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Beyond the Hype: Unveiling the Real Impact of Generative AI in Drug Discovery

Unite.AI

Since Insilico Medicine developed a drug for idiopathic pulmonary fibrosis (IPF) using generative AI, there's been a growing excitement about how this technology could change drug discovery. Traditional methods are slow and expensive , so the idea that AI could speed things up has caught the attention of the pharmaceutical industry.

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

Unite.AI

In the US alone, generative AI is expected to accelerate fraud losses to an annual growth rate of 32%, reaching US$40 billion by 2027, according to a recent report by Deloitte. Perhaps, then, the response from banks should be to arm themselves with even better tools, harnessing AI across financial crime prevention.

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How Quality Data Fuels Superior Model Performance

Unite.AI

Its not a choice between better data or better models. The future of AI demands both, but it starts with the data. Why Data Quality Matters More Than Ever According to one survey, 48% of businesses use big data , but a much lower number manage to use it successfully. Why is this the case?

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Understanding Generative AI Through Critical Thinking and Implementation

ODSC - Open Data Science

The discussion covered diverse and valuable insights on the application of generative AI in business, emphasizing the importance of critical thinking to harness its full potential. Yves Mulkers pointed out that, despite AI’s advancements, critical thinking and creativity remain at the forefront of AI implementation.

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Considerations for addressing the core dimensions of responsible AI for Amazon Bedrock applications

AWS Machine Learning Blog

The rapid advancement of generative AI promises transformative innovation, yet it also presents significant challenges. Concerns about legal implications, accuracy of AI-generated outputs, data privacy, and broader societal impacts have underscored the importance of responsible AI development.

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What is Data-driven vs AI-driven Practices?

Pickl AI

Define AI-driven Practices AI-driven practices are centred on processing data, identifying trends and patterns, making forecasts, and, most importantly, requiring minimum human intervention. On the other hand, AI-based systems can automate a large part of the decision-making process, from data analysis to obtaining insights.

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Maximizing compliance: Integrating gen AI into the financial regulatory framework

IBM Journey to AI blog

In an era where financial institutions are under increasing scrutiny to comply with Anti-Money Laundering (AML) and Bank Secrecy Act (BSA) regulations, leveraging advanced technologies like generative AI presents a significant opportunity.