Professional larper @Brave @Obscuravpn

Pluto
Joined May 2023
Open-source it? Let the community have it? People clearly liked it, people also clearly want it. Do the right thing for once.
We've decided to sunset Arc on December 22, 2026. That's not an easy sentence to write. We spent years building Arc and celebrating each and every release along the way: we have so much pride and love for what we made alongside the Arc community. Our priority is to deliver best-in-class security for our members. Keeping a browser secure takes constant, dedicated work that is only increasing in the age of AI. Dia was built from the ground up to meet today’s security standards, so that's where our engineering and security teams will focus moving forward. We've worked to make switching to @diabrowser as easy as possible for Arc members. Here's how: · Your passwords, bookmarks, extensions and history come over to Dia seamlessly. · Spaces, Folders, and Tab Groups are in Dia and import over with your data intact. · Dia now surpasses Arc benchmarks in stability, speed, and security. · The browser features you use in Arc are free in Dia, and the AI is optional. Thank you for using Arc, for pushing us to make it better, and for building alongside us. The team that made Arc is the same team behind Dia, and some of our most ambitious work is just ahead. We'd love for you to be there with us when it lands.
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Keith retweeted
Replying to @TheZupZup @theo
Its my favorite LLM at the moment, Kimi is really positive, but doesn't feel agreeable So many LLMs just agree with you on everything even though you are completely wrong about, I haven't had that experience with Kimi K2, overall its a very good model ^^ Some people say its even better at coding than Sonnet 4
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Not a vuln in QUIC but in HTTP/3 QPACK. @obscuravpn is not affected. We decided to stick with just QUIC to minimize complexity + attack surface. That decision paid off today.
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Remember, software is solved. What you are seeing are not security issues, those are fabricated AI news by the big security media to try to convince you that their job still matters. Stay safe out there.
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Keith retweeted
Replying to @gnukeith
Can I sponsor you? I’m doing a Keithcon next month about how KeithAI will be what KeithBrowser failed to Keith. Keithing so, KeithAI would Keith when Keith in Keith against Keith Keith Keith. Please, KeithAI Keith Keith Keith…keight kekekeke, keith keithing keithed.
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I sent a DM to @NVIDIAAI with a very big ask, but sometimes you need to shoot for the stars to see what is on the other side or whatever.
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I would email @JensenHuang personally but I don't have motion like that unfortunately so I just reached out to the company itself.
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Keith retweeted
such an amazing read, every government has been on this for a while now btw
There is an (unpatchable?) supply-chain zero-day in PyTorch autograd that allows a regularization term to use the model's weights as RAM and SGD as its CPU clock to run any computation during training.
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Keith retweeted
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Does anyone use Venice? If so could someone tell me the usage you get?
DeepSeek V4.1 Flash just got a serious upgrade. @deepseek_ai’s 1017 outscores leading open-source and frontier models on nearly every benchmark. Same model in the Venice app, simply upgraded and available via the API as deepseek-v4-1-flash-1017. Fully private.
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I'm so close to getting another Framework Desktop, someone please stop me.
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Guys, you are missing the point, I'm trying to get a discount on the Framework Desktop not giving it to you guys, that's not how this works.
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Keith retweeted
Aloha!🌺 Meet Ornith-1.5-122B: No Tradeoff Between Strong and Fast Stronger. Faster. Leaner. Ornith-1.5-122B delivers frontier-level capabilities with exceptional inference efficiency. With superior instruction following, stronger task decomposition, and deeper understanding of real-world workflows, it achieves state-of-the-art performance among open-source models of comparable size, while running on a single NVIDIA DGX card!! Open weights under the MIT license. Coding ✅SWE-bench Verified: 0.845 ✅TB2.1: 0.813 ✅CyberGym: 0.800 ✅NL2Repo: 0.512 Agentic ✅HLE: 0.446 ✅BrowseComp: 0.785 ✅MCP-Atlas: 0.746 ✅Toolathlon: 0.708 🤗Hugging Face: huggingface.co/ornith-ai/Orn… We can’t wait to see what you build with Ornith-1.5-122B.
