RRepoGEO

REPOGEO REPORT · LITE

basicmi/AI-Chip

Default branch master · commit 5ddedc71 · scanned 5/22/2026, 1:37:47 AM

GitHub: 1,707 stars · 278 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
28 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
2 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface basicmi/AI-Chip, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Reposition README's opening to clarify it's a list/database

    Why:

    CURRENT
    The current README starts with 'AI Chip (ICs and IPs)' but doesn't immediately clarify its nature as a list or resource.
    COPY-PASTE FIX
    This repository is a comprehensive, curated list and database of ICs and IPs for AI, Machine Learning, and Deep Learning hardware.
  • highlicense#2
    Add a LICENSE file

    Why:

    COPY-PASTE FIX
    Choose and add a standard open-source license file (e.g., MIT, Apache-2.0) to the repository root.
  • mediumabout#3
    Refine the repository description

    Why:

    CURRENT
    A list of ICs and IPs for AI, Machine Learning and Deep Learning.
    COPY-PASTE FIX
    A comprehensive, curated list and database of ICs and IPs for AI, Machine Learning, and Deep Learning hardware.

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface basicmi/AI-Chip
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
AnandTech
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. AnandTech · recommended 1×
  2. ServeTheHome (STH) · recommended 1×
  3. NVIDIA · recommended 1×
  4. AMD · recommended 1×
  5. Intel · recommended 1×
  • CATEGORY QUERY
    Where can I find a comprehensive list of available hardware for accelerating deep learning workloads?
    you: not recommended
    AI recommended (in order):
    1. AnandTech
    2. ServeTheHome (STH)
    3. NVIDIA
    4. AMD
    5. Intel
    6. Papers With Code
    7. TechRadar Pro
    8. Tom's Hardware

    AI recommended 8 alternatives but never named basicmi/AI-Chip. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best processor architectures and IPs for developing high-performance machine learning applications?
    you: not recommended
    AI recommended (in order):
    1. NVIDIA GPUs
    2. Google TPUs
    3. AMD Instinct GPUs
    4. Intel Gaudi
    5. Graphcore IPU
    6. Qualcomm Cloud AI 100
    7. NVIDIA Grace Hopper Superchip
    8. Apple M-series chips
    9. AWS Graviton processors

    AI recommended 9 alternatives but never named basicmi/AI-Chip. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of basicmi/AI-Chip?
    pass
    AI named basicmi/AI-Chip explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts basicmi/AI-Chip in production, what risks or prerequisites should they evaluate first?
    pass
    AI named basicmi/AI-Chip explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo basicmi/AI-Chip solve, and who is the primary audience?
    pass
    AI did not name basicmi/AI-Chip — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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basicmi/AI-Chip — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite