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.

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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