Mentis · Blog
Insights from Mentis.
Insights, tutorials and opinions on AI, machine learning and NLP from the Mentis team.
Are you AI-ready? Part 6 — Security & Trust: the AI you don't know about is the AI you should worry about
Ask an IT director which AI tools employees already use and the honest answer is usually "no idea". The final dimension of AI readiness: shadow AI, the leakage vectors that matter, model risk and auditability — and why banning tools fails where offering a better alternative works. Plus: what the full six-dimension radar tells you.
AI readiness · 28 August 2026Are you AI-ready? Part 5 — People & Operating Model: if an AI tool misbehaved tomorrow, who would act?
Ask that question in a leadership meeting and count the seconds of silence. The fifth dimension of AI readiness is the one organisations skip because it is not technical: who owns AI, what skills exist beyond the enthusiasts, and why AI literacy stopped being optional in February 2025.
AI readiness · 28 August 2026Are you AI-ready? Part 4 — Governance & AI Act: the deadline is no longer in the future
Since 2 August 2026, the bulk of the EU AI Act applies. Most mid-market organisations still have no inventory of their AI systems — which means their exposure is unnamed, not absent. The fourth dimension of AI readiness: the register, the risk classifications, what deployers actually owe, and why governance done right is a rhythm rather than a scramble.
AI readiness · 28 August 2026Are you AI-ready? Part 3 — Architecture & Infrastructure: the demo that quietly becomes your architecture
Nobody decides their AI architecture. It accumulates — one vendor demo, one SaaS contract, one pilot at a time. The third dimension of AI readiness: what your stack actually needs to run AI in production, why sovereignty is a requirements question rather than an ideology, and how to stop vendors deciding build-versus-buy for you.
AI readiness · 22 August 2026Are you AI-ready? Part 2 — Data Foundations: "our data isn’t ready" is half true, and fixable
The most common reason an AI idea dies is a sentence: "our data isn’t ready." It is usually half true — and the half that is true is smaller and cheaper to fix than people fear. The second dimension of AI readiness: what "ready" means, per use case, and why your documents may be your biggest asset.
AI readiness · 22 August 2026Are you AI-ready? Part 1 — Strategy & Value: why most AI programmes start in the wrong place
Boards want AI, vendors sell AI, pilots multiply — and nothing reaches production. The first of six dimensions of AI readiness explains why, and what to fix first: a scored use-case portfolio, an owner, and a decision on what AI is actually for.
Opinion · 16 April 2024Unlocking AGI: The Human Brain’s Blueprint for True Intelligence
How Brain Architecture, Data, and Compute Converge to Shape the Future of Artificial General Intelligence.
Tutorial · 16 April 2024Convolutional Neural Networks for Text Classification: An Exploration
Understanding How CNNs Can Tackle the Challenges of NLP and Document Classification.
Tutorial · 24 January 2020Exploring CNNs for NLP: Text Classification with Convolutional Neural Networks
Applications of Convolutional Neural Networks in Text Mining and Classification Tasks.