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AI model runs on $10 microcontroller using Google's embedding technique

By PulseAugur Editorial · [2 sources] ·

An AI developer has successfully run a 28.9-million-parameter language model on a low-cost ESP32-S3 microcontroller, a feat previously thought impossible due to the chip's limited memory. The developer, known as 'slvDev', utilized a technique inspired by Google's Gemma, called Per-Layer Embeddings, to manage the model's parameters. This method involves quantizing the model to 4-bit and storing the large embedding table in the slower flash memory, while keeping the core reasoning weights in the limited fast RAM. AI

IMPACT Enables running sophisticated AI models on extremely low-cost, embedded devices, potentially opening new applications in edge computing.

RANK_REASON Demonstrates running a significant AI model on extremely low-resource hardware, a novel technical achievement.

Read on Mastodon — mastodon.social →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

AI model runs on $10 microcontroller using Google's embedding technique

How we ranked this

Signal score
0 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Research
Demonstrates running a significant AI model on extremely low-resource hardware, a novel technical achievement.
Source corroboration
2 independent sources
Multiple independent publishers reporting the same story raises confidence that it's real and newsworthy.
Topics
model release, infra
Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance
High
Clearly on-topic for AI-industry coverage.
Story freshness
61 days old
Aged out of breaking-news scoring windows; ranking reflects the durable signal from the full source set.

Full methodology in our editorial standards.

COVERAGE [2]

  1. Tom's Hardware TIER_1 English(EN) · Zak Killian ·

    AI developer runs 28.9-million-parameter model on $10 ESP32-S3 microcontroller — uses Google's Per-Layer Embeddings technique, stores table on 16MB Flash memory

    Getting a local language model running on a sub-$10 microcontroller is impressive despite its obvious limitations.

  2. Mastodon — mastodon.social TIER_1 English(EN) · [email protected] ·

    AI developer runs 28.9-million-parameter model on $10 ESP32-S3 microcontroller — uses Google's Per-Layer Embeddings technique, stores table on 16MB Flash memory

    AI developer runs 28.9-million-parameter model on $10 ESP32-S3 microcontroller — uses Google's Per-Layer Embeddings technique, stores table on 16MB Flash memory Getting a local language model running on a sub-$10 microcontroller is impressive despite its obvious limitations. http…

    LINKS tomshardware.com/…/ai-developer-runs-28-9… tomshardware.com/tech-industry

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