2025-03-17 One-Minute Post
DeCloak Intelligences and NTUH’s Hsin-Chu Branch are set to showcase their AI privacy healthcare system at NVIDIA GTC 2025, focusing on enhancing patient safety with privacy-preserving AI. Meanwhile, ChatGPT highlights the silent AI revolution in workplaces and the concerns of AI bias, while Google unveils Gemma 3 AI models with multimodal capabilities, addressing the ongoing issues of bias and accuracy in AI-generated outputs. AI is also revolutionizing employee recognition, making it more inclusive by removing bias and basing recognition on data-driven performance.
Articles we found interesting:
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1. At NVIDIA GTC 2025, DeCloak Intelligences and NTUH's Hsin-Chu Branch will exhibit their … link Highlight: A featured presentation will be "Enhance Patient Safety With Privacy-Preserving AI: Multimodal DNN and VLM for Event Detection in Healthcare.".
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2. At NVIDIA GTC 2025, DeCloak Intelligences and NTUH's Hsin-Chu Branch will exhibit their … link Highlight: PRNewswire/ – DeCloak Intelligences, a subsidiary of Etron Technology (TPEx: 5351), is set to showcase its groundbreaking 'AI-aided Privacy Agent …
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3. At NVIDIA GTC 2025, DeCloak Intelligences and NTUH's Hsin-Chu Branch will exhibit their … link Highlight: … AI privacy healthcare system. March 16, 2025 12:00 PM. A featured presentation will be "Enhance Patient Safety With Privacy-Preserving AI …
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4. ChatGPT and Workplace Hypocrisy: The Silent AI Revolution No One Talks About link Highlight: … AI innovation leadershipAI integration in modern workplacesAI job displacement concernsAI productivity in businessAI technology biasAI …
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5. Elevating Employee Experience: Transforming Recognition with AI - People Matters link Highlight: AI is revolutionizing employee recognition making it more inclusive … By removing bias and basing recognition on data-driven performance …
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6. Google Unveils Gemma 3 AI Models with Multimodal Capabilities - Bizz Buzz link Highlight: - Bias and Accuracy Issues: While improvements have been made, AI-generated outputs may still reflect biases or inaccuracies present in training data.
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