NewApp Digest
search bot

1

The developer of an AI-powered driving instruction simulator is spending $1,000 per month just to keep its demo running
AppWizard
October 11, 2026

The developer of an AI-powered driving instruction simulator is spending $1,000 per month just to keep its demo running

Artificial intelligence, particularly through large language models (LLMs), is expected to significantly impact the gaming industry by enhancing non-player characters (NPCs). However, practical implementation has been limited, with few titles like Where Winds Meet exploring this technology. A case study from the developers of Teach My Little Sister How To Drive highlights the financial challenges of integrating LLMs, as daily operational costs have exceeded ,000 due to high player interactions. The developers, Easy Fox, have taken out a bank loan to sustain the demo but are uncertain about its long-term viability. They are considering alternatives like local AI models for players with powerful GPUs, though this would limit accessibility. The game’s reliance on a premium LLM raises questions about its necessity, especially given existing design challenges such as artificial dialogue and misinterpreted commands. The full release of the game is scheduled for January next year.
silver Android smartphone
AppWizard
October 11, 2026

Android 18 UI Breakdown: Deep Material You Upgrades, Progressive Blurs, and Hardware Synergy

Google is teasing the return of the Android Dev Summit, focusing on Android 18 and its visual transformation. Key upgrades include: 1. Modern Graphics: Introduction of multi-point mesh gradients and real-time progressive blurs for enhanced visual fidelity. 2. Evolved Material You: Development of tactile glassmorphism and fluid component scaling for a three-dimensional user experience. 3. App Efficiency: Stricter performance benchmarks to minimize resource-heavy background processes and ensure smooth operation. 4. Hardware Synergy: Optimizations in Android 18 designed to complement next-generation displays, particularly for the upcoming Pixel 12.
Microsoft design boss on why Windows 11 can’t please all 1 billion users: “Everyone has different preferences”
Winsage
October 11, 2026

Microsoft design boss on why Windows 11 can’t please all 1 billion users: “Everyone has different preferences”

Microsoft is planning a significant transformation of Windows 11, focusing on modernizing its user interface and legacy features while addressing diverse user preferences. The new Windows Search capabilities allow users to perform actions like toggling settings directly from search results, which has led to discussions about the relevance of the Start menu. Diego Baca, Vice President of Design at Windows, emphasized the challenge of designing for over a billion users while aiming to improve performance and customization. The Recommended/Recent section of the Start menu has received mixed feedback, with many users expressing discontent despite Microsoft viewing it as a valuable feature intended to enhance productivity. Scenarios for its use include displaying missed meeting recordings and suggesting frequently used apps. In March 2026, Microsoft acknowledged past oversights with Windows and committed to revitalizing the operating system, aiming to modernize interfaces and integrate more WinUI-based features. The company plans to deliver 100% native applications on the platform and is focused on providing greater customization options for users.
A practical guide to cost optimization with Lakebase Postgres
Tech Optimizer
October 11, 2026

A practical guide to cost optimization with Lakebase Postgres

Lakebase is a fully managed Postgres database designed for modern application development, featuring an architecture that separates storage and compute with a serverless compute layer. This design allows for cost efficiencies through various mechanisms: 1. **Branching**: Developers can create isolated environments for development, testing, or experimentation without duplicating storage costs, as branches share the same underlying storage. 2. **Autoscaling**: Lakebase adjusts compute resources based on activity levels, allowing users to pay only for the compute they use. It can scale down during low activity and can be suspended entirely after inactivity, reducing costs to zero. 3. **Read Replicas and High Availability**: The separation of storage and compute allows for adding read replicas and high availability without incurring additional storage costs, as these instances utilize the same storage layer. 4. **Synced Tables**: Integration with the Databricks Intelligence Platform enables efficient data syncing, allowing users to sync only the necessary working set of data, which helps avoid unnecessary storage and sync costs. 5. **Sync Modes**: There are three sync modes (Snapshot, Triggered, Continuous) for transferring data from the Lakehouse to Lakebase, each with different cost implications based on data freshness requirements. 6. **Right-sizing Compute**: Users can set the initial compute range during project provisioning to avoid over-provisioning and unnecessary costs. 7. **Monitoring and Metrics**: The Lakebase Metrics dashboard provides insights into working set size and cache utilization, helping users optimize their compute sizing and performance. 8. **Point-in-Time Restore (PITR) and Snapshots**: PITR maintains history for recovery within a configurable window, while snapshots offer discrete recovery points. Both are priced lower than standard storage, making them cost-effective options for data recovery. Lakebase costs are categorized into compute, storage, and serverless pipeline compute for syncing data. Compute is measured by CU usage, while storage includes branch storage, PITR history, and snapshot storage, all tracked separately. Users can access detailed usage and cost information through system billing tables.
Query Plan Hints in PostgreSQL 19: A New Postgres Feature You Will Probably Never Need
Tech Optimizer
October 11, 2026

Query Plan Hints in PostgreSQL 19: A New Postgres Feature You Will Probably Never Need

