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# The Dark Psychology of AI Startups: Opportunities, Impact, and Ethical Dilemmas *How modern…
## Introduction Artificial intelligence has completely transformed modern business operations and individual digital experiences.Continue reading on Medium »
Bayesian Wind Tunnels for Model Selection
arXiv:2607.19379v1 Announce Type: new Abstract: Prior work has shown that transformers can perform exact Bayesian filtering within a fixed hypothesis class. Can they also perform Bayesian model selection -- identifying the correct hypothesis class from data? We introduce model-selection Bayesian wind tunnels: controlled environments where ground-truth posteriors over hypothesis classes are available in closed form. Using fixed-point-free involutions -- whose defining property f(f(x))=x is purely relational -- a 2.8M-parameter transformer achieves 0.01-bit entropy agreement with the Bayesian optimum (3 seeds), with both integer tokens and opaque symbols whose meanings change every episode. This extends to non-nested comparisons: involutions vs. 3-cycles (where neither class is a subset of the other) achieve class-posterior MAE under 0.001, demonstrating genuine model selection beyond simplicity/subset bias. We then identify a sharp perceptual access condition: when the discriminative st
FineServe: A Fine-Grained Dataset and Characterization of Global LLM Serving Workloads
arXiv:2607.19349v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed as always-on online services, making efficient LLM serving a critical systems challenge. Achieving low latency and high throughput under volatile demand requires deep understanding of real-world serving workloads, yet existing studies often rely on proxy traces or coarse-grained characterizations that fail to capture the heterogeneity of modern multi-model LLM platforms. We present FineServe, an in-the-wild, multi-model LLM serving workload dataset collected from a global commercial marketplace, enabling fine-grained characterization of real-world serving dynamics across heterogeneous models and tasks. Leveraging FineServe, we conduct a comprehensive analysis of arrival dynamics and token behavior, revealing fundamentally different fluctuation regimes across model architectures, scales and task intents. Building on these insights, we develop the FineServe workload generator, which com
Emergent Autonomous Drifting for Collision Avoidance in Real-World Winter Driving Scenarios
arXiv:2607.19484v1 Announce Type: new Abstract: Real-world collision avoidance is a core motivation for studying the dynamics and control of high sideslip drifting in vehicles, yet the practical benefit of such maneuvers has so far primarily been tested in scenarios explicitly engineered to require drifting. In this work, we explore the question of if and when drifting may be optimal for safety in real-world winter driving conditions. We present a drift-capable nonlinear model predictive control (MPC) system designed to handle scenarios grounded in crash fatality data and deploy the controller in a high fidelity simulator across road departure and oncoming vehicle collision avoidance scenarios. The controller naturally initiates and sustains drifting maneuvers to stay on the road when hitting a patch of ice on the rear axle and to avoid an oncoming vehicle that has slid into its lane. Comparisons with a benchmark electronic stability control (ESC) system demonstrate how a drift-capable
ModPack: An Extensible Teleoperation Interface for Bimanual Mobile Manipulation
arXiv:2607.19479v1 Announce Type: new Abstract: Existing teleoperation systems are often tailored to specific robot hardware and task domains, limiting their scalability and adaptability. We present ModPack, a modular and extensible teleoperation system designed to support diverse robot embodiments and task requirements within a unified framework. At the core of ModPack is a self-contained wearable "backpack" that integrates onboard computation, power, communication, and data storage. Built on top of this shared interface, the system supports plug-and-play capability modules including joint-level teleoperation with haptic feedback, mobile manipulation, and active perception. Experiments across two distinct robot platforms and real-world mobile manipulation tasks demonstrate that ModPack provides a flexible and reusable framework for data collection and policy learning. To support future research, we open-source the complete hardware design and software stack. Project website: https://m
Native Multi-Dimensional Subquadratic Operators via Input Dependent Long Convolutions
arXiv:2607.19378v1 Announce Type: new Abstract: Subquadratic alternatives to attention require compromises when applied to multi-dimensional data: standard convolutions lack global receptive fields and input dependency, while recurrent models require rasterizing data such as images, volumes, and partial differential equation (PDE) into an ad-hoc $1\rm D$ scan order that violates their spatial structure. We introduce \textit{HyenaND}, a subquadratic, global, input-dependent operator that acts directly on the native geometry of multidimensional data through convolutions with implicitly parametrized global, input-dependent multi-dimensional convolutional kernels. Our CUDA implementation, \texttt{nSubQ}, fuses the FFT-convolution path to turn HyenaND's $\mathcal{O}(L \log L)$ scaling into wall-clock speedups. Across long-context genomics, computer vision, medical imaging, and PDE modeling, pure HyenaND stacks match the accuracy of strong attention baselines, while hybrid configurations tha
Hybrid LSTM-Graph Neural Framework for Robust Financial Fraud Detection and Adversarial Resilience
arXiv:2607.19350v1 Announce Type: new Abstract: Financial institutions face significant challenges in detecting sophisticated money laundering patterns, such as smurfing and layering, due to extreme data imbalance (0.13% fraud rate) and evolving adversarial evasion tactics. This paper proposes FraudShield AI, a hybrid framework that integrates Long Short-Term Memory (LSTM) networks with hand-crafted Graph Topological Features to capture both temporal sequences and structural relational context. By engineering network-centric features including PageRank Centrality, In-Degree dynamics, and a custom Flow Ratio, the system shifts the detection paradigm from isolated transaction analysis to network-level forensics. A Focal Loss objective is used to address class imbalance, and a dynamic thresholding mechanism is introduced to improve resilience against low-value smurfing attacks. Experimental evaluation on the PaySim dataset shows that the proposed hybrid model substantially outperforms Log
Running Out of Claude Code Usage Every 5 Hours? I Audited 15 Billion Tokens to Find Out Why.
The waste wasn t the model it was 7 invisible habits. Here s the audit, the numbers, and the self-enforcing skill that fixed them.Continue reading on Medium »
Your Vector Database Is Not the Product — Your Retrieval Strategy Is
Everyone is obsessed with the wrong thing.Continue reading on Medium »
Why Pi.dev Needs a Trusted Model Layer
Pi.dev gives developers control over the coding agent harness. Canopy Wave adds the SOC 2-backed model infrastructure behind it.Continue reading on Medium »
Markov Decision Processes: Making Good Decisions in an Uncertain World
Many decision-making problems look simple until uncertainty enters the picture.Continue reading on Medium »
Lego’s Donkey Kong arcade machine lets Mario jump endless barrels — Miyamoto is reportedly happy
Carl Merriam has designed some of my favorite nostalgia-inducing Lego sets, including the Lego Nintendo Game Boy and Piranha Plant. He's assisted on the incredible Lion Knights' Castle, Galaxy Explorer, and Pirates of Barracuda Bay. Now, he's helped the company create a $200 Donkey Kong arcade machine set that managed to win even Mario creator Shigeru Miyamoto's favor - or so he's told. It doesn't play quite like Donkey Kong, of course. Jumpman, the character that would be renamed Mario, can never reach the top under his own power. But like Lego's $230 pinball machine, it does contain a basic fully functional game. There's a working joyst … Read the full story at The Verge.