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Step into the exciting world of Artificial Intelligence and new age technology with AiThority.com‘s latest weekly roundup! This week the stories that are making waves in the digital landscape—cover everything from revolutionary advancements in AI infrastructure to the latest trends in cloud computing and product development.
Discover the Latest Advances in AI Technology
IBM ‘s AI in Action report, based on a survey of 2,000 global companies, identifies 15% as “AI Leaders” excelling in using AI for business growth, while 85% are “Learners.” AI Leaders drive success through aggressive investments (71% vs. 19%), effective data management (61% vs. 11%), aligned leadership (72% vs. 36%), and customized AI solutions (72% vs. 33%). Two-thirds report AI boosting revenue growth by at least 25%. The survey highlights key strategies like focusing on customer experience, automation, and cybersecurity, offering a roadmap for others to adopt AI-driven success.
At the NVIDIA AI Summit, Plato Systems showcased its innovations in sensor fusion, AI agents, and digital twins, highlighting their transformative impact on manufacturing. Partnering with NVIDIA Metropolis, Plato uses Vision Language Models (VLMs) to provide self-service Vision Question Answering (VQA), enabling factories to measure and manage operations without data specialists. This technology boosts efficiency and productivity through rapid, actionable insights.
Plato’s Spatial AI platform digitizes physical operations, delivering advanced spatio-temporal analysis. Founded in 2019, Plato Systems helps manufacturers in the U.S., Japan, and Mexico optimize capacity and productivity while minimizing costs, revolutionizing digital transformation in physical industries.
Red Hat, OpenShift AI 2.15 enhances AI development with improved performance, scalability, and flexibility for hybrid cloud environments. Key updates include model lifecycle management, data drift and bias detection, efficient model fine-tuning with LoRA, and support for NVIDIA NIM and AMD GPUs. The platform offers expanded training options, advanced experiment tracking, and optimized AI model serving through vLLM and KServe Modelcars. These features help enterprises scale AI innovation, ensure model reliability, and securely manage AI/ML workloads. With its advanced capabilities, the platform supports modern AI needs while maintaining compatibility with traditional applications and cloud-native solutions.
Writer, an enterprise-focused generative AI platform, secured $200M in Series C funding at a $1.9B valuation. The round, led by Premji Invest, Radical Ventures, and ICONIQ Growth, included major investors like Salesforce Ventures, Adobe Ventures, and IBM Ventures. Writer plans to use the funds to advance AI solutions that handle complex workflows, expand quick-start applications, and enhance autonomous AI tools for industries like healthcare and finance. Trusted by Fortune 500 companies, Writer’s AI platform delivers a 9x ROI by boosting productivity and efficiency. Its proprietary Palmyra LLMs and robust tools position it as a leader in enterprise AI innovation.
Blackbird.AI, and Databricks have partnered to enhance narrative intelligence solutions, helping organizations combat narrative attacks and information manipulation. By leveraging Databricks’ Data Intelligence Platform, Blackbird.AI improves real-time narrative intelligence with robust security, scalability, and compliance. The collaboration supports regulated industries with advanced governance and AI-powered risk defense tools. This partnership aligns with the World Economic Forum’s recognition of narrative attacks as a top global risk for 2024-2025. Blackbird.AI also joins Databricks’ Partner Program, gaining access to technologies and co-marketing opportunities. Through distributor Carahsoft, government agencies can access these solutions via major procurement contracts.
Hewlett Packard Enterprise (HPE) introduces a new portfolio of HPC and AI infrastructure, featuring supercomputers and AI training solutions. The products offer air cooling or HPE’s fanless direct liquid cooling. The portfolio includes next-gen compute and accelerators from AMD, Intel, and NVIDIA, offering performance and cost options. Key products include HPE Cray Supercomputing EX systems, the EX4252 Compute Blade, and EX154n Accelerator Blade. HPE also launches the ProLiant Compute XD server family for AI model training. These solutions are designed to accelerate scientific research and AI-driven innovation, available by 2025.
ServiceNow, has launched over 150 generative AI (GenAI) innovations, enhancing its Now Platform for secure, efficient, and responsible AI use. Key updates include AI Governance tools for visibility and compliance, multilingual support for global communications, and tailored solutions for contract management, legal services, and health and safety. New capabilities like Now Assist Guardian and Now Assist Analytics improve AI control, data management, and performance insights. Additionally, Workflow Data Fabric unifies enterprise data for seamless AI integration. These innovations aim to accelerate productivity, foster trust, and streamline global AI adoption. Key features are now available, with AI Governance fully rolling out by Q1 2025.
Weekly Roundup: Expert Views on AI Trends
Tom Butler, Lenovo’s Executive Director of WW Commercial Portfolio, shares his experience leading innovative product management teams in B2B tech. He emphasizes Lenovo’s focus on creating AI-driven solutions to boost efficiency in businesses, education, and government sectors. AI PCs enhance workflows, decision-making, and security by learning user preferences and providing tailored recommendations. Tom highlights the importance of preparing employees to work alongside AI through skill development in creativity and critical thinking. Lenovo collaborates with industry leaders to co-create impactful AI solutions, integrating AI with edge computing for real-time processing and driving innovation in healthcare, automation, and sustainable technology.
Lori Schafer, CEO of Digital Wave Technology, shares insights on AI’s transformative role in retail and strategies for successful digital transformation. She emphasizes the importance of hiring top technical talent, aligning technology with customer goals, and fostering team autonomy to drive innovation. AI enhances retail through personalized customer engagement, supply chain optimization, and advertising efficiency, enabling cost savings and faster operations. Lori highlights challenges like data quality, skills shortages, and legacy systems, addressed by Digital Wave’s unified, secure data platform. She stresses Master Data Management’s role in ensuring consistent data across brands and recommends starting small, fostering digital culture, and iterating strategies for digital transformation success.
Unmissable Articles of the Week on AI
The rise of AI has transformed industries, but the rush to launch new tools often backfires. Premature releases can result in flawed outputs, confusing features, and damaged user trust. At Zeligate, we emphasize pacing to ensure our AI solutions meet user needs and build long-term value.Key challenges include rushed launches leading to inconsistent performance, overwhelming users with too many features, and unclear communication about AI’s capabilities. The solution lies in launching incrementally, prioritizing user feedback, and maintaining transparency.By focusing on quality over speed, aligning tools with user needs, and iterating thoughtfully, developers can create AI products that stand the test of time.
With AI technology advancing rapidly, businesses use conversational AI to improve efficiency and customer communication. We reviewed Google Vertex AI, IBM Watsonx Assistant, and Microsoft AI Builder to compare features and limitations.
Google Vertex AI integrates well with third-party tools, supports real-time monitoring, and offers modular scalability. However, it uses outdated language models and has limited tools, making setup challenging.
IBM Watsonx Assistant excels in customization and managing complex conversations but struggles with user-friendliness, integration flexibility, and bot training.
Microsoft AI Builder is ideal for no-code AI within the Microsoft ecosystem but lacks flexibility outside it.
Choosing a platform depends on integration, customization, and technical resources.
AI is transforming the telecom industry by boosting efficiency, improving user experiences, and enabling new revenue streams. AI workloads, like model training and real-time inference, demand high-speed, low-latency networks, pushing telecom operators to adopt 5G, edge computing, and distributed architectures. AI optimizes networks by predicting traffic, reducing latency, and ensuring seamless service. It enhances customer support through chatbots and strengthens security by detecting threats in real time. However, challenges like talent shortages, budget constraints, and managing AI traffic persist. By investing in high-performance computing, scalable infrastructure, and efficient data management, telecom providers can unlock AI’s full potential and drive innovation.