The Evolving Global AI Landscape: Summary

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The Evolving Global AI Landscape: Mainstream and New to the Market

The Open-source AI Movement: Innovation in the Global AI Landscape

Artificial intelligence has transitioned from a phase of rapid innovation to an era of strategic deployment, global competition, and ethical reflection. While we do not claim to be experts in these evolving technologies, at JDSix, we are avid learners frequently asked for our perspective—particularly on distinguishing hype from real-world business applications.

At JDSix, we actively leverage many mainstream AI technologies for both internal use and client projects. However, we are just beginning our exploration of newer platforms such as DeepSeek and Coreweave, both of which launched in 2025. Our philosophy is simple: Embrace or be displaced—but always with caution and a foundation of practical wisdom.

Today’s AI landscape is shaped by a dynamic mix of industry leaders, emerging disruptors, and the growing open-source movement, each competing for dominance in an increasingly interconnected digital economy. In our analysis, we assess the role of key players across three categories—Mainstream, New to Market, and Open Source—examining what their positions reveal about the future of AI.

We’ve provided a summary below, but have published our detailed findings at 

Mainstream – 2 (+/-) years or greater

  1. ChatGPT (OpenAI, 2023): The Benchmark for General-Purpose AI
  2. CoPilot (Microsoft, 2023): The Enterprise AI Workhorse
  3. Gemini (Google DeepMind, 2023): AI-Native Search and Beyond – 
  4. Anthropic (Amazon, 2023): The Ethical AI Alternative – 

New to Market – 0-2 (+/-) years

  • DeepSeek (China, 2025): A Rising AI Superpower
  • CoreWeave (Coreweave, 2025): The Infrastructure Kingmaker
  • XI (xAI Elon Musk, 2023): Its stated goal is “to understand the true nature of the universe”

Open-Source AI – Continuously Evolving

Deep Learning Frameworks

  1. TensorFlow (Google): Ideal for both research and production use cases
  2. PyTorch (Backed by Meta): Particularly favored in academia and research
  3. Keras: Intuitive interface for building and experimenting with deep learning models
  4. Apache MXNet (Amaozon): Distributed deep learning

Machine Learning and AI Toolkits

  • Scikit-learn: Models such as decision trees, support vector machines, and ensemble methods
  • H2O.ai: Automated machine learning (AutoML)
  • Amazon SageMaker: Build, train, and deploy ML models in the AWS cloud ecosystem – 

Conversational AI and NLP

  • Rasa: Conversational AI framework to build chatbots and virtual assistants
  • OpenCV: Object detection and facial recognition to real-time augmented reality applications
  • OpenAI: A mix of open-source and paid model

Whether you’re deep into your AI journey, exploring on the sidelines, or just beginning to navigate the possibilities, JDSix is here to guide you. As business focused on outcomes, we prioritize your best interests, helping you make informed decisions in an evolving AI landscape.

Please see the full post on JDSix at,

The Evolving Global AI Landscape: Mainstream and New to the Market

The Open-source AI Movement: Innovation in the Global AI Landscape