Microsoft vs Meta: How The OpenAI Saga Affects Their Competitive Positions
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Short-Term Impacts For Microsoft and Google
Some of OpenAI's customers are reportedly looking for the exit amid the chaos surrounding the artificial intelligence startup.More than 100 of OpenAI's current patrons have reached out to competitor Anthropic, which is backed by Amazon $Amazon(AMZN.US$ and Google ( $Alphabet-C(GOOG.US$ ), The Information reported, citing a person familiar with the matter. Other OpenAI customers have reached out to Google Cloud and Cohere, an OpenAI startup rival, the news outlet added.
This incident has made the market realize that exclusive models like OpenAI's GPT are too closely tied to a single company, which poses too much instability.The cloud computing industry is a typical example.
The struggle between open source and closed source
In the AI wave, there are two opposing factions: the "closed source faction" represented by companies such as OpenAI and Anthropic, whose large model technology details are not publicly disclosed and whose code is controlled by themselves; and the "open source faction" represented by Meta, whose code is publicly available and can be modified or even redeveloped within the scope of copyright restrictions.
Those who support the "open source faction" believe that it is beneficial for the rapid establishment and development of the ecosystem and can gather global strength to help AI models iterate quickly. Decentralization can also counteract excessive concentration of power.
However, those who support the "closed source faction" point out that open source is harmful to creators, as competitors can replicate their work, and there may be potential dangers from people using the most advanced AI models for malicious purposes.
OpenAI's brief palace drama highlighted the imperfect governance. Some technical personnel who care about stability may be more willing to join Meta's AI research laboratory. Compared with OpenAI's GPT large model, Meta's open source model has little difference in capabilities and is therefore highly cost-effective. It is an ideal channel for companies to achieve AI configuration diversification. Enterprises that rely on proprietary models can deploy open source models to quickly minimize business risks.
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