Machine Learning Times
Machine Learning Times
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5 Ways To Hybridize Predictive AI And Generative AI
  Originally published in Forbes AI is in trouble. Both...
This Simple Arithmetic Can Optimize Your Main Business Operations
 Originally published in Forbes Deep down, we all know that...
Predictive AI Usually Fails Because It’s Not Usually Valuated
 Originally published in Forbes Why in the world would the...
Panic Over DeepSeek Exposes AI’s Weak Foundation On Hype
 Originally published in Forbes The story about DeepSeek has disrupted...
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5 years ago
Why Operationalizing Machine Learning Requires a Shrewd Business Perspective

 Originally published in Analytics Magazine For a rocket scientist, the math isn’t the hardest part. What’s hard is being so often misunderstood. The same goes for data scientists, who time and again lack the support needed to successfully launch the fruits of their brilliant labor into action. These math heads have got to integrate into the organization as a whole, lest they vanish into the obscurities of their analysis. Their isolation is an enemy to their usefulness. After all, the most wicked and pervasive pitfall of predictive analytics is organizational in nature, not technical: Predictive models often fail

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