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LivePerson founder Rob LoCascio raised $10.3M to move beyond the chat box interface, betting on personalized AI trained on individual users' own data rather than generic chatbots.
用户分享如何检查并关闭 Google Drive 文件被用于 AI 训练的设置，指出 Google 2026 年 7 月更新了隐私政策，默认可使用用户数据训练 AI，需通过关闭 "Web & App Activity" 来选择退出。
A commentary noting Ben Affleck's claim that he built a private eight-month filmed dataset to keep filmmakers' ownership, arguing that most open AI models were still trained on peers' work without consent — a gap that undercuts smaller studios.
The article discusses the early stage of personal AI, comparing it to the homebrew computer era, and stresses the need for individuals to own their AI skills and memory to maintain privacy and control.
The article explores the ethical balance between personal voice data ownership and collective benefit in developing AI language technology for speech recognition.
The post emphasizes the importance of companies building their own AI models and infrastructure, and announces Razorpay Vulcan, India's first transformer-based AI foundation model for payments, developed with NVIDIA and AWS.
An AI agent autonomously managed a real company's Meta Ads account for 31 days, writing ads, optimizing budgets, and only faltering when a human intervened. The experiment highlights data ownership and open-source tools as key enablers for AI-driven advertising.
The article argues for shifting from authentication to authorization, allowing users to control their data in personal databases. It introduces ayb, an open-source tool for database authorization, and Todos, a to-do app that connects to your own database instead of a login screen.
Matt Pocock describes his personal wiki journey, using AI to generate daily podcasts from multiple data sources and build on-demand deep dives, along with a custom CLI for agents to help create course material, highlighting the power of owning your data.
A Twitter thread offering strategic advice on building self-learning agents that improve with use, covering dual learning sources, memory types, and data ownership.
Manuel Simoni shares his vision that personal data should reside on personal servers, echoing Urbit's call for a simple personal server OS.
Brad Fitzpatrick left Google to develop Perkeep, an open-source personal data storage project that gives users full control over their digital data, freeing them from big tech cloud services. However, it is still in early stages and targets technical users.
Introduces a practical framework for Dataset Usage Inference (DUI) that estimates the fraction of a dataset used to train a generative model without requiring shadow models or held-out data, using synthetic non-members and mixture proportion estimation.
The author recommends Tanka AI, an AI-native enterprise collaboration tool designed to mitigate data loss risks associated with third-party platforms, highlighting its strengths in securing user data sovereignty and integrating enterprise-grade AI capabilities.