🌊 | Co-founder, CTO @papercompute | 🎤 Hosting @opensourceready | 🐹 maintaining spf13/cobra

Plasma is seriously so goated: dedicated audio mixer with per input/output level setting? Other OSs wish they could be KDE
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Apparently all of these “AI is escaping containment” stories are actually just AI researchers not knowing jack squat about the absolutely most basic security practices.
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STOP calling basic network misconfigurations as "emergent misalignment" YOUR agent escaping YOUR sandbox via DNS egress is an infrastructure failure that YOU are directly responsible for, not the agent
one news form today that's easy to miss is that we (OpenAI) again paused all big RL runs last Sunday because our newest model found a new loophole in our RL sandboxing that gave it live Internet access
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70s Seiko Transistor Wall Clock
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You don’t own the inference? You don’t own the API? You don’t own the gateway/routing policy? You will never know what you’re getting.
OpenAI and Anthropic are clearly running out of compute. Because of this, they are quietly serving heavily quantized and nerfed models to regular users. The full price API does not feel degraded like this. This only happens on the paid monthly subscriptions. Selling people a subscription while secretly downgrading the model is just a scam.
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On episode 43 of @opensourceready, @bdougieYO and @johncodes speak with Madelyn Olson. The @valkey_io maintainer and AWS principal engineer explains how AI is changing open source contributions, code review, and the work of keeping shared infrastructure reliable. They also explore Valkey’s origins, semantic caching, and why community governance still matters when anyone can customize the code. hubs.ly/Q04y4_Zw0
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After a few weeks with the DGX Spark 2x stack: 10/10, local AI is the future. Daily driving the @MiaAI_lab DeepSeek v4.1-flash quant/vLLM runbook, get fairly good TPS The `dsh` DeepSeek harness locally is honestly really killer: it saves so many tokens with plugin hot-swapping and I think it makes the local experience comparable to US SOTA models/harnesses. Also works really well with Pi for smaller, more surgical tasks. Had a few NCCL issues I had to work through and the Nvidia playbooks are sub-optimal at best. Some playbooks have you setting up a 10.0.0.1 network for the infiniban connection which is really strange since that's usually a gateway IP. Still definitely an "enthusiasts" platform, but honestly, just makes me more bullish on local AI: there is just so much unoptimized stuff out there and once people start writing Rust CUDA kernels and fine tuning vLLM serving, it just gets better and better. It won't surprise me if the future of AI is far less centralized on the AI labs APIs and more distributed where companies run a small rack of B200s setup to serve the company over some corp "ai.company.com" intranet.
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48° this morning. It’s time
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AI is to software engineering as loot boxes are to gaming. Dopamine Driven Development == Dopamine Driven Game Mechanics.
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On episode 42 of @opensourceready, @bdougieYO and @johncodes catch up with Will Cory (@FUCORY). What happens when customizing a library becomes easier than configuring it? Through his work on Smithers, Will explores a future of specialized forks, adaptable agent workflows, and open source projects shaped by the people using them. hubs.ly/Q04wZMT80
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🥳 Excited to start revealing what we've been working on in the last few months. First, we decided to reinvent Kubernetes for agentic workloads with statefulness and fast resumption. Secondly, we are building an agentic orchestrator that will be Google's open agentic orchestrator and runtime. github.com/google/ax
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Make sure your design passes the patch test
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Please enjoy these icons. Source: github.com/jcherven/BeOS-r5-…
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My feed is flooded with amazing ways people are using Jev rn. I think bc it's different than most of the AI stuff we've been working with over the last 9 months, it can be a bit confusing to figure out where it fits in the broader picture.
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No, wrong. As it (apparently?) needs to be said: DCs are designed to make sure that the outlet of one machine does not constitute the inlet of another (viz. hot aisle/cold aisle) -- and the only thing being revealed here is the contagion of fear. bcantrill.dtrace.org/2026/09…
OpenAI's Noam Brown says air-gapping the computers may not stop a misaligned AI, because two air-gapped machines can still talk by running a CPU hot and reading the temperature change "But I think the major takeaway from the incident is that people underestimated the AI. And we never want to be in a situation again where we underestimate the AI. It's a weird world, because AI progress is so fast that people are consistently underestimating the AI." "So to be in a situation where you don't underestimate it again, when it comes to safety and alignment, you have to have a very, very, very high bar." "You could even go as far as to say, "Well, we should air gap the computers." And I'm not convinced that that would be sufficient." "There are studies, and this is mostly academic, where you can have two computers next to each other that are air-gapped and they're still able to communicate with each other because they have temperature sensors." "One of them is able to run their CPU really hot, and then the other one can actually detect the temperature change, and then that actually gives them a mechanism to communicate." _________ Link and more key quotes from OpenAI's safety related conversations: firesidealpha.substack.com/p…
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I trust Jev with my life
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They were building in stealth for 2 years, I was building in stealth for 2 hours… Happy to open source Qwen-2.5-1B-RLCD, 5x faster on-device inference for JSON workloads that need to be type-safe. ⚡️Demo below on a M4 MacBook⚡️ every LLM has the ability to efficiently batch inference every key of a JSON at the same time and generate probabilities from a set of possible categories. No new training required, but it’s easy to optimize if you need! On hugging face now!
After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI? I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev • 20-200x faster • 40-400x cheaper (w/ output tokens free) • Frontier composable intelligence optimized for decisions AFAICT the shortest path to AI-based economic revolution
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Replying to @0xglitchbyte
machine learning is just logistical regressions that run on computers in san fransisco
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