As AI labs become beholden to the interests of investors and big tech companies, they may be incentivized to focus more on research with.
Big tech companies and venture capitalists are in the midst of a gold rush, investing astronomical sums into leading AI labs that are creating generative models. Last week, Amazon announced a $4 billion investment in AI lab Anthropic. Earlier this year, Microsoft invested a staggering $10 billion in OpenAI, which is now reportedly in discussions with investors to sell shares at a valuation of $80-90 billion.
Large language models (LLM) and generative AI have become hot areas of competition, prompting tech giants to strengthen their talent pool and gain access to advanced models through partnerships with AI labs. These partnerships and investments bear mutual benefits for both the AI labs and the tech companies that invest in them. However, they also have other less savory implications for the future of AI research that are worth exploring.Accelerated research and product integration
LLMs require substantial computational resources to train and run, resources that most AI labs don’t have access to. Partnerships with big tech companies provide these labs with the cloud servers and GPUs they need to train their models.
OpenAI, for instance, has been leveraging Microsoft’s Azure cloud infrastructure to train and serve its models, including ChatGPT, GPT-4, and DALL-E. Anthropic will now have access to Amazon Web Services (AWS) and its special Trainium and Inferentia chips for training and serving its AI models.
The impressive advances in LLMs in recent years owe a great deal to the investments of big tech companies in AI labs. In return, these tech companies can integrate the latest models into their products at scale, bringing new experiences to users. They can also provide tools for developers to use the latest AI models in their products without the technical overhead of setting up large compute clusters.
This feedback cycle will help the labs and companies navigate the challenges of these models and address them at a faster pace.Less transparency and more secrecy
However, as AI labs become embroiled in the competition between big tech companies for a larger share of the generative AI market, they may become less inclined to share knowledge.
