After nine years of grinding, Replit finally found its market. Can it keep it?
While AI coding startups like Cursor raise brow-raising rounds on barely three years of existence, Replit’s path to a $3 billion valuation has been anything but swift.
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Thinking Machines Launches Tinker: A Low-Level Training API that Abstracts Distributed LLM Fine-Tuning without Hiding the Knobs
Thinking Machines has released Tinker, a Python API that lets researchers and engineers write training loops locally while the platform executes them on managed distributed GPU clusters. The pitch is narrow and technical: keep full control of data, objectives, and…
How to Build an Advanced Voice AI Pipeline with WhisperX for Transcription, Alignment, Analysis, and Export?
In this tutorial, we walk through an advanced implementation of WhisperX, where we explore transcription, alignment, and word-level timestamps in detail. We set up the environment, load and preprocess the audio, and then run the full pipeline, from transcription to…
Comparing Contrastive and Triplet Loss in Audio-Visual Embedding: Intra-Class Variance and Greediness Analysis
arXiv:2510.02161v1 Announce Type: cross Abstract: Contrastive loss and triplet loss are widely used objectives in deep metric learning, yet their effects on representation quality remain insufficiently understood. We present a theoretical and empirical comparison of these losses, focusing on intra-…
Paving the Way Towards Kinematic Assessment Using Monocular Video: A Preclinical Benchmark of State-of-the-Art Deep-Learning-Based 3D Human Pose Estimators Against Inertial Sensors in Daily Living Activities
arXiv:2510.02264v1 Announce Type: cross Abstract: Advances in machine learning and wearable sensors offer new opportunities for capturing and analyzing human movement outside specialized laboratories. Accurate assessment of human movement under real-world conditions is essential for telemedicine, sports science, and rehabilitation.…
GeoSQL-Eval: First Evaluation of LLMs on PostGIS-Based NL2GeoSQL Queries
arXiv:2509.25264v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have shown strong performance in natural language to SQL (NL2SQL) tasks within general databases. However, extending to GeoSQL introduces additional complexity from spatial data types, function invocation, and coordinate systems, which…
Smooth Quasar-Convex Optimization with Constraints
arXiv:2510.01943v1 Announce Type: cross Abstract: Quasar-convex functions form a broad nonconvex class with applications to linear dynamical systems, generalized linear models, and Riemannian optimization, among others. Current nearly optimal algorithms work only in affine spaces due to the loss of…
Machine learning for accuracy in density functional approximations
arXiv:2311.00196v2 Announce Type: replace-cross Abstract: Machine learning techniques have found their way into computational chemistry as indispensable tools to accelerate atomistic simulations and materials design. In addition, machine learning approaches hold the potential to boost the predictive power of computationally…
MolLangBench: A Comprehensive Benchmark for Language-Prompted Molecular Structure Recognition, Editing, and Generation
arXiv:2505.15054v2 Announce Type: replace-cross Abstract: Precise recognition, editing, and generation of molecules are essential prerequisites for both chemists and AI systems tackling various chemical tasks. We present MolLangBench, a comprehensive benchmark designed to evaluate fundamental molecule-language interface tasks: language-prompted molecular…
A Framework for Scalable Heterogeneous Multi-Agent Adversarial Reinforcement Learning in IsaacLab
arXiv:2510.01264v1 Announce Type: new Abstract: Multi-Agent Reinforcement Learning (MARL) is central to robotic systems cooperating in dynamic environments. While prior work has focused on these collaborative settings, adversarial interactions are equally critical for real-world applications such as pursuit-evasion, security, and…