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6 trends framing the state of AI and ML

O'Reilly on Data

Deep learning cooled slightly in 2019, slipping 10% relative to 2018, but deep learning still accounted for 22% of all AI/ML usage. PyTorch looks like a contender: it posted triple-digit growth in usage share rates in both 2018 and 2019. For example, the chatbots topic continues to decline, first by 17% in 2018 and by 34% in 2019.

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Machine Learning Product Management: Lessons Learned

Domino Data Lab

Unfortunately, a common challenge that many industry people face includes battling “ the model myth ,” or the perception that because their work includes code and data, their work “should” be treated like software engineering. I was fortunate to see an early iteration of Pete Skomoroch ’s ML product management presentation in November 2018.

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HPE Looks to Edge-to-Cloud Strategy for Growth in 2018/2019

Hurwitz & Associates

Edge-to-cloud is the central focus of Hewlett Packard Enterprise (HPE) marketing and go-to-market efforts in 2018/2019. This central strategy, an evolution of the company’s plan for the Intelligent Edge and edge gateway systems, expands on the company’s broad portfolio of software, services, systems, storage and networking products.

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How Italian CIOs produce value with gen AI

CIO Business Intelligence

Telcos in general are also experimenting with gen AI to analyze network data and streamline the entire software lifecycle, including generating and scanning code for vulnerabilities before launch. I’ve given colleagues the freedom to do research and experimentation together with our automation partner Mauden,” says Ciuccarelli. “We

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Reflections on the Data Science Platform Market

Domino Data Lab

In 2018 we saw the “data science platform” market rapidly crystallize into three distinct product segments. These data scientists require the flexibility to use a constantly-evolving software and hardware stack to optimize each step of their model lifecycle. Reflections. Jupyter) or IDEs (e.g.,

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Towards optimal experimentation in online systems

The Unofficial Google Data Science Blog

To find optimal values of two parameters experimentally, the obvious strategy would be to experiment with and update them in separate, sequential stages. Our experimentation platform supports this kind of grouped-experiments analysis, which allows us to see rough summaries of our designed experiments without much work.

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Los agentes de IA transformarán procesos y encararán riesgos

CIO Business Intelligence

A partir de 2018, la agencia utilizó agentes, en forma de ordenadores Raspberry PI que ejecutan redes neuronales de inspiración biológica y modelos de series temporales, como base de una red cooperativa de sensores. La mayoría de los que trabajamos en IA somos ingenieros de software ”, afirma. Eso es lo primero que se está abordando”.

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