Example presentation · School
Artificial intelligence
What the presentation covers
Slide 1 Artificial Intelligence
Artificial Intelligence · A General Overview · The technology that learned to speak, see and reason — and what it means for everyone. · 1950 → today: from a question on paper to a billion users
Slide 2 What AI actually is
Definition · AI is software that learns patterns from data instead of following hand-written rules. · The machine improves at a task through examples, not instructions — and each layer below builds on the one before it. · Machine learning · examples in, improvement out · Deep learning · layered neural networks, loosely brain-inspired — the engine of the last decade · Generative AI
Slide 3 Seventy years in six moments
Milestones · Turing's question · "Can machines think?" — and his imitation test · Deep Blue wins · IBM's machine beats chess champion Kasparov · AlphaGo's move 37 · Defeats Go champion Lee Sedol, a decade early · AI gets its name
Slide 4 How a model learns
Under the hood · Training · The model reads enormous amounts of text and adjusts billions of internal numbers — weights — to predict the next word. · Pattern-finding at planetary scale · Grammar, facts, style and reasoning habits all emerge from statistics. · Inference · Once trained, the model answers in seconds on ordinary hardware. · Scale is the recipe
Slide 5 The fastest adoption in history
Scale of use · 100 million users in two months. Instagram took 2.5 years to get there. · 900M · Weekly users · Feb 2026 · 2M+ · Businesses building on OpenAI · AI assistants have become everyday tools — for writing, coding and search.
Slide 6 The money is moving
$252.3B · Corporate AI investment, 2024 · A record year — the largest sum ever committed to AI in a single cycle. · +26% · Year over year. Growth accelerated on top of an already historic 2023. · $33.9B · Generative AI, private investment. 8.5× the 2022 level — capital is concentrating on the new frontier. · 13×
Slide 7 Where you already meet it
Everyday uses · FIVE DOMAINS IN DAILY LIFE · 01 Search & answers Assistants that summarize, translate and explain on demand · 02 Software Code written, reviewed and debugged alongside developers · 03 Medicine Imaging analysis, drug discovery and clinical documentation · 04 Creative work Images, music, video and design generated from a sentence · 05 Science Protein folding, weather forecasting and materials discovery accelerated
Slide 8 The honest risks
R·01 Hallucination · Models state falsehoods fluently — verification still matters. · R·02 Jobs · Tasks are exposed faster than whole jobs — early evidence shows hiring slowing in the most exposed occupations, not mass unemployment. · R·03 Bias · Models inherit the patterns — and the prejudices — of their training data. · R·04 Concentration · Frontier capability sits with a handful of companies and countries.
Slide 9 What comes next
The frontier is shifting — from models that answer to systems that act, reason and move through the physical world, under rules that are only now being written. · Agents · From answering questions to completing multi-step work on your behalf. · Reasoning models · Systems that think longer on hard problems before answering. · Embodiment · The same techniques moving into robots and self-driving vehicles. · Regulation arrives
Slide 10 Think with it, not for it.
Closing · The most rapidly adopted technology in history — and still early. · It amplifies whatever feeds it: our data, our questions, our judgment. · The skill that matters now is knowing what to ask and what to verify. · Artificial Intelligence — A General Overview Questions Welcome
Photos: Foto: Google DeepMind · Pexels