AiThority’s Weekly Overview: Top AI Insights, Trends and Must-reads for 10th to 14th March 2025
Stay abreast of the latest Artificial Intelligence developments with AiThority.com’s weekly roundup. From machine learning and language models to AI bots, we cover the trending updates shaping the digital and IT industries. This week’s roundup, brings you valuable insights from tech leaders, executives, and decision-makers. Get a comprehensive look at the key AI stories making waves across the industry.
Uncover What’s New in AI
#1 Sharon AI to Forge Australia’s AI Future with Groundbreaking GPUaaS Supercomputer Featuring NVIDIA Accelerated Computing and Software
Sharon AI, Inc. is deploying a high-performance AI supercomputer in Australia using NVIDIA tech. The Sharon AI Supercluster, hosted at NEXTDC’s Tier IV data center, will provide scalable AI compute power for researchers and businesses. Featuring NVIDIA H200 GPUs and Quantum-2 InfiniBand networking, it ensures high efficiency and seamless scalability. Integrated with VAST Data and Lenovo infrastructure, the system supports AI training, large language models, and VFX rendering. Sharon AI’s cloud platform allows users to access powerful GPU resources on demand, reinforcing its role as a leader in AI innovation and positioning Australia as a key player in AI development.
#2 InterVision Systems Advances AI Capabilities With Cisco Specialization Achievement
InterVision, a top IT managed services provider, has earned the Cisco AI-Ready Infrastructure Specialization in the U.S. This recognition highlights its expertise in deploying AI infrastructure solutions for enterprises. As AI reshapes industries, InterVision helps businesses build scalable, secure, and high-performance AI environments. The company’s specialization ensures clients get cutting-edge networking, computing, and data security for AI workloads. Listed in Cisco’s Partner Locator, InterVision is now more accessible to organizations seeking AI solutions. With 30 years of experience, it continues to drive innovation, security, and compliance across various sectors.
#3 Pliops Announces Collaboration with vLLM Production Stack to Enhance LLM Inference Performance
Pliops has partnered with the vLLM Production Stack from LMCache Lab at the University of Chicago to enhance large language model (LLM) inference performance. This collaboration, announced ahead of GTC 2025, integrates Pliops’ KV storage technology with vLLM’s scalable AI framework. Key benefits include faster inference, efficient cache management, and cost-effective GPU compute applications. The partnership aims to improve AI task agents, optimize storage, and boost scalability. Future developments will refine integration, enhance caching, and streamline AI operations. This initiative sets a new benchmark for AI efficiency and performance.
#4 UiPath Acquires Peak to Launch Vertically Specialized Agents within its Agentic Automation Platform
UiPath, has acquired Peak, a UK-based AI company specializing in inventory and pricing optimization. This acquisition strengthens UiPath’s AI-driven automation capabilities, enabling businesses to streamline decision-making without large in-house tech teams. Peak’s AI platform integrates with UiPath to enhance automation, optimize industry-specific processes, and expand AI adoption in retail and manufacturing. The partnership will drive market growth, improve decision intelligence, and introduce AI-powered pricing and inventory solutions. Customers will benefit from increased efficiency and revenue, as demonstrated by UiPath and Peak’s successful automation of Heidelberg Materials’ quoting process.
#5 ServiceNow to Extend Leading Agentic AI to Every Employee for Every Corner of the Business With Acquisition of Moveworks
ServiceNow, has announced its acquisition of Moveworks for $2.85 billion, aiming to enhance AI-driven automation and enterprise search capabilities. The integration will combine ServiceNow’s agentic AI and automation with Moveworks’ AI assistant to improve employee experiences and productivity. Moveworks’ technology, already used by Fortune 500 companies, will enable AI-powered self-service, streamlined workflows, and automation across HR, CRM, finance, and IT. The acquisition strengthens ServiceNow’s AI strategy, positioning it as a leader in enterprise AI transformation. The transaction is expected to close in the second half of 2025, pending regulatory approval.
#6 Forcepoint to Acquire Getvisibility, Expanding AI-Driven Data Security and Risk Visibility
Forcepoint has announced its acquisition of Getvisibility to enhance AI-powered data security. The integration will strengthen Forcepoint’s Data Security Everywhere platform by incorporating Getvisibility’s Data Security Posture Management (DSPM) and Data Detection and Response (DDR) capabilities. This move enables proactive risk visibility, real-time threat mitigation, and adaptive security controls across enterprise environments. The acquisition builds on a multi-year partnership, helping businesses secure sensitive data, ensure compliance, and reduce cyber threats. The deal reinforces Forcepoint’s leadership in data protection, with further integration details expected later this year.
