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Chuck Ros, SoftServe: Delivering transformative AI solutions responsibly

AI News

. “Our AI engineers built a prompt evaluation pipeline that seamlessly considers cost, processing time, semantic similarity, and the likelihood of hallucinations,” Ros explained. It’s obviously an ambitious goal, but it’s important to our employees and it’s important to our clients,” explained Ros.

Big Data 236
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The risks and limitations of AI in insurance

IBM Journey to AI blog

Risk and limitations of AI The risk associated with the adoption of AI in insurance can be separated broadly into two categories—technological and usage. Technological risk—data confidentiality The chief technological risk is the matter of data confidentiality.

AI 184
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How AI facilitates more fair and accurate credit scoring

Snorkel AI

Some may choose to experiment with non-traditional data sources like digital footprints or recurring streaming payments to predict repayment behavior. How foundation models jumpstart AI development Foundation models (FMs) represent a massive leap forward in AI development.

AI 64
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How AI facilitates more fair and accurate credit scoring

Snorkel AI

Some may choose to experiment with non-traditional data sources like digital footprints or recurring streaming payments to predict repayment behavior. How foundation models jumpstart AI development Foundation models (FMs) represent a massive leap forward in AI development.

AI 59
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How AI saves money and improves banking complaint handling

Snorkel AI

Machine learning to identify emerging patterns in complaint data and solve widespread issues faster. However, banks may encounter roadblocks when integrating AI into their complaint-handling process. Banks cannot send their sensitive customer data to crowd labelers or to third-party models without compromising security.

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How AI saves money and improves banking complaint handling

Snorkel AI

Machine learning to identify emerging patterns in complaint data and solve widespread issues faster. However, banks may encounter roadblocks when integrating AI into their complaint-handling process. Banks cannot send their sensitive customer data to crowd labelers or to third-party models without compromising security.

article thumbnail

How AI saves money and improves banking complaint handling

Snorkel AI

Machine learning to identify emerging patterns in complaint data and solve widespread issues faster. However, banks may encounter roadblocks when integrating AI into their complaint-handling process. Banks cannot send their sensitive customer data to crowd labelers or to third-party models without compromising security.