Uploaded July 2025 | Updated September 2026, 1 week ago
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ByteDance Seed Proposed PMA which is a model merging technique for pre-training models to project your annealed performance without the need to go through annealing. This can save up to millions in big model training runs.
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Model Merging in Pre-training of Large Language Models
[Paper] alphaxiv.org/abs/2505.12082
Other "model merging" techniques I mentioned (but are used in completely different scenarios)
alphaxiv.org/abs/2410.03617
alphaxiv.org/abs/2410.15661
alphaxiv.org/abs/2403.07816
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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, Constantinos Charilaou, Abay Bektursun
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[Video Editor] Abhay
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Check out Runpod's Hub and Serverless to make deploying AI models even easier! https://runpod.io?ref=h9oj1vbp
ByteDance Seed Proposed PMA which is a model merging technique for pre-training models to project your annealed performance without the need to go through annealing. This can save up to millions in big model training runs.
My Newsletter
mail.bycloud.ai
my project: find, discover & explain AI research semantically
findmypapers.ai
My Patreon
patreon.com/c/bycloud
Model Merging in Pre-training of Large Language Models
[Paper] alphaxiv.org/abs/2505.12082
Other "model merging" techniques I mentioned (but are used in completely different scenarios)
alphaxiv.org/abs/2410.03617
alphaxiv.org/abs/2410.15661
alphaxiv.org/abs/2403.07816
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:
🙏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, Constantinos Charilaou, Abay Bektursun
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[Video Editor] Abhay
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![Robots Just Had Their GPT-3 Moment
In-context learning for robots has been a long-anticipated capability, as it could allow robots to quickly adapt to new tasks without additional training, and Gen-1.5 might have just demonstrated that it is possible for robots at complex tasks.
Gen-1.5
[Blog] https://generalistai.com/blog/gen-1.5
my latest project: Intuitive AI Academy
We just wrote a new piece on Linear Attention!!
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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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[Bitcoin (BTC)] 3JFMJQVGXNA2HJE5V9qCwLiqy6wHY9Vhdx
[Ethereum (ETH)] 0x3d784F55E0bE5f35c1566B2E014598C0f354f190
[Litecoin (LTC)] MGHnqALjyU2W6NuJSSW9fTWV4dcHfwHZd7
[Bitcoin Cash (BCH)] 1LkyGfzHxnSfqMF8tN7ZGDwUTyBB6vcii9
[Solana (SOL)] 6XyMCEdVhtxJQRjMKgUJaySL8cGoBPzzA2NPDMPfVkKN Robots Just Had Their GPT-3 Moment](https://i.ytimg.com/vi/cqwKceUSZ5Q/mqdefault.jpg)
![When AI Is Designed Like A Biological Brain
Remove your personal information from the web at https://JoinDeleteMe.com/BYCLOUD and use
code BYCLOUD for 20% off🙌
In this video, we take a look at this research paper called Continuous Thought Machines published by http://sakana.ai/ , where they integrate neural timing into an AI model.
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Continuous Thought Machines
[Paper] https://arxiv.org/abs/2505.05522
[Project Page] https://pub.sakana.ai/ctm/
[Code] https://github.com/SakanaAI/continuous-thought-machines
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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 When AI Is Designed Like A Biological Brain](https://i.ytimg.com/vi/dYHkj5UlJ_E/mqdefault.jpg)
![Stable Diffusion SDXL 0.9, Text To Video Zeroscope v2 & More [The AI Timeline #7]
Welcome to my 7th episode of the weekly AI news series The AI Timeline, where I go through the AI news in the past week with the most distilled information and memes!
