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Galileo Space Is Building Satellites That Turn Signals Into Answers in Orbit

Galileo Space is building satellites designed to turn signals into answers in orbit. Modern defense and commercial operations need fast answers about what is happening and where. Existing systems can

Google releases Gemini 4 Argon, called its most powerful model yet

Google has released its latest Gemini model, marketing it as a workhorse for coding and cybersecurity work.

SpaceX set to launch astronauts and a classified Falcon Heavy mission on the same day

SpaceX plans three launches Thursday, including Crew-13 astronauts and Falcon Heavy's first classified NRO mission. The post SpaceX set to launch astronauts and a classified Falcon Heavy mission on th

Chicago Metra calls its new battery-electric locomotive a first of its kind

Metra’s diesel-engined commuter trains are familiar sights in and around Chicago, and so is the smell of spent diesel that surrounds them – but a new battery-electric FLIRT locomotive from Stadler is

Tesla Cybercab and Semi have more in common than you might think

Although the two vehicles are built for completely different use cases, Tesla utilized engineering expertise while developing both the Cybercab and Semi to build a thermal architecture that would fit

Google DeepMind Unveils Gemini 4 Argon with 1M Output Tokens for Coding, Knowledge Work and Cyber Defense

Gemini 4 Argon tops GPT-6 Astra and Claude Opus 5.5 on most benchmarks, but access remains gated today. The post Google DeepMind Unveils Gemini 4 Argon with 1M Output Tokens for Coding, Knowledge Work

Skill-Space Shooting for Autonomous Robot Policy Improvement

Zihang Rui, Renhao Wang, Haoxu Huang +1

Robots deployed in the physical world must be able to improve beyond their initial training as they encounter new situations and failures. For this improvement to scale across tasks, it must make effective use of experience without requiring human de

Imagine3D-LLM: Teaching MLLMs to Imagine 3D Scenes Before Answering

Jaewoo Jung, Hyeonseo Yu, Honggyu An +10

Reasoning about the 3D world from multi-view images remains a fundamental challenge for Multimodal Large Language Models (MLLMs). While modern MLLMs handle single-image inputs effectively, they struggle to integrate evidence across viewpoints into a

Breakdown of Local Denoising as Semantic Speciation

Guangkuo Liu, Mert Okyay, Yifan F. Zhang +3

The dynamics of generative models exhibit two apparently distinct temporal windows: a speciation window, in which a sample commits to a semantic class, and a nonlocality window, in which local context windows become insufficient for generation. Motiv

STEPQuant: When and Where Errors Matter in Delta-Rule Recurrent State Quantization

Bingchen Yao, Haobo Xu, Haokun Lin +6

Linear attention replaces growing KV caches with fixed-size recurrent states, yet these persistent states can become a substantial memory bottleneck under concurrent serving. Directly quantizing recurrent states to low precision often leads to severe

LeapQuant: Efficient Linear Attention with Accurate Recurrent State Quantization

Yi Pan, Haocheng Xi, Kan Zhu +10

Recent LLMs increasingly adopt hybrid designs that replace standard attention with linear attention, such as Gated DeltaNet (GDN) and Kimi Delta Attention (KDA). Although they compress the context into a fixed-size recurrent state and substantially r

Cropland PAtteRNS: Parallel Dimensional Attention Networks and Attention to Dataset Disparity for Crop Segmentation in Satellite Imagery Time Series Data

Joseph Metcalfe, Sara Sharifzadeh, Fabio Caraffini

The landscape of satellite imagery time series datasets and boundary-pushing architectures for cropland segmentation has never been richer. However, in this gold rush, important truths are being missed on both fronts, as a drive for the most novel co