GPUs, training clusters, MLOps, and deployment
Hey all, I recently built an end-to-end fraud detection project using a large banking dataset: Trained an XGBoost model Used Databricks f...
TurboQuant was teased recently and tens of billions gone from memory chip market in 48 hours but anyone in this community who read the pa...
AI skeptics aren’t the only ones warning users not to unthinkingly trust models’ outputs — that’s what the AI companies say themselves in...
![[2602.21215] Inference-time Alignment via Sparse Junction Steering](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
This paper presents Sparse Inference-time Alignment (SIA), a novel approach to enhance alignment in large language models by intervening ...
The paper presents the 2-Step Agent framework, which models the interaction between decision makers and AI decision support systems, high...
The paper presents fEDM+, an enhanced fuzzy ethical decision-making framework that improves explainability and validation by integrating ...
This study investigates how different prompt architectures affect reasoning quality in large language models, specifically addressing the...
The paper explores the effectiveness of aggregating outputs from multiple AI models in compound AI systems, examining its potential to en...
This article discusses the evaluation of inference efficiency in Sparse+Linear Hybrid Architectures, specifically MiniCPM-SALA, and its p...
Nvidia reported record profits of $68 billion in its latest quarter, driven by skyrocketing demand for AI compute, while addressing conce...
Sentinel Gateway addresses the challenge of instruction provenance in AI agents by ensuring only user-signed prompts are treated as execu...
This article discusses a lightweight TensorRT implementation of FoundationPose, aimed at improving robotics research by eliminating the h...
The discussion explores how to efficiently call PyTorch models from Scala/Spark for inference, addressing performance concerns in a large...
President Trump announced plans for tech companies to sign a 'rate payer protection pledge' to manage rising electricity costs for AI dat...
The article discusses a proposed notation for improving contextual inference in probabilistic models, emphasizing the role of contextual ...
The White House is urging major AI companies to absorb rising electricity costs linked to their data centers. Most firms, including Micro...
Intrinsic, a robotics software company under Alphabet, is now joining Google to enhance its AI capabilities, focusing on making industria...
The article discusses how users of the OpenClaw AI tool are leveraging an open-source project called Scrapling to bypass anti-bot systems...
Discussion on whether ICLR is suspending Spotlights this year, with concerns over communication and potential impacts from OpenReview leaks.
Public opposition to AI infrastructure is rising, leading to legislative proposals for moratoriums on new data center constructions acros...
The article discusses the Anthropic-Pentagon situation, framing it as a governance-layer conflict in AI rather than a political debate, f...
The Trump administration has directed U.S. diplomats to oppose foreign data sovereignty laws, claiming they threaten AI advancement and g...
Sovereign Mohawk is a Go-based runtime for federated learning that addresses scaling and trust issues, achieving empirical validation for...
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