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AI governance: Analysing emerging global regulations

AI News

In 2021, they introduced regulation on recommendation algorithms, which [had] increased their capabilities in digital advertising. It was followed by regulations on deep synthesis models or, in common terms, deepfakes and content generation in 2022, he said.

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The High Cost of Dirty Data in AI Development

Unite.AI

It’s no secret that there is a modern-day gold rush going on in AI development. According to the 2024 Work Trend Index by Microsoft and Linkedin, over 40% of business leaders anticipate completely redesigning their business processes from the ground up using artificial intelligence (AI) within the next few years.

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Minimize generative AI hallucinations with Amazon Bedrock Automated Reasoning checks

Flipboard

Foundation models (FMs) and generative AI are transforming enterprise operations across industries. McKinsey & Companys recent research estimates generative AI could contribute up to $4.4 McKinsey & Companys recent research estimates generative AI could contribute up to $4.4

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Generative AI use cases for the enterprise

IBM Journey to AI blog

Generative AI ( artificial intelligence ) promises a similar leap in productivity and the emergence of new modes of working and creating. Generative AI represents a significant advancement in deep learning and AI development, with some suggesting it’s a move towards developing “ strong AI.”

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How Does AI Use Impact Critical Thinking?

Unite.AI

Survey respondents reported decreased effort when using AI technology compared to relying on their own minds. Microsoft reported that in the majority of instances, the respondents felt that they used much less effort or less effort when using generative AI. Many algorithms cannot think critically, reason or understand context.

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DeepMind Introduces JEST Algorithm: Making AI Model Training Faster, Cheaper, Greener

Unite.AI

Generative AI is making incredible strides, transforming areas like medicine, education, finance, art, sports, etc. This progress mainly comes from AI's improved ability to learn from larger datasets and build more complex models with billions of parameters. Financial Costs: Training generative AI models is a costly endeavour.

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Self-Evolving AI: Are We Entering the Era of AI That Builds Itself?

Unite.AI

In the 1960s, researchers developed adaptive techniques like genetic algorithms. These algorithms replicated natural evolutionary process, enabling solutions to improve over time. With advancements in computing and data access, self-evolving AI progressed rapidly.