Uploaded July 2026 | Updated September 2026, 1 week ago
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In this video, we are diving into the DELETED paper from DeepSeek called Visual Primitives, which is a vision model that grounds vision through pointers and boxes.
my latest project: Intuitive AI Academy
We just wrote a new piece on Optimization!!
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SOURCES:
Thinking With Visual Primitives
[Paper] alphaxiv.org/abs/visual-primitives
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This video is supported by the kind Patrons & YouTube Members:
🙏Spam Maj, Alex, Chris LeDoux, DX Research Group, Poof N' Inu, Deagan, Robert Zawiasa, Ryszard Warzocha, Tobe2d, Louis Muk, Akkusativ, Kevin Tai, Mark Buckler, NO U, Tony Jimenez, Ângelo Fonseca, jiye, Anushka, Asad Dhamani, Binnie Yiu, Calvin Yan, Clayton Ford, Diego Silva, Etrotta, Gonzalo Fidalgo, Handenon, Hector, Jake Disco very, Michael Brenner, Nilly K, OlegWock, Daddy Wen, Shuhong Chen, Sid_Cipher, Stefan Lorenz, Sup, tantan assawade, Thipok Tham, Thomas Di Martino, Thomas Lin, Richárd Nagyfi, Paperboy, mika, Leo, Berhane-Meskel, Kadhai Pesalam, mayssam, Bill Mangrum, nyaa, Toru Mon, Lame Plane, Matej Macak, Len Mo, saylikhapekar, ZyanSheep, THEVIERAOS, Ricardo Raphael Corona-Moreno, superchordate
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Need high quality cloud GPUs? Check out Verda now, and use the code BYCLOUD-50 to get $50 of compute credits for just $5!
verda.com/?utm_source=bycloud&utm_medium=referral&utm_campaign=sponsorship&utm_content=deepseekv4
How to redeem the discount: docs.verda.com/resources/obtaining-free-credits/how-to-redeem-credits/#redeem-discount-coupons
In this video, we are diving into the DELETED paper from DeepSeek called Visual Primitives, which is a vision model that grounds vision through pointers and boxes.
my latest project: Intuitive AI Academy
We just wrote a new piece on Optimization!!
https://intuitiveai.academy/
limited time code "LOCKIN" for 35% off yearly plan
My Newsletter (weekly top research papers)
mail.bycloud.ai
My Patreon
patreon.com/c/bycloud
SOURCES:
Thinking With Visual Primitives
[Paper] alphaxiv.org/abs/visual-primitives
Try out my new fav place to learn how to code scrimba.com/?via=bycloudAI
This video is supported by the kind Patrons & YouTube Members:
🙏Spam Maj, Alex, Chris LeDoux, DX Research Group, Poof N' Inu, Deagan, Robert Zawiasa, Ryszard Warzocha, Tobe2d, Louis Muk, Akkusativ, Kevin Tai, Mark Buckler, NO U, Tony Jimenez, Ângelo Fonseca, jiye, Anushka, Asad Dhamani, Binnie Yiu, Calvin Yan, Clayton Ford, Diego Silva, Etrotta, Gonzalo Fidalgo, Handenon, Hector, Jake Disco very, Michael Brenner, Nilly K, OlegWock, Daddy Wen, Shuhong Chen, Sid_Cipher, Stefan Lorenz, Sup, tantan assawade, Thipok Tham, Thomas Di Martino, Thomas Lin, Richárd Nagyfi, Paperboy, mika, Leo, Berhane-Meskel, Kadhai Pesalam, mayssam, Bill Mangrum, nyaa, Toru Mon, Lame Plane, Matej Macak, Len Mo, saylikhapekar, ZyanSheep, THEVIERAOS, Ricardo Raphael Corona-Moreno, superchordate
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![The Biggest Lie in AI? LLM doesnt think step-by-step
Remove your personal information from the web at https://JoinDeleteMe.com/BYCLOUD and use
code BYCLOUD for 20% off🙌
My Newsletter
https://mail.bycloud.ai/
my project: find, discover & explain AI research semantically
https://findmypapers.ai/
(just pushed out a new UI update! everything should be smoother now)
My Patreon
https://www.patreon.com/c/bycloud
Think before you speak: Training Language Models With Pause Tokens
[Paper] https://arxiv.org/abs/2310.02226
Lets Think Dot by Dot: Hidden Computation in Transformer Language Models
[Paper] https://arxiv.org/abs/2404.15758
Do LLMs Really Think Step-by-step In Implicit Reasoning?
