Pipcook is a JavaScript application framework for machine learning and its engineering, aimed at Web developers. It provides subprojects including a machine learning pipeline framework, management tools and a JavaScript runtime for machine learning. A Pipcook Pipeline composes scripts and outputs an NPM package containing the trained model and JavaScript functions. The documentation describes a workflow of install, train, test and deploy using the Pipcook command-line tool.
QSMM is a framework for learning finite automatons that perform goal-directed interaction with entities exhibiting deterministic or stochastic behavior. It implements the rudiments of a toolchain for working with probabilistic assembler programs, and development focus shifted to adaptive parsing and learning context-free grammars by template. It includes atd-parser and abu-parser tools.
Distill publishes articles about machine learning, including peer-reviewed explanations of neural network topics such as graph neural networks, feature visualization and feature-wise transformations. In a July 2, 2021 editorial, the team announced that after five years Distill would be taking a break.
ML-Ops is a site about Machine Learning Operations. It covers motivation for MLOps, designing ML-powered software, the end-to-end ML workflow lifecycle, three levels of ML-based software, MLOps principles, CRISP-ML(Q), the MLOps Stack Canvas and ML model governance. It describes MLOps as aiming to unify the release cycle for machine learning and software.
A weekly news and interview podcast covering the Kubernetes community, including release discussions, projects, and AI policy topics. Episodes feature guests from the Kubernetes ecosystem and are hosted as numbered installments with accompanying show notes.
A Gary Marcus article on his Marcus on AI Substack asking when the GenAI bubble might burst and how that could happen within 12 months. It cites survey findings on generative AI and security, notes $50B in and $3B out, and argues that hallucinations remain and that the industry is built on hype.
Meaning of is the personal blog of Kenny Bastani, covering open source software, graph databases, cloud native architectures, information theory, artificial intelligence, and machine learning. As of September 18, 2025, the blog is no longer maintained, with readers directed to the author's GitHub or LinkedIn profiles.
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QSMM is a framework for learning finite automatons that perform goal-directed interaction with entities exhibiting deterministic or stochastic behavior. It implements the rudiments of a toolchain for working with probabilistic assembler programs, and development focus shifted to adaptive parsing and learning context-free grammars by template. It includes atd-parser and abu-parser tools.
Distill publishes articles about machine learning, including peer-reviewed explanations of neural network topics such as graph neural networks, feature visualization and feature-wise transformations. In a July 2, 2021 editorial, the team announced that after five years Distill would be taking a break.
ML-Ops is a site about Machine Learning Operations. It covers motivation for MLOps, designing ML-powered software, the end-to-end ML workflow lifecycle, three levels of ML-based software, MLOps principles, CRISP-ML(Q), the MLOps Stack Canvas and ML model governance. It describes MLOps as aiming to unify the release cycle for machine learning and software.
A weekly news and interview podcast covering the Kubernetes community, including release discussions, projects, and AI policy topics. Episodes feature guests from the Kubernetes ecosystem and are hosted as numbered installments with accompanying show notes.
A Gary Marcus article on his Marcus on AI Substack asking when the GenAI bubble might burst and how that could happen within 12 months. It cites survey findings on generative AI and security, notes $50B in and $3B out, and argues that hallucinations remain and that the industry is built on hype.
Meaning of is the personal blog of Kenny Bastani, covering open source software, graph databases, cloud native architectures, information theory, artificial intelligence, and machine learning. As of September 18, 2025, the blog is no longer maintained, with readers directed to the author's GitHub or LinkedIn profiles.
