We say “AI” for everything: the spam filter, the chatbot writing poems, sometimes even the coffee machine that seems a bit too smart. Generative AI and machine learning are like a bike and a truck: both vehicles, but you don’t move a piano on a bike.
Machine learning: a fortune teller with a spreadsheet
Machine learning learns from examples to predict or classify: is this email spam? Will this customer leave? Will stock run out on Thursday? It’s a fortune teller who swapped the crystal ball for a spreadsheet. It answers with a label or a number, never a horoscope.
Generative AI: the intern who types faster than light
Generative AI creates new content: text, images, summaries, email drafts. It won’t tell you whether a customer will leave. It will write the letter to keep them. In three versions. With emojis if you insist.
Generative AI or machine learning: which one do you need?
- Anticipate (sales, breakdowns, late payments): machine learning, fed with your history.
- Write, summarise, extract (emails, minutes, incoming invoices): generative AI.
- Both: it happens, and they get along great. Like cousins at a wedding, before dessert.
A quick test to tell them apart: if the answer to your question is a number or a yes/no, think machine learning. If it’s a paragraph you’d otherwise have to write yourself, think generative AI. If it’s “a coffee”, think vending machine.
The limits (this is where we stop joking)
- A predictive model is never better than the data that fed it.
- Generative AI can invent facts with great confidence: check anything that matters.
Not sure which AI your business needs? It’s the first question in Octopote’s discovery workshop, asked without a crystal ball. Shall we talk? To see how software plugs together, read our article on APIs.
