Values Values instill a goal of action to perform. The realist, by the endless winters of death, has fashioned new methods of action. The right way is the best way in any condition, and the best foot forward. What values do you consider important in developing your software? How to put into practise design-to-development principles in software development? Tech Stacks Software frameworks differ based on the purposes of the software to define the tech stacks. What programming languages […]

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Safety Is Not a Switch, It Is a Process For a long time, AI safety seemed like something you could install. You specified constraints, tested for edge cases, built guardrails, and deployed with confidence. This paradigm was fine when systems were largely static. It starts to break when systems change. Today, AI systems do not merely follow pre-programmed logic. They learn. They adapt. They interact with other agents. In multi-agent settings, systems negotiate, compete, coordinate, and sometimes, game […]

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arXiv:2602.20223v1 Announce Type: new Abstract: Recently, TabPFN has gained attention as a foundation model for tabular data. However, it struggles to integrate heterogeneous modalities such as images and text, which are common in domains like healthcare and marketing, thereby limiting its applicability. To address this, we present the Multi-Modal Prior-data Fitted Network (MMPFN), which extends TabPFN to handle tabular and non-tabular modalities in a unified manner. MMPFN comprises per-modality encoders, modality projectors, and pre-trained foundation models. The modality […]

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Scientific machine learning (SciML) is increasingly applied to in-field processing, controlling, and monitoring; however, wide-area sensing, real-time demands, and strict energy and reliability constraints make centralized SciML implementation impractical. Most SciML models assume raw data aggregation at a central node, incurring prohibitively high communication latency and energy costs; yet, distributing models developed for general-purpose ML often breaks essential physical principles, resulting in degraded performance. To address these challenges, we introduce EPIC, a hardware- and physics-co-guided distributed SciML framework, […]

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I’ve been thinking about an approach for fine-tuning/RL on limited data and I’m not sure it’s the right one , curious if anyone has done something similar. i need a model that generates document templates from structured input + a nl comment. The only data I have are existing compiled templates, no input/output pairs. The idea is to bootstrap with reverse engineering, feed each template to a strong LLM, extract the parameters that could have generated it, use […]

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https://reddit.com/link/1sep2lt/video/tmacpy2vzptg1/player We scaled off-policy RL for sim-to-real. FlashSAC is the fastest and most performant RL algorithm across IsaacLab, MuJoCo Playground, Genesis, DeepMind Control Suite, and more, all with a single set of hyperparameters. If you’re still using PPO, give FlashSAC a try. submitted by /u/joonleesky [link] [comments]

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We are interested in enabling autonomous agents to learn and reason about systems with hidden states, such as furniture with hidden locking mechanisms. We cast this problem as learning the parameters of a discrete Partially Observable Markov Decision Process (POMDP). The agent begins with knowledge of the POMDP’s actions and observation spaces, but not its state space, transitions, or observation models. These properties must be constructed from action-observation sequences. Spectral approaches to learning models of partially observable domains, […]

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This study examines the impact of data augmentation on machine learning perfor-mance, focusing on how synthetic data influences various neural network architec-tures. Common issues such as limited data, class imbalance, and poor coverage often lead to low model metrics, and data augmentation is frequently used to address these problems. The research aims to identify the optimal proportion of synthetic data, assess its effects across different architectures, and analyze the impact of augmenting only specific classes in a multi-class […]

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