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AI and Financial Crime Prevention: Why Banks Need a Balanced Approach

Unite.AI

AI systems, especially deep learning models, can be difficult to interpret. To ensure accountability while adopting AI, banks need careful planning, thorough testing, specialized compliance frameworks and human oversight. A full replacement of rules-based systems with AI could leave blind spots in AFC monitoring.

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ImandraX: A Breakthrough in Neurosymbolic AI Reasoning and Automated Logical Verification

Unite.AI

The company has built a cloud-scale automated reasoning system, enabling organizations to harness mathematical logic for AI reasoning. With a strong emphasis on developing trustworthy and explainable AI , Imandras technology is relied upon by researchers, corporations, and government agencies worldwide.

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

IBM Journey to AI blog

Generative AI (gen AI) is artificial intelligence that responds to a user’s prompt or request with generated original content, such as audio, images, software code, text or video. Gen AI models are trained on massive volumes of raw data. What is predictive AI?

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Enhancing AI Transparency and Trust with Composite AI

Unite.AI

The adoption of Artificial Intelligence (AI) has increased rapidly across domains such as healthcare, finance, and legal systems. However, this surge in AI usage has raised concerns about transparency and accountability. Composite AI is a cutting-edge approach to holistically tackling complex business problems.

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How to responsibly scale business-ready generative AI

IBM Journey to AI blog

Generative AI is being analyzed for a variety of use cases including marketing, customer service, retail and education. ChatGPT was the first but today there are many competitors ChatGPT uses a deep learning architecture call the Transformer and represents a significant advancement in the field of NLP.

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Generative AI and Robotics: Are We on the Brink of a Breakthrough?

Unite.AI

GANs gave rise to DALL-E , an AI model that generates images based on textual descriptions. On the other hand, VAEs are used primarily in unsupervised learning. Looking further ahead, one critical area of focus is Explainable AI , which aims to make AI decisions transparent and understandable.

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Understanding Explainable AI And Interpretable AI

Marktechpost

To put it briefly, interpretable AI models can be easily understood by humans by only looking at their model summaries and parameters without the aid of any additional tools or approaches. In other words, it is safe to say that an IAI model provides its own explanation. Situations of this nature can be interpreted.