Gartner AI Hype Cycle: Autonomous AI Is on the Way (Apparently)
Gartner's 2024 Hype Cycle shows generative AI entering disillusionment, while autonomous AI development accelerates. Critics argue the Hype Cycle misrepresents tech trends, warning of potential financial sinkholes in AI investments.
Read original article
Gartner has published its 2024 Hype Cycle for Emerging Technologies, indicating that generative AI has moved past the "peak of inflated expectations" and is now entering the "trough of disillusionment." Despite this, the report suggests that the development of autonomous AI is accelerating, with research labs working on AI agents capable of interacting with their environments to achieve specific goals. However, the article critiques Gartner's Hype Cycle, arguing that it has historically been unreliable and often misrepresents the trajectory of new technologies. The commentary highlights skepticism about the actual progress of AI, likening the Hype Cycle to a narrative structure that does not reflect reality. It suggests that, similar to past tech trends like blockchain, the current AI hype may lead to significant financial investments without substantial returns, characterizing it as a "sinkhole" for capital rather than a foundation for future advancements.
- Gartner's 2024 Hype Cycle indicates generative AI is in a phase of disillusionment.
- Autonomous AI development is reportedly accelerating, despite skepticism about its current capabilities.
- The Hype Cycle has been criticized for its historical inaccuracies regarding technology trends.
- The commentary suggests that the AI investment landscape may not yield significant returns.
- The article draws parallels between current AI hype and past tech trends like blockchain.
Related
Pop Culture
Goldman Sachs report questions generative AI's productivity benefits, power demands, and industry hype. Economist Daron Acemoglu doubts AI's transformative potential, highlighting limitations in real-world applications and escalating training costs.
Goldman Sachs: AI Is overhyped, expensive, and unreliable
Goldman Sachs questions generative AI's economic viability due to high costs and limited benefits. Experts doubt AI's transformative impact, citing unreliable technology and skepticism about scalability and profitability. Venture capital analysis raises concerns about revenue generation.
VCs are still pouring billions into generative AI startups
Investments in generative AI startups reached $12.3 billion in H1 2023, focusing on early-stage ventures. Challenges include legal issues and rising costs, making profitability elusive for many companies.
Why the collapse of the Generative AI bubble may be imminent
The Generative AI bubble is predicted to collapse soon, with declining investor enthusiasm and funding, potentially leading to failures of high-valued companies by the end of 2024.
What comes after the AI crash?
Concerns about a generative AI bubble highlight potential market corrections, misuse of AI technologies, ongoing harms like misinformation, environmental issues from data centers, and the need for vigilance post-crash.
3 commentsWhile I agree that Gartner's "hype" analysis is generally over-optimistic, TFA is over-pessimistic in an entirely unsubstantiated manner and doesn't add anything of value to the discussion.
Related
Pop Culture
Goldman Sachs report questions generative AI's productivity benefits, power demands, and industry hype. Economist Daron Acemoglu doubts AI's transformative potential, highlighting limitations in real-world applications and escalating training costs.
Goldman Sachs: AI Is overhyped, expensive, and unreliable
Goldman Sachs questions generative AI's economic viability due to high costs and limited benefits. Experts doubt AI's transformative impact, citing unreliable technology and skepticism about scalability and profitability. Venture capital analysis raises concerns about revenue generation.
VCs are still pouring billions into generative AI startups
Investments in generative AI startups reached $12.3 billion in H1 2023, focusing on early-stage ventures. Challenges include legal issues and rising costs, making profitability elusive for many companies.
Why the collapse of the Generative AI bubble may be imminent
The Generative AI bubble is predicted to collapse soon, with declining investor enthusiasm and funding, potentially leading to failures of high-valued companies by the end of 2024.
What comes after the AI crash?
Concerns about a generative AI bubble highlight potential market corrections, misuse of AI technologies, ongoing harms like misinformation, environmental issues from data centers, and the need for vigilance post-crash.