Tech + AI + Science NewsTech + AI + Science News
10 item(s)
cPanel zero-day exploited for months before patch release (CVE-2026-41940) - Help Net Security
Brave News
A critical vulnerability (CVE-2026-41940) in the cPanel control panel for managing web hosting accounts, is being exploited by attackers.
Agentic AI Pushes CPUs to Pack 400 GB of Memory, 4x More Than Today, as DRAM Shortage Spirals Toward 2027
Brave News
CPUs or GPUs, but require lots of memory for running Agentic AI, and this demand is spiraling to unseen levels as DRAM constraints persist.
EU countries, lawmakers fail to reach deal on watered-down AI rules | Reuters new
Brave News
EU countries and European Parliament lawmakers failed to reach a deal on watered-down landmark artificial intelligence rules after 12 hours of negotiations on Tuesday and will resume talks next month.
Best AI Models: April + May 2026 Leaderboard (GPT-5.5, Claude Opus 4.7, DeepSeek V4) new
Brave News
The most competitive month in AI history just ended. Full rankings, benchmarks, and which model wins for coding, reasoning, video, and more.
A Couple Million Lines of Haskell: Production Engineering at Mercury new
Hacker News · 2026-05-03
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Tesla owner won $10k in court for Tesla's FSD lies. Tesla is still fighting him new
Hacker News · 2026-05-02
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The Claude Delusion: Richard Dawkins believes his AI chatbot is conscious new
Hacker News · 2026-05-02
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Voice-AI-for-Beginners – A curated learning path for developers new
Hacker News · 2026-05-02
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GitHub Copilot CLI for Beginners: Interactive v. non-interactive mode
GitHub Blog · 2026-04-30
Learn the difference between CLI interactive v. non-interactive modes. The post GitHub Copilot CLI for Beginners: Interactive v. non-interactive mode appeared first on The GitHub Blog .
This AI knew the answers but didn’t understand the questions
ScienceDaily — Artificial Intelligence · 2026-04-30
For decades, psychologists have debated whether the human mind can be explained by one unified theory or must be broken into separate parts like memory and attention. A recent AI model called Centaur seemed to offer a breakthrough, claiming it could mimic human thinking across 160 different cognitive tasks. But new research is challenging that bold claim, suggesting the model isn’t truly “thinking” at all—it’s just memorizing patterns.
Research (arXiv)Research (arXiv)
10 item(s)
HERMES++: Toward a Unified Driving World Model for 3D Scene Understanding and Generation
arXiv · 2026-04-30
Driving world models serve as a pivotal technology for autonomous driving by simulating environmental dynamics. However, existing approaches predominantly focus on future scene generation, often overlooking comprehensive 3D scene understanding. Conversely, while Large Language Models (LLMs) demonstrate impressive reasoning capabilities, they lack the capacity to predict future geometric evolution, creating a significant disparity between semantic interpretation and physical simulation. To bridge this gap, we propose HERMES++, a unified driving world model that integrates 3D scene understanding and future geometry prediction within a single framework. Our approach addresses the distinct requirements of these tasks through synergistic designs. First, a BEV representation consolidates multi-view spatial information into a structure compatible with LLMs. Second, we introduce LLM-enhanced wor
OmniRobotHome: A Multi-Camera Platform for Real-Time Multiadic Human-Robot Interaction
arXiv · 2026-04-30
Human-robot collaboration has been studied primarily in dyadic or sequential settings. However, real homes require multiadic collaboration, where multiple humans and robots share a workspace, acting concurrently on interleaved subtasks with tight spatial and temporal coupling. This regime remains underexplored because close-proximity interaction between humans, robots, and objects creates persistent occlusion and rapid state changes, making reliable real-time 3D tracking the central bottleneck. No existing platform provides the real-time, occlusion-robust, room-scale perception needed to make this regime experimentally tractable. We present OmniRobotHome, the first room-scale residential platform that unifies wide-area real-time 3D human and object perception with coordinated multi-robot actuation in a shared world frame. The system instruments a natural home environment with 48 hardware
Generalizable Sparse-View 3D Reconstruction from Unconstrained Images
arXiv · 2026-04-30
Reconstructing 3D scenes from sparse, unposed images remains challenging under real-world conditions with varying illumination and transient occlusions. Existing methods rely on scene-specific optimization using appearance embeddings or dynamic masks, which requires extensive per-scene training and fails under sparse views. Moreover, evaluations on limited scenes raise questions about generalization. We present GenWildSplat, a feed-forward framework for sparse-view outdoor reconstruction that requires no per-scene optimization. Given unposed internet images, GenWildSplat predicts depth, camera parameters, and 3D Gaussians in a canonical space using learned geometric priors. An appearance adapter modulates appearance for target lighting conditions, while semantic segmentation handles transient objects. Through curriculum learning on synthetic and real data, GenWildSplat generalizes across
Observation of Vinen turbulence during far-from-equilibrium Bose-Einstein condensation
arXiv · 2026-04-30
