The hype around generative AI is outpacing reality. This pattern mirrors past tech booms, like the dotcom and blockchain eras, where a few technologies succeed, but most fail. Many people lose money, yet the cycle persists due to the allure of quick wealth. Those claiming GenAI will become AGI should remember Carl Sagan's words: "Extraor…
The hype around generative AI is outpacing reality. This pattern mirrors past tech booms, like the dotcom and blockchain eras, where a few technologies succeed, but most fail. Many people lose money, yet the cycle persists due to the allure of quick wealth. Those claiming GenAI will become AGI should remember Carl Sagan's words: "Extraordinary claims require extraordinary evidence." Without such evidence, the focus should shift from hype to substantiation. However, high costs for new models often necessitate continued hype to secure funding. Despite recognizing its value, I find the product's cost unjustifiable based on my experience over the past 18 months.
Real-life applications demand 99.99% certainty, something statistical models alone can't provide. If a light switch worked only 90% of the time, we'd avoid using it if alternatives existed. We currently have other technologies that give us better reliability in most scenarios. I believe the present models won't achieve what the hype suggests. We need different or hybrid models that combine statistical and rule-based or other approaches to reach the next phase.
The hype around generative AI is outpacing reality. This pattern mirrors past tech booms, like the dotcom and blockchain eras, where a few technologies succeed, but most fail. Many people lose money, yet the cycle persists due to the allure of quick wealth. Those claiming GenAI will become AGI should remember Carl Sagan's words: "Extraordinary claims require extraordinary evidence." Without such evidence, the focus should shift from hype to substantiation. However, high costs for new models often necessitate continued hype to secure funding. Despite recognizing its value, I find the product's cost unjustifiable based on my experience over the past 18 months.
Real-life applications demand 99.99% certainty, something statistical models alone can't provide. If a light switch worked only 90% of the time, we'd avoid using it if alternatives existed. We currently have other technologies that give us better reliability in most scenarios. I believe the present models won't achieve what the hype suggests. We need different or hybrid models that combine statistical and rule-based or other approaches to reach the next phase.