Browsing Tag
machinelearning
270 posts
Detecta si tu modelo de materiales hace trampa con la ‘huella bibliográfica’
Detecta si tu modelo de materiales hace trampa con la “huella bibliográfica” Un modelo de ML puede predecir…
Migrating Off OpenAI: A Backend Engineer’s Notes From Production
Check this out: migrating Off OpenAI: A Backend Engineer’s Notes From Production I still remember the morning I…
DeepSeek vs Qwen vs Kimi vs GLM: Which AI API Actually Wins in 2025?
DeepSeek vs Qwen vs Kimi vs GLM: Which AI API Actually Wins in 2025? I’ve spent the last…
I Built a Research Memory Agent with Cognee—Five API Breaks, One Knowledge Graph, Seven Days
I applied strict TDD to build a Cognee knowledge graph agent — here is every upstream API break…
Vision Language Models — When AI Learns to See and Talk (Part 3 of 3)
Originally published on my blog. Cross-posted here with a canonical link. This is Part 3 of a 3-part…
How to automatically monitor new ML research papers on Arxiv by keyword
Staying on Top of ML Research With ~10,000 new papers on Arxiv every month, staying current in your…
Evaluating a C# LLM Eventparser with Promptfoo
If you’re a developer, your first instinct when testing code is simple: Call the function. Get the result.…
【红杉播客】AI Neolab–Engram【主攻记忆与持续学习】–分享未来 AI 发展趋势的独特见解
https://www.youtube.com/watch?v=aiR7F4jqjXY 在这期由红杉资本（Sequoia Capital）主持的《Training Data》播客节目中，初创公司 Engram 的联合创始人 Dan Biderman 和 Jessy Lin 深入探讨了 “记忆（Memory）与持续学习（Continual Learning）” 在 AI 领域的核心作用，并分享了他们对未来 AI…
Building LSTMs with PyTorch and Lightning AI Part 3: Finishing the LSTM Cell
In the previous article, we started with the creation of LSTM cell. In this article we will continue…
LunarSite: An end-to-end ML pipeline for lunar south pole landing site selection
LunarSite: An end-to-end ML pipeline for lunar south pole landing site selection Sim-to-real terrain segmentation, fine-tuned crater detection,…