#7 Bria Secures $40Million in Series Billion to Drive Fair Gen AI Usage for Enterprises
Bria an enterprise-focused visual generative AI platform built on 100% licensed data, has secured $40 million in Series B funding, raising its total capital to $65 million. Led by Red Dot Capital, the investment will scale Bria’s AI-driven content creation platform, expanding its patented attribution engine beyond images to music, video, and text. Bria’s technology ensures compliance by compensating data owners, addressing IP concerns in generative AI. With integrations into major cloud platforms and design tools, Bria is redefining responsible AI-driven content generation for businesses while maintaining transparency and creator rights.
Weekly Roundup: Expert Views on AI Trends
AiThority Interview With Krish Venkataraman, President of Dataiku
AIThority’s Weekly Voice: From the Expert
Krish Venkataraman, President of Dataiku, discusses his transition to AI, highlighting the industry’s shift from big data to AI-driven solutions. He emphasizes the importance of AI democratization, advocating for broader access across organizations, from data scientists to frontline workers. Dataiku’s platform integrates both traditional AI and GenAI, offering tools that cater to various user needs. AI’s impact on decision-making is particularly transformative in sectors like finance, healthcare, and manufacturing. Venkataraman also underscores the importance of ethical AI, addressing AI bias through robust governance and compliance. Looking ahead, Dataiku is focusing on empowering businesses with multi-agent solutions and governance.
Don’t Miss These Must-Read Articles of the Week
A New AI Search Engine Is Challenging Perplexity. And It’s Decentralized
AI-powered search has become a daily necessity, handling everything from simple queries to complex research. Google developed the FRAMES evaluation dataset to test Retrieval-Augmented Generation (RAG) systems, measuring how well search engines interpret queries, find relevant data, and synthesize accurate answers. AI-driven search engines achieved up to 70% accuracy when given full access to sources. However, Sentient Chat, an open-source, decentralized AI, outperformed traditional models. Powered by community contributions, it scales efficiently and remains censorship-resistant. With over 1M users on its waitlist, its core, Dobby, is the world’s first community-owned AI model, setting new standards in AI search.
The High-Speed Evolution of Fraud: Why Only Advanced Tech Can Keep Up
Identity fraud has become a global crisis, with cases surging due to sophisticated cybercrime tactics. In 2024, the FTC reported 1.4 million identity theft cases, while FBI estimates show cybercrime losses hitting $10.2 billion. AI-driven fraud, including deepfakes, is making identity theft harder to detect. Attackers use presentation and injection techniques to bypass security, requiring advanced fraud prevention. Solutions include AI-powered fraud detection, device integrity checks, multi-factor authentication, and stricter regulations. A holistic approach—combining technology, compliance, and collaboration—is essential to staying ahead of evolving threats and securing digital identities against increasingly industrialized fraud operations.
AI-Driven Analysis of Dark Web Data for Proactive Fraud Prevention
The dark web, a hidden part of the internet, is a hub for illegal activities such as identity theft, cybercrime, and the sale of stolen data. As cybercriminals evolve, traditional fraud prevention methods struggle to keep up. To address this, organizations are turning to AI-driven tools that analyze dark web data to detect, predict, and prevent fraud. AI-powered tools can scan massive amounts of encrypted data, identify patterns, and flag potential threats in real time. By automating data collection, threat assessment, and fraud detection, AI enhances security, reduces financial losses, and protects consumers from identity theft.
AI Quote of the Week Featuring Rodion Myronov, AVP of Technology at SoftServe
Without a solid data foundation and single source of truth, poor decisions are unavoidable. The consequences can be dire.
Consider a company seeking to reduce its carbon footprint and conform with regulations. Without a platform to unify raw data from disparate sources, management will struggle to understand where the greatest reduction potential lies. On top of that, the company might also end up paying big fines and needing to write off the sunk costs incurred through ineffective reduction strategies. The price tag could be enormous.
On the other hand, a simple dashboard with reliable analytics will drive cost-effective efficiency strategies while also streamlining regulatory reporting. But they have to be willing to do it the right way.
Part of this misalignment goes back to the focus of leadership; focusing on the tool or the latest market trend instead of focusing on the task at hand – which is the opportunity or solution the company pursues, or the issue it tries to solve – can also lead to flawed decision-making, like relying on false data to get ahead. This ironically puts them behind when the intended result never comes to fruition.
The question is not whether companies should be investing in data-driven decision-making. It is how long those that don’t – or do it incorrectly – will stay afloat. –Rodion Myronov, AVP of Technology at SoftServe
Comments are closed.