article thumbnail

Ben Ball, IBM: Revolutionising technology operations with IBM Concert

AI News

. “There can be a gap between the unstructured amoeba of data and then what you want in AI, which is sorted, ready to go,” he acknowledged. However, IBM is actively working to bridge this gap, with IBM Concert set to evolve and incorporate tools to organise data into a format more digestible for AI engines.

article thumbnail

Generative AI vs. predictive AI: What’s the difference?

IBM Journey to AI blog

Generative AI vs. predictive AI use cases The choice to use AI hinges on various factors.

professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

What is Grounding in AI and What are the Best Techniques?

ODSC - Open Data Science

Explainable AI(XAI) Explainable AI emphasizes transparency and interpretability, enabling users to understand how AI models arrive at decisions. Techniques such as embodied AI, multimodal learning, knowledge graphs, reinforcement learning, and explainable AI are paving the way for more grounded and reliablesystems.

article thumbnail

AI’s Opaque Box Is Actually a Supply Chain

Flipboard

Understanding AI’s mysterious “opaque box” is paramount to creating explainable AI. This can be simplified by considering that AI, like all other technology, has a supply chain. How does it weigh those factors? And so you are really left unable to make a case for your client in those circumstances.”

article thumbnail

Steven Hillion, SVP of Data and AI at Astronomer – Interview Series

Unite.AI

What are some future trends in AI and data science that you are excited about, and how is Astronomer preparing for them? Explainable AI is a hugely important and fascinating area of development. For software engineers, the prompt is a function name or the docs, but for data engineers there’s also the data.

article thumbnail

Where AI is headed in the next 5 years?

Pickl AI

Robotics also witnessed advancements, with AI-powered robots becoming more capable in navigation, manipulation, and interaction with the physical world. Explainable AI and Ethical Considerations (2010s-present): As AI systems became more complex and influential, concerns about transparency, fairness, and accountability arose.

article thumbnail

Beyond Consolidated Data: Why You Need AI-Powered Business Intelligence

Mlearning.ai

InsightsAct’s AI engine works continuously in the background to surface relevant insights. Our AI technologies meticulously sift through Big Data, capturing valuable nuggets often overlooked by traditional dashboards and reports. This report not only ranks your insights but deciphers them too, courtesy of eXplainable AI.