As big tech companies pour billions of dollars into building larger AI models and sprawling data centres, a startup has claimed to have developed a fundamentally different frontier-level AI model at a fraction of the cost and tokens of traditional large language models (LLMs).
HRM-Text is a one billion-parameter, open-weight AI model developed from scratch by researchers at Sapient Intelligence. While the ongoing AI boom is underpinned by models running on Transformer-based architectures, Sapient said that its new text generation model is based on a highly sample-efficient Hierarchical Recurrent Model (HRM) architecture that was first introduced by the Singapore-based startup last year.
The HRM architecture decouples computation into slow-evolving strategic and fast-evolving execution layers. While most LLMs are trained on raw text using brute-force autoregressive prediction, HRM-Text has been trained only on instruction-response pairs. This means that the model is specially designed to generate a targeted answer to a specific task. It is available on GitHub for download.
The launch of HRM-Text is potentially significant considering that training a foundational LLM from scratch costs millions of dollars and involves scraping internet-scale data. As a result, most enterprises and startups do not have the resources to develop their own in-house LLMs.
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