Poolside AI
PulseAugur coverage of Poolside AI — every cluster mentioning Poolside AI across labs, papers, and developer communities, ranked by signal.
3 day(s) with sentiment data
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Poolside AI's Laguna S 2.1 achieves superior performance with a smaller footprint
Poolside AI has released its Laguna S 2.1 model, which reportedly outperforms larger competitors despite being 10 times smaller. The model was developed using a "Model Factory" that conducts 10,000 to 20,000 experiments…
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Poolside AI releases Lagona S2.1, a 118B MoE coding model runnable on consumer hardware
Poolside AI has released Lagona S2.1, an 118-billion-parameter mixture-of-experts model designed for local deployment by developers. Despite its large parameter count, only a fraction are active per token, allowing it t…
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Poolside AI releases Laguna S 2.1, touts rapid model factory
Poolside AI has released its Laguna S 2.1 model, which reportedly outperforms models from Thinking Machines that are nearly ten times its size. The company's co-founder, Eiso Kant, discussed their "Model Factory" approa…
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Poolside AI releases Laguna S 2.1, a compact coding model with 1M context
Poolside AI has released Laguna S 2.1, an 118B parameter Mixture-of-Experts model with 8B activated parameters and a 1M token context window. The model was developed in under nine weeks and demonstrates strong performan…
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GLM-5.2 emerges as top open-weight AI model, rivaling GPT-5.5
The open-weight language model GLM-5.2 has garnered significant attention, with multiple sources indicating it performs comparably to frontier models like GPT-5.5 and Anthropic's Opus 4.8. This model features architectu…
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Open AI Models Lag Frontier Closed Models, Benchmarks Debated
Several leading AI labs have released new open-source models, including DeepSeek V4, Gemma 4, Kimi K2.6, and MiMo 2.5. An assessment by CAISI suggests these open models lag behind frontier closed models, with the gap wi…
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Blog post critiques AI benchmark hacking
A blog post on Poolside.ai critiques the practice of "benchmark hacking" in AI development. It argues that the focus on optimizing models for specific benchmarks can lead to systems that perform well on tests but fail i…
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Poolside AI releases open-weight agentic coding models Laguna XS.2 and M.1
Poolside AI has launched two new open-weight agentic coding models, Laguna XS.2 and M.1. The models achieved impressive scores on the SWE-bench Verified benchmark, with M.1 reaching 72.5% and XS.2 reaching 68.2%. The XS…
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Poolside AI releases open-weight Laguna XS.2 and M.1 coding models
Poolside AI has released two new agentic coding models, Laguna M.1 and Laguna XS.2, along with their agent training and operation runtime. Laguna M.1 is a large Mixture of Experts (MoE) model trained on 30T tokens using…