Two forms of AI dominate headlines today: predictive AI and generative AI. But what’s the difference between these juggernauts and how does OpenTextTM DevOps Cloud leverage them now and in the future? In this blog, we’ll highlight each AI model, shed light on their distinct capabilities, and show where they fit in OpenText’s portfolio.
Predictive AI vs. Generative AI
Predictive AI and generative AI represent two approaches within the broader field of artificial intelligence. While each exist as separate models, both exhibit the potential to help enterprises become more innovative, agile, and efficient. That being said, there’s no trickery or sorcery behind their names:
Predictive AI: Predicts things
Generative AI: Generates things
That’s a gross oversimplification, of course, but keep those in mind as we delve deeper into each model.
What is Predictive AI?
Predictive AI uses statistical algorithms and machine learning to forecast trends, behavior, patterns, and predictions from large data sources. Many of you are familiar with predictive analytics—a subset of Predictive AI that relies on historical data patterns to predict future outcomes. It aids the decision-making process, allowing enterprises to optimize quality, identify potential risks, and build data-driven strategies.
Core benefits of predictive AI include:
- Predicting future trends and reducing inaccuracy.
- Offering insights on how to reduce risks and inefficiencies.
- Finding information quickly using historical data, user behavior, and intent.
- Providing more relevant search/filtering results.
Predictive AI and OpenText DevOps Cloud
OpenText ValueEdge harnesses AI to improve flow and reduce waste. Its built-in AI reaches across the entire software delivery lifecycle to show you where to take action, enabling you to:
- Identify and drill down to root causes.
- Get insight into development velocity, project duration, and quality levels.
- Measure automation ROI to track the value of your investment.
- Get recommendations on how to remove bottlenecks and speed up time to market.
- Spot common issues and their strongest correlations.
What is Generative AI?
Generative AI models can generate realistic images, write text, create synthetic data, compose music, and more. With the latest advances in large language models (LLMs), generative AI has the capacity to revolutionize industries by producing high-quality content with minimal human effort. All the hype surrounding generative AI today is driven by its simplicity and breadth of possibilities.
Key benefits of generative AI as noted by Gartner include:
- Enabling enterprises to create new products more quickly.
- Generating, translating and verifying software code to help employees work more efficiently.
- Improving customer experiences by generating personalized content.
- Enhancing pattern recognition and identifying potential risks to enterprises more quickly.
Primary focus initiatives include customer experiences, revenue growth, and cost optimization, to name a few.
Generative AI and OpenText DevOps Cloud
OpenText is pioneering this new era of possibilities where generative AI complements human creativity to become tomorrow’s solutions. We recently announced opentext.ai and are on the verge of using large language models (LLMs) to predict delivery times, identify risks and gaps, and generate AI-generated test ideas that deliver high-quality software applications at unparalleled velocity and agility for DevOps. Stay tuned for more.
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Next-level DevOps for next-generation AI
Can AI improve how your enterprise tests, analyzes and delivers software? Get these answers and more from real, like-minded OpenText customers, industry experts, and thought leaders. Join us October 11-12 at The Venetian Resort Las Vegas for OpenText World. Explore the future of AI in DevOps at the ultimate information management conference. Register now to save your spot.