An AI FAQ
Let's demystify some common tech terms so you can level up your AI knitting skills! When we mention things like "artificial intelligence" and "neural networks" it sounds super complex. But most of these concepts are pretty straightforward once explained in simple terms. Read on for a cheat sheet of frequently asked questions about the language of AI knitting.
What is AI?
AI just stands for artificial intelligence. It refers to computer systems that can perform tasks that normally require human thinking - like recognizing patterns, interpreting data, learning from experience, and making decisions. With AI, we can teach computers how to design knitting stitches, generate images, and help us to write about them.
What are large language models (LLMs)?
LLMs like Claude are AI systems trained on massive amounts of text data to generate human-like writing. They learn the statistical patterns and relationships between words to predict probable sequences of language. With billions of parameters, LLMs can conversate, summarize, compose creative text, and more based on the capabilities they were trained for. It's like knitting a giant sweater using every stitch pattern ever published - you'll learn to knit just about anything! LLMs allow AI assistants like myself to have natural conversations and be helpful to humans.
What are algorithms?
Algorithms are just sets of instructions that tell a computer how to do something step-by-step. They're like knitting patterns that explain exactly how to stitch a design. Developers could create algorithms to analyze stitch patterns, learn about knitted fabrics, and produce new designs that improve over time.
How does natural language processing work?
Natural language processing, or NLP for short, is how AI can understand and generate human languages. It's like having a research assistant read and summarize a giant library of knitting books to uncover insights about stitches, techniques, and cultural references. This allows AI to have text conversations and give knitting advice.
What’s the difference between machine learning and deep learning?
With machine learning, algorithms analyze data to identify patterns, learn, and make decisions without human input. Deep learning uses neural networks modeled like the human brain to create more complex connections in data. It's the difference between following a basic sweater pattern and designing your own creative mash-up knit!
What are neural networks?
Neural networks mimic how neurons in our brains process information and recognize relationships. The AI systems could generate new knitting designs using neural networks to analyze huge amounts of stitch pattern data.
How does image and pattern recognition work?
AI can be trained to identify and understand visual information like photos, videos, and knitting patterns. By scanning many examples, it learns to recognize cables, lace, Fair Isle and other knitting techniques. It's like an experienced knitter looking at stitch patterns and understanding how they're constructed.
What is a blockchain?
Blockchain is technology that records data securely in blocks that link together in order like stitches in a row. This creates transparency so you can trace a knitted piece back to its raw materials - from sheep to finished sweater!
What are AI Hallucinations?
Just like when we're knitting late at night and our tired eyes momentarily play tricks on us by imagining a mistake in the stitches that's not actually there, an AI system working to interpret extensive data can sometimes fleetingly "hallucinate" and think it perceives something which doesn't exist; researchers call those glitches "AI hallucinations."
Much as we blink a few times and realize our variegated yarn didn't actually drop a stitch, if challenged the AI quickly corrects itself and moves on from those over-interpretations. They are just momentary illusions in a sea of noisy data rather than flaws in perception.