AI models
Also written: AI systems, Models, Proprietary models, Model architecture, Science AI models, AI for science models, ML model, Machine learning model
AI models are computer programs trained on data to perform tasks like writing, answering questions, or solving problems.
AI models are computer programs that have been trained on vast amounts of information. This training allows them to learn patterns and relationships within the data, enabling them to perform specific tasks.
Think of it like teaching a student by showing them many examples. For instance, an AI model trained on millions of books can learn to write stories, answer questions about history, or even translate languages. The more data and the better the training, the more capable the model becomes at its assigned tasks.
AI models, often referred to as neural networks or large language models (LLMs) in current contexts, are computational systems designed to process information and generate outputs. They are trained on massive datasets using algorithms that adjust internal parameters to minimize errors in prediction, classification, or generation tasks. The architecture and training methodology significantly influence their capabilities and limitations, with ongoing research focusing on efficiency, reasoning abilities, and multimodal understanding.
AI models are central to the latest advancements and challenges in frontier AI. Companies are releasing faster, cheaper versions of their models to make AI more accessible, while also grappling with security risks and the philosophical implications of increasingly capable systems.
- How Microsoft’s New Office Chief Fixed Copilot and Won Over NadellaMicrosoft · The Information ·
- bolt Gemini 3.5 Flash-LiteGoogle · Gemini Models ·
- spark Gemini 3.6 FlashGoogle · Gemini Models ·
- Gemini 2.5 Flash LiveGoogle · Gemini Models ·
- OpenAI's Altman: Ascribing religion to models a "safety issue"OpenAI · Axios AI ·
- Oxford lets OpenAI train its AI models on Bodleian libraryOpenAI · The Guardian AI ·
- Accenture Will Help Anthropic Test AI Model SafetyAnthropic · Bloomberg Technology ·
- Google says its Gemini AI model hacked three other companiesGoogle · The Guardian AI ·
- SpaceX Discusses Buying Data for AI Models From Failed StartupsxAI · Bloomberg Technology ·
- Anthropic CEO Says It’s Time to Slow AI Model AdvancesAnthropic · Bloomberg Technology ·
- Building Africa’s AI future on trustMicrosoft · Microsoft Source ·
- GLM-5.2 vs MiniMax-M3: Opus Has REAL COMPETITION (Model Stacking)Anthropic · IndyDevDan ·
- Who decides when AI is too dangerous?Anthropic · Decoder with Nilay Patel ·
- SpaceX’s IPO Triumph, Anthropic’s Fable Fumble, OpenAI’s Price WarAnthropic · Big Technology Podcast ·
- We’re launching the Google DeepMind Accelerator program in Asia Pacific to tackle environmental risksGoogle · Google DeepMind Blog ·
- 85: Reel Friends: Building Social Discovery that Scales to BillionsMeta · Meta Tech Podcast ·
- Building AI for better healthcare - Episode 14OpenAI · The OpenAI Podcast ·
- Accelerating discovery in India through AI-powered science and educationGoogle · Google DeepMind Blog ·
- AI literacy resources for teens and parentsOpenAI · OpenAI News ·
- Smaller, Faster, Cheaper & The Story of Flash 8BGoogle · Google AI: Release Notes ·
- Answering quantum physics questions with OpenAI o1OpenAI · OpenAI News ·
- Decoding genetics with OpenAI o1OpenAI · OpenAI News ·
- Anthropic Claude
- Anthropic is having its AI model safety tested by external experts before launch.
- Google Gemini
- Google is releasing faster, cheaper versions of its Gemini AI models, like Gemini 3.5 Flash, to enable more responsive AI applications.
- Microsoft Copilot
- Microsoft explored paying rivals for AI models to improve Copilot's performance.
- OpenAI ChatGPT
- OpenAI is training its AI models on historical data from the Bodleian library and discussing safety concerns around attributing consciousness to models.
- Algorithm
- An algorithm is a set of rules or instructions a computer follows to
- Software
- Software is a broad term for computer programs, whereas an AI model is
- Database
- A database stores information, while an AI model uses data to learn an
The concept of artificial intelligence models has roots in early machine learning research, with significant advancements driven by neural network architectures like transformers, popularized by Google's 2017 paper 'Attention Is All You Need'. Source ↗
Ask ChatGPT or Google Gemini to explain a complex scientific concept, like quantum entanglement, in simple terms. Then, ask it to explain it again as if you were a 10-year-old. This demonstrates the model's ability to adapt its output based on your request.
The Playbook: reusable how-tos, prompts, configs and tips pulled out of the news.
- Cost tipLeverage open-weight models for significant cost savingsUtilize open-weight models like GLM-5.2 and MiniMax-M3 for substantial cost reductions compared to proprietary models. · 5 min
- 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
Questions people ask
- How do AI models learn?
- AI models learn through a process called training, where they are fed large amounts of data and adjust their internal parameters to identify patterns and make predictions.
- What can AI models do?
- AI models can perform a wide range of tasks, including generating text and images, answering questions, translating languages, writing code, and solving complex problems.
- Are AI models conscious?
- No, current AI models are not conscious. They are sophisticated pattern-matching systems that simulate understanding and generation based on their training data.
First seen on Subvolts Sep 12, 2024. Updated Oct 17, 2026. Written by an AI model from the items above and reviewed against them weekly; report an error.