OSS Capiτal (@OSSCapital) / X

OSS Capiτal

5,168 posts

OSS Capiτal

@OSSCapital

🌏🌎🌍

Joined July 2018

OSS Capiτal reposted
JJ
@JosephJacks_
14h
Nikesh — not all secure open source is “friction fill” … when done right, it’s superior.. See @planepowers (replacing jira, et al), @calcom (replacing calendly, et al), @hoppscotch_io (replacing postman), @godotengine (replacing Unity)..
Nikesh Arora
@nikesharora
Jun 23
The AI Business model trap: LLMs want cash flow to fund the race to AGI or the next model. Enter free consumer AI - they are losing a lot of money on the breadth of models to serve consumers for free! They are caught in the post training data trap, free consumer usage feeds post
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OSS Capiτal reposted
Liquid AI
@liquidai
19h
Deploying a small model forces you to define accuracy before you train, not after. Our CTO Mathias Lechner, @mlech26l, talks with COO Jeffrey Li, @jeffr3yli, about customization, taste, and what it takes to ship small.
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OSS Capiτal reposted
Godot Engine
@godotengine
Jun 23
We would like to thank @Battlefield Studios for the Corporate Platinum sponsorship. Thanks to them, we will be able to continue improving the engine for everyone, and welcome new users who are creating custom Battlefield maps using Godot + Portal. fund.godotengine.org
109K
OSS Capiτal reposted
Vihar Kurama
@viharkurama
Jun 20
1/ Our team is working this weekend, pushing some major changes for @planepowers. v3.0.0 is close. Biggest one for enterprise: workspace governance. States, work item types, and workflows now live at the workspace level, not inside each project. One canonical set for the org.
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OSS Capiτal reposted
Liquid AI
@liquidai
Jun 19
Storing too many tools in your context window increases latency and can lead to wrong tool selection. In this demo, we used LFM2.5-ColBERT-350M as a filter to only select the five most relevant tools among 151 options. It's fast and reliable, even without any specific
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OSS Capiτal reposted
JJ
@JosephJacks_
Jun 19
The ONLY American foundation model AI lab continuously focused on shipping frontier open weights models from scratch (not tuning bases from other labs) is @liquidai. I just did a fact check on myself to verify this — lots of other names came up, but they do not train from
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OSS Capiτal reposted
Vihar Kurama
@viharkurama
Jun 18
We are trending globally on GitHub, again! Looks like a lot more agents are doing work on @planepowers.
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OSS Capiτal reposted
Maxime Labonne
@maximelabonne
Jun 18
LFM2.5-ColBERT-350M is a surprisingly reliable smart tool selector. We gave it 151 tools, and it consistently surfaces the 5 most relevant ones based on the user prompt. This saves tokens and improves accuracy. Ideal for hmmmm agentic edge models? 👀
00:00
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OSS Capiτal reposted
Godot Engine
@godotengine
Jun 18
#GodotEngine 4.7 is here! 🎉 Like a cult classic movie, Godot 4 has only gotten better with age; the 4.7 Director's Cut helms a bevy of new features to eliminate any remaining friction between you and your vision! godotengine.org/releases/4.7/
69K
OSS Capiτal reposted
JJ
@JosephJacks_
Jun 18
Wow.. seems @liquidai is the only American lab outperforming the Chinese on open weights models! 🌊 📲
Liquid AI
@liquidai
Jun 18
Introducing LFM2.5-Embedding-350M and LFM2.5-ColBERT-350M: two multilingual retrieval models built for ultra-fast and accurate search across 11 languages. > End-to-end retrieval latency as low as 1.5ms with our enterprise stack! 🚀 > Consistently best-in-class multilingual and
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OSS Capiτal reposted
Noctus
@noctus91
Jun 10
I recently switched from Qwen 3.5 9B to LFM2.5-8B-A1B by @liquidai, and it's quickly become my default local model in Hermes Agent Desktop. For agentic tasks, it's one of the strongest local models I've used so far. It's surprisingly fast, reliable, and works really well with
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Liquid AI
@liquidai
May 28
Today, we're releasing LFM2.5-8B-A1B, a device-optimized model designed to power real-life applications on phones, laptops, PCs, robots, and fast & lightweight server-side use-cases. > 8B MoE, 1.5B active > Expanded 128K context > LFM2.5 flagship hybrid MoE architecture >
75K
OSS Capiτal reposted
Umbrel ☂️
@umbrel
Jun 17
Today ~$20k of hardware can run GLM-5.2 locally. Think about it - frontier-class AI, fully local, in your house, sitting on your desk. Now fast-forward a year. The price only falls from here, and your home server is quietly going to become the most important device you own.
Z.ai
@Zai_org
Jun 16
Introducing GLM-5.2: Frontier Intelligence, Open Weights - Significant improvements in coding and agentic tasks - Strong long-horizon capabilities with a 1M context window - Two levels of reasoning effort: GLM-5.2 (max) pushes the limits, while GLM-5.2 (high) strikes a strong
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OSS Capiτal reposted
JJ
@JosephJacks_
Jun 16
AI control plane = @planepowers 🪄 I’ve never witnessed such speed of 10,000+ user enterprise adoption in my career. Several new multi-thousand-user enterprise deployment requests inbound weekly … and we spend ZERO dollars on marketing / ads.
Chamath Palihapitiya
@chamath
Jun 16
$60Billion. This is the first, but not the last, big exit at the application layer of AI. As product value accrues and accelerates upwards, the focus over the next few years will be firmly on the “control plane”: What gives organizations who want to go all in on AI the
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