Engineering posts about Self-attention
Curated summaries and key learnings for engineers working with Self-attention.
AI success starts with clean data, not just better models
The article emphasizes that the success of AI initiatives is heavily reliant on the quality of data rather than solely on advanced models. It features insights from Kristy Mayer-Mejia, Global Head of...
Adaptive Thinking: Large Language Models Know When to Think in Latent Space
The article presents research on adaptive thinking in large language models (LLMs), particularly focusing on how these models can optimize their reasoning processes during inference. It introduces...
Exclusive Self Attention
The article presents exclusive self-attention (XSA), a modification of traditional self-attention (SA) that enhances the performance of Transformers in sequence modeling tasks. By constraining...
Models That Prove Their Own Correctness
The paper introduces Self-Proving models, which are designed to guarantee the correctness of their outputs for specific inputs through a verification algorithm. By employing Interactive Proofs, these...
How to Build Production-Ready Genie Spaces, and Build Trust Along the Way
The article discusses the development of production-ready Genie spaces within Databricks, emphasizing the importance of benchmarks to objectively measure readiness and build user trust. It outlines a...
How PARTs Assemble into Wholes: Learning the Relative Composition of Images
The article discusses a novel self-supervised learning approach called PART, which addresses the limitations of traditional grid-based methods in understanding the relative composition of images. By...
From Data to Dialogue: A Best Practices Guide for Building High-Performing Genie Spaces
The article outlines best practices for constructing effective Genie Spaces within the Databricks platform, emphasizing the importance of a strong data foundation, proper metadata configuration, and...
Self-Supervised Learning with Gaussian Processes
The article presents Gaussian Process Self-Supervised Learning (GPSSL), a method that enhances self-supervised learning by leveraging Gaussian processes to impose priors on representations. This...
Background Coding Agents: Predictable Results Through Strong Feedback Loops (Part 3)
This article is the third part of a series detailing Spotify's exploration of background coding agents aimed at automating software maintenance. It highlights the challenges of ensuring reliable code...