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techloy.com · Nov 5

Why Low-Latency AI Inference Matters for Real-Time Applications and AI Agents

Modern software architectures demand sub-millisecond execution to support complex user requests.

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arXiv

Nov 4

From Pixels to Actions - Towards Native Vision-Language-Action Policies

Vision-language-action models are typically built on a simple premise: perception is first compressed by visual encoders, and action reasoning begins only afterwards. Yet manipulation often hinges on precisely the visual signals most vulnerable to this abstraction, e.g., local geometry, boundaries, depth, and subtle state changes. This raises a fundamental question: should action policies inherit a fixed visual endpoint, or directly access evolving visual computation? We introduce NEO-VLA, a structurally encoder-free vision-language-action framework. Images are tokenized by lightweight patch convolutional layers and evolve jointly with language throughout the backbone, allowing a flow-matching action expert to draw from instruction-conditioned visual representations at different depths. This simple change reveals a consistent pattern. Native architectures outperform encoder-based counterparts under controlled comparisons; full fine-tuning reduces but does not erase the gap, and additional scale alone cannot recover it. More strikingly, layer-wise probing shows that the action-critical signals often peak well before the final visual representation. Across diverse manipulation…

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arXiv

Sep 22

MICRO: Multi-Fidelity Active Search for Severe Error Discovery

Human feedback can vary in cost and informativeness. Strong feedback can reveal severe errors but is costly, so cheaper quality ratings can help decide which items to annotate. We propose MICRO (Multi-Fidelity Impact Clustered Rollout), an active search framework that allocates…

arXiv

Sep 22

Reciprocal Collaboration: how lessons from convergence in GLAMs can enhance interdisciplinary AI research

The need for collaboration between diverse fields of research is increasingly recognised as important by research funding agencies. A significant driver of this need is the current revolution in artificial intelligence (AI) and related technologies. There is a growing interest…

arXiv

Sep 22

A Holistic Assessment of the Carbon Footprint of Noor, a Very Large Arabic Language Model

As ever larger language models grow more ubiquitous, it is crucial to consider their environmental impact. Characterised by extreme size and resource use, recent generations of models have been criticised for their voracious appetite for compute, and thus significant carbon…

arXiv

Sep 22

BOBA: Dynamic Bayesian Optimization through Bayesian Active Inference

Dynamic black-box optimization presents significant challenges for Bayesian Optimization (BO), as the objective function evolves over time, causing optimal locations to shift continuously. Existing dynamic BO (DBO) methods using standard acquisition functions such as Upper…

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