We Need Efficient and Transparent Language Models

• Efficient Methods for Natural Language Processing: Roy Schwartz is Professor of NLP at The Hebrew University of Jerusalem. We discuss an important survey paper (co-written by Roy) that presents a broad overview of existing methods to improve NLP efficiency through the lens of NLP pipelines.
• Building a premier industrial AI research and product group .. in three years: Hung Bui is the CEO of Vietnam-based, VinAI, explains the process of building a team that within a span of three years found itself listed among the Top 20 Global Companies in AI Research.

Holistic Evaluation of Language Models. Stanford researchers recently introduced tools to help users and developers understand large language models (LLM) in their totality. Given the central role of LLMs in NLP and in GenerativeAI, this suite of tools is an important step towards better transparency for language models. I hope other researchers build upon this exciting suite of techniques and ideas.

Benchmarking Open Table Formats. When migrating to a modern data warehouse or data lakehouse, selecting the right table format is crucial. Brooklyn Data Company just released an important new benchmark comparing open source Delta Lake and Apache Iceberg. They found that Delta Lake is typically 1.5x – 3x better for write workloads. Read workloads ran consistently 7x – 8x faster on Delta Lake.

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