Many companies are rethinking if they should listen to big analyst firms when it comes to cloud computing and technology choices.

There is less trust because these firms sometimes put vendors higher in rankings only if they pay more, making the advice feel unfair.

Past predictions from analyst firms have often missed the mark, like saying almost every company would move to the cloud quickly, when in truth, many ran into problems and extra costs along the way.

This has led organizations to start looking for help elsewhere.

Today, many people believe direct chats with peers, advice from smaller groups, and learning from their own team is more helpful than only following analyst reports.

AI is providing improved, real-time advice, making it easier for companies to make decisions without relying heavily on well-known analysts.

Expensive analyst conferences also matter less, since companies want clear answers, not just sales pitches or big promises.

CoreWeave has signed a contract worth up to $14.2 billion with Meta to provide cloud computing power until the end of 2031, with an option to extend through 2032. This deal marks one of the largest AI infrastructure agreements and supports Meta’s growing AI projects.

Expanding AI Infrastructure Capacity

This agreement gives Meta access to CoreWeave’s advanced Nvidia GB300 systems, which are designed for large AI workloads such as training and running complex models. The deal follows CoreWeave’s recent multi-billion-dollar contracts with OpenAI, showing its key position in the AI cloud market.

Market Impact and Company Growth

Following the announcement, CoreWeave’s stock price rose nearly 15%, reflecting strong investor confidence. The company continues to expand its client base and infrastructure to meet rising demand for AI computing resources.

Strategic Implications for Enterprises

The scale of this contract highlights how important AI-focused cloud infrastructure is becoming for enterprises. It serves as a reminder that technology leaders need to plan for future AI capacity demands.

Overall, partnerships like this demonstrate the crucial role of specialized cloud providers in powering advanced AI capabilities for leading companies.

The National Basketball Association (NBA) has teamed up with Amazon Web Services (AWS) for a new multi-year partnership focused on advancing basketball technology. This deal will use AWS's cloud services to deliver better experiences for NBA fans, teams, and players.

What This Means

AWS will support the NBA with data analytics, machine learning, and cloud computing to improve how basketball games are covered, how players train, and how fans engage with content. Technologies like real-time data analysis and enhanced video tools will be part of this effort.

More than Just Data

The partnership aims to transform how basketball information is used. This includes creating new ways to display game stats during broadcasts and to offer personalized content to fans on their devices. It will also help teams and players by providing insights generated through advanced data processing.

A Look Ahead

With AWS's technology and the NBA's rich content, this partnership promises to bring fresh ideas to basketball entertainment. Fans can expect more immersive and interactive viewing experiences, and teams will benefit from smarter tools to improve performance.

This new collaboration highlights how sports and technology continue to merge, improving the game both on and off the court.

Operating effectively in tough communication conditions is a key need for today’s military teams. The U.S. Air Force, working with Google Public Sector and General Dynamics Information Technology (GDIT), deployed the Google Distributed Cloud (GDC) air-gapped appliance to meet this challenge. This rugged and portable solution provides a secure way to run data processing and AI workloads up to Secret classification, even when disconnected from the main network.

At the Mobility Guardian 2025 exercise in Guam, the GDC appliance proved its value by enabling real-time intelligence and AI insights without relying on constant connectivity. It supported resilient communications through a secure collaboration platform based on MatterMost, which used Google's AI models for live transcription, translation, and summarization, helping airmen work better with allies.

The appliance also integrated with GDIT’s Luna AI for quick processing of air defense data. This gave planners a near real-time view of flight paths and helped improve defense responses, including counter-Unmanned Aerial System operations. Developers in the field could build and improve applications on site using Jupyter notebooks, enhancing agility at the edge.

Beyond data processing, the Air Force used AI-powered tele-maintenance tools ingesting hundreds of technical manuals to deliver instant troubleshooting support. Computer vision analyzed imagery to identify maintenance issues and equipment status, making unstructured data actionable for mission readiness.

This partnership demonstrated how a secure, AI-driven cloud solution can work independently at the tactical edge and then sync data back to the core network when connections return. The success of this deployment supports the Department of Defense’s goal to equip smaller, dispersed teams with smart, reliable computing power wherever they operate.

IBM, AMD, and Zyphra are working together to build advanced infrastructure for artificial intelligence.

Their goal is to support new AI technologies and make AI systems faster and more efficient. They plan to combine the strengths of their technology to create better AI hardware and software platforms.

This collaboration focuses on improving how AI models are trained and run, which can help various industries by making AI more powerful and accessible.

By joining forces, they aim to push AI capabilities forward while addressing challenges like speed and power use. This work could lead to better AI tools that help businesses and researchers grow their work.

The partnership highlights the importance of teamwork between hardware and software companies to meet the fast pace of AI innovation.

Huawei is using cloud computing to shape the future of car audio systems, making them smarter and more adaptable. Their latest system features 43 speakers and advanced technology that creates a surround sound experience tailored to each passenger in the vehicle.

Cutting-Edge Audio Technology

The audio system includes independent sound zones, meaning passengers in different seats can listen to different music or audio streams without interference. This is made possible by powerful algorithms controlling speakers placed in headrests and throughout the car. Huawei claims the system can achieve 30 decibels of sound isolation between front and rear seats, giving a near-complete separation of audio energy.

Smart Sound Tuning Process

Behind the scenes, Huawei uses a high-tech lab with specialized rooms to measure and tune the audio precisely for the unique inside of a car. Cloud computing helps by processing the huge amount of sound data captured during tests, then running simulations to optimize sound for various seating positions, cabin loads, and road conditions. Real-time adjustments can also be made while driving to maintain the best sound performance.

Heavy Investment in Research and Development

Huawei has put billions into research and technology, hiring experts from top audio companies to build this system. The goal is to bring high-end audio performance, traditionally dominated by European brands, to a wider range of vehicles through advanced computing and smart design.

Challenges and Market Impact

While the technology is impressive, there are questions about how it will scale to different car models affordably and how cloud infrastructure will support updates and ongoing optimizations. If successful, this could set new standards for in-car sound quality and personalized listening experiences.

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