AiThority’s Weekly AI Update For the Week Ending 13th September: The AI World’s Biggest Headlines

Discover all about AI, technology, and innovation with our coverage of the latest and most viral stories making waves in the digital and AI industries, along with top insights from industry leaders.

From AI and Machine learning updates to cutting-edge developments in the tech world, our curated content helps you stay informed. Whether it’s a look into the future of AI or a focus on groundbreaking research, these highlights provide a comprehensive overview of the AI industry.

Explore the frontiers of AI technology, one headline at a time.  

1.Sony Research and AI Singapore Sign MOU to Conduct Collaborative Research on Large Language Models for Southeast Asian Languages  

Sony Research and AI Singapore (AISG) signed an MOU to collaborate on developing large language models (LLMs) for Southeast Asian languages, particularly Tamil. This partnership aims to address the underrepresentation of Southeast Asian languages in global LLMs, ensuring they better serve diverse populations. The collaboration will involve testing the SEA-LION model, sharing best practices, and leveraging Sony’s expertise in Indian languages. Sony Research’s Hiroaki Kitano emphasized the importance of creating AI models that reflect global linguistic diversity. AISG is excited to enhance multilingual AI technologies through this partnership.

2.Oracle Introduces Intelligent Data Lake and Generative AI-Powered Analytics for Oracle Data Intelligence Platform  

Oracle announced plans to introduce Oracle Intelligent Data Lake as a key feature of the Oracle Data Intelligence Platform, aiming for limited availability in 2025. This addition will allow organizations to integrate, manage, and analyze data from various sources within a unified platform powered by Oracle Cloud Infrastructure (OCI). Key features include an open data lake, data catalog capabilities, real-time data processing with Apache Spark and Flink, and integration with Oracle’s existing tools. The platform is designed to enhance data security, eliminate silos, and improve decision-making by providing comprehensive analytics and AI-driven insights.

3.Kyndryl Survey Reveals 86 Percent of Enterprises Are Moving Fast to Adopt AI to Accelerate Mainframe Modernization  

Kyndryl‘s second annual State of Mainframe Modernization Survey highlights 2024 as a pivotal year for AI adoption on mainframes. The survey reveals that 86% of business and IT leaders are rapidly integrating AI and generative AI to accelerate mainframe modernization, with nearly half using AI to convert critical mainframe data into actionable insights. Despite significant financial benefits and ROI from modernization, many organizations face skill shortages, particularly in AI and security. To address these challenges, 77% of companies are partnering with external providers for mainframe projects, underscoring the platform’s evolving role in hybrid IT environments.

4.Deloitte Launches Turnkey Generative AI Solution, AI Factory as a Service, Powered by NVIDIA and Oracle  

Deloitte has launched AI Factory as a Service, a comprehensive suite of Generative AI (GenAI) capabilities built on the NVIDIA AI platform, integrating with Oracle’s enterprise AI technology. This service combines Deloitte’s expertise in data science, model design, and industry knowledge with NVIDIA and Oracle’s technologies to offer customized AI solutions across industries. It enables faster AI adoption by providing tools for workload management, real-time AI processing, and data governance. Deloitte’s AI Factory as a Service is designed to help businesses modernize efficiently, leveraging the latest in AI innovations while ensuring secure and scalable deployments.

5.Lenovo Introduces New Services that Bring Flexible, Affordable and Manageable AI to Enterprises  

Lenovo has introduced a suite of services and solutions aimed at accelerating AI adoption for businesses. The new offerings include:

• Lenovo TruScale GPUaaS: Provides scalable, pay-as-you-go GPU resources for AI and HPC workloads, featuring metered NVIDIA GPUs and workload management through Lenovo’s Intelligent Computer Orchestration (LiCO) technology.

• AI-Driven Systems Management: Lenovo XClarity One integrates AI for IT operations, offering predictive failure analytics and streamlined management of Lenovo servers with a focus on security and efficiency.

• Advanced Liquid Cooling Services: Lenovo Neptune and Power and Cooling Services offer direct liquid cooling solutions to lower power consumption and support high-density computing, with a focus on sustainability and efficiency.

These solutions are designed to enhance AI capabilities, streamline IT management, and support sustainability goals for businesses.

