Artificial intelligence and machine learning have permeated nearly all practical spheres of our lives, making them an instant sensation with new tools and models promising new things every week. Here, I try to cover this AI popular culture as it unfolds, picking important news stories and publishing them after careful deliberation.


AI companies need data. The usual datasets don’t suffice anymore. There’s a real need for human-generated content that can speak better to the users of AI tools. But people trying to fight this backed by human-oriented copyright laws are naturally losing.

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I keep a list of sources about AI, ML, deep learning, and related fields that I check regularly. Anything that’s worth talking is picked up from these sources. The sources include Twitter lists, subreddits, AI/tech sections of big news websites, and a bunch of daily newsletters. Of course, sometimes I miss a few stories. I also ignore stories that are too shallow, such as a rumor or a minor leak because of my limited bandwidth.

When I find a story worth covering, I research all of its facets, often reading multiple articles to formulate the core of the matter. Then, I write on the story with my own opinions and biases. Nobody’s knowledge is perfect, and so, I do my best to clarify my research process and link to important resources throughout my coverage.

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Adobe AI Inference AI in Military AI Training Amazon AMD Anthropic Apple Autonomous Systems Azure ChatGPT Copilot Copyright Deepfake Elon Musk Gemini Generative AI Google GPT-4 Hardware Healthcare Humanoids Inflection AI Intel Investment Lawsuit LLaMA Llama 2 Meta Microsoft Misuse of AI Multimodal Music Nvidia Open-Source OpenAI Policymaking Privacy Regulation Research Paper Risks of AI Safety Sam Altman Study Tesla