AI Weekly

MARCH 20, 2025

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Robotics 147

Robotics Artificial Intelligence Artificial Intelligence Explainability 147

AI News

MARCH 7, 2024

Indeed, as Anthropic prompt engineer Alex Albert pointed out, during the testing phase of Claude 3 Opus, the most potent LLM (large language model) variant, the model exhibited signs of awareness that it was being evaluated. In addition, editorial guidance on AI has been updated to note that ‘all AI usage has active human oversight.’

Prompt Engineering 338

Prompt Engineering Prompt Engineer OpenAI Large Language Models 338

AI News

MAY 29, 2024

. “It’s using AI to figure out actually how your application works, and then provides recommendations about how to make it better,” Ball said. Upcoming AI opportunities According to Ball, a current opportunity is organising the unstructured data that feeds into AI models.

Explainability 329

Explainability Automation Big Data AI Engineer 329

Marktechpost

AUGUST 24, 2024

EXplainable AI (XAI) has become a critical research domain since AI systems have progressed to being deployed in essential sectors such as health, finance, and criminal justice. The intrinsic complexity—the so-called “black boxes”—given by AI models makes research in the field of XAI difficult.

Python 109

Python Explainability Explainable AI AI 109

Marktechpost

AUGUST 13, 2024

However, the challenge lies in integrating and explaining multimodal data from various sources, such as sensors and images. AI models are often sensitive to small changes, necessitating a focus on trustworthy AI that emphasizes explainability and robustness. If you like our work, you will love our newsletter.

Robotics 107

Robotics Explainability Explainable AI Categorization 107

IBM Journey to AI blog

JULY 17, 2023

Generative AI has the potential to significantly disrupt customer care, leveraging large language models (LLMs) and deep learning techniques designed to understand complex inquiries and offer to generate more human-like conversational responses. Watsonx.data allows scaling of AI workloads using customer data. Watsonx.ai

Generative AI 171

Generative AI Auto-complete Automation AI 171

Marktechpost

JULY 22, 2024

Current AV models focus mainly on binary classification, which often lacks transparency. This lack of explainability is a gap in academic interest and a practical concern. Analyzing the decision-making process of AI models is essential for building trust and reliability, particularly in identifying and addressing hidden biases.

Explainability 104

Explainability BERT Large Language Models Deep Learning 104