NER: Extracting Entities from Documents with AI
Turn company names, dates and locations in documents into verifiable information: NER, OCR, normalisation, evaluation and controlled CRM integration.
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AI Sentiment Analysis: Useful Customer Feedback for Business
How to analyse reviews and messages with AI: polarity, aspects, language, evaluation and dashboards. Clear examples, illustrative calculations and outcome checks.
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AI Alignment for Business: Objectives, Permissions and Evaluation
Understand AI alignment and its business application: verifiable objectives, access boundaries, approvals, evaluation and operational monitoring.
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ANI, AGI and ASI: AI Capabilities and Evaluation
Understand narrow AI, general AI and superintelligence. Distinguish generality, performance and autonomy with diagrams and business evaluation criteria.
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Deep Learning: Neural Networks and Business Applications
How deep learning works: layers, training and inference. Business examples, pretrained models, data, computing resources and application evaluation.
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Supervised, Unsupervised and Reinforcement Learning
Choose the right machine learning approach: labels, groups or rewards. Business examples, diagrams, evaluation and practical data preparation.
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Employee AI Skills: Practical Use and Verification
Prepare employees to use AI: permitted data, clear requests, output verification, approvals and practical role-based training exercises.
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AI in Marketing: Applications, Content and Measurement
Use AI in marketing for content, segmentation, leads and campaigns. Approval workflows, practical examples, costs and business measurement explained.
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Types of AI Agents: Architectures and Business Autonomy
Understand reflex, stateful, goal-based, utility-based and learning agents. LLM architectures, multi-agent systems, MCP, A2A and business approvals.
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Generative, Discriminative and Predictive AI: Business Differences
Compare generative AI, discriminative models and predictions. Business examples, diagrams, data requirements and evaluation for generation and estimation.
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Small Language Models (SLMs): When to Choose Them Over LLMs
Choose a small language model by task, memory, latency, hosting and total operating cost. Practical SLM vs LLM examples, diagrams and evaluation criteria.
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RAG, Fine-Tuning or Prompt Engineering: How to Choose
Choose prompt engineering, RAG or fine-tuning by data needs, behaviour, evaluation and operating cost. Practical diagrams and examples for business AI.
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Natural Language Processing (NLP) for Business
How NLP turns business emails and documents into useful data. Explore classification, extraction, search and summarisation with practical diagrams and evaluation.
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AI Context Window: What It Is and How It Shapes Applications
Understand AI context windows, document and response budgets, memory, RAG and compaction. Practical diagrams and tests for reliable business applications.
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DeepSeek Harness team releases an AI agent prototype for GitHub tasks
The dsh-superagent research prototype coordinates authorized GitHub tasks, separate work sessions and reviewable results. Its public code is MIT-licensed.
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AI Tokens: What They Are, Costs and Application Limits
Understand AI tokens, input and output costs, caching, context windows and API limits. Practical calculations, diagrams and controls for business applications.
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What Is an LLM? How Large Language Models Work
What is an LLM and how does it work? Understand tokens, training, context, document retrieval and tools through diagrams and practical business examples.
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AI vs Machine Learning vs Deep Learning: Key Differences
AI, machine learning and deep learning explained through clear diagrams, business examples and practical criteria for choosing the right approach.
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Types of Artificial Intelligence: A Practical Business Guide
Understand machine learning, generative AI, LLMs and AI agents. Clear classifications, diagrams and business examples for choosing an AI application.
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Google makes Gemini Computer Use generally available for interface automation
Google makes Computer Use generally available in Interactions and GenerateContent. Applications execute agents' screen actions with safety and confirmation controls.
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TikTok brings brand protection and AI advertising guidance into a new center
TikTok's Brand Safety Center brings together ad adjacency, reputation and AI transparency resources. Campaign controls remain in Ads Manager.
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ServiceNow brings business workflows to ChatGPT and expands its OpenAI partnership
The MCP plugin is available with company rules and permissions. Codex, cybersecurity and voice assessments have separate schedules in 2027.
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Meta updates Andromeda, the system selecting ads for Facebook and Instagram
Meta's new architecture brings ad retrieval and scoring onto a GPU, reporting over one billion evaluations per second for the production pipeline.
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Google and OpenAI back a shared signal for website AI training preferences
The proposed robots.txt signal retains existing controls. Google targets early 2027, while OpenAI plans implementation in the coming months.
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