
GPU Raffle: ykilcher.com/gtc
OUTLINE:
0:00 - Introduction
0:30 - What is Stable Diffusion?
2:25 - Open-Source Contributions and Creations
7:55 - Textual Inversion
9:30 - OpenAI vs Open AI
14:20 - Journalists be outraged
16:20 - AI Ethics be even more outraged
19:45 - Do we need a new social contract?
21:30 - More applications
22:55 - Helpful Things
23:45 - Sponsor: NVIDIA (& how to enter the GPU raffle)
References: https://early-hair-c20.notion.site/Stable-Diffusion-Takes-Over-Referenes-7a2f45b8f7e04ae0ba19dbfcd2b7f7c0
Links:
Homepage: ykilcher.com
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#stablediffusion #aiart #mlnews
Stable Diffusion has been released and is riding a wave of creativity and collaboration. But not everyone is happy about this...
Sponsor: NVIDIA
GPU Raffle: ykilcher.com/gtc
OUTLINE:
0:00 - Introduction
0:30 - What is Stable Diffusion?
2:25 - Open-Source Contributions and Creations
7:55 - Textual Inversion
9:30 - OpenAI vs Open AI
14:20 - Journalists be outraged
16:20 - AI Ethics be even more outraged
19:45 - Do we need a new social contract?
21:30 - More applications
22:55 - Helpful Things
23:45 - Sponsor: NVIDIA (& how to enter the GPU raffle)
References: https://early-hair-c20.notion.site/Stable-Diffusion-Takes-Over-Referenes-7a2f45b8f7e04ae0ba19dbfcd2b7f7c0
Links:
Homepage: ykilcher.com
Merch: ykilcher.com/merch
YouTube: youtube.com/c/yannickilcher
Twitter: twitter.com/ykilcher
Discord: ykilcher.com/discord
LinkedIn: linkedin.com/in/ykilcher
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: subscribestar.com/yannickilcher
Patreon: patreon.com/yannickilcher
Bitcoin (BTC): bc1q49lsw3q325tr58ygf8sudx2dqfguclvngvy2cq
Ethereum (ETH): 0x7ad3513E3B8f66799f507Aa7874b1B0eBC7F85e2
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![[ML News] Stable Diffusion Takes Over! (Open Source AI Art)](https://i.ytimg.com/vi/xbxe-x6wvRw/mqdefault.jpg "[ML News] Stable Diffusion Takes Over! (Open Source AI Art)
#stablediffusion #aiart #mlnews
Stable Diffusion has been released and is riding a wave of creativity and collaboration. But not everyone is happy about this...
Sponsor: NVIDIA
GPU Raffle: https://ykilcher.com/gtc
OUTLINE:
0:00 - Introduction
0:30 - What is Stable Diffusion?
2:25 - Open-Source Contributions and Creations
7:55 - Textual Inversion
9:30 - OpenAI vs Open AI
14:20 - Journalists be outraged
16:20 - AI Ethics be even more outraged
19:45 - Do we need a new social contract?
21:30 - More applications
22:55 - Helpful Things
23:45 - Sponsor: NVIDIA (& how to enter the GPU raffle)
References: https://early-hair-c20.notion.site/Stable-Diffusion-Takes-Over-Referenes-7a2f45b8f7e04ae0ba19dbfcd2b7f7c0
Links:
Homepage: https://ykilcher.com
Merch: https://ykilcher.com/merch
YouTube: https://www.youtube.com/c/yannickilcher
Twitter: https://twitter.com/ykilcher
Discord: https://ykilcher.com/discord
LinkedIn: https://www.linkedin.com/in/ykilcher
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/yannickilcher
Patreon: https://www.patreon.com/yannickilcher
Bitcoin (BTC): bc1q49lsw3q325tr58ygf8sudx2dqfguclvngvy2cq
Ethereum (ETH): 0x7ad3513E3B8f66799f507Aa7874b1B0eBC7F85e2
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Monero (XMR): 4ACL8AGrEo5hAir8A9CeVrW8pEauWvnp1WnSDZxW7tziCDLhZAGsgzhRQABDnFy8yuM9fWJDviJPHKRjV4FWt19CJZN9D4n")
![[ML News] This AI completes Wikipedia! Meta AI Sphere | Google Minerva | GPT-3 writes a paper](https://i.ytimg.com/vi/xnChXNUNS2A/mqdefault.jpg "[ML News] This AI completes Wikipedia! Meta AI Sphere | Google Minerva | GPT-3 writes a paper
#mlnews #ai #minerva
This episode is all about models that reason.