Relaxation of far-from-equilibrium quantum fluids, intimately related to the emergence of long-range order, is theoretically associated with the decay of a turbulent isotropic tangle of vortex lines. We observe and study such decaying quantum turbulence in a homogeneous 3D atomic Bose gas. Using matter-wave techniques to magnify the gas density distribution, and then imaging a thin slice of the magnified cloud, we observe imprints of randomly oriented vortex lines and measure the vortex line-length density $\mathcal{L}$. The observed decay of $\mathcal{L}$ agrees with the prediction for Vinen `ultraquantum' turbulence. Although our weakly interacting gases are highly compressible, their large-scale dynamics are consistent with the behavior of an incompressible hydrodynamic fluid, with the decay of $\mathcal{L}$ not depending on the strength of the interatomic interactions and being simil
LaST-R1: Reinforcing Action via Adaptive Physical Latent Reasoning for VLA Models
arXiv · 2026-04-30
Vision-Language-Action (VLA) models have increasingly incorporated reasoning mechanisms for complex robotic manipulation. However, existing approaches share a critical limitation: whether employing explicit linguistic reasoning that suffers from latency and discretization, or utilizing more expressive continuous latent reasoning, they are predominantly confined to static imitation learning that limits adaptability and generalization. While online reinforcement learning (RL) has been introduced to VLAs to enable trial-and-error exploration, current methods exclusively optimize the vanilla action space, bypassing the underlying physical reasoning process. In this paper, we present \textbf{LaST-R1}, a unified VLA framework that integrates latent Chain-of-Thought (CoT) reasoning over physical dynamics prior to action execution, along with a tailored RL post-training paradigm. Specifically, w
Representation Fréchet Loss for Visual Generation
arXiv · 2026-04-30
We show that Fréchet Distance (FD), long considered impractical as a training objective, can in fact be effectively optimized in the representation space. Our idea is simple: decouple the population size for FD estimation (e.g., 50k) from the batch size for gradient computation (e.g., 1024). We term this approach FD-loss. Optimizing FD-loss reveals several surprising findings. First, post-training a base generator with FD-loss in different representation spaces consistently improves visual quality. Under the Inception feature space, a one-step generator achieves0.72 FID on ImageNet 256x256. Second, the same FD-loss repurposes multi-step generators into strong one-step generators without teacher distillation, adversarial training or per-sample targets. Third, FID can misrank visual quality: modern representations can yield better samples despite worse Inception FID. This motivates FDr$^k$
Computing Equilibrium beyond Unilateral Deviation
arXiv · 2026-04-30
Most familiar equilibrium concepts, such as Nash and correlated equilibrium, guarantee only that no single player can improve their utility by deviating unilaterally. They offer no guarantees against profitable coordinated deviations by coalitions. Although the literature proposes solution concepts that provide stability against multilateral deviations (\emph{e.g.}, strong Nash and coalition-proof equilibrium), these generally fail to exist. In this paper, we study an alternative solution concept that minimizes coalitional deviation incentives, rather than requiring them to vanish, and is therefore guaranteed to exist. Specifically, we focus on minimizing the average gain of a deviating coalition, and extend the framework to weighted-average and maximum-within-coalition gains. In contrast, the minimum-gain analogue is shown to be computationally intractable. For the average-gain and maxi
Visual Generation in the New Era: An Evolution from Atomic Mapping to Agentic World Modeling
arXiv · 2026-04-30
Recent visual generation models have made major progress in photorealism, typography, instruction following, and interactive editing, yet they still struggle with spatial reasoning, persistent state, long-horizon consistency, and causal understanding. We argue that the field should move beyond appearance synthesis toward intelligent visual generation: plausible visuals grounded in structure, dynamics, domain knowledge, and causal relations. To frame this shift, we introduce a five-level taxonomy: Atomic Generation, Conditional Generation, In-Context Generation, Agentic Generation, and World-Modeling Generation, progressing from passive renderers to interactive, agentic, world-aware generators. We analyze key technical drivers, including flow matching, unified understanding-and-generation models, improved visual representations, post-training, reward modeling, data curation, synthetic dat
Uniaxial strain-driven ferroelastic domain control in LaAlO3
arXiv · 2026-04-30
Multiferroic domain walls in functional oxides exhibit properties distinct from the bulk and are increasingly exploited as active elements in nanoelectronic and photonic devices. Deterministic control of domain populations has typically remained limited to local control, or removal with temperature. Here we demonstrate continuous, reversible manipulation of the ferroelastic domain structure in single-crystal LaAlO$_3$ using in-situ uniaxial strain. Combining atomic force microscopy, X-ray diffraction, and Raman spectroscopy with first-principles calculations we map the complete microscopic evolution of the twin domain population through the strain-driven transition from the rhombohedral $R\bar{3}c$ ground state toward the predicted orthorhombic $Fmmm$ phase. Applied strains below $0.5\%$ produce pronounced surface flattening and large-scale domain reorganisation, establishing uniaxial st
Exploration Hacking: Can LLMs Learn to Resist RL Training?
