Tootfinder

The Lurie administration wants to slash #PotreroYard affordable housing because they "just can't find the money."
Our mayor is a billionaire. We have the third most billionaires living here of any city in the world. We can't accept these excuses.

I was looking forward to cycling to work in the snow today, but alas, the road salt corroded the rear brake cable housing on my bike over Christmas, so the U8 it is. Just as I cancelled my #Deutschlandticket.

In-the-Flow Agentic System Optimization for Effective Planning and Tool Use
Zhuofeng Li, Haoxiang Zhang, Seungju Han, Sheng Liu, Jianwen Xie, Yu Zhang, Yejin Choi, James Zou, Pan Lu
https://arxiv.org/abs/2510.05592

In-the-Flow Agentic System Optimization for Effective Planning and Tool Use
Outcome-driven reinforcement learning has advanced reasoning in large language models (LLMs), but prevailing tool-augmented approaches train a single, monolithic policy that interleaves thoughts and tool calls under full context; this scales poorly with long horizons and diverse tools and generalizes weakly to new scenarios. Agentic systems offer a promising alternative by decomposing work across specialized modules, yet most remain training-free or rely on offline training decoupled from the l…

OptPipe: Memory- and Scheduling-Optimized Pipeline Parallelism for LLM Training
Hongpei Li, Han Zhang, Huikang Liu, Dongdong Ge, Yinyu Ye
https://arxiv.org/abs/2510.05186 https:…

OptPipe: Memory- and Scheduling-Optimized Pipeline Parallelism for LLM Training
Pipeline parallelism (PP) has become a standard technique for scaling large language model (LLM) training across multiple devices. However, despite recent progress in reducing memory consumption through activation offloading, existing approaches remain largely heuristic and coarse-grained, often overlooking the fine-grained trade-offs between memory, computation, and scheduling latency. In this work, we revisit the pipeline scheduling problem from a principled optimization perspective. We obser…

Work, Housing and Health: Northampton Behind the Numbers https://edintone.com/work-housing-health/ In 1924, the boot and shoe industry dominated Northampton’s workforce. The Boot and Shoe O

Work, Housing and Health: Northampton Behind the Numbers - Miscellanea Edintone
In 1924, the boot and shoe industry dominated Northampton’s workforce. The Boot and Shoe Operatives Trade Union had 13,104 members; officials estimated that only 5% of adult workers were outside the union.

That's neat.
#Madison #Housing #YIGBY

Journalist Eoin Higgins says Matt Taibbi is suing him for defamation over Owned, his book about tech billionaires and the left, and "I stand by my work" (Eoin Higgins/The Flashpoint)
https://eoinhiggins.substack.com/p/yes-im-being-sued-by-matt-taibbi<…

Yes, I'm being sued by Matt Taibbi
Does that make me the realest free speech warrior?

Work, Housing and Health: Northampton Behind the Numbers https://edintone.com/work-housing-health/ In 1924, the boot and shoe industry dominated Northampton’s workforce. @…

Work, Housing and Health: Northampton Behind the Numbers - Miscellanea Edintone
In 1924, the boot and shoe industry dominated Northampton’s workforce. The Boot and Shoe Operatives Trade Union had 13,104 members; officials estimated that only 5% of adult workers were outside the union.

What @… said:
Providing employment after deployment = supporting troops
Providing housing = supporting troops
Destigmatizing mental health care = supporting troops
Preventing armed conflict = supporting troops
You know what’s NOT supporting troops? Starting wars as political cover for a failing president. Deploying National Guard just to terrorize people and provoke a backlash. Issuing illegal orders. •That• is not supporting troops.
https://hachyderm.io/@mekkaokereke/115634994186527377