SMRTR summary
Anthropic settled with authors who sued over using books to train AI models, despite a prior fair use ruling, due to the inclusion of pirated works, resolving a case that underscored AI-copyright conflicts.
SMRTR provides this summary for quick context. The original article belongs to TechCrunch.
Read the original articleThis archive is built from SMRTR newsletter stories. Subscribe for hand-picked stories without the extra noise.
Meta updated its AI glasses to prevent users from disabling the LED recording indicator and launched a campaign promoting the privacy feature, but a class action lawsuit claims...
Monarch Chrysalis v1 is a 6.93B parameter model that reasons in latent space and runs on a desktop CPU, but testing revealed its reasoning isn't reliably connected to its outputs....
CDLMs are regaining traction after being overshadowed by discrete methods in 2023, driven by their ability to be distilled into faster models, enabling better post-training and...
LLMs amplify existing intelligence rather than creating it. As information becomes commoditized, the real advantage shifts to judgment—knowing what to ask, recognizing what...
Build a byte-level BPE tokenizer from scratch—the encoding method used by modern LLMs. Progress from a basic word tokenizer to an optimized, multilingual tokenizer compatible with...
Classical spell-checkers miss valid-word substitutions, scrambled boundaries, and OCR misreads. Enterprise RAG pipelines need embedding-based semantic search paired with keyword...