Young readers may not remember, but cloud computing was once the future. The advent of unlimited computing and storage resources was one of the few technological "revolutions" worthy of its name.1 But the age of artificial intelligence has not only made the centralized cloud model obsolete, it also brings with it some risk to the people who use it and to all users.
The Consensus 2024 Artificial Intelligence Summit will be held in Austin, Texas, on Friday, September 31.
If that sounds a bit hyperbolic, think about a recently discovered vulnerability in the leading AI-as-a-service platform, Hugging Face. The vulnerability could allow a user-uploaded fake model to execute arbitrary code through the API and gain more control. Fortunately, it was discovered in time and doesn't seem to have a major impact on users - the researchers note that such vulnerabilities are "not unique. ""
The problem here is not artificial intelligence, but an outdated, centralized X-as-a-Service model that has no incentive to guarantee system security or develop applications needed by the market or regular users. The desired future for #AI , which would be safe, secure, reliable and above all able to use huge computing resources, can only be achieved by adopting cloud technologies and a decentralized revolution.
Giant companies such as Microsoft, OpenAI, Google and Amazon dominate the field of artificial intelligence as they have huge financial, human and computational resources to support large-scale operations.
This has a negative impact on the development of artificial intelligence and is completely contrary to its democratic potential. When algorithms and applications are created by a small group of developers at a $1 trillion dollar California-based company, they create a short-sighted, one-dimensional and incredibly subjective approach to AI agents. It affects everything from financial services to creativity..... Even human interaction. \n There is an equally compelling technical argument for monopolizing the AI market. AI must constantly acquire new data in the process of learning, including from other AI applications.
When it comes to artificial intelligence, the cloud model is a dangerous dead end.
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