--- title: "ml-surveys vs awesome-ai-tools" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/eugeneyan-ml-surveys-vs-mahseema-awesome-ai-tools" tools: ["eugeneyan-ml-surveys", "mahseema-awesome-ai-tools"] --- # ml-surveys vs awesome-ai-tools *GraphCanon updated Aug 22, 2026* ## Verdict Pick ml-surveys if ml-surveys is a collection of detailed review papers summarizing advancements in various AI domains such as deep learning, NLP, CV, graphs, reinforcement learning, and recommendation systems; pick awesome-ai-tools if awesome AI Tools provides a curated list of top-notch AI resources across various domains from text generation to marketing. [ml-surveys](https://github.com/eugeneyan/ml-surveys) reports 2.9k GitHub stars, 292 forks, and 2 open issues, last pushed Mar 17, 2023. [awesome-ai-tools](https://github.com/mahseema/awesome-ai-tools) has 5.9k stars, 2.0k forks, and 1.2k open issues, last pushed Dec 31, 2025. Figures are from public GitHub metadata via [ml-surveys's repository](https://github.com/eugeneyan/ml-surveys) and [awesome-ai-tools's repository](https://github.com/mahseema/awesome-ai-tools). | | [ml-surveys](/tools/eugeneyan-ml-surveys.md) | [awesome-ai-tools](/tools/mahseema-awesome-ai-tools.md) | | --- | --- | --- | | Tagline | Survey papers summarizing advances in various AI domains | A curated list of Artificial Intelligence Top Tools | | Stars | 2,902 | 5,912 | | Forks | 292 | 2,011 | | Open issues | 2 | 1,197 | | Language | - | - | | Adopt for | ml-surveys is a collection of detailed review papers summarizing advancements in various AI domains such as deep learning, NLP, CV, graphs, reinforcement learning, and recommendation systems. | Awesome AI Tools provides a curated list of top-notch AI resources across various domains from text generation to marketing. | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT | | Categories | Computer Vision, Evaluation & Observability, Model Training | AI Agents, Computer Vision, Data & Retrieval, Developer Tools, Evaluation & Observability, Inference & Serving, Model Training, Speech & Audio | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [ml-surveys](/tools/eugeneyan-ml-surveys.md) | [awesome-ai-tools](/tools/mahseema-awesome-ai-tools.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Slowing (36%) | | Days since push | 1254d | 221d | | Open issues (now) | 2 | 1.2k | | Stars delta | 0 (30d) | Unknown | | Open issues delta | 0 (30d) | Unknown | | Full report | [trust report](/tools/eugeneyan-ml-surveys/trust.md) | [trust report](/tools/mahseema-awesome-ai-tools/trust.md) | ## Decision facts: ml-surveys - **Adopt for:** ml-surveys is a collection of detailed review papers summarizing advancements in various AI domains such as deep learning, NLP, CV, graphs, reinforcement learning, and recommendation systems. ## Decision facts: awesome-ai-tools - **Adopt for:** Awesome AI Tools provides a curated list of top-notch AI resources across various domains from text generation to marketing. ## Choose when ### Choose ml-surveys if… - Tags unique to ml-surveys: computer-vision, deep-learning, embeddings, machine-learning. - When you need comprehensive overviews and summaries of the latest research trends in multiple areas within machine learning - Leaner open-issue backlog (2). ### Choose awesome-ai-tools if… - Tags unique to awesome-ai-tools: ai-tools-list, awesome-ai-tools, code-ai, editor-choice. - Also covers AI Agents, Data & Retrieval, Developer Tools, Inference & Serving, Speech & Audio. - When in need of a wide range of categorized AI tools for varied tasks like text generation, audio and video creation, or email management ## When NOT to use ml-surveys - If you are seeking detailed technical details, original experiments, or specific algorithm implementations as ml-surveys focuses more on synthesis and summary - In cases where deep-dive analysis is required into a single niche topic, as ml-surveys provides broad overviews rather than in-depth coverage of individual niches ## When NOT to use awesome-ai-tools - If you seek in-depth technical documentation on each tool since the repository mainly lists tools without comprehensive descriptions - When you are exclusively interested in AI tools focusing only on one niche domain as there is a broad spectrum of choices presented here ## Common questions ### What is the difference between ml-surveys and awesome-ai-tools? ml-surveys: Survey papers summarizing advances in various AI domains. awesome-ai-tools: A curated list of Artificial Intelligence Top Tools. See the comparison table for live GitHub stats and shared categories. ### When should I choose ml-surveys over awesome-ai-tools? Choose ml-surveys over awesome-ai-tools when Tags unique to ml-surveys: computer-vision, deep-learning, embeddings, machine-learning; When you need comprehensive overviews and summaries of the latest research trends in multiple areas within machine learning; Leaner open-issue backlog (2). ### When should I choose awesome-ai-tools over ml-surveys? Choose awesome-ai-tools over ml-surveys when Tags unique to awesome-ai-tools: ai-tools-list, awesome-ai-tools, code-ai, editor-choice; Also covers AI Agents, Data & Retrieval, Developer Tools, Inference & Serving, Speech & Audio; When in need of a wide range of categorized AI tools for varied tasks like text generation, audio and video creation, or email management. ### When should I avoid ml-surveys? If you are seeking detailed technical details, original experiments, or specific algorithm implementations as ml-surveys focuses more on synthesis and summary In cases where deep-dive analysis is required into a single niche topic, as ml-surveys provides broad overviews rather than in-depth coverage of individual niches ### When should I avoid awesome-ai-tools? If you seek in-depth technical documentation on each tool since the repository mainly lists tools without comprehensive descriptions When you are exclusively interested in AI tools focusing only on one niche domain as there is a broad spectrum of choices presented here ### Is ml-surveys or awesome-ai-tools more popular on GitHub? awesome-ai-tools has more GitHub stars (5,912 vs 2,902). Stars measure visibility, not whether either tool fits your constraints. ### Are ml-surveys and awesome-ai-tools open source? Yes - both are open-source projects on GitHub (ml-surveys: MIT, awesome-ai-tools: MIT). ### Where can I find alternatives to ml-surveys or awesome-ai-tools? GraphCanon lists graph-backed alternatives at [ml-surveys alternatives](/tools/eugeneyan-ml-surveys/alternatives) and [awesome-ai-tools alternatives](/tools/mahseema-awesome-ai-tools/alternatives) ([ml-surveys markdown twin](/tools/eugeneyan-ml-surveys/alternatives.md), [awesome-ai-tools markdown twin](/tools/mahseema-awesome-ai-tools/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/eugeneyan-ml-surveys-vs-mahseema-awesome-ai-tools.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, ml-surveys or awesome-ai-tools? ml-surveys: Dormant. awesome-ai-tools: Slowing. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for ml-surveys and awesome-ai-tools? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [ml-surveys trust report](/tools/eugeneyan-ml-surveys/trust); [awesome-ai-tools trust report](/tools/mahseema-awesome-ai-tools/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=eugeneyan-ml-surveys`](/api/graphcanon/graph?tool=eugeneyan-ml-surveys) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_