In this contributed article, Dr. Stefan Leichenauer, Vice President of Engineering and lead scientist at SandboxAQ, discusses the profound evolution that is now emerging: Large Quantitative Models (LQMs), designed to tackle complex real-world problems in areas such as healthcare, climate science, and materials design, are set to revolutionize industries and unlock new AI-powered breakthroughs for some of the world’s greatest challenges.
Generative AI’s Accuracy Depends on an Enterprise Storage-driven RAG Architecture
[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.
AI Has Run Into Data Shortage and Overtraining Problems
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
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?
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
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
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.
Unlocking the Power of Generative AI to Support the Software Development Lifecycle
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
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.
Kinesis Network Launches Serverless Feature to Solve Critical Computing Power Shortage for AI-Infrastructure
Kinesis Network, a global compute optimization platform, announced a new serverless feature enabling enterprises to run workloads across a dynamic, multi-cloud environment.