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Exploring the pros and cons of cloud-based large language models

CIO

The paradigm shift towards the cloud has dominated the technology landscape, providing organizations with stronger connectivity, efficiency, and scalability. In light of this, developer teams are beginning to turn to AI-enabled tools like large language models (LLMs) to simplify and automate tasks.

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20 Machine Learning/Artificial Intelligence Influencers To Follow In 2020

Hacker Earth Developers Blog

Machine Learning (ML) is emerging as one of the hottest fields today. The Machine Learning market is ever-growing, predicted to scale up at a CAGR of 43.8% Consequently, there has been a significant increase in the number of Machine Learning enthusiasts across the globe. billion by the end of 2025.

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20 Machine Learning/Artificial Intelligence Influencers To Follow In 2020

Hacker Earth Developers Blog

Machine Learning (ML) is emerging as one of the hottest fields today. The Machine Learning market is ever-growing, predicted to scale up at a CAGR of 43.8% Consequently, there has been a significant increase in the number of Machine Learning enthusiasts across the globe. billion by the end of 2025.

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5 ways to deploy your own large language model

CIO

It’s the fastest-moving new technology in history. A large language model (LLM) is a type of gen AI that focuses on text and code instead of images or audio, although some have begun to integrate different modalities. That question isn’t set to the LLM right away. Instead, it’s processed first.

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Embedding BI: Architectural Considerations and Technical Requirements

While data platforms, artificial intelligence (AI), machine learning (ML), and programming platforms have evolved to leverage big data and streaming data, the front-end user experience has not kept up. Holding onto old BI technology while everything else moves forward is holding back organizations.

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Machine learning model serving architectures

Xebia

After months of crunching data, plotting distributions, and testing out various machine learning algorithms you have finally proven to your stakeholders that your model can deliver business value. Serving a model cannot be too hard, right? Many different factors influence the architecture around a machine learning model.

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Article: Software Testing, Artificial Intelligence and Machine Learning Trends in 2023

InfoQ Culture Methods

Technology has taken significant leaps within the last few years, introducing advancements that have taken us further into the digital age — impacting the software testing industry and we're seeing advances in machine learning, artificial intelligence, and the neural networks making them possible.

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MLOps 101: The Foundation for Your AI Strategy

Many organizations are dipping their toes into machine learning and artificial intelligence (AI). Download this comprehensive guide to learn: What is MLOps? How can MLOps tools deliver trusted, scalable, and secure infrastructure for machine learning projects? Why do AI-driven organizations need it?

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5 Things a Data Scientist Can Do to Stay Current

And more is being asked of data scientists as companies look to implement artificial intelligence (AI) and machine learning technologies into key operations. Fostering collaboration between DevOps and machine learning operations (MLOps) teams. Collecting and accessing data from outside sources.

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Trusted AI 102: A Guide to Building Fair and Unbiased AI Systems

The risk of bias in artificial intelligence (AI) has been the source of much concern and debate. Numerous high-profile examples demonstrate the reality that AI is not a default “neutral” technology and can come to reflect or exacerbate bias encoded in human data.

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Data Science Fails: Building AI You Can Trust

The game-changing potential of artificial intelligence (AI) and machine learning is well-documented. Any organization that is considering adopting AI at their organization must first be willing to trust in AI technology.

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Realizing the Benefits of Automated Machine Learning

While everyone is talking about machine learning and artificial intelligence (AI), how are organizations actually using this technology to derive business value? This white paper covers: What’s new in machine learning and AI.

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The New Tech Experience: Innovation, Optimization, and Collaboration

Speaker: Paul Weald, Contact Center Innovator

Learn how to streamline productivity and efficiency across your organization with machine learning and artificial intelligence! Embrace automation, collaborate with new technology, and watch how you thrive!

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How AI and ML Can Accelerate and Optimize Software Development and Testing

Speaker: Eran Kinsbruner, Best-Selling Author, TechBeacon Top 30 Test Automation Leader & the Chief Evangelist and Senior Director at Perforce Software

In this session, Eran Kinsbruner will cover recommended areas where artificial intelligence and machine learning can be leveraged. This includes how to: Obtain an overview of existing AI/ML technologies throughout the DevOps pipeline across categories. Understand the future of DevOps tied with AI/ML technologies.