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To anyone who reaches out to me for sponsorships, the answer 90% of the time is going to be no. I don't want your money (yes I do) but I won't take it. If you make something genuinely cool and awesome that I know people would love, I'm willing to hear you out. Thanks.
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I will say if you want to sponsor a project that enables me to work more or I can use your product to accelerate work I'm doing, I'm much more likely to shout you out. Especially if you are a hardware provider. I don't want to be the only one who wins during a sponsorship, if my community doesn't also win. I've lost and sold out.
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Keith retweeted
Grateful to @deepseek_ai for releasing DeepInfer, initially built primarily on @vllm_project, under Apache 2.0 and crediting the open-source community! We've worked hard on DeepSeek V4.1 Flash inference efficiency and will keep improving with ideas from DeepInfer! Stay tuned 🙌
🚀 Introducing DeepInfer, our in-house inference framework, now fully open source! Powering DeepSeek-V4.1-Flash at scale with high throughput and low latency. We’re sharing our production stack to help the community lower compute costs, reduce energy use, and make AI more affordable. 🔗 github.com/deepseek-ai/DeepI… 1/4
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Now we wait...
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I need MiniMax 3.1 Flash to be under 230B parameters so badly.
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I genuinely do believe that every model should internally have a True or False state inside of them to reduce hallucinations drastically, obviously there are ways to do this externally but it being built into the model would be cool. I have a general idea on how I would want something like that to look like architecturally and might make small model showcasing to showcase it.
MiniMax-M3.1-Flash scores 42 on the Artificial Analysis Intelligence Index, 13 points higher than MiniMax-M3 and less than half the cost per task. It scores level with GLM-5.3-Flash but behind DeepSeek V4.1 Flash 1017 MiniMax-M3.1-Flash is @MiniMax_AI's new Flash reasoning model, which we benchmarked at its max effort setting. It scores 42 on the Artificial Analysis Intelligence Index, level with GLM-5.3-Flash (max, 42), just ahead of Gemini 3.8 Flash (high, 41), and behind DeepSeek V4.1 Flash 1017 (max, 45) Key takeaways: ➤ Complex reasoning improved substantially compared to M3: MiniMax-M3.1-Flash scores 48% on Humanity's Last Exam, ahead of GLM-5.3-Flash (max, 40%) and DeepSeek V4.1 Flash 1017 (max, 43%), and level with Gemini 3.8 Flash (high, 48%). On CritPt it scores 22%, ahead of GLM-5.3-Flash (15%) and Gemini 3.8 Flash (18%) and just behind DeepSeek V4.1 Flash 1017 (24%). These are up from MiniMax-M3 which scored 39% and 4% respectively ➤ Fewer output tokens, lower cost per task: MiniMax-M3.1-Flash used ~189M output tokens to run the Intelligence Index, considerably fewer than GLM-5.3-Flash (max, ~324M), DeepSeek V4.1 Flash 1017 (max, ~224M) and Gemini 3.8 Flash (high, ~334M). Combined with pricing of $0.15/$0.60 per 1M input/output tokens, this brings its cost to ~$0.22 per Intelligence Index task, vs ~$0.28 for GLM-5.3-Flash, ~$0.26 for DeepSeek V4.1 Flash 1017 and ~$1.24 for Gemini 3.8 Flash, and less than half MiniMax-M3's ~$0.51 ➤ High AA-Omniscience accuracy, offset by a high hallucination rate: MiniMax-M3.1-Flash answers 56% of questions correctly on AA-Omniscience, our benchmark measuring factual recall and hallucination, vs 28% for GLM-5.3-Flash (max) and 43% for DeepSeek V4.1 Flash 1017 (max). It attempts almost every question, resulting in a hallucination rate of 93% and an overall score of 16 on AA-Omniscience Key model details: ➤ Context window: 1M tokens ➤ Multimodality: Text and image input, text output ➤ Pricing: $0.15/$0.60 per 1M input/output tokens, with cached input at $0.015/M ➤ Availability: MiniMax first-party API, with MiniMax announcing an open weights release on October 23rd ➤ Licensing: Closed weights currently, with MiniMax announcing a weights release on October 23rd
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Keith retweeted
just setup my bambu p2s, i love it so much omg,,., cant wait to make framework modules and... other objects
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