zeroscope v2
[30fps] https://huggingface.co/cerspense/zeroscope_v2_dark_30x448x256
[576w] https://huggingface.co/cerspense/zeroscope_v2_576w
[XL] https://huggingface.co/cerspense/zeroscope_v2_XL
[HuggingFace Demo] https://huggingface.co/spaces/hysts/zeroscope-v2
[Modelscope] https://huggingface.co/damo-vilab/modelscope-damo-text-to-video-synthesis
SDXL 0.9
[Blog] https://stability.ai/blog/sdxl-09-stable-diffusion?utm_source=Website&utm_medium=Twitter&utm_campaign=SDXL.9
[ClipDrop] https://clipdrop.co/
Textbooks Are All You Need
[Paper] https://arxiv.org/pdf/2306.11644.pdf
Kosmos-2
[Paper] https://arxiv.org/pdf/2306.14824.pdf
MPT-30B-Chat
[Demo] https://huggingface.co/spaces/mosaicml/mpt-30b-chat
[HuggingFace Card] https://huggingface.co/mosaicml/mpt-30b-chat
AudioPaLM
[Paper] https://arxiv.org/abs/2306.12925
[Project Page] https://google-research.github.io/seanet/audiopalm/examples/#s2tt-section
Faith and Fate: Limits of Transformers on Compositionality
[Paper] https://arxiv.org/pdf/2305.18654.pdf
MotionGPT
[Paper] https://arxiv.org/pdf/2306.14795.pdf
[Project Page] https://motion-gpt.github.io/
[Code] https://github.com/OpenMotionLab/MotionGPT
AiBreakfast
[TW] https://twitter.com/AiBreakfast/status/1673350504162955266?s=20
Unity Muse & Unity Sentis
[Article] https://blog.unity.com/engine-platform/introducing-unity-muse-and-unity-sentis-ai
PanoHead
[Paper] https://arxiv.org/abs/2303.13071
[Project Page] https://sizhean.github.io/panohead
[Code] https://github.com/SizheAn/PanoHead
Drag Diffusion
[Paper] https://arxiv.org/pdf/2306.14435.pdf
[DragGAN] https://vcai.mpi-inf.mpg.de/projects/DragGAN/
Dream Editor
[Paper] https://arxiv.org/pdf/2306.13455.pdf
WALDO v2
[TW] https://twitter.com/StephanSturges/status/1674050823062536192?s=20
[TW] https://twitter.com/StephanSturges/status/1673036804352618496?s=20
[website] https://aircortex.com/
CS50 at Harvard
[article] https://www.thecrimson.com/article/2023/6/21/cs50-artificial-intelligence/
Japanese Upper Body Motion Tracking Software
[Webpage] https://webcammotioncapture.info/#accordion
[TW] https://twitter.com/webcammocap/status/1672865027827847169?s=20
Doraemon Comic Panel
[Reddit] https://www.reddit.com/r/StableDiffusion/comments/14k33wa/doraemon_predicted_ai_image_generation/?utm_source=share&utm_medium=web2x&context=3
1923 Comic
[Google Books] https://imgur.com/a/uccITRa
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Headlines of The Week 0:00
Weekly Dose of LLM 2:50
Rapid Fire News & FFA 8:11 Stable Diffusion SDXL 0.9, Text To Video Zeroscope v2 & More [The AI Timeline #7]](https://i.ytimg.com/vi/dusMxQoXkMg/mqdefault.jpg)
![A Closer Look At Kimi K3s INSANE Architecture Breakthrough
Need high quality cloud GPUs? Check out Verda now, and use the code BYCLOUD-50 to get $50 of compute credits for just $5!
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The 6 months gap between open source and closed source might not exist now. Moonshot AIs latest Kimi K3 just topped the LLM leaderboard, coming in as the 3rd best model in the world, while being open weights. In this video, I will be breaking down how they have achieve this insane feat.
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We just wrote a new piece on Optimization!!
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Kimi K3 Technical Report
[Paper] https://www.alphaxiv.org/abs/2607.24653
MoonEP
[GitHub] https://github.com/moonshotAI/moonep
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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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[Ko-fi] https://ko-fi.com/bycloudai A Closer Look At Kimi K3s INSANE Architecture Breakthrough](https://i.ytimg.com/vi/g683I1-4MKE/mqdefault.jpg)
![[VOD] First Look At Claude 3 - Can It Beat GPT-4?
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My Patreon goats:
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 [VOD] First Look At Claude 3 - Can It Beat GPT-4?](https://i.ytimg.com/vi/g8t3WUBXBPM/mqdefault.jpg)
![How Did DeepSeek Make V4 So Cheap?
Need to fine-tune a model without the hassle? Try out Crusoes serverless fine-tuning today! https://www.crusoe.ai/contact-sales/serverless-preview?utm_source=bycloud&utm_medium=influencer&utm_campaign=serverlessfinetuning
Learn AI intuitively, intro into LLMs with minimal math!
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limited time code SUMMER for 25% off yearly plan
We just wrote a new piece on Optimizers
After a month of delay, here is my part 1 breakdown of the DeepSeek-V4 paper. In this video, Ill be covering all the key developments theyve made that you should know if you want to keep up with the frontier of AI.
I will have a part 2 that is a deep dive into their infrastructure side of developments that is a lot more advanced so stay tuned!
*thumbnail: this is the price per million tokens when the input is a cache hit. The normal price for input (cache miss) is $0.435.
