That’s what you will find out after reading this story:
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The world is looking at the forecasts of exclusivity or when artificial intelligence (Agi) will come. Some experts predict that this will never happen, while others indicate their calendar in 2026.
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A new analysis of macro surveys in the last 15 years shows where scientists and industry experts have been following the question and how their forecasts have changed over time, especially after large language models such as Chatgpt.
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Although the forecasts vary in almost half a century, most agree than AGI will arrive by the end of 21 yearsSt Century.
Since the emergence of large language models (LLM), which now has taken advantage of every corner and whim of our digital life, scientists, experts, industrial leaders and almost everyone else have a certain opinion on AI and where it leads.
Some researchers, who have explored the emergence of machine intelligence, believe that exclusivity is the theoretical moment when a machine surpasses a person in intelligence intelligence – it can occur over decades.
At the other end of the forecasting spectrum is Anthropic CEO who thinks we are right to the threshold – disappear It’s about about 3 months;
A new analysis of “8,590 scientists” leading to entrepreneurs and community forecasts “is trying to understand all the confusing forecasts that exist today and follow these forecasts over time.
Although this survey deals with different AI thresholds (such as artificial general intelligence (AGI) and AI Superintelgence), the AI industry leaders were essentially more of their own forecasts. However, most respondents thought AGI would probably happen in the next half century.
However, this AGI arrival time and exclusivity have fundamentally changed when the first LLM has arrived in the last few years.
“Current research on AI researchers predicts AGI around 2040,” the report states. “However, just a few years before the progress of the fast large language models (LLM), scientists predicted about 2060 businessmen are even larger, predicting this around ~ 2030”.
Macroanalysis also provides some insights on why many experts believe that AGI is inevitable. The first thing is that, unlike human intelligence, the intelligence of the machine does not seem to have any limits – at least anything that has not yet been discovered. As the calculation power doubles every 18 months (the concept, known in computer engineering circles as the Moore law), LLM should quickly achieve calculations per second, which is equal to human intelligence. The report also states that if the calculation has ever hit a certain engineering wall, Quantum Computing could help find out.
“Most experts believe that during this decade, Moore’s law ends,” the report states. “The unique nature of quantum calculation can be used to effectively train nerve networks, currently the most popular AI architecture in commercial programs. Ai algorithms operating on stable quantum computers have the ability to unlock exclusivity.”
However, not everyone thinks that Agi is the dead certainty. Some experts say that human intelligence is more multifaceted than what the current definition of AGI describes. For example, some AI experts think about the human mind In terms of eight intelligencesof which “logical and mathematical” is only one (together exists, for example, interpersonal, intrapersonal and existential intelligence).
Deep learning pioneer Yann Lecun believes that AGI should be transformed into “advanced machine intelligence” and states that human intelligence is too specialized to replicate. The report also states that while AI can be an important means of creating new discoveries, it cannot independently make these discoveries.
“More intelligence can be better planned and controlled by experiments that allow more discoveries per experiment,” the report states. “Even the best machine that analyzes existing data may not be found to find cancer healing.”
Although the forecasts of individual experts and scientists AGI vary by about half a century, the message is clear: human society will inevitably face incredible changes due to these algorithms.
Will these changes be good or bad? Well, it is up to us.
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