One of the main reasons why AI Projects fail: Overpromising & Underdelivering The world of AI is full of exciting possibilities, but some of the claims being made about AI veer into the realm of breathless overpromising and underdelivering what AI can really do. Here are a few examples: “AI systems are becoming sentient! Watch …
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Just because over 80% of AI projects fail doesn’t mean yours should.
There are 7 common patterns of AI applications that apply to all AI use cases.
When AI practitioners talk about taking their machine learning models and deploying them into real-world environments, they don’t call it deployment. Instead the term that’s used in the industry is “operationalizing”. This might be confusing for traditional IT operations managers and applications developers. Why don’t we deploy or put into production AI models? What does …
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