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.”
Where Artificial Intelligence Is Making a Difference in Healthcare
April 18, 2024 by
In this contributed article, Rajesh Viswanathan, Chief Technology Officer for Inovalon, discusses how for the past year, AI was at the center of conversations throughout healthcare. While the potential for AI to revolutionize healthcare is clear, from care delivery to enhancing operational efficiencies and accelerating research, many organizations are still figuring out where to begin.
Heard on the Street – 4/18/2024
April 18, 2024 by
Welcome to insideAI News’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.
Video Highlights: Deep Reinforcement Learning for Maximizing Profits — with Prof. Barrett Thomas
April 13, 2024 by
In this video presentation, our good friend Jon Krohn, Co-Founder and Chief Data Scientist at the machine learning company Nebula, is joined by Dr. Barrett Thomas, an esteemed Research Professor in at the University of Iowa’s College of Business, to delve deep into Markov decision processes and how they relate to Deep Reinforcement Learning.
The Power of Data Visualization: Techniques and Best Practices
April 12, 2024 by
In this contributed article, freelance writer Ainsley Lawrence discusses how data visualization is a powerful tool that can help viewers quickly analyze and assess the status or results of an analysis. Good visualization can make even the largest and most complex datasets relatively straightforward to interpret.
Heard on the Street – 4/11/2024
April 11, 2024 by
Welcome to insideAI News’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.
How Can Companies Protect their Data from Misuse by LLMs?
April 10, 2024 by
In this contributed article, Jan Chorowski, CTO at AI-firm Pathway, highlights why LLM safety begins at the model build and input stage, rather than the output stage – and what this means in practice; how LLM models can be engineered with safety at the forefront, and the role that a structured LLM Ops model plays; and the role of data chosen to train models, and how businesses can appropriately select the right data to feed into LLMs
Opaque Systems Extends Confidential Computing to Augmented Language Model Implementations
April 8, 2024 by
In this contributed article, editorial consultant Jelani Harper discusses how Opaque Systems recently unveiled Opaque Gateway, a software offering that broadens the utility of confidential computing to include augmented prompt applications of language models. One of the chief use cases of the gateway technology is to protect the data privacy, data sovereignty, and data security of organizations’ data that frequently augments language model prompts with enterprise data sources.
Video Highlights: Gradient Boosting: XGBoost, LightGBM and CatBoost — with Kirill Eremenko
April 6, 2024 by
In this video presentation, our good friend Jon Krohn, Co-Founder and Chief Data Scientist at the machine learning company Nebula, is joined by Kirill Eremenko to walk listeners through why decision trees and random forests are fruitful for businesses, and he offers hands-on walkthroughs for the three leading gradient-boosting algorithms today: XGBoost, LightGBM, and CatBoost.
How Can AI-Powered Predictive Maintenance Boost Business Efficiency
April 5, 2024 by
In this contributed article, April Miller, senior IT and cybersecurity writer for ReHack Magazine, shows that when AI steps into predictive maintenance, it supercharges this capability. It offers more profound insights, accurate predictions and the ability to act swiftly. This blend of technology enhances operational efficiency and paves the way for a deeper exploration into how such innovations can transform the business landscape.
