Morgan Stanley: The Rise of Open-Weight AI Models to Accelerate AI Adoption by Reducing Costs

icon MarsBit
Share
This is the logo of the coin.
NVDA
----
AI summary iconSummary
Morgan Stanley said open-weight AI models such as Kimi K3, Qwen, and Llama will accelerate AI adoption by reducing costs, not diminishing the advantage of major players. The firm referenced the Jevons paradox, where efficiency gains stimulate increased demand. Open and closed models will coexist, with 63% of firms using both. NVIDIA is poised to benefit most from rising AI computing demands. Traders using open interest analysis should monitor changes in the risk-to-reward ratio as the market adjusts.

Huoxing Finance reports that on August 4, Morgan Stanley stated that the rise of open-weight AI models such as Kimi K3, Qwen, and Llama will accelerate AI adoption by reducing costs, rather than eroding the competitive advantages of industry leaders. The firm believes that lower-cost AI will drive broader enterprise adoption of AI technologies, citing the "Jevons Paradox" as evidence—that increased technological efficiency leads to greater overall demand. Morgan Stanley expects open-weight and proprietary models to coexist long-term, with 63% of enterprises already using both types. Additionally, the firm noted that regardless of which AI model architecture ultimately dominates, NVIDIA will be the biggest beneficiary, as demand for AI computing infrastructure continues to grow.

Source:Show original
Disclaimer: The information on this page may have been obtained from third parties and does not necessarily reflect the views or opinions of KuCoin. This content is provided for general informational purposes only, without any representation or warranty of any kind, nor shall it be construed as financial or investment advice. KuCoin shall not be liable for any errors or omissions, or for any outcomes resulting from the use of this information. Investments in digital assets can be risky. Please carefully evaluate the risks of a product and your risk tolerance based on your own financial circumstances. For more information, please refer to our Terms of Use and Risk Disclosure.