OUTLINE:
0:00 - Intro
0:35 - Meta AI learns Wikipedia citations
5:25 - Googles Minerva solves math problems by reading papers
9:10 - GPT-3 writes a paper on itself
13:35 - Jürgen Schmidhuber prompts LeCun for missing citations
References:
Meta AI learns Wikipedia citations
https://tech.fb.com/artificial-intelligence/2022/07/how-ai-could-help-make-wikipedia-entries-more-accurate/
https://ai.facebook.com/blog/introducing-sphere-meta-ais-web-scale-corpus-for-better-knowledge-intensive-nlp/?d=%7B%22u%22%3A100051861999022%2C%22f%22%3A207799259245384%2C%22t%22%3A1658664021%2C%22ed%22%3A[]%7D&s=AWVELTip1y4HowJprXc
https://github.com/facebookresearch/sphere
https://github.com/facebookresearch/side
https://verifier.sideeditor.com/main
https://openreview.net/forum?id=qfTqRtkDbWZ
Googles Minerva solves math problems by reading papers
https://minerva-demo.github.io/#category=Precalculus&index=9
https://ai.googleblog.com/2022/06/minerva-solving-quantitative-reasoning.html
GPT-3 writes a paper on itself
https://www.scientificamerican.com/article/we-asked-gpt-3-to-write-an-academic-paper-about-itself-then-we-tried-to-get-it-published/
https://hal.archives-ouvertes.fr/hal-03701250v1
https://hal.archives-ouvertes.fr/hal-03701250/document
Jürgen Schmidhuber prompts LeCun for missing citations
https://people.idsia.ch/~juergen/lecun-rehash-1990-2022.html
Links:
Homepage: https://ykilcher.com
Merch: https://ykilcher.com/merch
YouTube: https://www.youtube.com/c/yannickilcher
Twitter: https://twitter.com/ykilcher
Discord: https://ykilcher.com/discord
LinkedIn: https://www.linkedin.com/in/ykilcher
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/yannickilcher
Patreon: https://www.patreon.com/yannickilcher
Bitcoin (BTC): bc1q49lsw3q325tr58ygf8sudx2dqfguclvngvy2cq
Ethereum (ETH): 0x7ad3513E3B8f66799f507Aa7874b1B0eBC7F85e2
Litecoin (LTC): LQW2TRyKYetVC8WjFkhpPhtpbDM4Vw7r9m
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![[ML News] LLaMA2 Released | LLMs for Robots | Multimodality on the Rise](https://i.ytimg.com/vi/xs-0cp1hSnY/mqdefault.jpg "[ML News] LLaMA2 Released | LLMs for Robots | Multimodality on the Rise
#mlnews #llama2 #openai
Your regular irregular update on the world of Machine Learning.
References:
https://twitter.com/ylecun/status/1681336284453781505
https://ai.meta.com/llama/
https://about.fb.com/news/2023/07/llama-2-statement-of-support/
https://247wallst.com/special-report/2023/08/12/this-is-the-biggest-social-media-platform-ranking-the-worlds-largest-networking-sites/4/
https://github.com/Alpha-VLLM/LLaMA2-Accessory
https://together.ai/blog/llama-2-7b-32k?s=09&utm_source=pocket_saves
https://github.com/imoneoi/openchat
https://twitter.com/lmsysorg/status/1686794639469371393?s=09&t=sS3awkbavmSMSmwp64Ef4A&utm_source=pocket_saves
https://huggingface.co/lmsys/vicuna-13b-v1.5-16k
https://blog.google/outreach-initiatives/public-policy/google-microsoft-openai-anthropic-frontier-model-forum/
https://www.earthdata.nasa.gov/news/impact-ibm-hls-foundation-model?utm_source=pocket_reader
https://huggingface.co/ibm-nasa-geospatial/Prithvi-100M
https://ai.meta.com/blog/generative-ai-text-images-cm3leon/
https://www.deepmind.com/blog/rt-2-new-model-translates-vision-and-language-into-action?utm_source=twitter&utm_medium=social&utm_campaign=rt2
https://arxiv.org/abs/2307.14334
https://sites.research.google/med-palm/
https://open-catalyst.metademolab.com/?utm_source=twitter&utm_medium=organic_social&utm_campaign=opencatalyst&utm_content=card
https://open-catalyst.metademolab.com/demo
https://www.anthropic.com/index/claude-2?utm_source=pocket_reader
https://claude.ai/login
