In this contributed article, Lucas Bonatto, Director of Engineering for AI and ML at Semantix, discusses how generative AI applications extend from physiotherapists using text-to-video tools demonstrating patient recovery exercises to coding Q&As that decrease network language complexity. These pre-trained ML solutions, which previously required highly skilled teams to train, close the gap between tech giants and digital novices—but that’s if they understand the fine print.
The Future of AI Startups: Explainability Is Your Competitive Edge
New IDC Survey: 75% Expect to Gain Value from AI Decision Making
IDC estimates that organizations worldwide will spend $290 billion on data management, analytics, and AI technology – but is there enough return on the investment? In this feature article we share findings from a new IDC survey looking at the ROI in AI-powered decision making –- known in the market as decision intelligence. IDC contrasts leaders operationalizing and gaining outcomes through better, faster decisions, and challenges that exist. Enterprises already tapping decision intelligence are improving business metrics up to 20%. The survey also found 75% expect to gain significant benefits through future decision intelligence initiatives.
C-Suite Predicts 2024 to be Watershed Year for Financial Impact of Generative AI in Icertis Survey
Icertis, the contract intelligence company that pushes the boundaries of what’s possible with contract lifecycle management (CLM), released its inaugural AI impact report titled The Future of Generative AI: C-Suite Perspectives for 2024 and Beyond. 500 senior executives at businesses across the U.S. and U.K. shared their perspectives on how AI will transform the workforce, data privacy, the competitive landscape, and more.
NVIDIA Supercharges Hopper, the World’s Leading AI Computing Platform
NVIDIA today announced it has supercharged the world’s leading AI computing platform with the introduction of the NVIDIA HGX™ H200. Based on NVIDIA Hopper™ architecture, the platform features the NVIDIA H200 Tensor Core GPU with advanced memory to handle massive amounts of data for generative AI and high performance computing workloads.
Survey: Generative AI Shaking Up Digital Health Investors’ Funding Strategies and Industry Outlooks
Digital health investors say generative AI, oncology care and the challenges posed by clinician shortages are transforming their startup funding strategies and investment outlooks for the healthcare industry, according to the results of an online survey from GSR Ventures. Startup company valuation expectations among backers, however, are significantly lower than in 2022.
2023 ML Pulse Report: The Latest Trends and Challenges in Machine Learning
Our friends over at Sama recently published a comprehensive report on the potential and challenges of AI as reported by Machine Learning professionals.
Why Enterprises Should Run, Not Walk, to Combine AI & AR
In this contributed article, Kelly Peng, CEO and chief technology officer of Kura, discusses how marriage of AI and AR can combine to give us a world where we can do everything from communicate across language barriers to collaborate with remote employees like never before.
Video Highlights: PyTorch 2.0 on the ROCm Platform
From the recent PyTorch Conference we present a Lightning Talk: PyTorch 2.0 on the ROCm Platform by Douglas Lehr, Principal Engineer at AMD. Douglas talks about the current state of PyTorch on the ROCm platform including efforts to achieve day 0 support for Triton on Pytorch 2.0 as well as performance improvements, efforts with Huggingface, and other areas.
Heard on the Street – 11/2/2023
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.
Kickstart Your Business to the Next Level with AI Inferencing
The need to accelerate AI initiatives is real and widespread across all industries. The ability to integrate and deploy AI inferencing with pre-trained models can reduce development time with scalable secure solutions that would revolutionize how easily you can capture, store, analyze, and use data to be more competitive.