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.
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.
Podcast: The Batch 11/20/2024 Discussion
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
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.
Pure Storage Introduces New GenAI Pod to Accelerate AI Innovation
Pure Storage® (NYSE: PSTG), the IT pioneer that delivers the world’s most advanced data storage technology and services, today announced the expansion of its AI solutions with the new Pure Storage GenAI Pod, a full-stack solution providing turnkey designs built on the Pure Storage platform.
Why Mathematics is Essential for Data Science and Machine Learning
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
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.