标签：#an

The pale-blue Ojai vehicles will start picking up members of the public in California and Arizona today.

After several months of testing, Waymo is finally ready to invite non-employee passengers into its newest vehicle, the Zeekr RT minivan, which has been rebranded as Ojai. Waymo says it will begin offering "select riders" access in San Francisco, Los Angeles, and Phoenix, before "gradually" expanding to more riders and cities. Trips will be free […]

At least two owners have lost control of their vehicles after a critical suspension component broke. In both cases, the vehicles had been previously serviced.

Savings of up to $410 on TechCrunch Disrupt 2026 tickets end tomorrow, May 29, 11:59 p.m. PT. Register now to save and join 10,000+ tech leaders on October 13-15 in San Francisco.

General Compute is betting SambaNova will be the next breakout chipmaker.

Probabilistic Graph Neural Inference for deep-sea exploration habitat design for extreme data sparsity scenarios Introduction: The Abyssal Classroom It was 3 AM, and I was staring at a screen filled with bathymetric data from the Mariana Trench—or rather, the absence of it. The dataset I had painstakingly compiled from oceanographic surveys, autonomous underwater vehicle (AUV) logs, and satellite altimetry had 97% missing values. My initial approach—a standard deep learning model for habitat design—failed catastrophically, producing predictions that were physically impossible (like habitats floating 200 meters above the seafloor). That night, as I watched the loss curve plateau into nonsense, I realized something profound: deep-sea exploration habitat design isn't just an engineering challenge; it's an inference problem under extreme uncertainty. My learning journey into probabilistic graph neural inference began that night. While exploring how to model the sparse, irregularly sampled data from hydrothermal vent fields, I discovered that traditional neural networks treat observations as independent, ignoring the inherent relational structure of the deep-sea environment. Through studying geometric deep learning and Bayesian inference, I realized that graph neural networks (GNNs) could capture the complex dependencies between seafloor features—but only if we could handle the missing data probabilistically. This article documents what I learned from building a probabilistic graph neural inference system for deep-sea habitat design, where data sparsity isn't a bug but a feature. Technical Background: Why Graph Neural Networks for the Abyss? Deep-sea habitats—from hydrothermal vent chimneys to cold seep mounds—are not randomly distributed. They form interconnected networks governed by geological processes, fluid dynamics, and biological colonization patterns. In my research, I found that this relational structure is perfectly suited for graph neural networks. However, th

Trisha Ballakur discusses her journey from a backend software engineer to CTO and CEO, using her startup Pointz as a case study. She explains how to implement bottom-up customer discovery to find product-market fit, effectively delegate to global contractors to reduce build times, customize open-source repos like Valhalla, and apply engineering test-case models to business development. By Trisha Ballakur

It’s slimmer, lighter, and more durable. But the real upgrade is Oura’s push into AI-powered health insights and proactive monitoring.

I first realized there was an issue with Kia's flagship EV9 when I tried to unlock my car last year. The hulking three-row SUV was sitting on my driveway completely dead. The key didn't work, the app connection to the car was gone, and I was already late to an appointment. Luckily, I had prepared […]

Wherever I go, whatever I do, people point at my finger and ask, "Is that an Oura Ring?" Lots of people find they like the design, and they tell me why they're thinking about switching to a smart ring from a smartwatch. But the people who scrunch up their noses? They usually say something along […]

Forecasters say expected El Niño should temper hurricanes in Atlantic, urge preparedness.

Customer data from more than 350 hotels around the world may have been accessed as part of realistic reservation-hijacking scams.

This year, there’s been a wave of notable energy companies going public via IPO in the US. The solar and battery company Solv Energy went public in February, to the tune of $6 billion. X-energy, which is building small modular nuclear reactors, did the same in April, and its stocks surged on its first day…

Demystifying WebP to PNG: How to Secure Serverless Edge Routing Configurations Safely We have all been there. You are building a high-performance, modern web application and you decide to store all user-generated assets in modern, ultra-compressed WebP formats. It is a smart move for your Google Lighthouse scores. Then, the legacy enterprise integration request hits your inbox. A major client needs to pull these same assets dynamically, but their internal 15-year-old reporting engine only supports PNG. Suddenly, you need to configure a runtime conversion pipeline that handles complex input schemas, transforms formats on the fly, and manages edge routes without exposing your internal database claims or API secrets. Setting up secure serverless edge routing configurations to convert images on-demand can quickly turn into a security nightmare. If you do not handle incoming credential tokens correctly, you risk forwarding sensitive OAuth scopes or database keys directly to downstream image-processing worker nodes. In this guide, we will break down exactly how to architect a lightweight, secure, and fast edge routing pipeline that validates incoming image request schemas and converts WebP to PNG without leaking sensitive backend credentials. The Problem Modern edge runtimes like Cloudflare Workers, Vercel Edge Functions, or AWS CloudFront Functions are incredibly fast, but they have strict execution limits. They run on V8 isolates, meaning you do not have a full Node.js environment with unlimited memory and access to heavy C++ binaries like sharp or canvas without paying a massive cold-start penalty. If you want to support legacy clients by converting WebP to PNG on the fly, you are faced with three major challenges: Bundle Size Restrictions : Edge functions typically restrict your code size to 1MB or 2MB. Bundling heavy native libraries to parse image bytes is a recipe for deployment failures. Credential Leakage : Edge routers often intercept incoming JWT authorization

