The Invisible Workers Behind AI

At a training center, instructors directly impart knowledge to attentive students, fostering a learning environment where individual understanding is also rigorously assessed through proctored, handwritten examinations.

New research exposes the hidden human effort powering artificial intelligence systems, revealing the precarious conditions faced by those performing this essential ‘ghost work’.

The Compression Key to Smarter AI

Agentic language models increasingly depend on compression techniques to distill long inputs into succinct summaries, a process now feasible on consumer hardware like Google Pixel phones and Apple MacBooks, as demonstrated by performance benchmarks on open-weight models and indicated by LM-Arena rankings.

New research reveals that prioritizing computational resources on compressing information, rather than prediction, is a more effective pathway to building powerful agentic systems.