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Home Machine Learning

AI in Practice: How to Choose and Deploy the Right Strategy | by TDS Editors | Oct, 2024

AiNEWS2025 by AiNEWS2025
2024-12-10
in Machine Learning
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AI in Practice: How to Choose and Deploy the Right Strategy | by TDS Editors | Oct, 2024
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TDS Editors

Towards Data Science

Feeling impressed to write down your first TDS submit? We’re always open to contributions from new authors.

It’s change into kind of standard knowledge that the majority machine studying initiatives don’t make it into manufacturing, and of people who do, many fail to ship on their promise.

We should always at all times take sweeping claims like these with a grain of salt, as correct stats are exhausting to gather (and interpret), and a number of the organizations circulating them have a stake in convincing practitioners that their answer is the important thing to all of the AI-integration challenges they’re going through. Nonetheless, it’s exhausting to dismiss so many voices—from many various corners of our group—who acknowledge that reaping the advantages of this rising expertise is tougher than it might sound at first.

Our weekly highlights zoom in on the sensible elements of selecting, adopting, and benefiting from AI-powered merchandise and workflows. There’s by no means going to be a one-size-fits-all answer to the issue of integrating promising-yet-complex instruments right into a enterprise, however we predict that exploring these articles can body the dialog in additional helpful and pragmatic phrases. Let’s get to it.

  • Carving Out Your Competitive Advantage with AI
    What advantages can companies truly reap through the use of AI? Dr. Janna Lipenkova expands on the psychological mannequin you’ll be able to undertake to make smarter design and product selections that may assist you to discover the “candy spot” for AI in your group—going past automation to open up the area for extra creativity and innovation.
  • Integrating Multimodal Data into a Large Language Model
    Umair Ali Khan presents an in depth, hands-on introduction to a cutting-edge method that builds on latest work on contextual retrieval and makes it attainable to incorporate not simply textual information in your RAG pipelines, however visible media as nicely. From receipts to charts and tables, ML workflows can now change into extra sturdy with the usage of richer, multimodal information.
Picture by Stephen Harlan on Unsplash
  • How to Choose the Best ML Deployment Strategy: Cloud vs. Edge
    “As ML adoption grows, there’s a rising demand for scalable and environment friendly deployment strategies, but specifics usually stay unclear.” Vincent Vandenbussche patiently walks us by means of the varied components ML engineers want to think about as they determine on the best choice for his or her particular initiatives and use circumstances.
  • A Walkthrough of Nvidia’s Latest Multi-Modal LLM Family
    Staying up-to-date with new developments in AI is undoubtedly necessary, however the speedy tempo at which new fashions and instruments arrive on the scene usually makes it troublesome for busy information professionals to maintain up. Mengliu Zhao’s latest roundup is a useful overview of the brand new suite of multimodal LLMs launched by NVIDIA, and compares their efficiency to different fashions (each business and open supply).

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