Who do you believe when you talk about the potential effect of artificial intelligence? An MIT Nobel Prize -winning economist or former CEO of the world’s largest tech company?
MIT economist Daron Asimoglu says for his share that the current publicity is at the top. AI can automatically automate only 5% tasks and add only 1% to global GDP in the coming decade, he recently said in MIT Slone presentationAcemoglu also said that AI’s capacity is less clear than the Internet when it began to spread in the 1990s. Currently, he said, AI is seen as a cost -cutting tool as a new force for innovation, as the Internet in its early days.
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At the same time, former Google CEO and president Eric Schmid believes that, if anything, we are reducing AI and not reducing its full, widespread effects. “The arrival of non -Human intelligence is a very big thing,” that told Recently a TED conference. He Repeated The same number at a conference in July. Essentially, AI has become adept at developing solutions to problems – it is never considered by humans.
Esemoglu said that in the overheepd side, “the industry has not produced applications that are important for the production process or to generate new goods and services that are going to be extremely valuable,” Esimoglu said. He said that the rise of commercial internet has had more impact. Even the scenario in which machines will eventually do cognitive function, “It is not clear how you are going to get AI equipment in the production process.”
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The current status of art in AI has still been re -accused for the future tasks, which do not require high level of social interaction and decision, they continued. Broadly 20% of the economy is “either to be automated in AI’s crosshair or can be prominently increased by AI input.”
On the other hand, Schmid says that AI is also leading the economic model at the forefront. He said, “There are assumptions that we will end with an increase of 30% per year with an increase of 30%.” This is beyond the realm of traditional economics, as economists have never seen such benefits. And the speed is accelerating. “As this stuff happens quickly, you will forget what was true two years ago or three years ago,” Schmit said.
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Acemoglu is more doubted about such claims and that it will be some time ago when AI is ready to handle businesses in a deep way. “Do you really think in three, four, five years time you are going to do one (artificial general intelligence or AGI) that can do the functions without any human supervision – all your accounting, or all your marketing?” He asked. “With current architecture, what we can do is the best can copy human decisions.”
He said that “We are not developing AI in the best possible way. This is the best way to work with human decision manufacturers.
There are a lot of voices that claim that AI is different, more darker, and the world compared to previous technology waves. Is changing. Nevertheless, it is also noteworthy to anyone familiar with the Gartner Hype Cycle that before implementation, all the techniques of all Ballu will be covered and produced well on top of the hyp wave and are producing – production – production – for a slide for a slide “the trough of disillusionment.” But eventually the said technology will gain land as the implementation begins to show their values, and the less’ sexy “productivity plateau begins. At that point, something else that is relatively unused is being hypnotized.
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So, what to do a technique or professional professional?
Should you follow publicity and avoid the fear of disappearance (FOMO) and fall back, or move carefully? It is safe to assume that no AI is going to tear its existing system and analytics packages immediately in the hope of pushing the ladder. There are thousands of organizations that still rely on their mainframe for main commercial processes.
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But at the same time, it is clear that a lot of money is flowing for AI – not lost on a fact vendors, of course. AI spending increased by $ 13.8 billion in 2024, over $ 6 × 2.3 billion spent in 2023, according to Data From Menlo Ventures. Nevertheless, one of the officers in his survey does not have a clear vision for the direction of their AI strategy.
AI has been overheep as a solution to everything, yet underhip as an underlying platform will provide many tasks in less, sexy, and more behind ‘Scanus Way.
1. Avoid fomo mesh
It can be forgiven to feel as if the whole world around them is moving forward on AI. Actually, everyone is still trying to learn as much as possible about technology and may be surprised where it can go. Before the huge amount of money is spent, decision -makers need to consider whether more traditional systems can also work.
2. Work closely with business
Do they really need advanced AI, or have a more strong future analytics trick? Include employees in the processes of identifying areas required to improve, and listen to their ideas about goods and services that can help in production and distribute AI.
3. Be familiar with new technology development
The availability of large language models is really surprising, with new updates, and the announcement of capabilities seems every week. Fortunately, they are quite interchangeable. But remember, today’s amazing LLM can be small potatoes after one year from now.
4. Keep an eye on what others are doing with technology
Through user groups, forums and customer celebrations, one may understand that AI is breaching the success of its companies and where it can be a dood.
5. See AI as enhancing human skills, not to replace them
Find out that AI is better than humans, and where humans are better than AI – not only cost cuts.
6. Develop new types of goods and services an AI system can provide
Unlike only cut cost cuts or trying to change human roles with chatbott. In many cases, generic AI is used only as a new type of search engine, not as a generator of new goods and services. The world requires more health, educational and financial services.
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