Professional Computer Toucher

Salt Lake City, UT
Joined November 2021
Absolutely fascinated by this computer stuff. I time travel each time.
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iPad mini + omp on moshi running self-hosted DeepSeek-4.1-flash-1017 connected over tailscale and driving all of it on my custom built mechanical ergo keyboard
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Thinking was off in both of my harnesses 🤦 xitter.cf/sabastod/status/211312… Trying again!
Day 1 running DeepSeek locally on my 4xRTX 6000 It takes way too long to accomplish simple tasks. What takes Opus 5.5 40 seconds 4.1-Flash-1017 can work for 30 minutes and not accomplish anything meaningful.
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Day 1 running DeepSeek locally on my 4xRTX 6000 It takes way too long to accomplish simple tasks. What takes Opus 5.5 40 seconds 4.1-Flash-1017 can work for 30 minutes and not accomplish anything meaningful.
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Isn’t LLM a software?
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Updated from 3x3090(2x3090, 1x3090TI) to 2x5090 on my homelab
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10 hours in one video -- day job, some work on my app Whispera, then tried to build a local AI rig with two 5090s pulled from prebuilts. Turns out I need a new PSU that supports 5090s . So… no build yet. Part 2 soon. The first couple hours are out of focus
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Opus-5.5 is great at creating illustrations with JS. It created in 20 minutes what gpt-6 astra struggled for multiple days
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Apple should support Linux as first-class citizen on Mac studios if it wants to take AI seriously.
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Izzy Mansurov retweeted
Om Malik passed away today. He was one of my favorite writers. His pieces on the chaos and self-inflicted pains of Silicon Valley were truly novel. I will miss hearing his thoughts. If you haven't read this New Yorker piece, I highly recommend it. Lots we can still learn from.
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Is there a claude code skill that would deliver my favorite order from doordash? @DoorDash
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Got invited to Voice agents YC hackathon, who else is attending?
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Izzy Mansurov retweeted
llama.cpp at 100k stars now that 90% of the code worldwide is being written by AI agents, I predict that within 3-6 months, 90% of all AI agents will be running locally with llama.cpp 😄 Jokes aside, I am going to use this small milestone as an opportunity to reflect a bit on the project and the state of AI from the perspective of local applications. There is a lot to say and discuss and yet it feels less and less important to try to make a point. Opinions about viability of local LLMs are strongly polarized, details are overlooked, the scientific approach is lacking. Arguments are predominantly based on vibes and hype waves. One thing is clear though - local LLMs are used more and more. I expect this trend to continue and likely 2026 will end up being one of the most important years for the local AI movement. I admit that I didn't expect the agentic era to come so quickly to the local LLM space. One year ago, the available models were too computationally expensive for doing long-context tasks. There wasn't an obvious path towards meaningful agentic applications. The memory and compute requirements were huge. Last summer, with the release of gpt-oss, things started to change. It was the first time we saw a glimpse of tool calling that actually works well within the resource constraints of our daily devices. Later in the year, even better models were released and by now, useful local agentic workflows are a reality. Comparing local vs hosted capabilities at a given moment of time is pointless. To try put things into perspective: - We don't need frontier intelligence to automate searches and sending emails - We don't need trillion parameter models to be able to summarize articles or technical documents - We don't need massive GPU data centers to control our home appliances or turn the lights off in the garage I believe that there is a certain level of intelligence we as humans can comprehend and meaningfully utilize to improve our working process. Beyond that level, access to more intelligence becomes unnecessary at best and counterproductive at worst. I also believe that that level of useful artificial intelligence is completely within reach locally and it has always been just a matter of implementing the right software stack to bring it to the end user. With llama.cpp, I am confident that we continue to be on the right track of building that software stack! The llama.cpp project is going stronger than ever. With more than 1500 contributors, the project keeps growing steadily. From technical point of view, I think that llama.cpp + ggml is the only solution that actually makes sense. That is, the software stack must run efficiently on every possible device, hardware and operating system. The technology is too important to be vendor-locked. It has to be developed in the open, by the community, together with the independent hardware vendors. This is the only right way to build something that will truly make a difference in the long run. I won't try to convince you about what is currently and will be possible with local AI. We will just continue to build as usual. I am confident that after the smoke clears and we look objectively at what we have built together, the benefits will be obvious to everyone. Big shoutout to all llama.cpp maintainers. I feel extremely lucky to be able to work together with so many talented contributors. Every day I learn something new and I feel there is so much more cool stuff that we are going to build. Also, I am really thankful that the project continues to have reliable partners to support it! Cheers!
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I bought my first used 3090 @TheAhmadOsman
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Running Codex 5.3 and opus 4.6 side-by-side and codex understands and fixes the bug while Opus is just running super long to come up with the plan.
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Just used clawdbot with blubird cli to see what @TheAhmadOsman's opinion on AMD GPUs for local inference. Anywas, @TheAhmadOsman Would you recommend AMD over Mac Studio? I really don't want to buy used 3090s
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