[Paper] https://arxiv.org/abs/2411.15862
On the Biology of a Large Language Model
[Paper] https://transformer-circuits.pub/2025/attribution-graphs/biology.html
Try out my new fav place to learn how to code https://scrimba.com/?via=bycloudAI
This video is supported by the kind Patrons & YouTube Members:
🙏Nous Research, Chris LeDoux, Ben Shaener, DX Research Group, Poof N Inu, Andrew Lescelius, Deagan, Robert Zawiasa, Ryszard Warzocha, Tobe2d, Louis Muk, Akkusativ, Kevin Tai, Mark Buckler, NO U, Tony Jimenez, Ângelo Fonseca, jiye, Anushka, Asad Dhamani, Binnie Yiu, Calvin Yan, Clayton Ford, Diego Silva, Etrotta, Gonzalo Fidalgo, Handenon, Hector, Jake Disco very, Michael Brenner, Nilly K, OlegWock, Daddy Wen, Shuhong Chen, Sid_Cipher, Stefan Lorenz, Sup, tantan assawade, Thipok Tham, Thomas Di Martino, Thomas Lin, Richárd Nagyfi, Paperboy, mika, Leo, Berhane-Meskel, Kadhai Pesalam, mayssam, Bill Mangrum, nyaa
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[Ko-fi] https://ko-fi.com/bycloudai The Biggest Lie in AI? LLM doesnt think step-by-step](https://i.ytimg.com/vi/Dk36u4NGeSU/mqdefault.jpg)
![1 Million Tiny Experts in an AI? Fine-Grained MoE Explained
To try everything Brilliant has to offer—free—for a full 30 days, visit https://brilliant.org/bycloud/ . You’ll also get 20% off an annual premium subscription.
Mixture of Experts explained, well, re-explained. We are in the Fine-Grain era of Mixture of Experts and its about to get even more interesting as we further scale it up.
This video was sponsored by Brilliant
Check out my newsletter:
https://mail.bycloud.ai
Special thanks to LDJ for helping me with this video
Mixtral 8x7B Paper
[Paper] https://arxiv.org/abs/2401.04088
Sparse MoE (2017)
[Paper] https://arxiv.org/abs/1701.06538
Adaptive Mixtures of Local Experts (1991)
[Paper] https://direct.mit.edu/neco/article-abstract/3/1/79/5560/Adaptive-Mixtures-of-Local-Experts?redirectedFrom=fulltext
Gshard
[Paper] https://arxiv.org/pdf/2006.16668
Branch-Train Mix
[Paper] https://arxiv.org/pdf/2403.07816
DeepSeek-MoE
[Paper] https://arxiv.org/abs/2401.06066
MoWE (from the meme at 7:51)
[Paper] https://arxiv.org/abs/2311.10768
Mixture of A Million Experts
[Paper] https://web3.arxiv.org/abs/2407.04153
This video is supported by the kind Patrons & YouTube Members:
🙏Andrew Lescelius, alex j, Chris LeDoux, Alex Maurice, Miguilim, Deagan, FiFaŁ, Robert Zawiasa, Daddy Wen, Tony Jimenez, Panther Modern, Jake Disco, Demilson Quintao, Shuhong Chen, Hongbo Men, happi nyuu nyaa, Carol Lo, Mose Sakashita, Miguel, Bandera, Gennaro Schiano, gunwoo, Ravid Freedman, Mert Seftali, Mrityunjay, Richárd Nagyfi, Timo Steiner, Henrik G Sundt, projectAnthony, Brigham Hall, Kyle Hudson, Kalila, Jef Come, Jvari Williams, Tien Tien, BIll Mangrum, owned, Janne Kytölä, SO, Richárd Nagyfi, Hector, Drexon, Claxvii 177th, Inferencer, Michael Brenner, Akkusativ, Oleg Wock, FantomBloth
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[Video Editor] @Askejm 1 Million Tiny Experts in an AI? Fine-Grained MoE Explained](https://i.ytimg.com/vi/F70KlwO4wP0/mqdefault.jpg)
![byclouds 100k Subscribers Q&A Special
100K SPECIAL Q&A IS REAL GUYS!!! Just took awhile tho :p
[bycloud AI YouTube] @bycloud2
[bycloud AI Patreon] https://www.patreon.com/bycloud_AI
This video is supported by the kind Patrons & YouTube Members:
🙏Andrew Lescelius, alex j, Chris LeDoux, Alex Maurice, Miguilim, Deagan, FiFaŁ, Daddy Wen, Tony Jimenez, Panther Modern, Jake Disco, Demilson Quintao, Shuhong Chen, Hongbo Men, happi nyuu nyaa, Carol Lo, Mose Sakashita, Miguel, Bandera, Gennaro Schiano, gunwoo, Ravid Freedman, Mert Seftali, Mrityunjay, Richárd Nagyfi, Timo Steiner, Henrik G Sundt, projectAnthony, Brigham Hall, Kyle Hudson, Kalila, Jef Come, Jvari Williams, Tien Tien, BIll Mangrum, owned, Janne Kytölä
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[Video Editor] @askejm byclouds 100k Subscribers Q&A Special](https://i.ytimg.com/vi/G4yjpBdki78/mqdefault.jpg)
![What If We Remove Tokenization In LLMs?
