A new study by Shanghai Jiao Tong University and SII Generative AI Research Lab (GAIR) shows that training large language models (LLMs) for complex, autonomous tasks does not require massive datasets.

As a result, researchers are now exploring new strategies such as iterative and hierarchical reasoning. These methods aim to make reasoning deeper, more efficient, and more robust. This article ...

String manipulation is a core skill for every Python developer. Whether you’re working with CSV files, log entries, or text analytics, knowing how to split strings in Python makes your code cleaner ...

Learn what inventory accounting is, how it works, and key methods like FIFO, LIFO, and WAC. Includes real-world examples, tips, and best practices. I like to think of inventory accounting like ...

IGUA is a method for high-throughput content-agnostic identification of Gene Cluster Families (GCFs) from gene clusters of genomic and metagenomic origin. It performs three clustering iterations to ...

Having lived in several states, owning primary residences and investment properties, Josh Patoka uses his experience using mortgages and HELOCs to help first-time home buyers and home owners find the ...

Although large language models (LLMs) such as GPT-4 and LLaMA are rapidly reimagining modern-day applications, their inference is slow and difficult to optimize because it is based on autoregressive ...