GPT-4
OpenAI's most widely deployed frontier model, released in March 2023, which brought significant improvements in reasoning, coding, and multi-modal capabilities over GPT-3.5.
GPT-4 passed the bar exam in the 90th percentile, scored in the 88th percentile on the LSAT, and achieved a 5 on multiple AP exams. Training reportedly cost $78-191 million and consumed 3,600 MWh of electricity. GPT-4V (Vision) added image understanding, and GPT-4 Turbo expanded the context window to 128K tokens. The model is widely reported to use a mixture-of-experts architecture. GPT-4 powers ChatGPT Plus, Microsoft Copilot, and thousands of enterprise applications.
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Related Terms
Artificial General Intelligence (AGI)
A hypothetical form of AI that can understand, learn, and apply knowledge across any intellectual task at or above human level, rather than being specialized for specific tasks.
AI Compute
The computational resources — primarily GPU and TPU processing power — required to train and run AI models, typically measured in FLOP (floating-point operations) or GPU-hours.
Capex (Capital Expenditure)
Long-term investment spending by companies on physical assets like data centers, GPU clusters, and networking infrastructure — the backbone of AI deployment at scale.
ChatGPT
OpenAI's conversational AI assistant, launched in November 2022, which catalyzed the current generative AI boom by demonstrating the capabilities of large language models to a mainstream audience.
Data Center
A facility housing computer systems and infrastructure used to process, store, and distribute data — increasingly built specifically for AI training and inference workloads.
Fine-Tuning
The process of further training a pre-trained AI model on a specific, smaller dataset to specialize it for a particular task or domain, requiring far less compute than training from scratch.
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