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Gemini Ultra Training Costs in 2023 Neared $200 Million, More Than 2X GPT4

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By Edith Muthoni

Updated May 14, 2024

As the demand for cutting-edge AI models grows, so does the investment required to develop and train them. According to Stocklytics.com, Google allocated an astounding $191 million to train the ingenious Gemini Ultra model in 2023. This reflects the immense financial investment required to push the boundaries of artificial intelligence. Notably, this figure significantly exceeds the training costs for GPT-4, which amounted to $78 million during the corresponding period.

Stocklytics financial analyst Edith Reads comments:

The astronomical training costs pegged on Google’s new foundation model underscores the underlying cost pressure of developing new advanced technologies. However, the cost burden is a pain worth investing in as more tech giants augment their efforts to expand their AI network and develop new language models, including Microsoft and Meta.

Stocklytics financial analyst Edith Reads

Training Costs for Foundation Models

The era of expensive foundation models started in 2017 with the release of the Google Transformer, rounding up to a rough estimate of $930 before the gradual transition to BERT-Large, another Google parody whose training bill shot up to $3,288. Meta soon took over from Google, developing the RoBERTa Large, coming off with a notable $160,018 expenditure. 

The trend of substantially augmented training costs raged on with GPT 3, costing Open AI millions and adding more than $4 million to its expenditure belt.

Soon after, many AI foundation models mushroomed with escalated developing costs, including the GPT4 model, whose total training cost nearly surpassed the $100 million mark. 

While this model was an outstanding addition to the AI community, the Gemini Ultra, Google’s latest model, will out shadow nearly all of the model’s achievements with over 50 billion petaFLOPS embedded in its infrastructure, hinting at faster training and adaptability features.

In 2023, the release of Gemini Ultra marked just one among the 149 foundation models, surpassing the previous year’s record launch by more than double. Notably, 66% of these models were open-sourced, indicating an anticipated surge in the growth of AI technologies due to the availability of source codes. Leading the charge in model development, Google added 18 to its roster, closely followed by Meta with 11 and Microsoft with 9.

What does the Creation of Gemini Ultra Mean For its Users and the Future of AI?

Gemini Ultra’s multimodal capabilities are a game-changer for its users. With revamped multilingual capabilities, the AI model can break down communication barriers with its advanced translation power. It can even translate sign language in real time, generate audio descriptions for images, and allow for voice control of devices. Gemini Ultra can also analyze your code, suggest improvements, and develop new snippets in various languages, making coding more straightforward.

The start of these remarkable models only fuels AI competition among these tech giants and could lead to the rise of even better-quality AI models as these tech firms brawl for the top spot in the AI space.

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