History of Large Language Models
3 bite-size cards · 60 seconds each
What is the History of Large Language Models?
Large language models didn't appear overnight. They emerged from decades of NLP research, with breakthroughs in 2017 (transformers), 2018 (BERT/GPT), 2020 (GPT-3), and 2022 (ChatGPT) each pushing capabilities dramatically forward. Understanding this arc helps make sense of where LLMs are heading next.
Sources: Anthropic Could Raise a New $50B Round at a Valuation of $900B
Anthropic, the company behind the AI assistant Claude, is reportedly in discussions to raise a staggering $50 billion. Current valuations place the company between $850 billion and $900 billion, according to insider sources. This funding round highlights the escalating financial stakes in the AI landscape.
The Scaling Laws That Shaped LLM Development
Between 2020 and 2024, LLM capabilities grew predictably with model size, training data, and compute — relationships formalized as scaling laws. These laws guided billions in AI investment, and their apparent limits in 2024–2026 triggered the shift to reasoning models that scale inference compute instead.
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