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Triton Is Said to Near €3 Billion Deal for Carlyle’s Flender

Triton Partners is nearing a deal to buy Flender GmbH, a provider of mechanical and electrical drive technology, in a transaction valuing the firm at about €3 billion ($3.5 billion), according to people familiar with the matter.

Bloomberg Markets 8d ago

Fast-Vollib: A Fast Implied Volatility Library for Pythonwith PyTorch, JAX, and CUDA Fused-Kernel Backends

arXiv:2604.27210v2 Announce Type: replace-cross Abstract: We present fast-vollib, an open-source Python library that provides high-performance European option pricing, implied volatility (IV) computation, and Greeks under the Black-76, Black-Scholes, and Black-Scholes-Merton models. The library is designed as a drop-in alternative to the de-facto-standard py_vollib and py_vollib_vectorized packages, with pluggable PyTorch and JAX execution backends, a CUDA fused-kernel Triton contribution...

arXiv CS 1d ago

Evaluating CUDA Tile for AI Workloads on Hopper and Blackwell GPUs

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arXiv CS 5d ago

Bringing Up DeepSeek-V4-Flash on AMD MI300X

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Hacker News 7d ago

CS336: Language Modeling from Scratch

Course Staff Logistics - Lectures: Monday/Wednesday 3:00-4:20pm in Skilling Auditorium - Recordings: YouTube playlist - Office hours: - Percy Liang: Fridays 11am-12pm in Gates 366 - Tatsu Hashimoto: Tuesdays 11-12am in Gates 364 - Marcel Rød: Tuesdays 4:30-5:30pm in Gates 498, Wednesdays 4:30-5:30pm in Gates 415 - Herman Brunborg: Wednesdays 1:30-2:30pm, Fridays 1:30-2:30pm, location Gates 392 - Steven Cao: Mondays 4:30-5:30pm, Thursdays 9:30-10:30am, Gates 200 - Contact: Students should ask...

Hacker News 9d ago

AI Agent Guidelines for CS336 at Stanford

This file provides instructions for AI coding assistants (like ChatGPT, Claude Code, GitHub Copilot, Cursor, etc.) working with students in CS336. AI agents should function as teaching aids that help students learn through explanation, guidance, and feedback—not by completing assignments for them.

Hacker News 9d ago

Deterministic Inference across Tensor Parallel Sizes That Eliminates Training-Inference Mismatch

arXiv:2511.17826v2 Announce Type: replace Abstract: Deterministic inference is increasingly critical for large language model (LLM) applications such as LLM-as-a-judge evaluation, multi-agent systems, and Reinforcement Learning (RL). However, existing LLM serving frameworks exhibit non-deterministic behavior: identical inputs can yield different outputs when system configurations (e.g., tensor parallel (TP) size, batch size) vary, even under greedy decoding. This arises from the...

arXiv CS 9d ago

Light Interaction: Training-Free Inference Acceleration for Interactive Video World Models

arXiv:2605.31158v1 Announce Type: new Abstract: Interactive video world models generate video chunk by chunk in response to user-controlled camera movements, enabling applications such as real-time game simulation, virtual scene navigation, and embodied AI training. However, scaling to long interactive trajectories is prohibitively expensive due to growing context memory, quadratic attention complexity, and repeated denoising steps. We present Light Interaction, a training-free inference...

arXiv CS 9d ago

Best early Prime Day camping deals: Up to 40% off tents, grills, outdoor fans and more

Gear up for camping season and all your outdoor adventures now that warmer weather is here to stay. Early Amazon Prime Day deals are already live, with savings of up to 40% on solar string lights, Coleman tents, Jackery power banks, grills and more. Whether you're planning a weekend getaway in the woods or upgrading your backyard setup, these discounts have you covered.2-gallon camping water container: $6.99 (30% off)Traeger Grills 22 pellet grill and smoker: $389 (29% off)Mosquito head net:...

Fox News 1d ago

STAR-KV: Low-Rank KV Cache Compression via Soft Thresholding for Adaptive Rank Control

arXiv:2606.08382v1 Announce Type: new Abstract: Low-rank projection has emerged as a promising approach for compressing the KV cache by exploiting hidden-dimension redundancy. However, prior methods rely on fixed or heuristic rank selection and struggle to achieve aggressive compression with minimal accuracy degradation. We propose STAR-KV, an adaptive low-rank KV cache compression framework with fine-grained rank control.

arXiv CS 1d ago