#model-optimization

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fromHackernoon
2 years ago

Using LLVM To Supercharge AI Model Execution On Edge Devices | HackerNoon

LLVM simplifies optimizing AI workloads for edge devices, transforming deployment pipelines into efficient processes.
fromHackernoon
55 years ago

Keep the Channel, Change the Filter: A Smarter Way to Fine-Tune AI Models | HackerNoon

Efficient fine-tuning of large pre-trained models can be achieved by adjusting only filter atoms while preserving overall model capabilities.
fromHackernoon
6 months ago

Chinese AI Model Promises Gemini 2.5 Pro-level Performance at One-fourth of the Cost | HackerNoon

MiniMax's M1 model stands out with its open-weight reasoning capabilities, scoring high on multiple benchmarks, including an impressive 86.0% accuracy on AIME 2024.
Artificial intelligence
fromHackernoon
1 month ago

Can Smaller AI Outperform the Giants? | HackerNoon

The advancement of vision-language models (VLMs) relies on foundational design choices, yet many lack justification, hindering progress by obscuring performance improvements.
Artificial intelligence
Growth hacking
fromInfoQ
2 months ago

Scaling Large Language Model Serving Infrastructure at Meta

LLM serving is evolving into a foundational technology similar to an operating system.
fromInfoWorld
1 year ago

All the brilliance of AI on minimalist platforms

Fast forward to 2024, our reliance on massive data infrastructures is evaporating, with AI systems running on palm-sized devices. Apple & Qualcomm chips integrate AI for tasks like language translation and photo processing.
Digital life
fromTechzine Global
4 months ago

Pruna AI makes compression framework open source

Pruna AI's open-source framework simplifies the application of various AI model compression methods like caching, pruning, quantization, and distillation, enhancing model efficiency.
Artificial intelligence
fromHackernoon
4 months ago

Mamba: A Generalized Sequence Model Backbone for AI | HackerNoon

Selective State Space Models enhance performance on discrete data but can hinder efficiency on continuous tasks.
Artificial intelligence
fromHackernoon
4 months ago

Rethinking AI Quantization: The Missing Piece in Model Efficiency | HackerNoon

Quantum strategies optimize LLM precision while balancing accuracy and effectiveness through methods like post-training quantization and quantization-aware training.
Scala
fromHackernoon
4 months ago

The Hidden Power of "Cherry" Parameters in Large Language Models | HackerNoon

Parameter heterogeneity in LLMs shows that a small number of parameters greatly influence performance, leading to the development of the CherryQ quantization method.
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