AI workloads Archives

AppWizard

September 7, 2026

Xbox Cloud Gaming Caps Hours: 15 for Ultimate [2026]

On September 3, 2026, Microsoft announced that Xbox Game Pass subscribers will see a shift in cloud gaming access. Starting November 2026, unlimited cloud streaming will be replaced by a tiered hour bank system: 15 hours for Ultimate, 10 for Premium, and 5 for Essential subscribers. Once a subscriber exhausts their allotted hours, they must wait for the next billing cycle or purchase additional time. This change is the most significant since the beta launch of Xbox Cloud Gaming in 2019. The announcement was made on Xbox Wire, and the new structure is reflected on Xbox’s product pages. The new tiered system introduces a scarcity model, with every paid tier now having its own cloud gaming quota. Essential subscribers, who previously had no cloud access, will now receive 5 hours per month. The pricing for the Game Pass tiers is as follows: Ultimate at .99 for 15 hours, Premium at .99 for 10 hours, and Essential at .99 for 5 hours. The free ad-supported tier remains unchanged at 5 hours per month. Microsoft's rationale for the change is based on usage data indicating that most subscribers do not heavily utilize cloud streaming, coupled with the rising costs of operating cloud gaming services. The company has stated that additional hours can be purchased once a subscriber's monthly allotment is used up, although pricing details for these add-ons have not yet been disclosed. The new hour caps will take effect in November 2026, following a shorter notice period compared to NVIDIA's GeForce NOW service, which implemented a 100-hour monthly cap earlier in 2026. The response from gaming communities has been largely negative, with concerns about the limits falling short of typical usage patterns and conflicting with the marketing of Game Pass as offering unlimited access. The introduction of hour caps could impact Game Pass's subscriber base, particularly among those who rely on cloud gaming as their primary access point. Microsoft's internal usage data will determine the extent of this impact, as the company aims to control costs without raising subscription prices.

Winsage

September 5, 2026

Nvidia & Microsoft push local AI agents on Windows

NVIDIA has enhanced the capability to run AI agents locally on its hardware in collaboration with Microsoft and software partners, coinciding with the launch of new RTX Spark Windows PCs. The installation process for local agent software has been simplified, with improved inference speeds and the introduction of NVIDIA PAIR, which distributes inference tasks across multiple PCs on a local network. Three applications benefiting from these enhancements are Hermes Agent, OpenClaw, and Perplexity Portable Computer, all designed to minimize manual configuration. Hermes Agent offers a one-click local setup for RTX and DGX systems, automatically detecting the GPU and optimizing model selection. OpenClaw simplifies local model setups for RTX GPUs with at least 24GB of VRAM, backed by an open-source community. Perplexity Portable Computer, already available on Linux, is extending support to NVIDIA RTX GPUs and Windows. NVIDIA is also improving performance in the open-source inference stack, achieving throughput increases of up to 1.9 times on GeForce RTX 5090 and up to 1.4 times on DGX Spark clusters. The PAIR software identifies compatible PCs on the same network to optimize computing resources, supporting various hardware configurations. The upcoming RTX Spark Windows PCs, set to launch in October, will include compact desktop and laptop designs featuring Blackwell GPU and Grace CPU architecture. Game publishers like Electronic Arts and Ubisoft are developing titles for these systems. Additionally, CyberLink's PhotoDirector AI PC Mode will integrate local AI processing for creative tasks, emphasizing the trend of migrating generative AI workloads from cloud to local devices. NVIDIA notes that over half of U.S. households have two or more PCs, indicating potential for maximizing computing power.

Tech Optimizer

September 4, 2026

EDB Highlights Postgres AI Growth in Regulated Enterprise Markets

EnterpriseDB (EDB) has reported advancements in the adoption of its EDB Postgres AI (EDB PG AI) platform, which integrates transactional, analytical, and AI workloads. While 95% of enterprises aspire to become their own AI and data platforms within three years, only 13% have achieved this. EDB PG AI supports existing systems and prepares enterprises for future AI capabilities. A case study highlights PAC 2000A Conad, which restructured its data infrastructure with EDB PG AI, serving over 1,600 stores and 7,000 devices. In Korea, over billion has been invested in the sovereign AI market, with organizations seeking hybrid and on-premises solutions despite challenges from fragmented data environments. Notable users of EDB PG AI include the Industrial Bank of Korea and Shinhan EZ Insurance. EDB PG AI is built on Postgres and allows enterprises to optimize data and AI capabilities with governance at the data layer.

