AGI

AI implementation often stalls due to poor data quality. Snowflake’s Martin Frederik emphasizes that a robust data strategy is crucial; AI is only as good as the data it uses. Successful AI projects require clear business alignment, addressing data challenges from the start, and viewing AI as an enabler, not the end goal. Key factors include accessible, governed, and centralized data platforms and breaking down data silos. The future lies in AI agents capable of reasoning across diverse data, empowering users and freeing data scientists for strategic tasks.

A recent study reveals a significant lack of public trust in AI, hindering its widespread adoption despite government efforts. This skepticism stems from unfamiliarity and concerns about ethical considerations like data privacy and potential misuse. Trust correlates with usage, as those familiar with AI are less likely to perceive it as a risk. The report emphasizes the need for targeted communication highlighting tangible benefits, demonstrable effectiveness in public services, and robust regulations to ensure ethical and responsible development. Building trust requires transparency and a collaborative approach.

Agentic AI promises to unlock generative AI’s potential, addressing the current disconnect between adoption and bottom-line impact. AI agent orchestration is emerging as crucial, with platforms like BMC’s Control-M evolving to manage autonomous agent deployments across diverse systems. BMC envisions Control-M as an “orchestrator of orchestrators,” connecting various tools and facilitating AI agent coordination. As companies like Salesforce develop “digital labor platforms,” demand for robust orchestration layers is growing. Effective orchestration is vital for operationalizing AI, mitigating risks, and ensuring compliance, thereby maximizing business outcomes and ROI.

TechEx Europe 2025 in Amsterdam will host over 8,000 attendees and 250+ speakers across AI, cybersecurity, IoT, digital transformation, and data center expos. Focused on AI operations, particularly agentic AI, the conference addresses governance, trust, and infrastructure needs for scaling AI. Sessions feature leaders from Deutsche Bank, Mastercard, Reddit, NVIDIA, and NATO, discussing responsible scaling, monitoring frameworks, and infrastructure readiness. Attendees will gain practical insights and network with industry peers to navigate the evolving AI landscape.

Dell Technologies is focusing on helping enterprises scale AI projects into production with its AI Factory, AI Data Platform, and Data Lakehouse. Collaborations with NVIDIA and others provide infrastructure and data management for seamless AI integration. Key features include an unstructured data engine (powered by Elastic and GPU-accelerated PowerEdge servers), addressing data gravity with federated queries, and prioritizing on-premise solutions for data-sensitive industries. Dell emphasizes governance, security, and a unified ecosystem to accelerate AI adoption across various environments, including personal devices.

At Huawei Connect 2025, Huawei revealed its Ascend chip roadmap, including the 950, 960, and 970 series for AI and HPC, challenging NVIDIA’s dominance. Despite semiconductor manufacturing challenges, Huawei focuses on domestic design, proprietary tech, and open-source strategies. New Ascend chips promise performance leaps with enhanced interconnects. Huawei’s SuperPoD and SuperCluster strategy, powered by UnifiedBus 2.0 (an open protocol), aims to provide scalable, high-performance computing, expanding into general-purpose computing with Kunpeng 950 processors and TaiShan SuperPod. Huawei claims significant performance advantages over competitors.

An ISG report reveals a dynamic shift in French cybersecurity due to rising AI threats and stricter regulations. French enterprises are increasing security budgets and seeking expert guidance for modern security challenges, moving towards comprehensive, integrated solutions like SASE. Driven by compliance burdens from EU regulations like NIS2 and the AI Act affecting over 15,000 French firms, companies are adopting AI-driven threat detection and automation via managed services to address skill shortages and proactively defend against increasingly sophisticated cyberattacks.

CSI and HuLoop have partnered to integrate HuLoop’s AI-powered, no-code Work Intelligence platform with CSI’s NuPoint Core Banking System. This aims to boost efficiency for community and regional banks facing rising regulatory burdens and operational costs. The integration streamlines processes like customer onboarding and transaction processing by automating routine tasks and freeing employees for higher-value activities. The “human-in-the-loop” approach ensures AI enhances human work. Early adopters are already seeing benefits in operational efficiency and service delivery.

Mythos AI’s Advanced Pilot Assistance System (APAS) has been deployed on a CB Tankers chemical cargo ship. APAS uses a radar-first approach, fusing multi-sensor data to provide mariners with timely alerts and enhanced situational awareness. The year-long trial aims to evaluate APAS’s safety and effectiveness, adhering to international regulations. This project, building on a previous installation, aims to accelerate the adoption of AI-driven navigation and attract attention from both commercial and defense sectors. The system’s adaptability to diverse port environments is key to broader fleet deployment.

Broadcom has declared VMware Cloud Foundation (VCF) “AI native,” integrating artificial intelligence capabilities into its core. This move, announced amidst integration challenges following Broadcom’s acquisition of VMware, aims to address the rising demand for AI-driven solutions. VCF 9 will include VMware Private AI Services for on-premise AI deployment. While enhancing AI integration, Broadcom faces the challenge of avoiding disruptions to existing VMware deployments and addressing customer concerns over licensing and support. They also introduced enhancements to the Tanzu Platform and Intelligent Assist for VCF. The strategy balances AI innovation with preserving legacy infrastructure and revenue.