Tired of fighting cluster queues and cloud infrastructure just to run training jobs? We built 22+ pre-configured templates covering: For RL researchers: ∙ PPO training (Stable Baselines3, custom environments) ∙ Multi-agent setups ∙ Hyperparameter sweeps ∙ Different model sizes and frameworks Other templates: ∙ LLM fine-tuning (GRPO, LoRA) ∙ Video/image generation ∙ Monte Carlo simulations ∙ Scientific computing workflows How it works: 1. Pick your template 2. Upload your data/code 3. Select compute (T4, A100, H100, etc.) 4. […]

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The Question That Started This When you put an AI agent on live infrastructure, a question follows immediately: How do you know what it tells you actually happened? Not whether the AI is capable. Whether the observation it hands you — “BGP session down, here’s why” — reflects what the device actually said. Whether the change it claims to have made actually exists on the device. Whether the signed output you’re trusting as ground truth was collected from […]

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arXiv:2601.09842v1 Announce Type: new Abstract: Teaching software development basics to hundreds of students in a frontal setting is cost-efficient and thus still common in universities. However, in a large lecture hall, students can easily get bored, distracted, and disengaged. The frontal setting can also frustrate lecturers since interaction opportunities are limited and hard to scale. Fun activities can activate students and, if well designed, can also help remember and reflect on abstract software development concepts. We present a […]

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February 10, 2026 – OSL Group (863.HK), Asia’s leading stablecoin trading and payment platform, today announced the official launch of USDGO, a regulated, enterprise-grade U.S. dollar stablecoin. As a cornerstone of OSL Group’s global payment infrastructure, USDGO is positioned for institutional settlement and corporate payments, serving the cross-border business ecosystem of Asian enterprises. Leveraging its enterprise-level features and services, USDGO provides users with a compliant tool for liquidity management and settlement. It is dedicated to the long-term empowerment […]

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(Dylan Foster and Alex Lamb both helped in creating this.) In thinking about what are good research problems, it’s sometimes helpful to switch from what is understood to what is clearly possible. This encourages us to think beyond simply improving the existing system. For example, we have seen instances throughout the history of machine learning where researchers have argued for fixing an architecture and using it for short-term success, ignoring potential for long-term disruption. As an example, the […]

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arXiv:2601.02385v1 Announce Type: new Abstract: As 5G networks rapidly expand and 6G technologies emerge, characterized by dense deployments, millimeter-wave communications, and dynamic beamforming, the need for scalable simulation tools becomes increasingly critical. These tools must support efficient evaluation of key performance metrics such as coverage and radio-frequency electromagnetic field (RF-EMF) exposure, inform network design decisions, and ensure compliance with safety regulations. Moreover, base station (BS) placement is a crucial task in the network design, where satisfying coverage requirements […]

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A smartly deployed choice menu can provide viewers, platforms, and advertisers more of what they all want.

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arXiv:2604.13067v1 Announce Type: new Abstract: SpeechLLMs process spoken language directly from audio, but accent and vocal identity cues can lead to biased behaviour. Current bias evaluations often miss how such bias manifests in end-to-end speech interactions and how users experience it. We distinguish quality-of-service disparities (e.g., off-topic or low-effort responses) from content-level bias in coherent outputs, and examine intersectional effects of accent and perceived gender. In this work, we explore a two-part evaluation approach: (1) a controlled test […]

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Dominant approaches for modelling Partial Differential Equations (PDEs) rely on deterministic predictions, yet many physical systems of interest are inherently chaotic and uncertain. While training probabilistic models from scratch is possible, it is computationally expensive and fails to leverage the significant resources already invested in high-performing deterministic backbones. In this work, we adopt a training-efficient strategy to transform pre-trained deterministic models into probabilistic ones via retrofitting with a proper scoring rule: the Continuous Ranked Probability Score (CRPS). Crucially, […]

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arXiv:2603.25906v1 Announce Type: new Abstract: Estimating human pose, classifying actions, and predicting movement progress are essential for human-robot interaction. While vision-based methods suffer from occlusion and privacy concerns in realistic environments, tactile sensing avoids these issues. However, prior tactile-based approaches handle each task separately, leading to suboptimal performance. In this study, we propose a Shared COnvolutional Transformer for Tactile Inference (SCOTTI) that learns a shared representation to simultaneously address three separate prediction tasks: 3D human pose estimation, action […]

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