PostgreSQL 19 features an advanced query planner that utilizes table statistics from pg_statistic, gathered during the ANALYZE process, to generate and evaluate potential query plans based on their costs. The planner assesses various configurations, especially in complex joins, to select the most efficient option. Instances of poor planning are treated as bugs and addressed promptly. To improve query performance, users are advised to refresh statistics with ANALYZE, use CREATE STATISTICS for column correlations, modify indexes, and adjust memory settings. In cases where the query cannot be altered, providing planner advice may be necessary, particularly when the planner misestimates the output of PL/pgSQL functions or other custom functions, leading to inefficient query execution.
Security Week 2639: вредоносное ПО на торрент-трекерах
TrendTechie
October 10, 2026

Security Week 2639: вредоносное ПО на торрент-трекерах

MovieReaper — это ранее неизвестное вредоносное ПО, распространяющееся на торрент-трекерах под видом фильмов и игр, которое стало причиной компрометации сотен пользователей по всему миру. Оно использует сложную схему работы, включая контрмеры против обнаружения защитным ПО. При запуске пользователь получает файл с именем, похожим на название фильма, который связывается с командным сервером для установки шелл-кода. Далее происходит подключение к блокчейну Solana для получения закодированного адреса второго командного сервера, откуда загружается еще одна вредоносная программа, обходящая защитную систему UAC в Windows. Финальный модуль предоставляет доступ к файловой системе зараженного ПК, позволяя удаленному оператору манипулировать файлами и эксфильтровать данные. Заражения были выявлены в разных странах Европы, Азии и Африки, а активность организатора атаки прослеживается с октября 2025 года. Первоначальное распространение произошло после взлома репозитория торрент-файлов itorrents[.]org.
AWS Embeds DuckDB in Aurora PostgreSQL, Enabling Direct Data Lake Queries Without ETL
Tech Optimizer
October 10, 2026

AWS Embeds DuckDB in Aurora PostgreSQL, Enabling Direct Data Lake Queries Without ETL

Amazon Web Services (AWS) has integrated the open-source analytics engine DuckDB into its Amazon Aurora PostgreSQL database, allowing users to query Apache Iceberg tables and Parquet files directly from data lakes without traditional ETL processes. This feature, announced on September 30, 2026, enables seamless access to both operational and historical data in a single SQL statement. Users can enable the aurora_analytics extension, assign an IAM role for S3 and AWS Glue access, and create external tables using standard PostgreSQL syntax. The integration supports Iceberg tables managed by AWS Glue Data Catalog, Iceberg REST Catalog-compatible external catalogs, Parquet files on S3, and S3 Tables. Performance optimizations include predicate pushdown and column pruning on the data lake side, with caching for frequently accessed data. This feature is available for Aurora PostgreSQL versions 17.11 and later, and 18.6 and later, across all commercial regions and AWS GovCloud (US), with no additional charges beyond Aurora compute and S3 request fees. In a separate development, AWS has a significant contract with AI company Anthropic, anticipating billion in cloud-related contractual obligations over several years, with approximately billion projected to be paid to Amazon from a 10-year agreement announced in April 2026. Anthropic's revenue has shown impressive growth, with first-quarter 2026 revenue reaching 0 million and second-quarter revenue at .8 billion. However, risks are present, as a significant portion of Anthropic's revenue comes from a few customers, and many larger clients lack long-term contracts. Amazon has invested .8 billion in Anthropic, with its stake valued at approximately billion as of June 2026.
The advent of first-person shooters introduced a wild frontier of unregulated video game level packs, and it ended in a lawsuit that changed copyright forever
AppWizard
October 10, 2026

The advent of first-person shooters introduced a wild frontier of unregulated video game level packs, and it ended in a lawsuit that changed copyright forever

In the 1990s, level packs emerged as a unique category of content for early first-person shooters like Duke Nukem 3D and Quake, sold as boxed products. Notable level packs included Duke Caribbean: Life's A Beach and Duke It Out in DC, which were well-received. Designer Wiederhold, recruited by Sunstorm Interactive after a LAN tournament, contributed to these packs alongside Robert Travis. The period was characterized by a lack of industry structure, allowing for creative exploration. However, some level packs, like Duke Assault, suffered from poor curation. The Nuke It series led to a legal battle over copyright infringement, with a 1998 court ruling favoring FormGen, establishing that video game mods are derivative works. This ruling curtailed unregulated FPS mission packs and clarified the distinction between official expansions and unofficial mods. Despite this, the mapping scene for iconic shooters continues to thrive today.
Supabase Announces $150M in New Funding and Turso Acquisition
Tech Optimizer
October 10, 2026

Supabase Announces $150M in New Funding and Turso Acquisition

Supabase has secured 0 million in funding led by GIC, with participation from Alphabet's CapitalG, IronArc, and SquarePeg. This follows a million Series F round four months earlier. Supabase has acquired Turso, a platform for managing databases for agentic workloads, to enhance its product development and provide liquidity for employees. The company is adding over 1 million users and 4 million databases monthly, with 70% created by AI-driven tools, reflecting a 600% year-over-year increase in databases. Turso's architecture allows for on-demand provisioning of databases in public cloud and BYOC setups. Glauber Costa, founder of Turso, will become Head of Agentic Services at Supabase. Supabase, established in 2020, supports over 13 million developers with a comprehensive backend solution.
Search