Beyond Imagination, Baltic Transport Journal

By December 19, 2024December 20th, 2024Articles
Chad Van Derrick

Earlier this month Jack Ma, the cofounder of Alibaba Group, made a rare public appearance discussing how over the next two decades “AI will change everything.” According to The South China Morning Post, Ma stated that “from today’s perspective, the changes brought by artificial intelligence in the next 20 years will go beyond everyone’s imagination, as AI will bring a greater era.” 

These visions of AI are becoming more common place from today’s executive suite, and certainly many claim that the ongoing stock market bubble is in fact not a bubble but indicative of the potential value that AI will produce for companies across many industries.  

What then is the impact to marine terminals, and how can operators prepare now to reap this value and establish themselves as leaders in an AI future? Let’s start by dissecting these acronyms and how they apply to our industry. 

The Technologies that will Power the Future: AI, ML, and GenAI 

Artificial Intelligence (AI) is the broadest term, referring to any system or algorithm designed to mimic human intelligence. It encompasses tasks such as learning, reasoning, and problem-solving. AI includes rule-based systems, robotics, and more advanced techniques like ML and GenAI. 

Machine Learning (ML) is a subset of AI focused on developing algorithms that can identify patterns in data. ML is typically used for predictions, classifications, and decision-making tasks, relying on techniques like supervised or reinforcement learning for improvement. ML examples include spam filters, recommendation engines, and fraud detection. Yes, your last Netflix watch was probably recommended or influenced by ML. And those CAPTCHA systems to verify that you’re a human – like identifying buses, crosswalks, or traffic lights – often contribute to supervised learning, helping to train ML models for image recognition tasks. 

Generative AI (GenAI) is a specialized subset of ML that focuses on creating new content that mimics existing data, such as text, images, music, or code. ChatGPT, Microsoft Copilot, and Google Gemini are all examples of large language models (LLMs). GenAI excels in creative tasks such as generating images, writing text and code, and producing synthetic data for training other models. 

Read the full article on pages 60-61 

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