systems
AI agents help explain other AI systems | MIT News
Explaining the behavior of trained neural networks remains a compelling puzzle, especially as these models grow in size and sophistication. Like other scientific challenges throughout history, reverse-engineering how artificial intelligence systems work requires a substantial amount of experimentation: making hypotheses, intervening on behavior, and even dissecting large networks to examine individual neurons. To date, most…
Search algorithm reveals nearly 200 new kinds of CRISPR systems | MIT News
Microbial sequence databases contain a wealth of information about enzymes and other molecules that could be adapted for biotechnology. But these databases have grown so large in recent years that they’ve become difficult to search efficiently for enzymes of interest. Now, scientists at the McGovern Institute for Brain Research at MIT, the Broad Institute of…