Digitate, a leading provider of SaaS-based enterprise software for IT and business operations, released the results of its new study, “AI and Automation: Laying the Foundation for the Autonomous Enterprise” revealing that 90% of IT decision-makers plan to deploy more automation, including AI, in the next 12 months.
IT Survey Finds Enterprises Identify Automation and Generative AI as Top Business Priorities
AI Isn’t Screenwriters’ Enemy – In Fact, It Can be a Creative Superpower
In this contributed article, Ben Pines, director of content at AI21 Labs, discusses how generative AI can help screenwriters—not put them out of business, a concern that many have expressed and which is also among the reasons the Writers Guild of America went on strike.
New Report on Potential Impact of AI on Future of Work
A new special report, “Future of Work Report: AI at Work,” was just-released by LinkedIn that looks at the emerging trends within AI in the workplace and examines the potential impact of AI on the future of work.
Deci Unveils DeciLM-7B: A Leap Forward in Language Model Performance and Inference Cost Efficiency
Deci, the deep learning company harnessing AI to build AI, unveiled the latest addition to its suite of innovative generative AI models, DeciLM-7B, a 7 billion parameter large language model. Building upon the success of its predecessor DeciLM 6B, DeciLM 7B is setting new benchmarks in the large language model (LLM) space, outperforming prominent open-source models such as Llama2 7B and Mistral 7B in both accuracy and efficiency.
Get Lit: 5 Steps to Building your Organization’s Data Literacy as you Prep for AI
In this contributed article, Christine Andrukonis, Workplace Transformation Expert and founder of Notion Consulting, believes that the ultimate goal of data literacy is to provide a framework for data-driven decision-making. Nothing is stopping you from developing a learning program that’s also fun, engaging, and beneficial to employees in all parts of their lives.
The Future of AI Startups: Explainability Is Your Competitive Edge
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.
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.
IBM Launches $500 Million Enterprise AI Venture Fund
IBM (NYSE: IBM) today announced that it is launching a $500 million venture fund to invest in a range of AI companies – from early-stage to hyper-growth startups – focused on accelerating generative AI technology and research for the enterprise.
Report Highlights Policy Changes to Manage AI Displacement
The Global Partnership on Artificial Intelligence (GPAI) has just released a new report, “Generative AI, Jobs, and Policy Response,” focused on the biggest pain points regarding GenAI, specifically how it will impact the workforce.
IBM’s Groundbreaking Analog AI Chip: Ushers New Era of Efficiency and Accuracy
In this contributed article blogger Justin Varghise discusses the ground breaking advancement for AI that IBM has unveiled – a cutting edge analog AI chip that promises and has potential to redefine the landscape of deep neural networks (DNNs). This chip is 100 times more energy-efficient and up to 10 times faster than traditional digital AI chips for performing deep neural network (DNN) computations.