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They still require a human to know what the problem is and give the right command.
How much more could be achieved?
But lets get real, are we really that close to AGI?
And even if so, should we look past agents now and wait for the promise of AGI?
Dhaval Jadav is the Global CEO and Co-Founder of alliant.
Chris Stephenson is the Managing Director of Intelligent Automation, AI & Digital Services at alliant.
Reasoning models likeOpenAIs o1 and Xs Grok 3, are designed to think through problems before they respond.
The human mind, however, is much more sophisticated than a reasoning machine.
Reasoning models dont solve the three biggest problems with achieving AGI.
The first problem is AI models, even reasoning models, need to be continually updated and trained.
That requires continual human oversight to reinforce the AIs logic.
The second problem is that current AI models cannot assimilate information or adapt to novel situations.
Finally, the biggest problem is that AIs are unable to form unique ideas.
AI thought is confined to thedatait was trained on.
To put it another way, AI can only restate concepts that already existed.
We are struggling to find a way for AIs to come up with anything original.
Dont mistake AI agents as some sort of magic Easy Button, though.
That means you oughta create underlying automations for your AI to execute in pursuance of its objective.
Recruiting and training people is not only expensive but continuous no matter the role.
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The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc.
