We found most apps send PII to LLMs and built a 2 line fix
A company found that most applications send personally identifiable information to large language models. They developed a two-line solution to address this privacy issue.
Related stories
A new phishing-as-a-service called Starkiller uses disguised links to load real login pages from target brands. It acts as a relay between victims and legitimate sites, forwarding usernames, passwords, and MFA codes to bypass security measures.
An investigation uncovered a large network of fake support groups on Telegram that spread cryptocurrency stealers and drainers. The network was found to be actively promoting malicious tools designed to drain crypto wallets.
Gemini can identify public figures in images, while ChatGPT and Claude currently do not offer this capability. This represents a functional difference between major AI models regarding image recognition of people.
Inception Labs has launched Mercury 2, described as the world's first reasoning diffusion LLM. The diffusion language model reportedly delivers 5x faster inference speed compared to leading speed-optimized LLMs.
Andrej Karpathy describes using LLMs to build personal knowledge bases by indexing source documents into a raw directory, then having the LLM compile them into a markdown wiki with summaries, backlinks, and categorization. The system allows for complex Q&A against the wiki and can generate various output formats like markdown files, slideshows, and images, all viewable in Obsidian.