Master AI agents now using HubSpots FREE resource! https://clickhubspot.com/e3c3d1
In this video, we will take a look at research papers that aim to remove tokenization in LLMs.
My Newsletter
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my project: find, discover & explain AI research semantically
https://findmypapers.ai/
My Patreon
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Dynamic Byte Latent Transformer
[Paper] https://arxiv.org/abs/2412.09871
[Code] https://github.com/facebookresearch/blt
From Bytes to Ideas: Language Modeling with Autoregressive U-Nets
[Paper] https://arxiv.org/abs/2506.14761
Try out my new fav place to learn how to code https://scrimba.com/?via=bycloudAI
This video is supported by the kind Patrons & YouTube Members:
🙏Nous Research, Chris LeDoux, Ben Shaener, DX Research Group, Poof N Inu, Andrew Lescelius, Deagan, Robert Zawiasa, Ryszard Warzocha, Tobe2d, Louis Muk, Akkusativ, Kevin Tai, Mark Buckler, NO U, Tony Jimenez, Ângelo Fonseca, jiye, Anushka, Asad Dhamani, Binnie Yiu, Calvin Yan, Clayton Ford, Diego Silva, Etrotta, Gonzalo Fidalgo, Handenon, Hector, Jake Disco very, Michael Brenner, Nilly K, OlegWock, Daddy Wen, Shuhong Chen, Sid_Cipher, Stefan Lorenz, Sup, tantan assawade, Thipok Tham, Thomas Di Martino, Thomas Lin, Richárd Nagyfi, Paperboy, mika, Leo, Berhane-Meskel, Kadhai Pesalam, mayssam, Bill Mangrum, nyaa,
Toru Mon
[Discord] https://discord.gg/NhJZGtH
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[Ko-fi] https://ko-fi.com/bycloudai What If We Remove Tokenization In LLMs?](https://i.ytimg.com/vi/G7ryb91BDG8/mqdefault.jpg)
![DeepSeek Just Added Parameters Where There Were None
Stop scraping manually and check out SerpAPI now! https://serpapi.link/bycloud-feb-2026
So what in the world did DeepSeek publish? This Hyper Connections paper probably confused more people than it should. But under the hood, it is a fairly simple idea that everyone can easily follow! So in this video, let me break it down for you.
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Sources...
(ByteDance) Hyper Connections
[Paper] https://arxiv.org/abs/2409.19606
(DeepSeek) mHC: Manifold-Constrained Hyper-Connections
[Paper] https://arxiv.org/abs/2512.24880
Try out my new fav place to learn how to code https://scrimba.com/?via=bycloudAI
This video is supported by the kind Patrons & YouTube Members:
🙏Spam Maj, Alex, Chris LeDoux, DX Research Group, Poof N Inu, Deagan, Robert Zawiasa, Ryszard Warzocha, Tobe2d, Louis Muk, Akkusativ, Kevin Tai, Mark Buckler, NO U, Tony Jimenez, Ângelo Fonseca, jiye, Anushka, Asad Dhamani, Binnie Yiu, Calvin Yan, Clayton Ford, Diego Silva, Etrotta, Gonzalo Fidalgo, Handenon, Hector, Jake Disco very, Michael Brenner, Nilly K, OlegWock, Daddy Wen, Shuhong Chen, Sid_Cipher, Stefan Lorenz, Sup, tantan assawade, Thipok Tham, Thomas Di Martino, Thomas Lin, Richárd Nagyfi, Paperboy, mika, Leo, Berhane-Meskel, Kadhai Pesalam, mayssam, Bill Mangrum, nyaa, Toru Mon, Lame Plane, Matej Macak
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[Ko-fi] https://ko-fi.com/bycloudai DeepSeek Just Added Parameters Where There Were None](https://i.ytimg.com/vi/Gb0jLRC8uWM/mqdefault.jpg)
![How does AI REALLY Steal Art?
