The development of large language models (LLMs) like GPT-2 marked a significant turning point for OpenAI, showcasing the potential of AI.

With the advent of 10 trillion parameter models, we could see a leap in innovation similar to the transition from GPT-2 to GPT-3, which sparked a new era of AI companies.

With the release of GPT-3, it seems the sky is the limit for this new paradigm of scaling large language models.

GPT-4.5 is OpenAI's largest and most humanlike model to date, representing a significant step in scaling up unsupervised learning and achieving a deeper understanding of the world and human experience.

OpenAI revealed GPT-4.5 as a model capable of reasoning and systematically thinking through complex problems, clearly surpassing GPT-4 in mathematics, coding, and logical tasks.

GPT-3 made headlines by smashing benchmarks previously considered out of reach for AI, excelling in software engineering, math, and PhD-level science questions.

Research indicated that previous models like GPT-3 were undertrained; despite their size, they hadn't been trained on enough text to reach their full potential. For instance, Chinchilla, a model smaller than GPT-3, outperformed larger models by being trained on four times more data.

GPT-4.5 is potentially more than 10 times the size of GPT-4, representing a step forward in both pre-training and post-training processes.

The evolution of language models, particularly with the introduction of GPT-3, has demonstrated a significant leap in their ability to perform language tasks, even though they do not possess real-world knowledge.