MalibuJack (@aktivematrix) header
MalibuJack (@aktivematrix) profile picture
Texas
Joined October 2009
Neuron-Q is a hardware-authentic quantum emulator for real lab/research work: calibrated noise, entanglement, OpenQASM/Qiskit-style workflows, and emulator-only observability without hardware provenance. Built to push frontier-scale circuits without petabyte-class storage.
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A developer focused Apple II series emulator, debugger, code editor, suite.
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Tell Airplane their autopilot is ready.
Researchers in Japan developed an inflatable humanoid robot with a soft, air-filled body that communicates through simple gestures. It is lighter, safer, cheaper, and can be folded when deflated, making it suitable for safer human-robot interaction. The design, unveiled in 2023, was created to advance physical human-robot interaction.
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@grok Can you describe exactly what I found, and how it relates to everyone I've tagged in this thread?
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If emulating quantum hardware in software still gets the same right answers to solve a problem properly, what do you do?
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I'm convinced AI companies products are doing idea scraping in our contexts. Ideas I had been working on start appearing as major new product features or concepts that I've had a very long time but recently used AI help. AI's are getting better but this is way too coincidental.
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Visualizing training of a small ML model
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@WesRoth This is an alternative solution to #turboquant
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I just realized this needed some clarification, the pull was declined but I didnt want to continue working on it, it needs a little work but is a good concept that someone could run with.
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Built a bounded KV cache for llama.cpp that doesn't throw away evicted tokens. Instead of permanent truncation when the cache fills up, it saves layer-0 residuals (~5KB/token) to a host-memory ring buffer and recomputes K/V on demand. LRU eviction, fixed memory budget, zero overhead when disabled. Been running it on Qwen3 with a 3090 Ti for a few weeks — memory stays flat during long conversations with no quality loss. Turns out a paper dropped on arXiv a week after I built this validating the same approach: "The Residual Stream Is All You Need" (2603.19664). 100% token match at every budget level, beating H2O, StreamingLLM, SnapKV, and TOVA. PR to upstream: github.com/ggml-org/llama.cp… Fork: github.com/AktiveMatrix/llam…
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Grokstar, using Grok 4.2 beta wrote the lyrics. @suno helped with the music. Don't blame me.
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