Fraud prevention analysts are overwhelmed with work as bot-based and synthetic identity fraud proliferates globally. The models they’re using aren’t designed to deal with synthetic identities or fraud’s unstructured and fast-changing nature. A look at five ways AI is helping to detect and prevent growing identity fraud. (Article)

A group of over 1,000 AI researchers has created a multilingual large language model bigger than GPT-3—and they’re giving it out for free. A look inside BLOOM: a radical new project to democratize AI. (Article)

Businesses are using AI for everything from resolving customer service issues to making financial decisions. But do customers trust their use of AI? For building trust, it’s vital that both developers and customers understand the reasons why AI makes the decisions and predictions it does. (Article)

“We need AI builders from diverse backgrounds who understand the complex interplay of data, AI and how it can affect different communities.” – Solana Larsen

“The AI Infrastructure market is projected to grow from $28.7 billion in 2022 to $96.6 billion by 2027.”  – MarketsandMarkets

Do you have a streamlined way to gather information on your model’s strengths, weaknesses, and how it might behave in the future?

... and a short update on Apres

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