Category Archives: Machine Learning

ML has a proof-of-concept-to-production gap

Andrew Ng: “All of AI, not just healthcare, has a proof-of-concept-to-production gap. The full cycle of a machine learning project is not just modeling. It is finding the right data, deploying it, monitoring it, feeding data back [into the model], … Continue reading

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Machine Learning vs. Knowledge Acquisition

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Everything old is new again

Prof. Gene Freuder writes about Human-Centered AI: “human-centered”, “human-aware“, “human-AI collaboration” are, rightly, very prominent nowadays. But “everything old is new again”: I ran across an interesting twenty-year-old paper from the European Journal of Operational Research on Human centered processes and decision support … Continue reading

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Improving code vs improving data quality

Andrew Ng: “Traditional software is powered by code, whereas AI systems are built using both code (models + algorithms) and data. When a system isn’t performing well, many teams instinctually try to improve the code. But for many practical applications, … Continue reading

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Can Your Machine Learning Do the Lambada?

Ulrich Wiesner from FICO wrote: “Machine learning and data analytics are powerful methods, but typically the benefits do not come without effort, and careful considerations are required to make these tools efficient. When you purchase a tool or service, make … Continue reading

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Why a YouTube Chat About Chess Got Flagged for Hate Speech

This WIRED article talks about shortcomings in AI programs designed to automatically detect hate speech, abuse, and misinformation online. When WIRED fed some of statements gathered by the CMU researchers into two hate-speech classifiers, the statement “White’s attack on black is … Continue reading

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AI is not equal to ML

Alain Chabrier from IBM Decision Optimization team in his Medium.com article argues that not only “AI != ML” pointing to the difference between Data-driven and Knowledge-driven decision models. He even claims that “Decision Optimization has more impact on the real … Continue reading

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Recent Advances in Google Translate

Google Translate was introduced in 2016 and it enabled great improvements to the quality of translation for over 100 languages since then. In this post Google Research describes how recent advances in machine learning drive improvements to automated translation. Link

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Pragmatic Approach to Predictive Decision Automation

In this webinar Red Hat specialists explain how explainable Predictive Decisioning can help us trust AI. Their  approach combines AI/ML, decision optimization, and traditional business rules to better understand the factors that contribute to an automated decision. They use the … Continue reading

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Decision-Driven Data Analytics

“Data analysts often fail to produce insights for making effective business decisions, but that’s not their fault. Data-driven decision-making anchors on available data. This often leads decision makers to focus on the wrong question. Decision-driven data analytics starts from a proper … Continue reading

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