Observed Signal · Apr 18, 2024 · Technical Release · Source: Trending Topics · Impact: 3/5 · Sentiment: Neutral
AI Model Training Costs Soar Toward $200 Million
Stanford University's 2024 AI Index report reveals that training costs for frontier AI models have exploded. OpenAI's GPT-4 is estimated to have required $78 million in compute, while Google's Gemini Ultra is estimated at $191 million—a sharp contrast to the roughly $900 cost of training the original Transformer model in 2017. The report also found that the number of published foundation models more than doubled in 2023 to 149, with 65.7% being open source, up from 44.4% in 2022. On ten selected benchmarks, closed LLMs outperformed open models by a median of 24.2%. The US leads in producing notable AI models with 61, ahead of the EU (21) and China (15). The report was sponsored by Google and OpenAI.
Rising AI training costs and the performance gap between open and closed models have significant implications for AI-dependent industries, including advertising technology, which increasingly relies on foundation models.
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Key Takeaways & Evidence Grounding
- OpenAI's GPT-4 training consumed an estimated $78M in compute, while Google's Gemini Ultra cost around $191M.
- The number of published foundation models more than doubled in 2023 to 149, with 65.7% being open source (up from 44.4% in 2022 and 33.3% in 2021).
- Training the original Transformer model in 2017 cost roughly $900, versus RoBERTa Large at $160,000 in 2019.
- On 10 selected AI benchmarks, closed LLMs outperformed open models by a median of 24.2%.
- US institutions produced 61 notable AI models in 2023, ahead of the EU (21) and China (15).
Connected Companies & Entities
2 Entities mapped“So soll OpenAIs GPT-4 Rechenleistung im Wert von 78 Millionen Dollar für das Training benötigt haben....”
“während Googles Gemini Ultra sogar 191 Millionen Dollar verschlungen haben soll...”
Ontology Mapping & Concepts
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