IBM Journey to AI blog

OCTOBER 16, 2023

It’s essential for an enterprise to work with responsible, transparent and explainable AI, which can be challenging to come by in these early days of the technology. Generative AI chatbots have been known to insult customers and make up facts. But how trustworthy is that training data?

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Towards AI

APRIL 2, 2024

On the other hand, new developments in techniques such as model merging (see story below from Sakana) can provide a new avenue for affordable development and improvement of open-source models. Hence, we are focused on making AI more accessible and releasing AI learning materials and courses! Why should you care?

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NVIDIA

MARCH 1, 2024

Trustworthy AI initiatives recognize the real-world effects that AI can have on people and society, and aim to channel that power responsibly for positive change. What Is Trustworthy AI? Trustworthy AI is an approach to AI development that prioritizes safety and transparency for those who interact with it.

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Unite.AI

JANUARY 12, 2024

Competitions also continue heating up between companies like Google, Meta, Anthropic and Cohere vying to push boundaries in responsible AI development. The Evolution of AI Research As capabilities have grown, research trends and priorities have also shifted, often corresponding with technological milestones.

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ODSC - Open Data Science

SEPTEMBER 26, 2024

Using AI to Detect Anomalies in Robotics at the Edge Integrating AI-driven anomaly detection for edge robotics can transform countless industries by enhancing operational efficiency and improving safety. Where do explainable AI models come into play? Here’s everything that you can watch on-demand whenever you like!

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ODSC - Open Data Science

FEBRUARY 18, 2025

FinanceAlgorithmic trading and fraud detection powered by autonomous AI decision-making. Customer ServiceAI chatbots provide advanced customer support with contextual understanding. ManufacturingRobotic automation with AI-powered quality control and predictive maintenance.

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Pickl AI

APRIL 8, 2024

Overhyped Expectations The media and tech companies often portray AI as a revolutionary technology capable of solving all our problems. This can lead to unrealistic expectations and disappointment when AI fails to live up to the hype. Example In 2016, a chatbot developed by Microsoft called Tay was launched on Twitter.

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The MLOps Blog

FEBRUARY 27, 2025

Picture this: youve spent months fine-tuning an AI-powered chatbot to provide mental health support. After months of development, you launch it, confident it will make therapy more accessible for those in need. How to integrate transparency, accountability, and explainability? Lets get into it!

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Pickl AI

JANUARY 13, 2025

It simplifies complex AI topics like clustering , dimensionality , and regression , providing practical examples and numeric calculations to enhance understanding. Key Features: Explains AI algorithms like clustering and regression. Key Features: Focuses on ethical AI development. Minimal technical jargon.

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IBM Journey to AI blog

SEPTEMBER 3, 2024

These systems inadvertently learn biases that might be present in the training data and exhibited in the machine learning (ML) algorithms and deep learning models that underpin AI development. Those learned biases might be perpetuated during the deployment of AI, resulting in skewed outcomes.

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AI Weekly

AUGUST 22, 2024

wired.com A new ‘AI scientist’ can write science papers without any human input. theconversation.com AI Predicts Earthquakes With Unprecedented Accuracy Researchers at the University of Texas have developed an AI that predicted 70% of earthquakes during a trial in China, indicating potential for future quake risk mitigation.

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IBM Journey to AI blog

FEBRUARY 9, 2024

They make AI more explainable: the larger the model, the more difficult it is to pinpoint how and where it makes important decisions. Explainable AI is essential to understanding, improving and trusting the output of AI systems. “2023 was the year of being able to chat with an AI.

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