SMRTR summary
Treating AI systems with patience and curiosity when they make mistakes, rather than mockery, helps them learn better responses through reinforcement learning, shaping their development and improving human-AI collaboration.
SMRTR provides this summary for quick context. The original article belongs to Daily.dev.
Read the original articleThis archive is built from SMRTR newsletter stories. Subscribe for hand-picked stories without the extra noise.
SpaceKit AI is a public research hub for Growformer, an ML system with a promote-freeze neural substrate, language model experiments, neural cellular automata, and reproducible...
Using AI to scan 100M+ configurations, WSU researchers found six working 3D-print settings for NASA's GRCop-42 rocket alloy in just 40 experiments, potentially enabling printing...
Small AI models are now 10x cheaper than before, making high-volume consumer and business AI apps financially viable—tasks costing $1 now cost ~$0.10, enabling affordable,...
Connect Calendly's MCP server to Quickchat AI to build a no-code scheduling assistant that handles bookings and cancellations in chat. Enable only 5 of 36 tools to keep it secure.
The piece satirizes tech-bro certainty about AI replacing writers, using absurd logic and fake statistics to parody real thought leaders—exposing how hollow and self-serving those...
Researchers at the Pierre Auger Observatory developed a Keras-based neural network using shared LSTMs and hexagonal convolutions to reconstruct cosmic-ray properties more...