2023 is the year AI integration becomes a product requirement rather than a differentiator.
GPT-4 launches in March 2023 with multimodal inputs, significantly improved reasoning and a substantially higher capability ceiling. The model passes the bar exam in the 90th percentile, writes working code for non-trivial problems and reasons through multi-step problems more reliably than any previous public model. The API becomes the infrastructure layer for a new category of AI-native products.
Meta releases Llama and Llama 2, bringing open-weight large language models competitive with commercial alternatives into reach of any team with GPU access. For enterprise teams with data privacy requirements, on-premises LLM deployment becomes a viable option for the first time.
Every major software vendor ships an AI integration. Microsoft 365 Copilot, Google Workspace AI, Salesforce Einstein GPT and dozens of vertical SaaS products embed language model capability directly into existing workflows. Retrieval-Augmented Generation (RAG) emerges as the dominant pattern for grounding language model outputs in domain-specific data. Vector databases — Pinecone, Weaviate, Chroma — see rapid adoption. The modern AI application stack is assembled in 2023.