Tech Optimizer

August 29, 2026

Overcoming the Barriers of Commercial DBs with Open Source and AI… EDB Hosts ‘PostgreSQL AI Summit’

A company's approach to artificial intelligence (AI) begins with determining the optimal structure for data storage and management, often facing challenges such as high costs of commercial databases and reliance on specific enterprise technologies. To effectively utilize AI, companies need to establish new infrastructures, including vector search capabilities, Search Augmentation Generative (RAG) systems, and data lakehouses. EDB is notable for connecting companies and technology partners that have transitioned to open-source databases. On September 3, EDB will host the 'EDB Postgres AI Summit Seoul 2026' at the Sofitel Ambassador Seoul, starting at 10:00 AM. This event is the largest PostgreSQL conference in Korea, themed 'Change the Game,' focusing on the shift from commercial databases to open-source and AI-driven frameworks, featuring real-world case studies. Approximately 300 C-level executives and IT decision-makers from various sectors are expected to attend, with participation by invitation only. The summit will include 15 sessions with customer case studies and technical presentations. Notable discussions will include IBK Industrial Bank of Korea's migration of 15 core systems to PostgreSQL, a semiconductor company's diversification of MPP databases on a DBaaS platform, and Kyobo Book Centre's database modernization strategy. Shopcast will present its development of an 'Agentic Lakehouse' integrating AI technology with a data lakehouse framework. The keynote address will be given by Kim Deok-joong, discussing organizational management strategies for integrating AI agents. The technical sessions will cover the architecture of the 'EDB Postgres AI' platform, which supports AI vector search and RAG, with live demonstrations of the analytics engine ClickHouse and LakeHouse technology for analyzing petabyte-scale data. EDB's domestic distributors and international partners will participate as sponsors. The summit aims to showcase technologies and case studies from the domestic ecosystem, addressing PostgreSQL adoption, system migration, operations, data analysis, and AI implementation. EDB manages transaction, analytics, and AI workloads using Postgres in cloud environments, serving over 1,500 global customers. Herve Timsit, EDB's Chief Revenue Officer, emphasized the event's focus on sharing tangible results and addressing the challenges of commercial databases while investing in AI infrastructure.

Winsage

August 20, 2026

Windows 365 turns five, as Microsoft pushes Cloud PCs deeper into AI

Microsoft's cloud PC platform, Windows 365, has reached its fifth anniversary since its launch in 2021. It is designed for business and enterprise customers, allowing users to stream a complete Windows desktop from the cloud. Over the past five years, Microsoft has enhanced Windows 365 by integrating business tools for IT teams, including mini PCs optimized for the service. Windows 365 now integrates with tools like Intune for managing Cloud PCs and Entra for identity and access management. Microsoft is developing Windows 365 for Agents, enabling AI agents to access managed Cloud PCs and execute tasks. Support for Microsoft Execution Containers (MXC) is also forthcoming, facilitating sandboxed environments for AI workloads.

Winsage

August 20, 2026

Microsoft brings improved Windows 11 hardware monitoring with upgraded Task Manager

Microsoft released a guide to optimize internet bandwidth usage for Windows 11 update downloads, focusing on policy settings for network efficiency. Enhancements to Task Manager include new columns for monitoring NPU (Neural Processing Unit) and NPU Engine usage, allowing users to see which applications leverage the neural processor. Additional columns for NPU Dedicated Memory and NPU Shared Memory provide insights into memory consumption for AI workloads. Neural engines in GPUs will also be visible on the Performance page. An optional Isolation column has been added to help users evaluate AI workload management. Applications optimized for NPUs will show specific designations in Task Manager, while high CPU usage with idle NPU indicates underutilization of dedicated AI hardware. Users can activate new metrics by right-clicking on column headers in Task Manager.

