Analyzes push notifications as a recommender system, discussing intent, personalization, timeliness, and user engagement challenges.
A recap of key announcements from the second half of AWS re:Invent 2023, focusing on new AI/ML services and management tools.
Explores how AI and LLMs can enhance CI/CD pipelines by predicting test failures, generating tests, enabling intelligent rollbacks, and detecting anomalies.
Scikit-learn remains a dominant and impactful machine learning library, especially for classic ML and tabular data, despite the hype around deep learning.
Announcing libactivation, a new Python package on PyPI providing activation functions and their derivatives for machine learning and neural networks.
Exploring how Java code can be executed on GPUs for high-performance computing and machine learning, covering challenges and potential APIs.
Explores using out-of-domain data to improve LLM finetuning for detecting factual inconsistencies (hallucinations) in text summaries.
A developer recreates a research project using wireless earbuds' microphones to detect facial touch gestures and control UIs via machine learning in JavaScript.
A critical analysis of the machine learning bubble, arguing its lasting impact will be a proliferation of low-quality, automated content and services, not true AGI.
A technical guide on building and deploying a custom machine learning model using Vertex AI on Google Cloud, implemented with Go, Python, and Docker.
Interview with Itai Bar Sinai, co-founder of Mona Labs, discussing AI monitoring, product-oriented data science, and the Israeli ML community.
A developer shares insights from building an AI audit prototype, discussing the importance of defensibility and lessons from banking model audits.
Author shares how following curiosity in writing and tech led to writing a machine learning book, promotions, and career growth.
A guide to deploying open-source Large Language Models (LLMs) like Falcon using Hugging Face's managed Inference Endpoints service.
Interview with Chetan Sharma, CEO of Eppo, discussing A/B testing, statistics engineering, and building a modern experimentation platform.
A summary and analysis of DeepMind's RoboCat paper, a self-improving foundation agent for robotic manipulation using Transformer models.
A guide to running open-source Large Language Models (LLMs) like LLaMA locally on your CPU using C# and the LLamaSharp library.
Interview with AI researcher Curtis Northcutt on his journey from rural Kentucky to MIT, founding Cleanlab, and his work on confident learning and dataset improvement.
Interview with Frank Liu on vector databases, embeddings, his career in ML/hardware, and work culture differences between China and the US.
A curated list of open-source Large Language Models (LLMs) available for commercial use, including community-contributed updates and details.
