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Category Archives: deep learning

Podcast Episode: Data Mesh Under Fire

25 Tuesday Aug 2026

Posted by Martyn Rhisiart Jones in data architecture, Data governance, data hub, Data Lake, data management, data mesh, data science, Data Supply Framework, Data Warehouse, Data Warehousing, deep learning

≈ 1 Comment

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Ask Martyn, data mesh, the bizarre world of data mesh

Pip: Good Strategy Rebellion — where the sacred cows of enterprise tech get a proper going-over. Today we’re deep in the data wars, asking whether the industry’s favourite architectural revolution is actually a revolution, or just the same old chaos in a new lanyard.

Mara: Martyn Jones has been writing about exactly that — covering the case against Data Mesh, what it means for how organisations actually govern and use their data, and why the rational data warehouse keeps refusing to stay dead.

Pip: Let’s start with the bonfire.

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Deep learning; shallow understanding.

02 Sunday Jun 2019

Posted by Martyn Rhisiart Jones in agile, Artificial Intelligence, business strategy, deep learning, Good Strategy, IT strategy, iterations, Strategy

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Deep learning, shallow understanding.

The original article is here: https://goodstrat.com/2019/05/11/deep-learning-and-shallow-understanding/

CEO BRIEFING: Deep learning and shallow understanding

11 Saturday May 2019

Posted by Martyn Rhisiart Jones in AI, All Data, Big Data, deep learning, Inform, educate and entertain.

≈ 3 Comments

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Martyn Richard Jones

Bruxelles, 29th April 2019

To begin at the beginning

In spite of or perhaps because of the many years I worked in artificial intelligence I believe that the current long-distance love affair with AI and what is also euphemistically termed ‘deep learning’ to be somewhat irrational in its exuberance.

In the eighties I was experimenting with automatic feature extraction, pattern recognition and parallel distributed processing (see Rumelhart and McClelland), which led me to adaptive neural networks.

As a result, my research and development in this field showed me that automatically mining nuggets of gold or automatically gaining real insight from data is not easy, far from stable and frequently not achievable.  Interesting experiments, but frequently impractical in a business setting.

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