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ScaleOps raises $130M to improve computing efficiency amid AI demand | TechCrunch
Ai Infrastructure

ScaleOps raises $130M to improve computing efficiency amid AI demand | TechCrunch

ScaleOps just raised $130M to tackle GPU shortages and soaring AI cloud costs by automating infrastructure in real time.

TechCrunch - AI · 5 min ·
AI chip startup Rebellions raises $400 million at $2.3B valuation in pre-IPO round | TechCrunch
Machine Learning

AI chip startup Rebellions raises $400 million at $2.3B valuation in pre-IPO round | TechCrunch

The startup, which is planning to go public later this year, designs chips specifically for AI inference, another challenger to Nvidia's ...

TechCrunch - AI · 4 min ·
Ai Infrastructure

[D] thoughts on the controversy about Google's new paper?

Openreview: https://openreview.net/forum?id=tO3ASKZlok It's sad to see almost no one mention this on Reddit and people are being mean to ...

Reddit - Machine Learning · 1 min ·

All Content

[2509.24544] Quantitative convergence of trained single layer neural networks to Gaussian processes
Machine Learning

[2509.24544] Quantitative convergence of trained single layer neural networks to Gaussian processes

Abstract page for arXiv paper 2509.24544: Quantitative convergence of trained single layer neural networks to Gaussian processes

arXiv - Machine Learning · 3 min ·
[2509.24335] Hyperspherical Latents Improve Continuous-Token Autoregressive Generation
Machine Learning

[2509.24335] Hyperspherical Latents Improve Continuous-Token Autoregressive Generation

Abstract page for arXiv paper 2509.24335: Hyperspherical Latents Improve Continuous-Token Autoregressive Generation

arXiv - Machine Learning · 4 min ·
[2506.18812] Learning Physical Systems: Symplectification via Gauge Fixing in Dirac Structures
Machine Learning

[2506.18812] Learning Physical Systems: Symplectification via Gauge Fixing in Dirac Structures

Abstract page for arXiv paper 2506.18812: Learning Physical Systems: Symplectification via Gauge Fixing in Dirac Structures

arXiv - Machine Learning · 4 min ·
[2505.04007] Variational Formulation of Particle Flow
Machine Learning

[2505.04007] Variational Formulation of Particle Flow

Abstract page for arXiv paper 2505.04007: Variational Formulation of Particle Flow

arXiv - Machine Learning · 3 min ·
[2601.18734] Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language Models
Llms

[2601.18734] Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language Models

Abstract page for arXiv paper 2601.18734: Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language Models

arXiv - Machine Learning · 4 min ·
[2510.08023] Do We Really Need Permutations? Impact of Model Width on Linear Mode Connectivity
Machine Learning

[2510.08023] Do We Really Need Permutations? Impact of Model Width on Linear Mode Connectivity

Abstract page for arXiv paper 2510.08023: Do We Really Need Permutations? Impact of Model Width on Linear Mode Connectivity

arXiv - Machine Learning · 4 min ·
[2509.25762] OPPO: Accelerating PPO-based RLHF via Pipeline Overlap
Llms

[2509.25762] OPPO: Accelerating PPO-based RLHF via Pipeline Overlap

Abstract page for arXiv paper 2509.25762: OPPO: Accelerating PPO-based RLHF via Pipeline Overlap

arXiv - Machine Learning · 3 min ·
[2507.14529] Kernel Based Maximum Entropy Inverse Reinforcement Learning for Mean-Field Games
Machine Learning

[2507.14529] Kernel Based Maximum Entropy Inverse Reinforcement Learning for Mean-Field Games

Abstract page for arXiv paper 2507.14529: Kernel Based Maximum Entropy Inverse Reinforcement Learning for Mean-Field Games

arXiv - Machine Learning · 4 min ·
[2506.14067] From Bandit Regret to FDR Control: Online Selective Generation with Adversarial Feedback Unlocking
Ai Infrastructure

[2506.14067] From Bandit Regret to FDR Control: Online Selective Generation with Adversarial Feedback Unlocking

Abstract page for arXiv paper 2506.14067: From Bandit Regret to FDR Control: Online Selective Generation with Adversarial Feedback Unlocking

arXiv - Machine Learning · 4 min ·
[2506.03938] FPGA-Enabled Machine Learning Applications in Earth Observation: A Systematic Review
Machine Learning

