!Cover image for Awesome AI Agent Papers 2026https://media2.dev.to/dynamic/image/width=1000,height=420,fit=cover,gravity=auto,format=auto/https%3A%2F%2Fdev-to-u...

This brief presents a runtime-adaptive, performance-enhanced vector engine featuring a low-resource, iterative CORDIC-based MAC unit for edge AI acceleration. T...

Reinforcement learning fine-tuning has proven effective for steering generative diffusion models toward desired properties in image and molecular domains. Graph...

Fuzzy systems show strong potential in explainable AI due to their rule-based architecture and linguistic variables. Existing approaches navigate the accuracy-e...

!Cover image for Where Intelligence Meets Connection: My Journey Through the India AI Impact Summit 2026https://media2.dev.to/dynamic/image/width=1000,height=42...

I got tired of pitching bad ideas to polite friends. You know the drill: you share your latest “revolutionary” concept, and everyone nods. “Sounds cool.” “Inter...

The remarkable performance of modern AI systems has been driven by unprecedented scales of data, computation, and energy -- far exceeding the resources required...

Transformer models contain substantial internal redundancy arising from coordinate-dependent representations and continuous symmetries, in model space and in he...

Clustering is widely used for unsupervised structure discovery, yet it offers limited insight into how reliable each individual assignment is. Diagnostics, such...

Autonomous (noise-agnostic) generative models, such as Equilibrium Matching and blind diffusion, challenge the standard paradigm by learning a single, time-inva...

Graph neural networks (GNNs) are increasingly applied to hard optimization problems, often claiming superiority over classical heuristics. However, such claims ...

This paper presents a direct framework for sequence models with hidden states on closed subgroups of U(d). We use a minimal axiomatic setup and derive recurrent...