6.OutSystems and KPMG Announce New Survey Exploring AI and the Future of Software Development  

A new survey by  OutSystems and KPMG reveals that AI is increasingly being integrated into the software development lifecycle (SDLC). Surveying 555 software executives, the report shows that AI is widely used in testing, quality assurance, and security vulnerability detection. 75% of respondents noted a 50% reduction in development time due to AI. While generative AI is set to further transform the industry, challenges remain, including data privacy concerns and integration difficulties. Despite fears of job losses, AI is expected to create new roles, shifting developers’ focus from coding to orchestrating and testing AI-generated outputs.

7.Glean Announces Over $260 Million Series E and Next-Generation Prompting as it Brings Work AI to the Enterprise  

Glean has raised over $260 million in Series E funding, doubling its valuation to $4.6 billion. This new funding, led by Altimeter and DST Global, will accelerate AI innovation and global expansion. Glean has introduced advanced prompting features to simplify complex workflows and new integrations for Zendesk and Salesforce Service Cloud. The company’s Work AI platform, built by former Google engineers, connects to over 100 SaaS applications and is now a leading solution in the enterprise AI market. Glean’s ARR has more than tripled in the past year, reflecting its strong revenue growth and customer base.

Weekly Expert Perspectives on Emerging AI Trends

AiThority Interview with Michael Berthold, CEO of KNIME  

Dive into the Highlights of the Interview  

Michael Berthold, CEO of KNIME, discusses how integrating AI and ML into business can drive efficiency but faces challenges like scaling and automation. Berthold shares his journey from an academic background to leading KNIME, emphasizing the importance of sales, marketing, and effective management. KNIME stands out with its open-source platform, offering users access to advanced analytics, seamless integration with new technologies, and scalable automation. Berthold highlights the need for centralized data governance, nimble tech stacks, and upskilling non-technical staff to ensure successful data-driven initiatives. He also predicts advancements in AI, prescriptive analytics, and beyond-big data processing.

AiThority Interview with Dave Dickson Founder of PicoNext  

Dave Dickson, Founder of PicoNext, discusses Digital Product Passports (DPPs) and their role in enhancing sustainability and transparency for brands. DPPs, soon to be required in the EU, allow consumers to access product information via QR codes. PicoNext uses Web3 technologies, including blockchains and generative AI, to help companies create and publish these DPPs securely. The platform targets Gen Z and Millennials, who value sustainability but are skeptical of greenwashing. By leveraging these technologies, PicoNext helps brands engage customers, build trust, and protect data, ensuring secure and transparent product information.

Must-Read Recommendations  

The Matrix Reloaded: How Digital Twins Are Reshaping Reality  

Must-catch Staff Article  

Digital twins are virtual replicas of physical objects, processes, or systems, created using real-time data from sources like sensors and IoT devices. They allow simulation, analysis, and optimization of their real-world counterparts. This technology is transforming fields like healthcare and urban planning, improving efficiency and reducing costs. However, it raises privacy concerns due to the vast amounts of personal data collected and potential misuse. To navigate these challenges, transparency, consent, data minimization, strong regulations, and ethical AI are crucial. The future of digital twins lies in balancing innovation with privacy protection and individual control.

How AI Empowers Us to Surf the Data Tsunami  

Every day, companies generate massive amounts of data, with unstructured data expected to reach 175 billion zettabytes by 2025. AI helps businesses manage this data by identifying useful insights, saving analysts from manually sifting through large datasets. AI-powered analytics platforms provide explainable insights, suggesting next steps and creating easy-to-understand visualizations. This technology improves personalization, predicts risks, and boosts operational efficiency by analyzing patterns and preventing issues. As businesses face increasing complexity, AI streamlines decision-making, turning data into actionable intelligence, driving innovation, and providing a competitive edge.

Synthetic Data in AI: The Future of Training Algorithms Without Real-World Data  

AI models like GPT-4 have revolutionized industries but face challenges such as “model collapse,” where AI trained on AI-generated content degrades in quality. As real-world data becomes scarce, synthetic data offers a solution. Generated by algorithms, synthetic data mimics real-world patterns without privacy risks, making it useful for AI training. It helps businesses comply with regulations, improve personalization, predict risks, and boost efficiency. Despite its benefits, synthetic data has limitations, such as potential biases and de-anonymization risks. However, it remains a vital tool for AI innovation, ensuring safe, scalable, and diverse data for model development.

Top AI Insights: Quote of the Week

“Centralized management of GenAI providers and models enhances governance and security, allowing IT to control model accessibility in alignment with enterprise policies”.- Michael Berthold, CEO of KNIME

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