Check out NordVPN at https://www.nordvpn.com/bycloud and get started to browse the internet safely!
You probably could tell that this video is a bit outdated and ya it was actually delayed for nearly a month, but I am glad that I am still able to wrapped it up and show it to you guys though! Had to also add the new content since this whole thing is pretty much related to the AI protest that happened over on Art Station. I did not talk about the Kickstarter because it was a very sus deal for both AI researchers AND individual artists. It was funded by major corps and the lobbying may screw some individual artists up too actually.
Curt.Skeltons fake charater TikTok
https://www.tiktok.com/@curt.skelton/video/7135836562771758382
AI Art Wins Art Competition
https://impakter.com/art-made-by-ai-wins-fine-arts-competition/#:~:text=An%20artwork%20made%20by%20Artificial,used%20to%20compete%20in%20competitions.
Raiden Shoguns Art
[img2img example] https://www.pixiv.net/en/artworks/100737960
[Watermark example] https://www.pixiv.net/en/artworks/100494535
Kasukanras SD TI img2img workflow
https://youtu.be/LwLg592Duvg
US Copyright Law Article (old)
https://www.theregister.com/2022/08/14/ai_digital_artwork_copyright/
VQGAN+CLIP
[Paper] https://arxiv.org/abs/2204.08583
[Notebook] https://colab.research.google.com/drive/1ZAus_gn2RhTZWzOWUpPERNC0Q8OhZRTZ
[Nerdy Rodent Local Codes] https://github.com/nerdyrodent/VQGAN-CLIP
LAION-5B
[Project Page] https://laion.ai/blog/laion-5b/
DALL-E 2
[Blog] https://openai.com/dall-e-2/
[Paper] https://arxiv.org/abs/2204.06125
DALL-E
[Blog] https://openai.com/blog/dall-e/
[Paper] https://arxiv.org/abs/2102.12092
Stable Diffusion v2.0
[blog] https://stability.ai/blog/stable-diffusion-v2-release
Stable Diffusion v2.1
[blog] https://stability.ai/blog/stablediffusion2-1-release7-dec-2022
Yahoo Flickr Dataset
[Paper] https://arxiv.org/abs/1503.01817
[Project Page] http://projects.dfki.uni-kl.de/yfcc100m/
This video is supported by the kind Patrons & YouTube Members:
🙏Andrew Lescelius, Chris LeDoux, Shawn77134, Panther Modern, Jake Disco, Demilson Quintao, Tony Jimenez, Shuhong Chen, Hongbo Men, happi nyuu nyaa, Carol Lo, Mose Sakashita, Miguel, Bandera, Gennaro Schiano, gunwoo, Ravid Freedman, Mert Seftali, Mrityunjay, Richárd Nagyfi, Timo Steiner, Henrik G Sundt, tianmuhui, projectAnthony
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0:00 intro
1:39 training data
5:06 watermark removal AI
6:01 img2img
10:10 dreambooth & TI
12:48 copyright law
13:48 AI Protest & LAION-5B
17:20 Sponsor & Outro How does AI REALLY Steal Art?](https://i.ytimg.com/vi/GgU7CipUH38/mqdefault.jpg)
![NVIDIA Just Started A New Era of Supercomputing... GTC2024 Highlight
RTX4080 SUPER giveaway!
Sign-up for NVIDIAs GTC2024: https://nvda.ws/48s4tmc
Giveaway participation link: https://forms.gle/2w5fQoMjjNfXSRqf7
Please read all the rules & steps carefully in the Google Form!!
1. Sign-up for ANY Live NVIDIAs Virtual GTC2024 session between Mar 18 - 21st
2. Go to those LIVE sessions that you signed up, take a selfie for proof of attendance
3. Participate the giveaway DURING Mar 18 - 21st
4. ???
