[SPONSORED POST] In this sponsored article, Eric Herzog, CMO of Infinidat, suggests that as part of a transformative effort to bring one’s company into the AI-enhanced future, it’s an opportunity to leverage intelligent automation with RAG to create better, more accurate and timely responses. Further, to optimize your storage systems for this enhancement, look for industry-leading performance, 100% availability and cyber storage resilience. They make you RAG-ready.
Generative AI’s Accuracy Depends on an Enterprise Storage-driven RAG Architecture
December 4, 2024 by
New AI Service will Replace Entire Marketing Department
December 4, 2024 by
Experienced marketer is launching a new AI-based product designed to replace an entire marketing department in small and medium-sized businesses. After a ten-year career in marketing, including four years as CMO in digital agencies, Mikalai Kudlasevich came up with the idea of creating a service designed to integrate AI agents that would cope with real market challenges.
AI Has Run Into Data Shortage and Overtraining Problems
December 3, 2024 by
In this contributed article, Jason Hardy, Chief Technology Officer for Artificial Intelligence for Hitachi Vantara, explores how the growing demand for training data is testing the limits of AI development and triggering challenges like overtraining, which can lead to regression or biased outcomes.
How to Craft an AI Plan for Customer Service
December 2, 2024 by
In this contributed article, Chris Filly, Vice President of Marketing for CX automation company Callvu, discusses how AI can assist in customer service, but getting AI right requires a well-defined strategy and a commitment to continuous improvement. By taking an intelligent approach, customer service leaders can use AI to deliver great customer experiences, empower support teams, and dramatically reduce service costs.
Is AI-Powered Surveillance Contributing to the Rise of Totalitarianism?
November 30, 2024 by
In this contributed article, Aayam Bansal explores the increasing reliance on AI in surveillance systems and the profound societal implications that could lead us toward a surveillance state. This piece delves into the ethical risks of AI-powered tools like predictive policing, facial recognition, and social credit systems, while raising the question: Are we willing to trade our personal liberties for the promise of safety?
Embracing AI Devices in the Workplace: Navigating the Ethical Challenges
November 29, 2024 by
In this contributed article, Mary Giery-Smith, Senior Publications Manager for CalypsoAI, believes that by developing a culture grounded in responsible AI use, businesses can sidestep unintended pitfalls and build a workplace that values ethical integrity as much as innovation.
Small Language Models Set for High Market Impact in 2025
November 29, 2024 by
As the initial hype surrounding GenAI continues to mellow, the market impact of small language models (SLMs) is set to soar. Benefitting from faster training times, lower carbon footprint, and improved security, SLMs could prove more attractive for enterprises compared to the LLMs that have thus far dominated headlines.
Research Insights: The Complex Role of AI Disclosure in Building Trust
November 28, 2024 by
Big Valley Marketing – just put out a report on AI disclosure that is very compelling. Since ChatGPT’s release, the debate around AI’s impact on productivity, job security, and creativity has only grown. Research now shows that nearly 80% of people distrust AI, which complicates the call for transparency in AI-driven content creation—disclosure could actually reduce credibility rather than build it.
Unlocking the Power of Generative AI to Support the Software Development Lifecycle
November 27, 2024 by
In this contributed article, Keri Olson, IBM’s Vice President of Product Management, AI for Code, discusses how AI code assistants can help accelerate the software development lifecycle (SDLC), enhance productivity, and improve code quality through generative AI.
Embrace Innovation While Reducing Risk: The Three Steps to AI-grade Data at Scale
November 26, 2024 by
In this contributed article, Kunju Kashalikar, Senior Director of Product Management at Pentaho, discusses how to dream big without the risk: three steps to AI-grade data. The industry adage of ‘garbage-in-garbage-out’ has never been more applicable than now. Clean, accurate data is the key to winning the AI race – but leaving the starting blocks is the challenge for most. Winning the race means working with data that’s match fit for AI.
