AI researchers and investors say reinforcement‑learning (RL) environments are becoming a core tool for training next‑generation AI agents. Large labs such as OpenAI, Anthropic and Google are building or sourcing simulated workspaces where agents can practice multi‑step tasks, while a wave of startups—Mechanize, Prime Intellect, Surge, Mercur and others—are racing to supply high‑quality environments. The push reflects a shift from static data sets to interactive simulations, but experts warn that scaling and reward‑hacking remain significant hurdles. Read more →

AI researchers and investors say reinforcement‑learning (RL) environments are becoming a core tool for training next‑generation AI agents. Large labs such as OpenAI, Anthropic and Google are building or sourcing simulated workspaces where agents can practice multi‑step tasks, while a wave of startups—Mechanize, Prime Intellect, Surge, Mercur and others—are racing to supply high‑quality environments. The push reflects a shift from static data sets to interactive simulations, but experts warn that scaling and reward‑hacking remain significant hurdles. Read more →

AI researchers and investors say reinforcement‑learning (RL) environments are becoming a core tool for training next‑generation AI agents. Large labs such as OpenAI, Anthropic and Google are building or sourcing simulated workspaces where agents can practice multi‑step tasks, while a wave of startups—Mechanize, Prime Intellect, Surge, Mercur and others—are racing to supply high‑quality environments. The push reflects a shift from static data sets to interactive simulations, but experts warn that scaling and reward‑hacking remain significant hurdles. Read more →

AI researchers and investors say reinforcement‑learning (RL) environments are becoming a core tool for training next‑generation AI agents. Large labs such as OpenAI, Anthropic and Google are building or sourcing simulated workspaces where agents can practice multi‑step tasks, while a wave of startups—Mechanize, Prime Intellect, Surge, Mercur and others—are racing to supply high‑quality environments. The push reflects a shift from static data sets to interactive simulations, but experts warn that scaling and reward‑hacking remain significant hurdles. Read more →

AI researchers and investors say reinforcement‑learning (RL) environments are becoming a core tool for training next‑generation AI agents. Large labs such as OpenAI, Anthropic and Google are building or sourcing simulated workspaces where agents can practice multi‑step tasks, while a wave of startups—Mechanize, Prime Intellect, Surge, Mercur and others—are racing to supply high‑quality environments. The push reflects a shift from static data sets to interactive simulations, but experts warn that scaling and reward‑hacking remain significant hurdles. Read more →

Meta's multi‑billion‑dollar investment in data‑labeling firm Scale AI is encountering challenges. Key executives, including former Scale AI senior vice president Ruben Mayer, have departed shortly after joining Meta's Superintelligence Labs. Researchers within Meta's TBD Labs are reportedly favoring alternative labeling vendors such as Surge and Mercur, citing concerns over data quality. Scale AI, meanwhile, has faced customer losses, staff reductions, and a strategic shift toward government contracts. The turbulence reflects broader upheaval within Meta's AI organization as it seeks to accelerate its generative‑AI ambitions. Read more →