5. Profit
Full NVIDIA GTC Keynote
https://youtu.be/Y2F8yisiS6E
This video is supported by the kind Patrons & YouTube Members:
🙏Andrew Lescelius, alex j, Chris LeDoux, Alex Maurice, Miguilim, Deagan, FiFaŁ, Daddy Wen, Tony Jimenez, Panther Modern, Jake Disco, Demilson Quintao, Shuhong Chen, Hongbo Men, happi nyuu nyaa, Carol Lo, Mose Sakashita, Miguel, Bandera, Gennaro Schiano, gunwoo, Ravid Freedman, Mert Seftali, Mrityunjay, Richárd Nagyfi, Timo Steiner, Henrik G Sundt, projectAnthony, Brigham Hall, Kyle Hudson, Kalila, Jef Come, Jvari Williams, Tien Tien, BIll Mangrum, owned, Janne Kytölä, SO, Richárd Nagyfi, Hector, Drexon, Claxvii 177th, Inferencer Deus
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[Profile & Banner Art] https://twitter.com/pygm7 NVIDIA Just Started A New Era of Supercomputing... GTC2024 Highlight](https://i.ytimg.com/vi/GkBX9bTlNQA/mqdefault.jpg)
![LongCat 2.0: The Beginning of the End of NVIDIA MOAT?
In this video, Ill be covering the Meituan LongCats latest flagship model: LongCat 2.0. This model release has some pretty interesting architectural improvements, along with a huge twist: everything was fully trained and inferenced on Chinese ASICs.
my latest project: Intuitive AI Academy
We just wrote a new piece on Optimization!!
https://intuitiveai.academy/
limited time code LOCKIN for 35% off yearly plan
My Newsletter (weekly top research papers)
https://mail.bycloud.ai/
My Patreon
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LongCat 2.0
[Blog] https://longcat.ai/blog/longcat-2.0/
[HuggingFace] https://huggingface.co/meituan-longcat/LongCat-2.0
LongCat Sparse Attention
[Paper] https://arxiv.org/abs/2608.01662
Try out my new fav place to learn how to code https://scrimba.com/?via=bycloudAI
This video is supported by the kind Patrons & YouTube Members:
🙏Spam Maj, Alex, Chris LeDoux, DX Research Group, Poof N Inu, Deagan, Robert Zawiasa, Ryszard Warzocha, Tobe2d, Louis Muk, Akkusativ, Kevin Tai, Mark Buckler, NO U, Tony Jimenez, Ângelo Fonseca, jiye, Anushka, Asad Dhamani, Binnie Yiu, Calvin Yan, Clayton Ford, Diego Silva, Etrotta, Gonzalo Fidalgo, Handenon, Hector, Jake Disco very, Michael Brenner, Nilly K, OlegWock, Daddy Wen, Shuhong Chen, Sid_Cipher, Stefan Lorenz, Sup, tantan assawade, Thipok Tham, Thomas Di Martino, Thomas Lin, Richárd Nagyfi, Paperboy, mika, Leo, Berhane-Meskel, Kadhai Pesalam, mayssam, Bill Mangrum, nyaa, Toru Mon, Lame Plane, Matej Macak, Len Mo, saylikhapekar, ZyanSheep, THEVIERAOS, Ricardo Raphael Corona-Moreno, superchordate
[Discord] https://discord.gg/NhJZGtH
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[Business Inquiries] bycloud@smoothmedia.co
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[Solana (SOL)] 6XyMCEdVhtxJQRjMKgUJaySL8cGoBPzzA2NPDMPfVkKN LongCat 2.0: The Beginning of the End of NVIDIA MOAT?](https://i.ytimg.com/vi/GyyXaCcCxPs/mqdefault.jpg)
![AI Learns To Play Minecraft By Watching YouTube!
Introducing the first Minecraft AI that has obtained a diamond pickaxe without any human input! OpenAI has blown our mind away with this incredible Minecraft agent and an amazing research paper along with it. This research paper VPT demonstrates a very reliable method on how to create a very large amount of dataset and with a very high accuracy.
