Inference
Inference is the process of running a trained AI model on new inputs to generate predictions or outputs, as opposed to training the model on data.
13 results
Inference is the process of running a trained AI model on new inputs to generate predictions or outputs, as opposed to training the model on data.
AI models whose weights, architecture, and training details are publicly released - enabling free use, modification, and self-hosting.
A database optimized for storing and searching vector embeddings - the backbone of AI-powered search and RAG systems.
Everything as a Service - the delivery model where any product or capability is offered via subscription over the internet instead of as a one-time purchase.
How to pick between GPT-4o, Claude 3.5, Gemini, Llama 3, and Mistral: a decision framework covering cost, context, and task performance.
Six proven strategies to cut LLM API spending without sacrificing product quality - from caching to model tiering to open-source alternatives.
The layered architecture of modern AI systems - from compute and foundation models to applications - and where startups should focus.
When to build custom AI vs buy an off-the-shelf solution - a practical framework for AI infrastructure decisions at each startup stage.
How DeepSeek changes the AI cost equation - and when startups should use DeepSeek-V3 and R1 instead of OpenAI or Anthropic.
Comparing the three leading AI API providers for startup use cases - pricing, strengths, weaknesses, and when to choose each.
When OpenClaw's local-first approach beats cloud AI agent platforms - a practical comparison of privacy, cost, and control tradeoffs.
When Alibaba's Qwen is a viable alternative to GPT for your startup - performance, pricing, licensing, and use cases compared.
A clear-eyed breakdown of AI startup costs - infrastructure, inference, people, and what unit economics actually look like at different revenue stages.