One equation changed everything in 2017. Here’s the complete taxonomy of what came after — and what’s killing it right now.Continue reading on Towards AI »
Coding agents are getting smarter, but they still waste most of their tokens reading irrelevant code. Here is how AST-based semantic search, LSP, and a lightweight CLI can change that. We built an embedded lightweight semantic code search tool for codi…
How Analytical workflows, SQL queries and reasoning loops become agentic systemsFor years, dashboards have been the primary interface for interacting with data. They surface metrics, visualize trends, and enable decision-making through charts and filte…
The features on social media apps like Snapchat evolve nearly as fast as what’s trending. To keep pace, its parent company Snap has adopted open data processing libraries from NVIDIA on Google Cloud services to boost development. Every new feature rolled out to Snapchat’s more than 940 million monthly active users goes through a set […]
It’s another month in AI research, and it’s hard to pick favorites. This month, I am going over a paper that discusses strategies for the continued…
Once again, this has been an exciting month in AI research. This month, I’m covering two new openly available LLMs, insights into small finetuned LLMs, and…
Low-rank adaptation (LoRA) is a machine learning technique that modifies a pretrained model (for example, an LLM or vision transformer) to better suit a…
This article focuses on improving the modeling performance of LLMs by finetuning them using carefully curated datasets. Specifically, this article…
Large language models (LLMs) offer one of the most interesting opportunities for developing more efficient training methods. A few weeks ago, the NeurIPS…
Peak memory consumption is a common bottleneck when training deep learning models such as vision transformers and LLMs. This article provides a series of…