Tootfinder

Anthropic co-founder Jared Kaplan says Anthropic cut Windsurf's direct access to Claude models because of reports that OpenAI is acquiring Windsurf (Maxwell Zeff/TechCrunch)
https://techcrunch.com/2025/06/05/anth

Anthropic co-founder on cutting access to Windsurf: 'It would be odd for us to sell Claude to OpenAI' | TechCrunch
Anthropic's Jared Kaplan said the company largely cut Windsurf's direct access to Anthropic's Claude AI models because of rumors OpenAI is acquiring the startup.

Sources: WBD initiates a round of layoffs in its cable TV divisions, affecting well under 100 employees and largely impacting the Discovery side of the company (Peter White/Deadline)
https://deadline.com/2025/06/warner-bros-discovery-layoffs-tv-d…

Warner Bros. Discovery Initiates More Layoffs In Cable TV Divisions
Deadline understands that the company is set to layoff a number of people, particularly on the cable television side of its business.

National TV news largely failed to connect the record-breaking eastern U.S. heat dome to climate change (Evlondo Cooper/Media Matters for America)
https://www.mediamatters.org/broadcast-networks/national-tv-news-largely-failed-connect-record-breaking-eastern-us-heat-dome
http://www.memeorandum.com/250702/p60#a250702p60

Interesting study of eastern Joshua tree mycorrhizal associations from trees near the Dome Fire burn in Mojave National Preserve, with sampling stratified by season
#ecology #mutualism #JoshuaTree …

This https://arxiv.org/abs/2506.02308 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

MINT: Multimodal Instruction Tuning with Multimodal Interaction Grouping
Recent advances in multimodal foundation models have achieved state-of-the-art performance across a range of tasks. These breakthroughs are largely driven by new pre-training paradigms that leverage large-scale, unlabeled multimodal data, followed by instruction fine-tuning on curated labeled datasets and high-quality prompts. While there is growing interest in scaling instruction fine-tuning to ever-larger datasets in both quantity and scale, our findings reveal that simply increasing the numb…

This https://arxiv.org/abs/2505.20290 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

EgoZero: Robot Learning from Smart Glasses
Despite recent progress in general purpose robotics, robot policies still lag far behind basic human capabilities in the real world. Humans interact constantly with the physical world, yet this rich data resource remains largely untapped in robot learning. We propose EgoZero, a minimal system that learns robust manipulation policies from human demonstrations captured with Project Aria smart glasses, $\textbf{and zero robot data}$. EgoZero enables: (1) extraction of complete, robot-executable ac…

They Planned Parties and Salsa Music for July 4th.
ICE Raids Made Them Think Twice.
Some communities in the Los Angeles region canceled events over fears of immigration raids,
as Latinos grapple with how, and whether, to celebrate Independence Day.
Bell Gardens, where more than 96 percent of residents are Hispanic, is one of more than two dozen so-called Gateway Cities that make up a hub of largely Latino working-class communities.
In recent days, the mayor of …

They Planned Parties and Salsa Music for July 4th. ICE Raids Made Them Think Twice.
Some communities in the Los Angeles region canceled events over fears of immigration raids, as Latinos grapple with how, and whether, to celebrate Independence Day.

This https://arxiv.org/abs/2410.01050 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Steering Elongate Multi-legged Robots By Modulating Body Undulation Waves
Centipedes exhibit great maneuverability in diverse environments due to their many legs and body-driven control. By leveraging similar morphologies and control strategies, their robotic counterparts also demonstrate effective terrestrial locomotion. However, the success of these multi-legged robots is largely limited to forward locomotion; steering is substantially less studied, in part because of the difficulty in coordinating a high degree-of-freedom robot to follow predictable, planar trajec…

This https://arxiv.org/abs/2506.01538 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

LAMARL: LLM-Aided Multi-Agent Reinforcement Learning for Cooperative Policy Generation
Although Multi-Agent Reinforcement Learning (MARL) is effective for complex multi-robot tasks, it suffers from low sample efficiency and requires iterative manual reward tuning. Large Language Models (LLMs) have shown promise in single-robot settings, but their application in multi-robot systems remains largely unexplored. This paper introduces a novel LLM-Aided MARL (LAMARL) approach, which integrates MARL with LLMs, significantly enhancing sample efficiency without requiring manual design. LA…

MultiGen: Using Multimodal Generation in Simulation to Learn Multimodal Policies in Real
Renhao Wang, Haoran Geng, Tingle Li, Feishi Wang, Gopala Anumanchipalli, Philipp Wu, Trevor Darrell, Boyi Li, Pieter Abbeel, Jitendra Malik, Alexei A. Efros
https://arxiv.org/abs/2507.02864

MultiGen: Using Multimodal Generation in Simulation to Learn Multimodal Policies in Real
Robots must integrate multiple sensory modalities to act effectively in the real world. Yet, learning such multimodal policies at scale remains challenging. Simulation offers a viable solution, but while vision has benefited from high-fidelity simulators, other modalities (e.g. sound) can be notoriously difficult to simulate. As a result, sim-to-real transfer has succeeded primarily in vision-based tasks, with multimodal transfer still largely unrealized. In this work, we tackle these challenge…