Subject archive for "data-science"

Speeding cars at night in Hong Kong (Photo by Jimmy Chan: https://www.pexels.com/photo/time-lapse-photography-of-road-near-buildings-2552595/)
NVIDIA

Crush Pandas Speed Barriers with NVIDIA GPUs on Domino

See how NVIDIA's RAPIDS v23.10 revolutionizes AI workloads with GPU-accelerated Pandas on Domino, offering massive speed boosts and data handling efficiency.

By Yuval Zukerman4 min read

Data Science

New! Domino AutoML

Domino's integrated AutoML offers scalable, reproducible, & flexible solutions with editable code, diverse team collaboration, & hybrid-cloud support.

By Thomas Dinsmore4 min read

Image of a man shaking hands with a robot
Data Science

Generative AI Must Be Responsible AI. What You Need to Know.

Companies diving head-first into Generative AI must consider the risks it brings. Domino’s guide shows you how to harness GenAI responsibly. Download now!

By Yuval Zukerman3 min read

An illustration of a large language model as production line
Data Science

Crossing the Frontier: LLM Inference on Domino

Generative AI transforms industries, but LLM deployment is tough. See how Domino simplifies LLM hosting & inference.

By Subir Mansukhani10 min read

Watchmaker working on an exquisite watch
Generative Models

Breaking Generative AI Barriers with Efficient Fine-Tuning Techniques

This blog post explores the challenges of fine-tuning large language models (LLMs) and introduces resource-optimized and parameter-efficient techniques such as quantization, LoRA, and Zero Redundancy Optimization (ZeRO). By fine-tuning Falcon-7b, Falcon-40b, and GPTJ-6b, we demonstrate how these techniques offer improved performance, cost-effectiveness, and resource optimization in LLM fine-tuning. The blog post also discusses the future of fine-tuning and its potential for unlocking new possibilities in enterprise AI applications.

By Subir Mansukhani9 min read

Domino and NVIDIA bring generative AI to the enterprise
Product Updates

Beyond the Hype: Domino Offers Production-Ready Generative AI Powered by NVIDIA

With the ongoing generative AI hype, one concept is becoming increasingly clear: giant, generic generative AI models, by themselves, are not the key to unlocking business value. While they are excellent for experimentation, entertainment, and some limited end-user work augmentation (ChatGPT might have helped with parts of this blog), they often fall short in terms of performance, accuracy, and risk when they aren't production grade.

By David Schulman9 min read

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