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Арналар:Барлық арналар▶OpenAI Official113▶Matthew Berman72▶Google Research68▶Microsoft Developer65▶Astana Hub Official65▶AI Master54▶Pixel Perfect50▶AI Flash News49▶Lex Fridman Podcast48▶Matt Wolfe46▶David Ondrej (AI Agents)45▶PyTorch Official43▶IBM Technology AI42▶Hugging Face41▶Yannic Kilcher40▶Y Combinator AI38▶DeepLearning.AI38▶Armeta Kazakhstan37▶sentdex37▶Fireship AI36▶Google Quantum AI35▶The AI Grid35▶ProdAdvice35▶ISSAI (Nazarbayev University)34▶Andrej Karpathy32▶Wes Roth31▶All About AI31▶Two Minute Papers31▶Astar Acceptman30▶Artemii Miller AI29▶Amorev28▶StatQuest AI27▶Robotics & AI (KBTU)25▶Computerphile AI22▶freeCodeCamp AI22▶3Blue1Brown13▶Digital Business KZ13▶ISOFT Kazakhstan6▶Kazi AI3▶Kolesa Group Tech1▶NITEC (GovTech / NAIP)1
📺Yannic Kilcher
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▶ YouTube — Yannic Kilcher
Leave No Context Behind: Efficient Infinite Context Transformers with Infini-attention
#YouTube
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▶ YouTube — Yannic Kilcher
ORPO: Monolithic Preference Optimization without Reference Model (Paper Explained)
#YouTube
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▶ YouTube — Yannic Kilcher
[ML News] OpenAI is in hot waters (GPT-4o, Ilya Leaving, Scarlett Johansson legal action)
#OpenAI#GPT-4o
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▶ YouTube — Yannic Kilcher
Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools (Paper Explained)
#YouTube
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▶ YouTube — Yannic Kilcher
Privacy Backdoors: Stealing Data with Corrupted Pretrained Models (Paper Explained)
#YouTube
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▶ YouTube — Yannic Kilcher
Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters (Paper)
#YouTube
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▶ YouTube — Yannic Kilcher
GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models
#YouTube
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▶ YouTube — Yannic Kilcher
Safety Alignment Should be Made More Than Just a Few Tokens Deep (Paper Explained)
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▶ YouTube — Yannic Kilcher
TokenFormer: Rethinking Transformer Scaling with Tokenized Model Parameters (Paper Explained)
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▶ YouTube — Yannic Kilcher
Byte Latent Transformer: Patches Scale Better Than Tokens (Paper Explained)
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▶ YouTube — Yannic Kilcher
[GRPO Explained] DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
#YouTube
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▶ YouTube — Yannic Kilcher
Energy-Based Transformers are Scalable Learners and Thinkers (Paper Review)
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▶ YouTube — Yannic Kilcher
Context Rot: How Increasing Input Tokens Impacts LLM Performance (Paper Analysis)
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▶ YouTube — Yannic Kilcher
[Қағазды талдау] Еркін трансформатор (және кейбір вариациялық автокодер материалдары)
#YouTube
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▶ YouTube — Yannic Kilcher
[Бейнеге жауап] Cloudflare код режимі MCP және құралды шақыру туралы нені жіберіп алады
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▶ YouTube — Yannic Kilcher
[Paper Analysis] On the Theoretical Limitations of Embedding-Based Retrieval (Warning: Rant)
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▶ YouTube — Yannic Kilcher
TiDAR: диффузияда ойлаңыз, авторегрессияда сөйлесіңіз (қағазды талдау)
#YouTube
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▶ YouTube — Yannic Kilcher
This game was made for robots, I played it anyway - Crafter Let's Play
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▶ YouTube — Yannic Kilcher
What is the Hardware Lottery? (Machine Learning Research Paper Explained by Yannic Kilcher) #Shorts
#arXiv#YouTube
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