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Towards optimal experimentation in online systems

The Unofficial Google Data Science Blog

It is also a sound strategy when experimenting with several parameters at the same time. To find optimal values of two parameters experimentally, the obvious strategy would be to experiment with and update them in separate, sequential stages. (And sometimes even if it is not[1].)

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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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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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ChatGPT, the rise of generative AI

CIO Business Intelligence

ChatGPT was trained with 175 billion parameters; for comparison, GPT-2 was 1.5B (2019), Google’s LaMBDA was 137B (2021), and Google’s BERT was 0.3B (2018). It’s hard to achieve a deep, experiential understanding of new technology without experimentation.

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Generative AI’s change management challenge

CIO Business Intelligence

A lot has happened since that last survey on attitudes to AI in 2018. It’s important folks get a chance to interact with these technologies and use them; stopping experimentation is not the answer,” Mills said, noting that it’s also not practical. “AI

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How generative AI impacts your digital transformation priorities

CIO Business Intelligence

During keynotes and discussions with CIOs, I remind everyone how strategic priorities evolve significantly every two years or less, from growth in 2018, to pandemic and remote work in 2020, to hybrid work and financial constraints in 2022. Customizing and developing LLMs requires a strong business case, technical expertise, and funding.

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Havmor’s VP IT Dhaval Mankad on ‘melting’ hurdles with a scoop of digital innovation

CIO Business Intelligence

To add perspective, since I joined Havmor, the company has grown significantly, but not the workforce, having reduced by 30% compare to our numbers in 2018, thanks to digital innovation and transformation. Technology has enabled us to operate in a very cost competitive market, allowing us to do more with fewer people.

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