Sapient Intelligence (@Sapient

Sapient Intelligence

32 posts

Sapient Intelligence

@Sapient_Int

Building efficient & powerful general intelligence through brain-inspired architecture

Palo Alto, CA

Joined July 2024

Pinned
Sapient Intelligence
@Sapient_Int
May 18
Introducing HRM-Text. An ultra-lean 1B-parameter reasoning language model designed to deliver strong general performance with a fraction of the data, compute, and infrastructure. Trained on just 40B structured tokens, HRM-Text achieves competitive performance while using
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Sapient Intelligence
@Sapient_Int
May 26
Excited to see our community building with HRM-Text! Can’t wait to see where you take it next.🚀 Whether you’re reproducing the benchmarks, testing it out in your own field, or building something entirely new, we’d love to hear about it. Drop your ideas, questions, and
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Sapient Intelligence
@Sapient_Int
May 22
Replying to @Sapient_Int
Paper: arxiv.org/abs/2605.20613 GitHub: github.com/sapientinc/HRM… Hugging Face: huggingface.co/sapientinc/HRM…
arxiv.org
HRM-Text: Efficient Pretraining Beyond Scaling
The current pretraining paradigm for large language models relies on massive compute and internet-scale raw text, creating a significant barrier to foundational research. In contrast, biological...
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Sapient Intelligence
@Sapient_Int
May 22
Replying to @Sapient_Int
Paper:
arxiv.org
HRM-Text: Efficient Pretraining Beyond Scaling
The current pretraining paradigm for large language models relies on massive compute and internet-scale raw text, creating a significant barrier to foundational research. In contrast, biological...
806
Sapient Intelligence reposted
Guan Wang
@makingAGI
May 20
The HRM-Text paper is now available 🎉 HRM-Text explores a different approach to language model pretraining: hierarchical recurrent computation, task-completion training, and latent-space reasoning. At just 1B parameters, HRM-Text achieves competitive performance with
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Sapient Intelligence
@Sapient_Int
May 19
In this benchmark deep-dive, Sapient’s founders William and Guan are joined by research team members Changling and Yasin to unpack HRM-Text’s performance across MATH, DROP, ARC-Challenge, and MMLU. 📊 Beyond the scores, they discuss what each benchmark measures, how HRM-Text
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Sapient Intelligence
@Sapient_Int
May 19
Replying to @Sapient_Int
Download HRM-Text🔗 GitHub: github.com/sapientinc/HRM… Hugging Face: huggingface.co/sapientinc/HRM…
GitHub - sapientinc/HRM-Text: HRM-Text is a 1B text generation model based on the HRM architecture,...
From github.com
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Sapient Intelligence
@Sapient_Int
May 19
HRM-Text 101 is here. This tutorial takes you from zero to one: from setup to fine-tuning to evaluation. Download the base checkpoint. Fine-tune it on a real task. Evaluate the results. End to end, on a single GPU. Watch the tutorial and start building with HRM-Text.
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Sapient Intelligence
@Sapient_Int
May 18
Replying to @Sapient_Int
Download HRM-Text 🔗 Github: github.com/sapientinc/HRM… Hugging Face: huggingface.co/sapientinc/HRM…
GitHub - sapientinc/HRM-Text: HRM-Text is a 1B text generation model based on the HRM architecture,...
From github.com
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Sapient Intelligence
@Sapient_Int
May 18
Tomorrow, we will unveil a new path to general intelligence. Lean. Powerful. Efficient. The countdown is on⏳
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Sapient Intelligence
@Sapient_Int
May 16
It is time to liberate reasoning from language! HRM (Hierarchical Reasoning Model) takes a simple idea from the brain: separating reasoning (thinking) from language. When we think, our brains process information in high-dimensional, abstract streams--deep, instantaneous, and
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Sapient Intelligence
@Sapient_Int
May 13
Is bigger always better in AI? 🧠 We've reached incredible SOTAs by brute-forcing scale with astronomical token counts. But consider the human brain: running on just 20W of power and trained on ~1B language tokens, it's still making miracles happen. That efficiency is
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Sapient Intelligence
@Sapient_Int
May 4
At Sapient Intelligence, we enable deep, efficient reasoning with our Hierarchical Reasoning Model (HRM)—a brain-inspired, latent-space architecture that moves beyond traditional, data-heavy AI. By decoupling the cognitive load, HRM uses a Slower Controller to guide abstract,
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