https://audiocraft.metademolab.com/?utm_source=pocket_saves
https://venturebeat.com/programming-development/stability-ai-launches-stablecode-an-llm-for-code-generation/
https://stability.ai/blog/stablecode-llm-generative-ai-coding
https://twitter.com/JeffDean/status/1686806525862608896?s=09&t=LG2z9ok9QExHbSy0fvBsxA&utm_source=pocket_saves
https://sites.research.google/open-buildings/
https://twitter.com/deliprao/status/1687283117873106946?s=09&t=1NmC-B55Z8IuF_HTuGOo7w&utm_source=pocket_saves
https://arxiv.org/pdf/2308.01320.pdf
https://twitter.com/javilopen/status/1687795349719547905?utm_source=pocket_saves
https://research.nvidia.com/labs/par/Perfusion/
https://ar5iv.labs.arxiv.org/html/2307.14936
https://www.linkedin.com/feed/update/urn:li:activity:7093463974750371840/?utm_source=pocket_saves
https://huggingface.co/syzymon/long_llama_3b_instruct
https://arxiv.org/abs/2307.03170
https://dynalang.github.io/
https://github.com/mlfoundations/open_flamingo
https://twitter.com/akshay_pachaar/status/1687079353937698816?s=09&t=fos8QSCsGEEM6dMflhq0Mg&utm_source=pocket_saves
https://github.com/OpenBMB/ToolBench
https://llm-attacks.org/
https://arstechnica.com/information-technology/2023/07/openai-discontinues-its-ai-writing-detector-due-to-low-rate-of-accuracy/
https://sites.google.com/view/steve-1
https://github.com/Shalev-Lifshitz/STEVE-1
https://erichartford.com/dolphin
https://huggingface.co/ehartford/dolphin-llama-13b
https://www.mosaicml.com/blog/long-context-mpt-7b-8k
https://twitter.com/camenduru/status/1688045780244848640?s=09&t=ubJ2Qtz-TG6Xo3_GMtt2Cw&utm_source=pocket_saves
https://github.com/IDEA-Research/DWPose
https://twitter.com/tri_dao/status/1680987577913065472?s=09&t=Q181vFmM6d3nDq-5BwfDeg&utm_source=pocket_saves
https://tridao.me/publications/flash2/flash2.pdf
https://thehackernews.com/2023/07/wormgpt-new-ai-tool-allows.html
https://www.tomshardware.com/news/ai-steals-data-with-keystroke-audio
https://arxiv.org/pdf/2308.01074.pdf
https://www.foxnews.com/politics/ai-test-flight-air-force-unmanned-wingman-aircraft
https://www.theverge.com/2023/8/2/23817406/white-castle-soundhound-ai-sliders
https://www.google.com/search?sca_esv=556495916&q=food+delivery+bot+kicked&tbm=vid&source=lnms&sa=X&ved=2ahUKEwjZ6PDPrdmAAxUThf0HHWzrBGgQ0pQJegQIChAB&cshid=1691920142432720&biw=2327&bih=1180&dpr=2.2
https://www.youtube.com/watch?v n_NhmXnfc
https://www.thesun.co.uk/tech/20793591/coop-delivery-robots-cambridge-kicked-by-workers-tiktok/
https://ktla.com/news/local-news/food-delivery-robots-under-attack-from-vandals-thieves-local-businesses-starting-to-be-affected/
https://www.youtube.com/watch?v=xxzS9qaARv0
https://www.psypost.org/2023/08/chatgpt-is-much-better-than-humans-at-accurately-identifying-emotions-in-fictional-textual-scenarios-167380
https://www.theverge.com/2023/8/1/23815287/meta-ai-persona-generative-llama-instagram-facebook
https://www.cnbc.com/2023/07/28/microsoft-annual-report-highlights-importance-of-gpus.html
Links:
Homepage: https://ykilcher.com
Merch: https://ykilcher.com/merch
YouTube: https://www.youtube.com/c/yannickilcher
Twitter: https://twitter.com/ykilcher
Discord: https://ykilcher.com/discord
LinkedIn: https://www.linkedin.com/in/ykilcher
If you want to support me, the best thing to do is to share out the content :)")
![[ML News] ConvNeXt: Convolutions return | China regulates algorithms | Saliency cropping examined](https://i.ytimg.com/vi/yVKiMh2vEWQ/mqdefault.jpg "[ML News] ConvNeXt: Convolutions return | China regulates algorithms | Saliency cropping examined
#mlnews #convnext #mt3
Your update on whats new in the Machine Learning world!
