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Tag: James Kobielus

Giving DevOps Teeth To Crunch Down on AI Ethics Governance

Jun 4, 2019 |

AI ethics is definitely trending. I’ve seen the phrase in my reading and heard it trip from the tongues of professional acquaintances many times in the past several months.

Management fads come and go, and I wonder whether AI ethics might be one of them. Read more…

Let’s Accept That AI Leadership Is Everywhere

Feb 13, 2019 |

Artificial intelligence (AI) is the new space race, or at least that’s how it’s being perceived in the general population, and being presented by the movers and shakers of this world. Read more…

Predictions for Application Development in 2019

Jan 3, 2019 |

Application development has become a cloud-focused initiative in many enterprises. Consequently, the languages, tools, and platforms needed to support today’s development initiatives are rapidly evolving.

Application development is also a discipline in which data science is assuming a greater role. Read more…

The Pain of Watching AI Become A Pawn in the Geopolitical Fray

Jul 17, 2018 |

Artificial intelligence (AI) has been a predominantly transnational phenomenon for most of this decade.

Radical cross-border openness has been a central driver of the AI revolution. One of the primary factors stimulating advances in AI research, commercialization, and adoption has been the growing open-source stack of data analytics platforms and tools. Read more…

Giving Machine Learning Freer Rein to Design Next-Generation Communications Protocols

Sep 6, 2017 |

Protocol engineering is an abstruse but essential art. So much depends on a well-tuned protocol. If engineers build inefficiencies into the conversational framework that computers use to interoperate, those issues afflict every application that relies on it. Read more…

Training Your AI With As Little Manually Labeled Data As Possible

Aug 14, 2017 |

Let’s imagine a future in which developers are creating and deploying artificial intelligence (AI) apps faster than people can consume them.

Please ignore the minor issue of whether the developers in question can make a decent living building stuff that almost nobody is using. Read more…

Scrutinizing the Inscrutability of Deep Learning

Mar 15, 2017 |

Most people can’t make heads or tails out of most algorithms. By “most people,” I’m referring to anyone who didn’t literally develop the algorithm in question or doesn’t manage the rules, data, and other artifacts that govern how its results drive automated decision processes. Read more…

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