Machine Learning
Also written: ML, Machine-learning technologies, Machine learning model, Machine learning framework, ML framework, Machine learning experiments, Transfer learning
Machine learning lets computers learn from data to make predictions or decisions without explicit programming.
Machine learning is a way for computers to learn without being directly told what to do. Instead of writing specific instructions for every possible situation, developers feed the computer lots of data. The computer then finds patterns in that data to perform a task.
For example, imagine teaching a computer to recognize pictures of cats. You would show it thousands of cat pictures. The machine learning system would learn what features make a cat a cat, like pointy ears and whiskers. Eventually, it could identify a cat in a new picture it has never seen before.
Machine learning (ML) is a field of artificial intelligence (AI) focused on building systems that can learn from and make decisions based on data. Unlike traditional programming, where rules are explicitly defined, ML algorithms infer patterns and relationships from training data to perform tasks such as classification, regression, or clustering. The core idea is to enable systems to improve their performance on a task with experience, often measured by a loss function.
Key ML approaches include supervised learning (learning from labeled data), unsupervised learning (finding patterns in unlabeled data), and reinforcement learning (learning through trial and error with rewards). Tradeoffs involve the amount of data required, computational resources for training, model interpretability, and the risk of overfitting or underfitting the data.
Machine learning is central to the advancements seen in frontier AI labs. The recent news highlights how ML enables systems like Microsoft Copilot and OpenAI's models to move beyond simple tasks, transforming industries like agriculture and business operations by learning from vast datasets.
- Learn about generative AIGoogle · Gemini Help Center ·
- Gemini Apps Privacy HubGoogle · Gemini Help Center ·
- The biggest AI mistake?Microsoft · Microsoft on YouTube ·
- How NVIDIA engineers and researchers build with CodexOpenAI · OpenAI News ·
- How AI trained on birds is surfacing underwater mysteriesGoogle · Google Research Blog ·
- AI helps John Deere transform agricultureOpenAI · OpenAI News ·
- 52: The success story behind PyTorchMeta · Meta Tech Podcast ·
- Fair for allGoogle · Google DeepMind: The Podcast ·
- Steven Bathiche: Microsoft Technical FellowMicrosoft · Behind The Tech with Kevin Scott ·
- Microsoft Copilot
- Microsoft Copilot leverages machine learning to enhance productivity and transform business processes, as indicated by discussions on AI transformation.
- OpenAI ChatGPT
- OpenAI utilizes machine learning extensively in its models, such as those powering applications that help transform industries like agriculture with AI.
- Artificial Intelligence
- AI is a broader field that encompasses machine learning
- Deep Learning
- Deep learning is a subfield of machine learning that uses artific
- Programming
- Programming involves writing explicit instructions for a computer t
The term 'machine learning' was popularized by Arthur Samuel in 1959, who defined it as a field of study that gives computers the ability to learn without being explicitly programmed. Source ↗
Use a tool like Google's Teachable Machine. Upload a few images of different objects (e.g., a pen, a mug). Train the model, and then test it by showing it new images to see if it can correctly identify them based on what it learned.
The Playbook: reusable how-tos, prompts, configs and tips pulled out of the news.
- PromptRole-play a student struggling with math for AI tutor simulationSimulate a student's math struggles and uncertainty for AI tutor evaluation. · 5 min
- TemplateReusable workflow templates for healthcare teamsTeams can create and share templates for common workflows like documentation or prior authorizations. · 15 min
- TemplateTemplate for building an AI tool tailored to your workA structured approach to defining and building a custom AI tool for specific business needs. · 15 min
- TemplateEvals CSV prompt list for agent skillsA CSV file template for listing prompts used in evaluating agent skills. · 20 min
- HeuristicDouble coding agent task completion with docs linksProviding coding agents with a documentation link significantly increases their task completion rate. · 2 min
Questions people ask
- How is machine learning different from regular computer programs?
- Regular programs follow explicit instructions written by humans. Machine learning programs learn to perform tasks by finding patterns in data, without needing every step to be pre-programmed.
- What kind of data is used for machine learning?
- Machine learning can use many types of data, including text, images, numbers, and sounds. The more relevant and high-quality the data, the better the machine learning model can perform.
First seen on Subvolts Jun 2, 2023. Updated Oct 12, 2026. Written by an AI model from the items above and reviewed against them weekly; report an error.