OUTLINE:
0:00 - Intro
0:15 - ConvNeXt: Return of the Convolutions
2:50 - Investigating Saliency Cropping Algorithms
9:40 - YourTTS: SOTA zero-shot Text-to-Speech
10:40 - MT3: Multi-Track Music Transcription
11:35 - China regulates addictive algorithms
13:00 - A collection of Deep Learning interview questions & solutions
13:35 - Helpful Things
16:05 - AlphaZero explained blog post
16:45 - Ru-DOLPH: HyperModal Text-to-Image-to-Text model
17:45 - Google AI 2021 Review
References:
ConvNeXt: Return of the Convolutions
https://arxiv.org/abs/2201.03545
https://github.com/facebookresearch/ConvNeXt
https://twitter.com/giffmana/status/1481054929573888005
https://twitter.com/wightmanr/status/1481150080765739009
https://twitter.com/tanmingxing/status/1481362887272636417
Investigating Saliency Cropping Algorithms
https://openaccess.thecvf.com/content/WACV2022/papers/Birhane_Auditing_Saliency_Cropping_Algorithms_WACV_2022_paper.pdf
https://vinayprabhu.github.io/Saliency_Image_Cropping/paper_html/main.html
https://vinayprabhu.medium.com/on-the-twitter-cropping-controversy-critique-clarifications-and-comments-7ac66154f687
https://vinayprabhu.github.io/Saliency_Image_Cropping/
YourTTS: SOTA zero-shot Text-to-Speech
https://github.com/coqui-ai/TTS?utm_source=pocket_mylist
https://arxiv.org/abs/2112.02418?utm_source=pocket_mylist
https://coqui.ai/?utm_source=pocket_mylist
https://coqui.ai/blog/tts/yourtts-zero-shot-text-synthesis-low-resource-languages
MT3: Multi-Track Music Transcription
https://arxiv.org/abs/2111.03017
https://github.com/magenta/mt3
https://huggingface.co/spaces/akhaliq/MT3
https://www.reddit.com/r/MachineLearning/comments/rtlx0r/r_mt3_multitask_multitrack_music_transcription/
China regulates addictive algorithms
https://technode.com/2022/01/05/china-issues-new-rules-to-regulate-algorithms-targeting-addiction-monopolies-and-overspending/
https://qz.com/2109618/china-reveals-new-algorithm-rules-to-weaken-platforms-control-of-users/
A collection of Deep Learning interview questions & solutions
https://arxiv.org/abs/2201.00650?utm_source=pocket_mylist
https://arxiv.org/pdf/2201.00650.pdf
Helpful Things
https://docs.deepchecks.com/en/stable/index.html
https://github.com/deepchecks/deepchecks
https://docs.deepchecks.com/en/stable/examples/guides/quickstart_in_5_minutes.html
https://www.dagshub.com/
https://www.dagshub.com/docs/index.html
https://www.dagshub.com/blog/launching-dagshub-2-0/
https://bayesiancomputationbook.com/welcome.html
https://mlcontests.com/
https://github.com/Yard1/ray-skorch
https://github.com/skorch-dev/skorch
https://www.rumbledb.org/?utm_source=pocket_mylist
https://github.com/DarshanDeshpande/jax-models
https://github.com/s3prl/s3prl
AlphaZero explained blog post
https://joshvarty.github.io/AlphaZero/?utm_source=pocket_mylist
Ru-DOLPH: HyperModal Text-to-Image-to-Text model
https://github.com/sberbank-ai/ru-dolph
https://colab.research.google.com/drive/1gmTDA13u709OXiAeXWGm7sPixRhEJCga?usp=sharing
Google AI 2021 Review
https://ai.googleblog.com/2022/01/google-research-themes-from-2021-and.html
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/yannic-kilcher
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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/yannickilcher
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![[Paper Analysis] On the Theoretical Limitations of Embedding-Based Retrieval (Warning: Rant)](https://i.ytimg.com/vi/zKohTkN0Fyk/mqdefault.jpg "[Paper Analysis] On the Theoretical Limitations of Embedding-Based Retrieval (Warning: Rant)
Paper: https://arxiv.org/abs/2508.21038
Abstract:
Vector embeddings have been tasked with an ever-increasing set of retrieval tasks over the years, with a nascent rise in using them for reasoning, instruction-following, coding, and more. These new benchmarks push embeddings to work for any query and any notion of relevance that could be given. While prior works have pointed out theoretical limitations of vector embeddings, there is a common assumption that these difficulties are exclusively due to unrealistic queries, and those that are not can be overcome with better training data and larger models. In this work, we demonstrate that we may encounter these theoretical limitations in realistic settings with extremely simple queries. We connect known results in learning theory, showing that the number of top-k subsets of documents capable of being returned as the result of some query is limited by the dimension of the embedding. We empirically show that this holds true even if we restrict to k=2, and directly optimize on the test set with free parameterized embeddings. We then create a realistic dataset called LIMIT that stress tests models based on these theoretical results, and observe that even state-of-the-art models fail on this dataset despite the simple nature of the task. Our work shows the limits of embedding models under the existing single vector paradigm and calls for future research to develop methods that can resolve this fundamental limitation.
Authors: Orion Weller, Michael Boratko, Iftekhar Naim, Jinhyuk Lee
Links:
Homepage: https://ykilcher.com
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Twitter: https://twitter.com/ykilcher
Discord: https://ykilcher.com/discord
LinkedIn: https://www.linkedin.com/in/ykilcher
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/yannickilcher
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