The AGI Shift
by Ankush Das · Inc42SUMMARY
- AI is moving from answering questions to doing the work. As agents grow more autonomous, the bigger question is whether AGI has already arrived.
- Added to Saved Stories in Login
Imagine handing an AI agent a task you would normally give to a junior employee: open the company’s software, find the right customer record, fill in a form, check a few details and send the result back. You simply assign AI the job and let it work.
OpenAI claims to have achieved just that, with the launch of GPT-6 Astra earlier this month. Unlike a chatbot that simply responds to prompts, Astra can take on a task and work through a computer like a human would.
OpenAI calls Astra its most intelligent and aligned model yet. But what drew more attention was OpenAI president Greg Brockman’s proclamation of the arrival of “the AGI era” at a press briefing following the launch.
OpenAI is not alone in pushing AI towards greater autonomy. Zhipu, a major Chinese AI company, says its general language model, GLM, helped build the computing infrastructure it now runs on. Google DeepMind and Anthropic are also developing AI agents capable of taking action, albeit with their own limits and safeguards. But none of them has explicitly claimed that their models have achieved AGI.
If everyone is moving in the same direction, why is there still no consensus that the AGI era has arrived? Perhaps because there is no fixed definition of AGI, and no universally agreed threshold for what would count as reaching it.
Therefore, in this edition of The AI Shift, we explore whether we have already crossed the AGI threshold, and if not, how far we are from reaching it.
But first…
What Is AGI?
AGI stands for artificial general intelligence. But there is no universally accepted definition of what it actually means. OpenAI’s public document on its principles defines AGI as “highly autonomous systems that outperform humans at most economically valuable work”. Its benchmark is based on how much economically valuable work a system can do, rather than how it thinks.