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DeepSeek-V4
[Paper] https://www.alphaxiv.org/abs/deepseek-v4
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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
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[Ko-fi] https://ko-fi.com/bycloudai How Did DeepSeek Make V4 So Cheap?](https://i.ytimg.com/vi/gC76aeibdFA/mqdefault.jpg)

![Neuralink Just Released Their First Human Demo
[Neuralink Live Stream VOD] https://x.com/neuralink/status/1770563939413496146?s=20
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
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[Music] massobeats - breeze
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[Video Editor] @askejm Neuralink Just Released Their First Human Demo](https://i.ytimg.com/vi/h1BYG4dCGmU/mqdefault.jpg)
![I used NotebookLM’s AI podcast to study… Is it actually good?
The first 500 people to use my link will get a 1 month free trial of Skillshare https://skl.sh/bycloud10241
Here are my review and thoughts on Googles NotebookLM used as a tool to help me study...
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notebookLM
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[Video Editor] bhargavesque
0:00 Intro & context
4:07 Review I used NotebookLM’s AI podcast to study… Is it actually good?](https://i.ytimg.com/vi/h24Tr_cnpo8/mqdefault.jpg)
![Googles TurboQuant Memory Reduction Claim vs Reality
Check out Inngest and let your AI agents wear a harness now!
https://www.inngest.com/?utm_source=youtube&utm_medium=video&utm_campaign=yt-bycl-4
With how TurboQuant shook the general public with its insane 6x memory reduction claim for LLMs, lets take a closer look at what actually happened underneath, and validate their claims by understanding how TurboQuant actually works.
my latest project: Intuitive AI Academy
We just wrote a new piece on Distillation & MoE!
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TurboQuant
[Paper] https://arxiv.org/abs/2504.19874
[Project Page] https://research.google/blog/turboquant-redefining-ai-efficiency-with-extreme-compression/
[OpenReview Comments] https://openreview.net/forum?id=tO3ASKZlok
PolarQuant
[Paper] https://arxiv.org/abs/2502.02617
QJL
[Paper] https://arxiv.org/abs/2406.03482
KIVI
[Paper] https://arxiv.org/abs/2402.02750
RabitQ
[Paper] https://arxiv.org/abs/2405.12497
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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
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[Ko-fi] https://ko-fi.com/bycloudai Googles TurboQuant Memory Reduction Claim vs Reality](https://i.ytimg.com/vi/haoAI2lIZ74/mqdefault.jpg)
![LLM’s Billion Dollar Problem
Check out Inngest and let your AI agents wear a harness now https://innge.st/yt-bycl-1
This video originally was going to be about the Linear Attention Saga that happened between June and November last year, but it turned out I needed quite some build up to explain what the significance of Linear Attention, 1 million context window, and compute scaling are. So it accidentally became a 17 mins video...
my latest project: Intuitive AI Academy
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limited time code NYNM for 50% off forever (only a 25 spots left!)
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my project: find, discover & explain AI research semantically
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Sauces (will try to be in order of apperance)
GPT-OSS
[Code] https://github.com/openai/gpt-oss
[Paper] https://arxiv.org/abs/2508.10925
(they did not mention it is sliding window attention explicitly in its paper)
DeepSeek V3.2
[Paper] https://arxiv.org/pdf/2512.02556
DeepSeek V2 (Multi-head Latent Attention)
[Paper] https://arxiv.org/abs/2405.04434
Kimi K2.5
[Paper] https://arxiv.org/abs/2602.02276
MiniMax
[Text-01] https://arxiv.org/abs/2501.08313
[M1] https://arxiv.org/abs/2506.13585
[M2] https://huggingface.co/MiniMaxAI/MiniMax-M2
[Zhihu Blog] https://www.zhihu.com/question/1965302088260104295/answer/1966810157473335067
Qwen-3 Next
[Project Page] https://qwen.ai/blog?id=4074cca80393150c248e508aa62983f9cb7d27cd
Hunyuan T1
[Project Page] https://tencent.github.io/llm.hunyuan.T1/README_EN.html
Kimi Linear
[Paper] https://arxiv.org/abs/2510.26692
Context Arena (used for comparing long context performance)
[Project Page] https://contextarena.ai/
Gemini 3 Flash
[Blog] https://blog.google/products-and-platforms/products/gemini/gemini-3-flash/
Claude 4.6
[Blog] https://www.anthropic.com/news/claude-opus-4-6
Try out my new fav place to learn how to code https://scrimba.com/?via=bycloudAI
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