arXiv · 2026-04-30
Reinforcement learning (RL) has become essential to the post-training of large language models (LLMs) for reasoning, agentic capabilities and alignment. Successful RL relies on sufficient exploration of diverse actions by the model during training, which creates a potential failure mode: a model could strategically alter its exploration during training to influence the subsequent training outcome. In this paper we study this behavior, called exploration hacking. First, we create model organisms of selective RL resistance by fine-tuning LLMs to follow specific underperformance strategies; these models can successfully resist our RL-based capability elicitation in agentic biosecurity and AI R&D environments while maintaining performance on related tasks. We then use our model organisms to evaluate detection and mitigation strategies, including monitoring, weight noising, and SFT-based elic
Projects + Resources (Discovery)Projects + Resources (Discovery)
10 item(s)
GitHub - AllenDowney/ThinkDSP: Think DSP: Digital Signal Processing in Python, by Allen B. Downey. · GitHub new
Brave Search
<strong>Think DSP</strong> is an introduction to Digital Signal Processing in Python.
Network security: 4.1 An introduction to encryption and cryptography | OpenLearn - Open University new
Brave Search
Encryption of files and firewalls are just some of the security measures that can be used in security. This free course, Network security, which assumes you have a substantial knowledge of ...
Cryptography I | Coursera new
Brave Search
In this course you will <strong>learn the inner workings of cryptographic systems and how to correctly use them in real-world applications</strong>. The course begins with a detailed discussion of how two parties who have a shared secret key can communicate ...
Cryptography and Network Security Course -uCertify new
Brave Search
<strong>Uncover how secure communication protocols like TLS/SSL and SSH safeguard data transmission</strong>. You’ll also learn how firewalls and intrusion detection systems work to identify and mitigate threats like DDoS attacks.
FreeFEM - An open-source PDE Solver using the Finite Element Method new
Brave Search
We consider a model for Koiter linear elastic elliptic shells in contact with a deformable obstacle and we study the convergence of the solution of this model towards the solution of the corresponding model for elastic elliptic membrane shells when the small parameter of the model (thickness) tends to zero. Furthermore, we propose a numerical scheme for this kind of contact problems for Koiter shells and show numerical simulations after implementation by using the free software package FreeFem++.
OpenFDEM — OpenFDEM new
Brave Search
<strong>OpenFDEM is an open-source(free) and object-oriented finite and discrete element solver for solving diverse multiscale, multiphase and multiphysics (3M) problems accurately with high performance computations</strong>. Its applications include but are not limited to mechanical, thermal and fluid dynamics.
FEniCS | FEniCS Project new
Brave Search
<strong>FEniCS is a popular open-source computing platform for solving partial differential equations (PDEs) with the finite element method (FEM).</strong> FEniCS enables users to quickly translate scientific models into efficient finite element code. With the high-level Python and C++ interfaces to FEniCS, ...
GitHub - joamatab/awesome_photonics: 😎 curated list of open source photonics projects new
Brave Search
A curated list of awesome resource for photonic engineers, physicists and hobbyists · Most tools in this list are written or have a python interface, which require some basic knowledge of python. If you are new to python you can find many books, YouTube videos and courses available online. If you are new to Git and Python I recommend reading this article · layout: define the geometrical shapes that guide the light. simulation: simulate how photons propagate, and optimize the geometrical shapes
Think DSP: Digital Signal Processing in Python - Open Textbook Library new
Brave Search
<strong>Think DSP</strong> is an introduction to Digital Signal Processing in Python.
Open Neuromorphic is a global community fostering education, research, and open-source collaboration in brain-inspired AI and hardware. new
Brave Search
Submit your open-source neuromorphic projects for transparent community review and recognition through the ONR Program.