Homotopic AI @HomotopicAI
The offline AI company. We deliver AI without the internet. Deterministic Zero-Data AI delivered to mobile devices (From Feature Phones to Flagship Phones) homotopicai.com San Francisco, CA Joined December 2024-
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HomotopicAI’s Virtual Graph Memory Fabric (vGMF) gives us deterministic control over tensors, scratch buffers, and residency across large AI workloads. It orchestrates shards, windows, and prefetch plans so that inference runs with predictable p95/p99 latency even on mobile GPUs
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HomotopicAI vGMF - bringing datacenter-grade memory determinism to every device
HomotopicAI vGMF - bringing datacenter-grade memory determinism to every device
vGMF replaces heuristic memory management with a prescriptive program authored alongside the workload graph. Deterministic residency and scratch policies yield bounded tails, reproducible behavior across devices, and actionable telemetry.
vGMF replaces heuristic memory management with a prescriptive program authored alongside the workload graph. Deterministic residency and scratch policies yield bounded tails, reproducible behavior across devices, and actionable telemetry.
Homotopic AI retweeted
HomotopicAI: Deterministic On‑Device Execution for Large Language Models on Apple Platforms Summary (What is HomotopicAI?) HomotopicAI, is a production system for executing large language models (LLMs) privately and reliably on commodity Apple devices (iOS/macOS) without cloud…
HomotopicAI converts models to run privately, offline, on iPhone—no cloud needed. You give us any GGUF/HuggingFace model; we return a GII file and an iOS runtime so it just works on device. Example: Llama‑2 7B, steady latency on iPhone.
What we sell: A conversion platform that transforms GGUF/HF models into GII artifacts with topology‑aware metadata; paired SDK/runtime ensures bounded RAM, deterministic I/O, and steady tokens/sec on Apple devices.
Homotopic AI retweeted
Running large decoder-style LLMs (e.g., LLaMA-family) on iPhones using .gguf and generic runtimes (e.g., llama.cpp) encounters three hard limits: (i) memory residency dominated by KV caches and irregular tensor access, (ii) I/O and orientation/quantization penalties that cause VM…
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