In this contributed article, Josh Reini, Developer Relations Data Scientist, TruEra, discusses how gaining the required confidence to deploy GenAI apps at scale can be challenging, and structured evaluation has gained recognition as a key requirement on the path from science experiment to customer value. Evaluation frameworks can play a critical role in this journey by allowing developers to run experiments faster and gain systematic validation for production readiness. Connecting such an evaluation framework with a scaled observability platform brings confidence in production. This article explores five practical steps to move LLM applications from early prototypes to scaled, production applications.
How Optical I/O is Enabling the Future of Generative AI: A Q&A with Ayar Labs CTO Vladimir Stojanovic
As we look at the future of AI and the challenges it faces, who better to provide insights than Vladimir Stojanovic, CTO and co-founder of Ayar Labs. In this Q&A interview, we’ve asked Vladimir a dozen questions about how Ayar Labs’ technology is enabling the growth of generative AI.
Fine-Tune Your LLMs or Face AI Failure
In this contributed artticle, Dr. Muddu Sudhakar, CEO and Co-founder of Aisera, focuses on the downsides of general-purpose Gen AI platforms and why enterprises can derive more value from a fine-tuned model approach.
Heard on the Street – 3/7/2024
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.
Hammerspace Unveils the Fastest File System in the World for Training Enterprise AI Models at Scale
Hammerspace, the company orchestrating the Next Data Cycle, unveiled the high-performance NAS architecture needed to address the requirements of broad-based enterprise AI, machine learning and deep learning (AI/ML/DL) initiatives and the widespread rise of GPU computing both on-premises and in the cloud. This new category of storage architecture – Hyperscale NAS – is built on the tenants required for large language model (LLM) training and provides the speed to efficiently power GPU clusters of any size for GenAI, rendering and enterprise high-performance computing.
Securing GenAI in the Enterprise
Opaque Systems released a new whitepaper titled “Securing GenAI in the Enterprise.” Enterprises are chomping at the bit to use GenAI to their benefit but they are stuck. Data privacy is the number one factor that stalls GenAI initiatives. Concerns about data leaks, malicious use, and ever-changing regulations loom over the exciting world of Generative AI (GenAI), specifically large language models (LLMs).
A Brief Overview of the Strengths and Weaknesses Artificial Intelligence
In this contributed article, editorial consultant Jelani Harper suggests that since there are strengths and challenges for each form of AI, prudent organizations will combine these approaches for the most effective results. Certain solutions in this space combine vector databases and applications of LLMs alongside knowledge graph environs, which are ideal for employing Graph Neural Networks and other forms of advanced machine learning.
Harnessing the Capabilities of Gen AI for Unprecedented Impact and Effortless Integration
In this contributed article, Ajay Kumar, CEO at SLK Software, discusses how generative AI provides unprecedented impact and effortless integration for the banking, insurance, and manufacturing industries. Ajay elaborates on why you need an adoption framework to successfully implement generative AI, how different categories of generative AI fit into an enterprise adoption framework, and navigating stakeholder challenges of adopting generative AI
Veritas Survey Finds Workers are Putting Businesses at Risk by Oversharing with GenAI Tools
Our friends over at Veritas just released a new survey revealing that workers are oversharing with generative AI tools, putting businesses at risk. Nearly a third (31%) of global office workers admitted to inputting potentially sensitive information into generative AI tools, such as customer details or employee financials.
Survey: 1 in 3 People are Using AI to Save their Love Lives
To find out exactly how people feel about AI influencing their dating journey, our friends over at Top10.com recently surveyed over one thousand adults about the idea. The results might surprise you!