Explainable AI, meaning interpretable machine learning, is at the peak of inflated expectations. Ontologies, a part of symbolic AI which is explainable, is in the trough of disillusionment ...

CoT models, like OpenAI’s o1 CoT model, are huge breakthroughs in the field of machine learning. However, making such models better and meaningfully integrating them into stagnant industries is ...

Dr. Adi Hod. Cofounder & CEO at Velotix. Driven by a passion for data and cybernetic AI. Entrepreneur, professor, leader & innovator. AI is fast becoming embedded in industries, economies and ...

As the capabilities of artificial intelligence (AI) evolve, they push the boundaries of human understanding. Instead of transparent, explainable mechanisms, many AI applications are “black boxes,” ...

This is where explainable artificial intelligence (XAI) comes in. XAI is an emerging field that helps interpret complicated machine learning models, providing an entry point to new applications. XAI ...

However, this means that most machine learning models built today fail to make it into production. Fewer than 10% of companies using AI have fully put it into operation within their business ...

The 10 hottest data science and machine learning tools include MLflow 3.0, PyTorch, Snowflake Data Science Agent and ...

The purpose of the challenge was to canvas the ATEC workforce for opportunities to solve real-world problems with AI and machine learning solutions that had a high potential return on investment.

Advances in artificial intelligence (AI) are revolutionizing the field of anomaly detection. The result is improved accuracy, faster detection, reduced false positives, scalability, and cost ...

As increasing use cases of AI in insurance add urgency to the need for explainability and transparency, experts are recommending "explainable AI" best practices to follow and key challenges to ...

The “black box” metaphor stems from the notion that AI systems and machine learning models operate in a manner concealed from human understanding. AI’s black box problem: Challenges and ...