--- title: "best_AI_papers_2023 vs ai-engineering-from-scratch" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/louisfb01-best-ai-papers-2023-vs-rohitg00-ai-engineering-from-scratch" tools: ["louisfb01-best-ai-papers-2023", "rohitg00-ai-engineering-from-scratch"] --- # best_AI_papers_2023 vs ai-engineering-from-scratch *GraphCanon updated Jul 12, 2026* ## Verdict Pick best_AI_papers_2023 when tags unique to best_AI_papers_2023: ai, artificial-intelligence, ml, nlp; pick ai-engineering-from-scratch when pricing: The `ai-engineering-from-scratch` repository is free and open-source under an MIT license, but for full access to additional resources or support, a paid option may be provided. Consult official or up. [best_AI_papers_2023](https://github.com/louisfb01/best_AI_papers_2023) reports 251 GitHub stars, 23 forks, and 0 open issues, last pushed Dec 24, 2023. [ai-engineering-from-scratch](https://aiengineeringfromscratch.com) has 38k stars, 6.3k forks, and 96 open issues, last pushed Jun 25, 2026. Figures are from public GitHub metadata via [best_AI_papers_2023's repository](https://github.com/louisfb01/best_AI_papers_2023) and [ai-engineering-from-scratch's repository](https://github.com/rohitg00/ai-engineering-from-scratch). | | [best_AI_papers_2023](/tools/louisfb01-best-ai-papers-2023.md) | [ai-engineering-from-scratch](/tools/rohitg00-ai-engineering-from-scratch.md) | | --- | --- | --- | | Tagline | A curated list of the latest breakthroughs in AI (in 2023) by release date with a clear video explanation, link to a more in-depth article, and code. | Learn it. Build it. Ship it for others. | | Stars | 251 | 37,922 | | Forks | 23 | 6,329 | | Open issues | 0 | 96 | | Language | - | Python | | Adopt for | - | Specifically designed for individuals looking to build a comprehensive understanding of AI tools and frameworks from the ground up. | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT | | Categories | Computer Vision, Developer Tools, Evaluation & Observability, Model Training | AI Agents, Computer Vision, Developer Tools, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [best_AI_papers_2023](/tools/louisfb01-best-ai-papers-2023.md) | [ai-engineering-from-scratch](/tools/rohitg00-ai-engineering-from-scratch.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Active (82%) | | Days since push | 929d | 15d | | Open issues (now) | 0 | 96 | | Security scan | No lockfile | No MCP manifest | | Full report | [trust report](/tools/louisfb01-best-ai-papers-2023/trust.md) | [trust report](/tools/rohitg00-ai-engineering-from-scratch/trust.md) | ## Decision facts: ai-engineering-from-scratch - **Pricing:** freemium - The `ai-engineering-from-scratch` repository is free and open-source under an MIT license, but for full access to additional resources or support, a paid option may be provided. Consult official or up - **Adopt for:** Specifically designed for individuals looking to build a comprehensive understanding of AI tools and frameworks from the ground up. ## Choose when ### Choose best_AI_papers_2023 if… - Tags unique to best_AI_papers_2023: ai, artificial-intelligence, ml, nlp. - Also covers Evaluation & Observability, Model Training. - Leaner open-issue backlog (0). ### Choose ai-engineering-from-scratch if… - Pricing: The `ai-engineering-from-scratch` repository is free and open-source under an MIT license, but for full access to additional resources or support, a paid option may be provided. Consult official or up. - Tags unique to ai-engineering-from-scratch: agents, ai-engineering, deep-learning, from-scratch. - Also covers AI Agents, LLM Frameworks. - When you want to start with foundational knowledge and learn the intricacies behind AI systems. ## When NOT to use best_AI_papers_2023 - Last GitHub push was 930 days ago (dormant maintenance, Dec 24, 2023). Validate activity before betting a new project on best_AI_papers_2023. - Developer Tools: A gateway is overkill when you're pinned to a single provider and model. - Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. - Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. ## When NOT to use ai-engineering-from-scratch - If you are looking for a quick setup or ready-to-go solution without diving into the foundational understanding. - When your project requires immediate practical application with less emphasis on self-implemented solutions from scratch. ## Common questions ### What is the difference between best_AI_papers_2023 and ai-engineering-from-scratch? best_AI_papers_2023: A curated list of the latest breakthroughs in AI (in 2023) by release date with a clear video explanation, link to a more in-depth article, and code.. ai-engineering-from-scratch: Learn it. Build it. Ship it for others.. See the comparison table for live GitHub stats and shared categories. ### When should I choose best_AI_papers_2023 over ai-engineering-from-scratch? Choose best_AI_papers_2023 over ai-engineering-from-scratch when Tags unique to best_AI_papers_2023: ai, artificial-intelligence, ml, nlp; Also covers Evaluation & Observability, Model Training; Leaner open-issue backlog (0). ### When should I choose ai-engineering-from-scratch over best_AI_papers_2023? Choose ai-engineering-from-scratch over best_AI_papers_2023 when Pricing: The `ai-engineering-from-scratch` repository is free and open-source under an MIT license, but for full access to additional resources or support, a paid option may be provided. Consult official or up; Tags unique to ai-engineering-from-scratch: agents, ai-engineering, deep-learning, from-scratch; Also covers AI Agents, LLM Frameworks; When you want to start with foundational knowledge and learn the intricacies behind AI systems. ### When should I avoid best_AI_papers_2023? Last GitHub push was 930 days ago (dormant maintenance, Dec 24, 2023). Validate activity before betting a new project on best_AI_papers_2023. Developer Tools: A gateway is overkill when you're pinned to a single provider and model. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. ### When should I avoid ai-engineering-from-scratch? If you are looking for a quick setup or ready-to-go solution without diving into the foundational understanding. When your project requires immediate practical application with less emphasis on self-implemented solutions from scratch. ### Is best_AI_papers_2023 or ai-engineering-from-scratch more popular on GitHub? ai-engineering-from-scratch has more GitHub stars (37,922 vs 251). Stars measure visibility, not whether either tool fits your constraints. ### Are best_AI_papers_2023 and ai-engineering-from-scratch open source? Yes - both are open-source projects on GitHub (best_AI_papers_2023: MIT, ai-engineering-from-scratch: MIT). ### Where can I find alternatives to best_AI_papers_2023 or ai-engineering-from-scratch? GraphCanon lists graph-backed alternatives at [best_AI_papers_2023 alternatives](/tools/louisfb01-best-ai-papers-2023/alternatives) and [ai-engineering-from-scratch alternatives](/tools/rohitg00-ai-engineering-from-scratch/alternatives) ([best_AI_papers_2023 markdown twin](/tools/louisfb01-best-ai-papers-2023/alternatives.md), [ai-engineering-from-scratch markdown twin](/tools/rohitg00-ai-engineering-from-scratch/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/louisfb01-best-ai-papers-2023-vs-rohitg00-ai-engineering-from-scratch.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, best_AI_papers_2023 or ai-engineering-from-scratch? best_AI_papers_2023: Dormant. ai-engineering-from-scratch: Active. 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 best_AI_papers_2023 and ai-engineering-from-scratch? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [best_AI_papers_2023 trust report](/tools/louisfb01-best-ai-papers-2023/trust); [ai-engineering-from-scratch trust report](/tools/rohitg00-ai-engineering-from-scratch/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=louisfb01-best-ai-papers-2023`](/api/graphcanon/graph?tool=louisfb01-best-ai-papers-2023) - 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/_