Learning to Play Minecraft with Video PreTraining (VPT)
[Paper] https://arxiv.org/abs/2206.11795
[OpenAI Blog] https://openai.com/blog/vpt/
[Code] https://github.com/openai/Video-Pre-Training
MineRL Competition
[Website] https://www.aicrowd.com/challenges/neurips-2022-minerl-basalt-competition
This video is supported by the kind Patrons & YouTube Members:
🙏Andrew Lescelius, Chris LeDoux, Panther Modern, 正毅 水野, Jake Disco, Demilson Quintao, Tony Jimenez, Shuhong Chen, Hongbo Men, happi nyuu nyaa, Carol Lo, Deagan, Mose Sakashita, Miguel, Bandera, Todd, Tono Cabanelas, Gennaro Schiano, gunwoo
[Discord] https://discord.gg/NhJZGtH
[Twitter] https://twitter.com/bycloudai
[Patreon] https://www.patreon.com/bycloud
[PayPal] https://paypal.me/cloudweather
[Music 1] https://youtu.be/Mk4oToSq1GE
[Music 2] https://youtu.be/u2DNoZ73etI
[Music 3] https://youtu.be/OgOc1xDD5-E
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[Video Editor] https://twitter.com/MishnImpossible AI Learns To Play Minecraft By Watching YouTube!](https://i.ytimg.com/vi/GzCvLhsN-p8/mqdefault.jpg)
![How Did A Chinese Phone Company Topped Open Source LLM?
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In todays video, let us find out how Xiaomi went from phones, appliances, and EVs to suddenly becoming one of the fastest-rising players in open-source AI. This video breaks down Xiaomi’s MiMo models, the research behind their insane progress, and how they caught up to frontier AI labs in just about a year since their first model release.
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[MiMo-Embodied] https://arxiv.org/pdf/2511.16518
[HySparse] https://arxiv.org/pdf/2602.03560
[MiMo] https://arxiv.org/pdf/2505.07608
[MiMo Audio] https://arxiv.org/abs/2512.23808
[MiMo VL] https://arxiv.org/abs/2506.03569
[MiMo V2 Flash] https://arxiv.org/abs/2601.02780
[MiMo V2.5 Pro] https://mimo.xiaomi.com/mimo-v2-5-pro/
[MiMo Huggingface Models] https://huggingface.co/XiaomiMiMo
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![This new AI that will take your job at McDonalds
Here is a glimpse into the future of robots powered by AI and trained with teleoperated data.
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ALOHA
[Paper] https://arxiv.org/abs/2304.13705
[Project Page] https://tonyzhaozh.github.io/aloha/
Mobile ALOHA
[Paper] https://arxiv.org/abs/2401.02117
[Project Page] https://mobile-aloha.github.io/
[Code] https://github.com/MarkFzp/act-plus-plus
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ALOHA: Abstract
Fine manipulation tasks, such as threading cable ties or slotting a battery, are notoriously difficult for robots because they require precision, careful coordination of contact forces, and closed-loop visual feedback. Performing these tasks typically requires high-end robots, accurate sensors, or careful calibration, which can be expensive and difficult to set up. Can learning enable low-cost and imprecise hardware to perform these fine manipulation tasks? We present a low-cost system that performs end-to-end imitation learning directly from real demonstrations, collected with a custom teleoperation interface. Imitation learning, however, presents its own challenges, particularly in high-precision domains: the error of the policy can compound over time, drifting out of the training distribution. To address this challenge, we develop a novel algorithm Action Chunking with Transformers (ACT) which reduces the effective horizon by simply predicting actions in chunks. This allows us to learn difficult tasks such as opening a translucent condiment cup and slotting a battery with 80-90% success, with only 10 minutes worth of demonstration data.
Mobile ALOHA: Abstract
Imitation learning from human demonstrations has shown impressive performance in robotics. However, most results focus on table-top manipulation, lacking the mobility and dexterity necessary for generally useful tasks. In this work, we develop a system for imitating mobile manipulation tasks that are bimanual and require whole-body control. We first present Mobile ALOHA, a low-cost and whole-body teleoperation system for data collection. It augments the ALOHA system with a mobile base, and a whole-body teleoperation interface. Using data collected with Mobile ALOHA, we then perform supervised behavior cloning and find that co-training with existing static ALOHA datasets boosts performance on mobile manipulation tasks. With 50 demonstrations for each task, co-training can increase success rates by up to 90%, allowing Mobile ALOHA to autonomously complete complex mobile manipulation tasks such as sauteing and serving a piece of shrimp, opening a two-door wall cabinet to store heavy cooking pots, calling and entering an elevator, and lightly rinsing a used pan using a kitchen faucet. This new AI that will take your job at McDonalds](https://i.ytimg.com/vi/HNlS7GyVYK4/mqdefault.jpg)