The Disruptive Potential of Large Language Models: Will They Kill Google Ads?

The recent conversations about large language models, such as ChatGPT, and the potential of them being “Google killers” have brought to light some interesting questions. How will Google pivot its ad engine to work with these AI-driven chat systems? What does this mean for content creators? What are the economics of running these models? Will this disrupt Google or will they simply evolve and make more money?

These questions have no easy answers. The training costs for large language models like GPT are enormous, and the inference costs are substantial too. Right now things like ChatGPT are very cool parlor tricks, but there’s absolutely no way to justify them in terms of the economics of running the service today. In addition, there is a lack of incentive for content creators - what value does ChatGPT give back to primary sources? Without an answer to this problem, it is difficult to see how ChatGPT can be economically viable in the long term.

However, it is impossible to predict just how efficient we’ll become at training/serving these models as most of the gains there are going to come from improved model architectures. It’s also unknown what sort of monetization strategies could emerge from using chat bots instead of search engines for information retrieval. We may end up seeing targeted ads injected into chat responses or even autogenerated YouTube channels explaining popular or trending topics that link back directly adsense pages - eliminating any revenue sharing with websites where Google Ads appear currently .

In conclusion, while many people believe large language models may disrupt Google’s current position in the market and make their AdSense platform irrelevant , we still don’t know exactly how things will play out in terms future economic viability or monetization strategies that could emerge from using such technology . Only time will tell if these ideas become reality , but until then we can only speculate on its potential impact on our current search engine landscape .

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