Tech Optimizer

July 30, 2026

EDB Says Postgres AI Tops Enterprise AI Data Platform Benchmarks

EnterpriseDB (EDB) has released benchmark results for its EDB Postgres AI (EDB PG AI), showing superior performance compared to various AI data platforms, including vector databases and managed Postgres platforms. The independent testing by McKnight Consulting Group indicated that EDB PG AI outperformed competitors in all evaluated metrics, including query speed, accuracy, and cost efficiency. Key findings include: - EDB PG AI achieved a median query latency of 50 milliseconds at 50 million vectors, making it the fastest platform tested, 80 times faster than Databricks and 21 times faster than MongoDB Atlas. - It demonstrated the highest accuracy for core vector search with a recall rate of 0.911, outperforming MongoDB by 26% and Databricks by 17%. - In a concurrent agent loop test, EDB PG AI completed tasks in 27 milliseconds, significantly faster than MongoDB Atlas (699 milliseconds) and Databricks (5.1 seconds). - EDB PG AI provided 76 times better price performance than Databricks and 34 times better than MongoDB. - The platform integrates vectors, structured data, and analytics within a single operational database, enhancing efficiency and reducing the risk of data inconsistency. The benchmark study assessed the performance of EDB PG AI against Amazon Aurora PostgreSQL, Databricks, Crunchy Bridge, MongoDB Atlas, and open source PostgreSQL, all standardized on equivalent enterprise hardware.

Tech Optimizer

July 29, 2026

EDB Postgres® AI Outperforms Vector Databases, Lakehouses, and Document Stores for Agentic AI on Speed, Accuracy, and Cost

EDB Postgres AI is a pioneering solution that integrates intelligence and data on a unified sovereign foundation, eliminating the need for ETL processes, data duplication, and separate vector stores. Independent benchmarks show that EDB Postgres AI outperforms competing platforms in speed, accuracy, and cost-effectiveness. A study by McKnight Consulting Group indicates that EDB Postgres AI excels in key performance metrics, including query latency, accuracy, cost, and data freshness, outperforming specialized vector databases and other managed Postgres platforms. EDB Postgres AI achieves median query latencies of 50 milliseconds at a scale of 50 million vectors, making it 80x faster than Databricks, 21x faster than MongoDB Atlas, and up to 2x faster than alternatives like Aurora and Crunchy Bridge. It also delivers the highest recall rates for core vector searches, surpassing competitors like MongoDB and Databricks. In tests involving concurrent retrievals, EDB Postgres AI completed a three-arm agent loop in 27 milliseconds, significantly faster than other platforms. In terms of cost efficiency, EDB Postgres AI offers 76x better price performance than Databricks, 34x better than MongoDB, and 23%–28% better than the nearest managed Postgres competitors when considering query speed. The architecture of EDB Postgres AI allows for the integration of vector, filtered, and full-text retrieval in a single query path, ensuring real-time data access and eliminating the need for separate systems.

Tech Optimizer

July 22, 2026

Google boosts AlloyDB vector search with HNSW preview

Google has introduced a preview of its columnar engine-accelerated HNSW feature for AlloyDB, enhancing vector search throughput by up to four times for users of the pgvector extension in PostgreSQL. This improvement is aimed at approximate nearest neighbor searches using HNSW across large datasets. AlloyDB utilizes a columnar engine that allows HNSW indexes to reside in memory, improving throughput and recall metrics. In benchmark tests on the GloVe 100 Angular dataset, queries per second increased by approximately 4.2x to 4.9x, with recall improving from about 0.78 to over 0.94 at a throughput of around 350 queries per second. The columnar engine's design bypasses traditional PostgreSQL buffer management bottlenecks, enhancing efficiency during graph traversal. The memory architecture is distinct from basic caching techniques, and the feature requires no changes to application code. Users must enable the columnar engine and index caching flags to utilize this feature. Benchmarks were conducted on an AlloyDB C4A machine with 16 virtual CPUs.

Winsage

July 21, 2026

Samsung’s new GAIA PC chip challenges Microsoft’s Copilot+ program — and why I can only see that as a positive for the AI PC industry

NVIDIA announced the RTX Spark at Computex 2026, prompting competition among major silicon market players, including Intel, AMD, and Qualcomm. Samsung is entering the market with its custom silicon for AI-driven PCs, named GAIA, marking its first development of PC-centric silicon since 2012. GAIA will function as a companion Neural Processing Unit (NPU) rather than a traditional System-on-Chip (SoC). It is expected to use a 4nm process and may incorporate processing-in-memory (PIM) capabilities. Lenovo China and HP USA have received samples for testing. Competitors like Snapdragon X/X2, Intel Core Ultra, and AMD Ryzen AI are integrating NPUs with at least 40 TOPS. Samsung's GAIA has not been officially confirmed, and details regarding TOPS, power consumption, and pricing are unclear. The 40 TOPS benchmark by Microsoft for integrated NPUs raises questions about how GAIA would be evaluated alongside Intel or AMD CPUs.