AI21, a leader in AI systems for the enterprise, unveiled Jamba, the production-grade Mamba-style model – integrating Mamba Structured State Space model (SSM) technology with elements of traditional Transformer architecture. Jamba marks a significant advancement in large language model (LLM) development, offering unparalleled efficiency, throughput, and performance.
Unveiling Jamba: AI21’s Groundbreaking Hybrid SSM-Transformer Open-Source Model
April 26, 2024 by Leave a Comment
Heard on the Street – 4/25/2024
April 25, 2024 by Leave a Comment
Welcome to insideBIGDATA’s “Heard on the Street” round-up column! In this regular feature, we highlight thought-leadership commentaries from members of the big data ecosystem. Each edition covers the trends of the day with compelling perspectives that can provide important insights to give you a competitive advantage in the marketplace.
Artificial Intelligence Means Smaller Teams Doing More with Less Makes the Small Autonomous Teams Structure Even More Important
April 24, 2024 by Leave a Comment
In this contributed article, Brady Brim-DeForest, CEO of Formula.Monks, discusses how the more that we incorporate AI technology into white collar workflows in large organizations, the more that it becomes important to lean into the work structures that make humans function at their best.
Nature Communications Publishes Zapata AI Research on Generative AI for Optimization
April 23, 2024 by Leave a Comment
Zapata Computing Holdings Inc. (Nasdaq: ZPTA), the Industrial Generative AI company, announced that its foundational research on generator-enhanced optimization (GEO) has been published in the esteemed Nature Communications journal. The research, titled “Enhancing Combinatorial Optimization with Classical and Quantum Generative Models,” introduces Generator-Enhanced Optimization (GEO), a novel optimization method that leverages the power of generative modeling to suggest high-quality candidate solutions to complex optimization problems.
What AI Could, Should, and Would Do
April 22, 2024 by Leave a Comment
In this contributed article, Dr. Chirag Shah, professor in the Information School at the University of Washington, highlights how we are at a crossroads in our relationship with AI where what we choose now can have a huge impact on the future of AI and that of humanity. So the question is — how do we make good choices? Let’s start by examining two extreme visions of AI.
Video Highlights: Gemini Ultra — How to Release an AI Product for Billions of Users — with Google’s Lisa Cohen
April 20, 2024 by Leave a Comment
In this video presentation, our good friend Jon Krohn, Co-Founder and Chief Data Scientist at the machine learning company Nebula, is joined by Lisa Cohen, Google’s Director of Data Science and Engineering, to discuss the launch of Gemini Ultra. Discover the capabilities of this cutting-edge large language model and how it stands toe-to-toe with GPT-4.
What Happens When We Train AI on AI-Generated Data?
April 19, 2024 by Leave a Comment
In this contributed article, Ranjeeta Bhattacharya, senior data scientist within the AI Hub wing of BNY Mellon, points out that In the world of AI and LLMs, finding appropriate training data is the core requirement for building generative solutions. As the capabilities of Generative AI models like Chat GPT, DALL-E continues to grow, there is an increasing temptation to use their AI-generated outputs as training data for new AI systems. However, recent research has shown the dangerous effects of doing this, leading to a phenomenon called “model collapse.”
Heard on the Street – 4/18/2024
April 18, 2024 by Leave a Comment
Welcome to insideBIGDATA’s “Heard on the Street” round-up column! In this regular feature, we highlight thought-leadership commentaries from members of the big data ecosystem. Each edition covers the trends of the day with compelling perspectives that can provide important insights to give you a competitive advantage in the marketplace.
Vero AI Evaluates 10 Leading Generative AI Models Using Its Comprehensive VIOLET Framework to Gauge Responsible AI
April 17, 2024 by Leave a Comment
Vero AI, an analytical engine and scoreboard that helps enterprises fully harness the potential of advanced technology including artificial intelligence while minimizing risk, announced the findings of its inaugural “Generating Responsibility: Assessing AI Using AI” report.
Avoid these 7 Common Business-related Mistakes On Data Projects
April 16, 2024 by Leave a Comment
This article is excerpted from the book, “Winning with Data Science: A Handbook for Business Leaders,” by Howard Friedman and Akshay Swaminathan with permission from the publisher, Columbia Business School Publishing. The article covers how to avoid 7 common business-related mistakes on data projects that all stem from failures in planning, preparation and communication.
