Agathon: Latest articles
Contextual chunking strategies that improve RAG performance
In the evolving AI landscape, mastering contextual chunking is essential for optimising Retrieval-Augmented Generation (RAG) performance.
Understanding how QLoRA works
QLoRA revolutionises the fine-tuning of large language models by combining quantisation and low-rank adaptation to significantly reduce memory usage while preserving performance, making advanced AI accessible to a broader range of users.
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.
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.
The Non-Executive Director's guide to assessing AI system performance
The guide equips Non-Executive Directors with essential frameworks and insights to effectively assess AI system performance, ensuring alignment with corporate objectives and ethical standards.
Creating custom benchmarks that align with business objectives
Custom benchmarks, tailored to specific business objectives, are essential for driving meaningful performance insights and strategic success, far outperforming generic metrics.
Enterprise knowledge graphs as RAG foundations: implementation lessons
Enterprise knowledge graphs, enhanced by retrieval-augmented generation, are essential for transforming data silos into interconnected knowledge ecosystems, but their success hinges on data quality, scalability, security, and user-centric design.
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.
Skills taxonomy for modern AI teams: beyond traditional data science
A modern AI skills taxonomy is essential for building versatile teams that go beyond traditional data science to include advanced technical, interdisciplinary, and ethical competencies for future innovation.
The fractional CTO's guide to building AI teams that deliver
The Fractional CTO's Guide highlights the crucial role of fractional CTOs in building high-performing AI teams that align with business objectives while fostering innovation and ethical practices.
The strategic value of a Non-Executive Director with AI expertise
The inclusion of Non-Executive Directors with AI expertise is essential for organisations to effectively navigate the complexities of modern business strategy and ethical considerations in an increasingly AI-driven landscape.
An executive’s guide to AI agents
AI agents are transformative software entities that enhance operational efficiency and decision-making in businesses by autonomously performing tasks and leveraging advanced technologies like generative AI.
Reinforcement learning: practical guide for business users
Reinforcement Learning is a pivotal AI component for business, enabling adaptive decision-making through interaction with environments, balancing exploration and exploitation, and offering benefits such as enhanced decision-making and increased efficiency, despite challenges like data requirements and ethical considerations.
Common technical challenges fractional CTOs solve for startups
Fractional CTOs provide expert technical leadership to startups, addressing critical challenges like technical debt, scaling infrastructure, security, and cloud cost optimisation without the need for a full-time hire.
Your private LLM: deploying LLMs locally and offline using Ollama
Ollama enables local deployment of Large Language Models (LLMs), offering enhanced privacy, control, and efficiency for organisations seeking to harness the power of LLMs while maintaining oversight of their operational environment.
Understanding the AI Skills for Business Framework — dimensions and implementation (part 2)
Successful AI adoption for SMEs requires focusing on five dimensions: privacy and stewardship, technical infrastructure, problem definition, problem solving, and evaluation.
Understanding the AI Skills for Business Framework — leaders guide and personas (part 1)
The AI Skills for Business Framework outlines four key personas—AI Citizens, AI Workers, AI Professionals, and AI Leaders—essential for organisations to effectively integrate AI.
Unlocking business potential with AI agents
AI agents are intelligent systems that autonomously handle tasks, enhancing efficiency and reducing costs.
Building your AI-first company
The rise of AI-first lean startups: rethinking organisational structure in the genAI era
Process reward models: a simple explainer
Process reward models (PRMs) train AI by providing feedback at each step of a task, enhancing understanding and problem-solving abilities.
Should I build my own large language model (LLM)?
Organizations considering building their own large language models (LLMs) should weigh the benefits of control and specialisation against challenges like high computational needs and expertise requirements.
What does a fractional CTO do?
A fractional AI CTO provides strategic guidance and technical leadership to help organizations assess, plan, and responsibly implement AI solutions.
Who are the best AI consulting firms in 2024?
When selecting an AI consulting partner, the right fit will depend on your organisation's unique needs, budget, and desire for a hands-on collaborative engagement.
Can you reason with LLMs?
Research from Apple reveals that large language models struggle with genuine mathematical reasoning and perform inconsistently on complex math problems
Understanding large language models: a group discussion analogy
By visualising the transformer as a dynamic conversation between human participants, we can grasp the core principles behind this influential neural network architecture.
What is multi-modal AI?
Promising the ability to interact with large language models in a range of ways — what exactly is multi-modal AI?
Conducting a data assessment
We outline our process for and benefits of conducting a data assessment prior to initiating any project.
Delivery excellence through multi-disciplinarity and diverse teams
Unlocking the potential of AI through diverse teams: why it is crucial to employ a multidisciplinary team
Quantifying the benefits and risks of an AI deployment
How we at Agathon quantify the benefits and risks of any project we embark upon
Adversarial models: what are they and when should you use them?
A brief explanation of adversarial models and some potential use cases for them
Responsible and ethical AI — why does it matter?
Responsible AI is all the rage, but why should one care?
ChatGPT’s impact on the enterprise
Potential impacts and use cases for ChatGPT on the enterprise
Recent trends in NLP
Examining some recent trends in NLP and AI, including transformer-based models, transfer learning, multimodal AI and conversational AI