Opinion
CIOOpinion

AI isn’t failing, people are failing with AI

AI isn’t the problem — rushing it into the wrong tasks without the right data, expertise or guardrails is what makes projects fall apart.
Morning Overview on MSN

AI model cracks yeast DNA code to turbocharge protein drug output

MIT researchers have built an AI language model that learns the internal coding patterns of a yeast species widely used to manufacture protein-based drugs, then rewrites gene sequences to push protein ...
VentureBeat

Z.ai debuts open source GLM-4.6V, a native tool-calling vision model for multimodal reasoning

Chinese AI startup Zhipu AI aka Z.ai has released its GLM-4.6V series, a new generation of open-source vision-language models (VLMs) optimized for multimodal reasoning, frontend automation, and ...
marktechpost

This AI Paper Proposes a Novel Dual-Branch Encoder-Decoder Architecture for Unsupervised Speech Enhancement (SE)

Most learning-based speech enhancement pipelines depend on paired clean–noisy recordings, which are expensive or impossible to collect at scale in real-world conditions. Unsupervised routes like ...
Scientific Research Publishing

Malhotra, P., Ramakrishnan, A., Anand, G., Vig, L., Agarwal, P. and Shroff, G. (2016) LSTM-Based Encoder-Decoder for Multi-Sensor Anomaly Detection.

ABSTRACT: This work presents an innovative Intrusion Detection System (IDS) for Edge-IoT environments, based on an unsupervised architecture combining LSTM networks and Autoencoders. Deployed on ...
GitHub

[RFC]: Prototype Separating Vision Encoder to Its Own Worker

In the current multi-modality support within vLLM, the vision encoder (e.g., Qwen_vl) and the language model decoder run within the same worker process. While this tightly coupled architecture is ...
IEEE

Improved Encoder-Decoder Architecture With Human-Like Perception Attention for Monaural Speech Enhancement

Abstract: Speech enhancement (SE) models based on deep neural networks (DNNs) have shown excellent denoising performance. However, mainstream SE models often have high structural complexity and large ...