Tabla de Contenidos Objetivo Restricciones de los Errores Basados en Texto Errores Personalizados en Go Conceptos Clave Implementar e Inspeccionar Errores Casos de Uso Comunes Para no morir en el intento y consejos que no pediste Conclusiones del Tema Objetivo Aprender a diseñar tipos de errores personalizados con metadatos de negocio en Go y a propagarlos correctamente a través del flujo de la aplicación sin perder su tipo ni su información de origen. Restricciones de los Errores Basados en Texto En programas sencillos, el uso de errors.New es perfecto. Sin embargo, en aplicaciones empresariales los errores necesitan transportar datos estructurados. Por ejemplo, si una validación de entrada falla, el frontend no solo quiere saber que "hubo un error", necesita saber qué campo exacto falló (ej. email ) y qué regla se violó (ej. formato inválido ). Si solo devolvemos una cadena de texto, la capa superior de nuestra aplicación tendría que parsear el texto del error con expresiones regulares para extraer los metadatos. Esto es extremadamente ineficiente, propenso a errores de formato y acopla la lógica interna a los mensajes de texto visibles al usuario. Tipos de Errores Comunes en Go Antes de analizar cómo propagar y envolver errores, es fundamental comprender los dos patrones principales que se utilizan en Go: Sentinel Errors : Son variables globales predefinidas que representan un estado de error estático y específico. Se definen a nivel de paquete y se comparan directamente por valor. Ejemplos estándar: io.EOF , sql.ErrNoRows . Creación: Generalmente declarados con errors.New (como var ErrNotFound = errors.New("not found") ). Custom Structs (Errores estructurados personalizados): Son estructuras que implementan la interfaz error y contienen campos adicionales para transportar metadatos dinámicos del fallo en tiempo de ejecución (como códigos de estado o parámetros de entrada). Creación: Un struct personalizado que implementa el método Error() (ej. type ValidationErr

𝗚𝗶𝘁𝗛𝘂𝗯 𝗦𝘂𝘀𝗽𝗲𝗻𝗱𝗲𝗱 𝗠𝘆 𝟮‑𝗬𝗲𝗮𝗿 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿 𝗔𝗰𝗰𝗼𝘂𝗻𝘁 — 𝗛𝗲𝗿𝗲’𝘀 𝗪𝗵𝗮𝘁 𝗜 𝗟𝗲𝗮𝗿𝗻𝗲𝗱 A few days ago, something happened that genuinely shook me as a developer. My GitHub account, KelvCodes, which I had used and built on for over 2 years, got restricted unexpectedly. At first, I thought it was a mistake that would be resolved quickly. I had experienced a temporary restriction before that was lifted within a short time, so I assumed this would be similar. But this time was different. Suddenly, I lost access to years of work and history tied to my developer identity: · 60+ projects · 110+ stars · 50+ followers · client work · collaborations · repositories connected to applications and opportunities For context, GitHub was not just a coding platform for me. It had become part of my professional identity as a software engineer. My resume linked to it. Applications linked to it. Opportunities came through it. In fact, some people literally looked at my GitHub profile before deciding to work with me. That's what made this experience difficult. The Emotional Side Nobody Talks About When developers lose access to an account, people often think: "Just create another account." But when you've spent years building a reputation, consistency, commit history, projects, and credibility under one identity, it doesn't feel that simple. It feels like losing a digital portfolio you carefully built over time. And honestly, for a moment, I felt stuck. Do I wait endlessly for support? Do I pause my work? Do I rebuild everything from scratch? What I Decided After thinking about it deeply, I realized something important: I cannot pause my growth waiting for a platform decision. So I made the decision to continue building. I created a new GitHub account: 👉 https://github.com/kelvinagyareyeboah And while I still hope my old account may eventually be restored, I'm no longer allowing the situation to stop my momentum. Lessons I Learned From This Your skills matter more than one platform Platforms are important

n fan-out microservice architectures, slow-but-completing requests accumulate across services and drive p99 latency far higher than per-service metrics suggest. This article presents an adaptive hedging mechanism that uses DDSketch for real-time quantile estimation, windowed rotation to handle distribution drift, and a token-bucket budget to prevent load amplification. By Prathamesh Bhope

If you’ve been doing Android development for a while, you know the drill. You start a new project,...

The beleaguered luxury phone maker is pushing the AlphaFold, which has decent specs and comes with Vertu’s new Hermes Agent on board, to wealthy would-be buyers.

For a few glorious years, a $399 portable gadget could run almost anything you'd want to play. In 2022, the Steam Deck finally made PC gaming portable and affordable. I played through the vast majority of Elden Ring on a Steam Deck, agape that such a rich world could comfortably fit between my two hands. […]