Panda is the world's first personal AI computer. All the power of AI, running inside your home. No data centers, no surveillance, no subscriptions. Preorder for a $100 deposit.
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Basically vapourware.
We left the specs out because the landing page was made for non-technical consumers who aren't aware of the hardware required in general.
Here are the specs: Processor (SoC): AMD Ryzen AI Max+ 395 Memory: 128 GB LPDDR5X-8000 Motherboard: custom Storage: NVMe SSD, 4 TB: WD_Black SN850X 4TB
Rest is basic: ethernet, usb c ports, wifi module, power supply
Inference engine: llama.cpp
Models: A fast default for chat, email and calendar: a 30B-class mixture-of-experts model like Qwen3-30B-A3B. A larger model for harder tasks: gpt-oss-120b. A coding model: Qwen3-Coder-Next.
The late release date is specifically to fine tune the experience for the non technical consumer, someone who wouldn't know what model to switch to for what task. We want this to be a seamless out of the box experience. UI/UX is very important here. Another reason for the late release is the chip cant be bought off the shelf and need AMD to sell us the chip at a certain volume
How are you going to build an entire system shipped for $3k?
This spec sheet looks more like a dreamed-up spec sheet than pricing reality.
December 2027 shipping date is hilarious for an AI hardware product.
They're targetting people who want AI and will spend thousands, but don't know enough to ask _any_ details? Why wouldn't that audience just be on chatgpt?
We left the specs out because the landing page was made for non-technical consumers who aren't aware of the hardware required in general.
Here are the specs: Processor (SoC): AMD Ryzen AI Max+ 395 Memory: 128 GB LPDDR5X-8000 Motherboard: custom Storage: NVMe SSD, 4 TB: WD_Black SN850X 4TB
Rest is basic: ethernet, usb c ports, wifi module, power supply
Inference engine: llama.cpp
Models: A fast default for chat, email and calendar: a 30B-class mixture-of-experts model like Qwen3-30B-A3B. A larger model for harder tasks: gpt-oss-120b. A coding model: Qwen3-Coder-Next.
The late release date is specifically to fine tune the experience for the non technical consumer, someone who wouldn't know what model to switch to for what task. We want this to be a seamless out of the box experience. UI/UX is very important here. Another reason for the late release is the chip cant be bought off the shelf and need AMD to sell us the chip at a certain volume
Every single non-technical user I can think of would either say "why should I buy this if chatgpt is free" or "ai is dumb and I don't want to use it."
I've been using these things a bit differently lately, more of a personal assistant - probably more of the OpenClaw setup I'd guess, though I haven't used OpenClaw. I have my macbook running constantly and it has a session running for reach of my projects, plus one session called pa (personal assistant) which is set up to track tasks and to talk to all the other sessions.
The pa is the only session I directly interact with anymore. It's got it's own Signal account and a single Signal chat is the way I interact with all my sessions. Actually, there are a few sessions run on other machines too that it knows how to get to, but mostly it's just the per-project sessions on my macbook.
I think that's how I'm gonna want stuff like this to work - mostly in one single text thread that delegates to the others. The others don't have to be totally invisible, being able to drop into them individually would be fine as long as it doesn't interfere with the simplicity of the main thread.
Not a gotcha, just trying to understand how your setup works
But the actual answer is just one session per project and auto-compacting. Actually I run into usage limits on both codex and claude max subscriptions and so there is also a fair bit of it having to do codex/claude handoffs which is like a worse auto-compact.
I am quite sure I get worse results at a higher cost than I do for my actual day job, where I'm taking ownership of code, getting the actual code I want, and therefore doing a lot more manual context management.
But for side projects and other personal computer usage it's all vibing and auto-compacting.
Read the full thread on Hacker News →
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