NetMind Powers Groundbreaking AI Research with Carnegie Mellon University
NetMind is extremely honoured to announce our ongoing partnership with Carnegie Mellon's School of Computer Science. This collaboration has already borne significant fruit, with us contributing our GPU power and infrastructure to a groundbreaking research study by the institution. This study itself could have significant positive implications for AI development and underscores our commitment to advancing artificial intelligence through critical research – and making cutting-edge technology accessible to all, for the benefit of all.
The study itself, titled "An Empirical Analysis of Compute-Optimal Inference for Problem-Solving with Language Models” focused on optimising the efficiency of language models (LLMs) during inference. Specifically it dove into compute-optimal inference, which is a critical area that explores how to design models and inference strategies that balance computational efficiency with performance – essentially doing more with less. Traditionally, larger language models have been favoured for their superior accuracy. However, they need a lot of computational resources, making them impractical for many applications.
The study's findings demonstrated the alternative potential benefits of deploying smaller models with sophisticated decoding algorithms, to achieve exactly what their larger counterparts can – especially in budget-constrained scenarios. This approach can significantly enhance problem-solving accuracy while maintaining computational efficiency, making it extremely valuable for applications on end-devices.
We’re proud to announce that NetMind's powerful computing infrastructure played a crucial role in this critical research, enabling the team to test various inference strategies. This partnership also acts as a microcosm to highlight our evolving commitment to advancing artificial intelligence by supporting top-tier academic research in a variety of AI development areas. (We also wanted to take this opportunity to say a big thank you to Professor Graham Neubig and Zhiqing Sun for making this collaboration possible - and congratulations on them having their research published).
So why are we helping support research like this?
The answer is easy – because we think that AI should benefit everyone, not just those with the deepest pockets. So, by providing the computing resources needed for research by the prestigious likes of Carnegie Mellon, we’re simultaneously enabling ground-breaking discoveries that could reshape the future of AI, spearheaded by institutions dedicated to scientific discovery rather than financial bottom-lines.
Plus we also believe in enabling innovation through dynamic collaboration, and our continued partnership with Carnegie Mellon showcases our dedication to doing that through aligning with excellent academic institutes who seek to positively advance AI technologies. To that end we look forward to continuing our work with both Carnegie and other leading research institutions, providing the tools and support necessary for them to explore exciting new frontiers in artificial intelligence. Together, we’re using decentralised technology and our platform to help shape the future of AI at a time when it is critical to do so, to ensure that its continued development is inclusive and beneficial for all.
Stay tuned for more updates on our collaborations and the exciting innovations they bring!
(Link to study here )
Disclaimer: The content of this article solely reflects the author's opinion and does not represent the platform in any capacity. This article is not intended to serve as a reference for making investment decisions.
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