# Token Overhead
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Top podcast episodes featuring token overhead.
How to Build AI that actually Ships in Production - Aleksandr Kim
In this talk, Aleksandr Kim, Senior Data Scientist at Intuit, shares his expertise in building AI-powered features in production from fine-tuning BERT models in cyber security to engineering scalable data verification platforms. We explore the reality of moving beyond messy research code to build o…
Tokenomics | The new AI currency & your options explained
Control what you're billed on. Tokens are the currency of AI, and how you design your app determines how many you spend. Compress conversation history instead of resending it raw, cap output tokens with matching prompt instructions, and cache static context so each reuse costs a fraction of the fir…
Amazon API Data Pipelines & AI Design Workflows — Broad Match Show
In this Broad Match Show, Danny McMillan and Adam Heist cover two of the most practical AI frontiers for Amazon sellers right now: getting direct API access to your Seller Central data and building a fully automated design workflow from inspiration through to live assets.
Adam breaks down how he c…
ai morning #3 — fable 5 trained another ai. nobody was watching.
A benchmark result landed overnight that most people missed. A model ran for 17 hours with no human in the loop and trained a weaker model. The gap versus every other frontier model wasn't close. Then open-source weights dropped on a Friday, and the same model everyone is praising hit a 48-hour int…
🦃 ThursdAI - Thanksgiving special 25’ - Claude 4.5, Flux 2 & Z-image vs 🍌, MCP gets Apps + New DeepSeek!?
Hey ya’ll, Happy Thanskgiving to everyone who celebrates and thank you for being a subscriber, I truly appreciate each and every one of you!
Just wrapped up the third (1, 2) Thanksgiving special Episode of ThursdAI, can you believe November is almost over?
We had another banger week in AI, with a …
LatentSkill: From In-Context Textual Skills to In-Weight Latent Skills for LLM Agents
🤗 Upvotes: 52 | cs.CL, cs.AI
Authors:
Aofan Yu, Chenyu Zhou, Tianyi Xu, Zihan Guo, Rong Shan, Zhihui Fu, Jun Wang, Weiwen Liu, Yong Yu, Weinan Zhang, Jianghao Lin
Title:
LatentSkill: From In-Context Textual Skills to In-Weight Latent Skills for LL…
SKILL0: In-Context Agentic Reinforcement Learning for Skill Internalization
🤗 Upvotes: 72 | cs.LG
Authors:
Zhengxi Lu, Zhiyuan Yao, Jinyang Wu, Chengcheng Han, Qi Gu, Xunliang Cai, Weiming Lu, Jun Xiao, Yueting Zhuang, Yongliang Shen
Title:
SKILL0: In-Context Agentic Reinforcement Learning for Skill Internalization
…
Why AI is Turning Websites Liquid
the International Journal on Science and Technology (IJSAT) explores the strategic selection between fine-tuning and prompt engineering when implementing Large Language Models (LLMs) in consumer products. Fine-tuning is characterized as a resource-intensive process that adapts a model to specialize…
AI Daily – Monday, July 13, 2026
Tencent's massive 295-billion-parameter Hy3 model bets on agent-first architecture over raw scale, signaling a distinct Chinese approach to frontier AI. • China's GLM-5.2 delivers DeepSeek-level coding performance on consumer hardware, deepening fears of margin collapse for US AI labs. • Claude Cod…
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