Critical evidence for builders evaluating ROI of AI coding tools in real workflows.
Harvard study finds AI coding agents increase code output by 30% but create review bottlenecks, resulting in no net gain in software production or employment reduction.
Researchers developed Prompteina, the first all-atom protein structure generation model that accepts natural language descriptions as input.
Theoretical paper proves that prediction alone is insufficient for memory in learning systems, requiring additional state information for exact cumulative learning.
New Humanity's Sixth Sense benchmark reveals AI models score 53.6% vs humans' 93.1% on intuitive visual reasoning tasks like spatial logic and causal dynamics.
Researchers tested language models on Wikipedia Game navigation tasks across five languages and academic datasets, finding top models achieved human-comparable performance.
Researchers prove AI models can cryptographically hide arbitrary capabilities using backdoor attacks that embed encrypted neural networks only triggered by secret inputs.
