Two threads are reshaping LLMs beyond generic chat: OpenTSLM treats time series as a native modality. And Liquid AI's LFM2-Audio-1.5 pushes audio into foundation-model territory. These conversations sketch a future where modality-specific models meet edge needs and raise fresh questions about attention and causality. [1][2]
Time-series as a native modality - OpenTSLM lets time-series play alongside text, enabling questions, explanations, and interpretable chain-of-thought with a cross-attention architecture that scales to long streams. [1] - Sleep staging: 4.4× accuracy with a model 200× smaller (~880× efficiency); Activity recognition: ~6× accuracy with 200× smaller (~1,000× efficiency); ECG interpretation: ~2× accuracy with 200× smaller (~400× efficiency). [1] - First model to process 12-lead ECG signals and text simultaneously with chain-of-thought reasoning verified by cardiologists. [1] - Cross-domain attention and causality debates accompany the push, with discussions about whether time-series reasoning yields true causality. [1] - The efficiency and long-stream cross-attention hint at edge-friendly deployments for healthcare, robotics, and resilient infrastructure. [1]
Audio foundation model headline - LFM2-Audio-1.5 is described as an end-to-end Audio Foundation Model with inputs: Audio & Text and outputs: Audio & Text; steerable via prompting; and it’s available on HuggingFace. [2] - For many, it’s exciting as an ASR solution with a custom vocabulary, something Parakeet and Whisper don’t fully support yet. It’s also described as snappy, though opinions vary. [2] - Release blog post: LFM2-Audio: An End-to-End Audio Foundation Model | Liquid AI; GitHub: liquid-audio; Playground demos show practical angles. [2]
Closing thought Modality-specific LLMs like OpenTSLM and LFM2-Audio-1.5 signal a future where domain-optimized models live alongside generalists, with edge deployment, interpretability, and cross-modality attention as the next big asks. [1][2]
References
OpenTSLM: Language models that understand time series
OpenTSLM enables time-series as a native modality; discussions on attention, causality, edge deployment, and cross-domain implications.
View sourceLiquid AI released its Audio Foundation Model: LFM2-Audio-1.5
Discussion of Liquid's LFM2-Audio; mixed reception; comparisons with Parakeet/Whisper; mentions of LLMs like Qwen, Gemma; debates on graphs and benchmarks.
View source