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Hybrid AI and apps will be in focus in 2024, says Goldman Sachs CIO

Only the richest companies such as OpenAI can build 'foundation models,' like GPT-4. The rest of the corporate world will need to build smaller, more-focused programs that tie into the foundation models.
Written by Tiernan Ray, Senior Contributing Writer
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This year in artificial intelligence will be dominated by "hybrid" AI, and by the rise of applications running on top of large language models, according to a year-outlook interview disseminated by investment bank Goldman Sachs featuring its chief information officer, Marco Argenti.

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"Hybrid AI is where you are using these larger models as the brain that interprets the prompt and what the user wants, or the orchestrator that kind of spells out tasks to a number of worker models specialized for a specific task," said Argenti, referring to "foundation" models such as ChatGPT

m-argenti-headshot

Goldman Sachs CIO Marco Argenti

Goldman Sachs

It will be too expensive for any companies other than the world's richest to build such large programs, contends Argenti. Therefore, most enterprises will content themselves with building smaller neural nets, either in their own data centers or in cloud computing services, trained on their proprietary data. 

The idea of specialized models fine-tuned with corporate data aligns well with the current trend to string together functionality, such as with LangChain, an open-source framework built on top of generative AI

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"Most companies in 2024 are going to focus on the proof-of-concepts that are likely to show the highest return," said Argenti of the likely roll-out of hybrid AI.

In addition to hybrid structures, Argenti sees 2024 heralding a new class of third-party applications built on top of the foundation models. 

"If you think of those [foundation models] as operating systems or platforms, there's a whole world of applications that haven't really emerged yet around those models," said Argenti. 

"There's a great opportunity for capital to move towards the application layer, the toolset layer. I think we will see that shift happening, most likely as early as next year."

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The need to coordinate security across different parties is a large issue, Argenti emphasized. 

"Looking ahead, it will be important to continue to foster an environment that encourages collaboration between players, encourages open sourcing of the models when appropriate, and develops appropriate principle-based rules designed to help manage potential risks including bias, discrimination, safety-and-soundness, and privacy," said Argenti. "This will allow the technology to move forward so that the US will continue to be a leader in the development of AI."

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