In this contributed article, Chris Peake, Chief Information Security Officer (CISO) and Senior Vice President of Security at Smartsheet, explores how the role of CISOs is evolving to address new security challenges posed by generative AI. The article underscores the importance of collaboration and adaptability to keep organizations secure as AI is expected to continue to reshape cybersecurity in 2025.
How Generative AI Can Transform the Future of Identity and Access Management
December 13, 2024 by
In this contributed article, Anirban Bhattacharya dives into how generative AI addresses persistent challenges like proper role definition, inefficient access reviews, and the limitations of static authentication methods. From AI-driven threat detection to delivering seamless, personalized user experiences, this article outlines the innovative ways generative AI is shaping the future of IAM.
AI Beyond LLMs: How LQMs Are Unlocking the Next Wave of AI Breakthroughs
December 5, 2024 by
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
December 4, 2024 by
[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.
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.
Podcast: The Batch 11/20/2024 Discussion
November 25, 2024 by
Hello friends! We hope you enjoy this new podcast featuring Andrew Ng’s “The Batch” newsletter from November 11, 2024 featuring a rousing discussion of the emerging trend of writing text specifically for large language models (LLMs).
New Release of Graphwise GraphDB Delivers Multi-Method Graph RAG to Accelerate R&D for GenAI Applications, Increase Precision, and Enable Self-Service Data
November 25, 2024 by
Graphwise, a leading Graph AI provider, announced the immediate availability of GraphDB 10.8. This release includes the next-generation Talk-to-Your-Graph capability that integrates LLMs with vector-based retrieval of relevant enterprise information and precise querying of knowledge graphs.
Why Mathematics is Essential for Data Science and Machine Learning
November 12, 2024 by
In this feature article, Daniel D. Gutierrez, insideAInews Editor-in-Chief & Resident Data Scientist, explores why mathematics is so integral to data science and machine learning, with a special focus on the areas most crucial for these disciplines, including the foundation needed to understand generative AI.
GenAI and the Role of GraphRAG in Expanding LLM Accuracy
November 7, 2024 by
In this feature article, Daniel D. Gutierrez, insideAInews Editor-in-Chief & Resident Data Scientist, discusses RAG techniques, particularly those involving graph-based knowledge representation, can significantly enhance their performance. One such innovative solution is GraphRAG, which combines the power of knowledge graphs with LLMs to boost accuracy and contextual understanding.