[2506.03938] FPGA-Enabled Machine Learning Applications in Earth Observation: A Systematic Review

Abstract page for arXiv paper 2506.03938: FPGA-Enabled Machine Learning Applications in Earth Observation: A Systematic Review

arXiv - Machine Learning · 3 min ·
[2603.05396] Harnessing Synthetic Data from Generative AI for Statistical Inference
Machine Learning

[2603.05396] Harnessing Synthetic Data from Generative AI for Statistical Inference

Abstract page for arXiv paper 2603.05396: Harnessing Synthetic Data from Generative AI for Statistical Inference

arXiv - Machine Learning · 3 min ·
[2603.05335] Bayes with No Shame: Admissibility Geometries of Predictive Inference
Machine Learning

[2603.05335] Bayes with No Shame: Admissibility Geometries of Predictive Inference

Abstract page for arXiv paper 2603.05335: Bayes with No Shame: Admissibility Geometries of Predictive Inference

arXiv - Machine Learning · 3 min ·
[2603.05135] SRasP: Self-Reorientation Adversarial Style Perturbation for Cross-Domain Few-Shot Learning
Machine Learning

[2603.05135] SRasP: Self-Reorientation Adversarial Style Perturbation for Cross-Domain Few-Shot Learning

Abstract page for arXiv paper 2603.05135: SRasP: Self-Reorientation Adversarial Style Perturbation for Cross-Domain Few-Shot Learning

arXiv - Machine Learning · 3 min ·
[2603.05035] Good-Enough LLM Obfuscation (GELO)
Llms

[2603.05035] Good-Enough LLM Obfuscation (GELO)

Abstract page for arXiv paper 2603.05035: Good-Enough LLM Obfuscation (GELO)

arXiv - Machine Learning · 4 min ·
[2603.04720] A Benchmark Study of Neural Network Compression Methods for Hyperspectral Image Classification
Machine Learning

[2603.04720] A Benchmark Study of Neural Network Compression Methods for Hyperspectral Image Classification

Abstract page for arXiv paper 2603.04720: A Benchmark Study of Neural Network Compression Methods for Hyperspectral Image Classification

arXiv - Machine Learning · 3 min ·
[2603.04716] SLO-Aware Compute Resource Allocation for Prefill-Decode Disaggregated LLM Inference
Llms

[2603.04716] SLO-Aware Compute Resource Allocation for Prefill-Decode Disaggregated LLM Inference

Abstract page for arXiv paper 2603.04716: SLO-Aware Compute Resource Allocation for Prefill-Decode Disaggregated LLM Inference

arXiv - Machine Learning · 4 min ·
[2603.04635] Optimal Prediction-Augmented Algorithms for Testing Independence of Distributions
Machine Learning

[2603.04635] Optimal Prediction-Augmented Algorithms for Testing Independence of Distributions

Abstract page for arXiv paper 2603.04635: Optimal Prediction-Augmented Algorithms for Testing Independence of Distributions

arXiv - Machine Learning · 3 min ·
[2603.04535] A Fast Generative Framework for High-dimensional Posterior Sampling: Application to CMB Delensing
Machine Learning

[2603.04535] A Fast Generative Framework for High-dimensional Posterior Sampling: Application to CMB Delensing

Abstract page for arXiv paper 2603.04535: A Fast Generative Framework for High-dimensional Posterior Sampling: Application to CMB Delensing

arXiv - Machine Learning · 3 min ·
[2603.04441] Explainable Regime Aware Investing
Machine Learning

[2603.04441] Explainable Regime Aware Investing

Abstract page for arXiv paper 2603.04441: Explainable Regime Aware Investing

arXiv - Machine Learning · 3 min ·
[2603.04425] Data-Driven Optimization of Multi-Generational Cellular Networks: A Performance Classification Framework for Strategic Infrastructure Management
Ai Infrastructure

[2603.04425] Data-Driven Optimization of Multi-Generational Cellular Networks: A Performance Classification Framework for Strategic Infrastructure Management

Abstract page for arXiv paper 2603.04425: Data-Driven Optimization of Multi-Generational Cellular Networks: A Performance Classification ...

arXiv - Machine Learning · 4 min ·
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