iFeeling Daily
Daily curated AI insights you can't miss.
Run AI Workloads on Any Cloud with Zero-Egress Hugging Face Storage
Hugging Face Storage now integrates with SkyPilot, allowing zero-egress reads of models and datasets from any GPU cloud.
Hugging Face Models on Microsoft Foundry Managed Compute
Microsoft Foundry launches a curated Hugging Face Collection with pre-screened, pre-staged open-weight models deployable onto managed GPU infrastructure via a single click.
PRX Part 4: Data Strategy for Diffusion Model Training
Photoroom's PRX data strategy emphasizes diverse pre-training, VLM re-captioning, and a flexible pipeline using Lance for curation and MDS for streaming.
Anatomy of a Self-Improving Agent: Arize’s Signal
Arize's Signal agent inverts the debugging loop: traces pulled to the filesystem, Claude Code produces a fix, and you wake up to a PR instead of a pager.
Through the AI Fog: The Architectural Decision Agentic Security Depends On
Manoj Nair from Snyk warns that security backlog is growing 108% quarter over quarter because agents write code faster than vulnerabilities can be closed. The generator and validator must be separate systems, because no probabilistic model can reliably police another.
From Agent Traces to Agent Simulations — Rustem Feyzkhanov, Snorkel AI
基于生产环境 Agent 轨迹重建私有仿真环境，用于评估成本、延迟和策略合规性，替代依赖公共基准测试的思路。
Special Topics in Kernels, RL, Reward Hacking in Agents — Daniel Han, Unsloth
This seminar exposes a persistent tension in AI: models shrink dramatically without a proportional loss of intelligence. Daniel Han makes the case that if you make a model 86% smaller, it does not get 86% dumber—it only gets 14% less dumb. That single observation cuts through the hype around ever-larger models and reframes the problem as one of efficiency and infrastructure. At the same time, the talk reveals a darker side of progress: systematic cheating on benchmarks, where models or their harnesses are tuned to game leaderboards rather than solve real tasks.
Garry Tan: The 400x Leverage of AI-Native Organizations
Garry Tan, president of Y Combinator, explains how AI-native companies achieve massive productivity gains by treating AI as a workforce and encoding roles as markdown skill files. The real leverage lies not in model weights but in how you wire the work, enabling lean teams to operate at scales previously requiring hundreds of employees.
How an AI Agent Became the #1 Contributor in OpenAI’s Hiring Challenge
In OpenAI's Parameter Golf competition, an autonomous AI agent became the top contributor—producing more merged records than any human—forcing us to rethink how we measure research contributions and collaborate with AI systems in practice.