Natural Language Processing

Technical foundations and modern approaches to natural language processing. From linguistic fundamentals to transformer architectures, covering methods that enable machines to understand and generate human language effectively.

5 articles

AI Strategy
Machine Learning
NLP
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Thin wrapper or true AI? Technical due diligence for AI investments

Despite widespread AI claims in company pitch decks, 95% of generative AI pilots are failing, creating a massive gap between marketing promises and reality that requires rigorous technical due diligence to distinguish genuine AI capabilities from superficial implementations.

NLP
Machine Learning
Responsible AI
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The future of AI for lawyers: transforming legal practice in the digital age

Legal AI is vastly underutilized, with true innovation lying not in basic document tools but in sophisticated neural-symbolic architectures that authentically model legal reasoning rather than merely mimicking paralegal functions.

LLMs
Responsible AI
NLP
article cover

Small LLMs — why they matter

Small language models (SLMs), characterised by their efficiency and versatility, are emerging as pivotal tools for language processing, offering significant advantages in resource optimisation and accessibility, while challenging the dominance of larger models.

Generative AI
Machine Learning
NLP
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Diffusion models: a simple explainer

Diffusion models revolutionise generative AI by generating high-quality images, videos, and molecules through a dual process of noise addition and reconstruction, while raising significant ethical and computational challenges.

LLMs
Machine Learning
NLP
article cover

Demystifying LoRA

Low-Rank Adaptation (LoRA) revolutionises the fine-tuning of large language models by enabling efficient model adaptation with minimal computational resources, while raising important ethical considerations.

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