Generative AI, and ChatGPT in particular have been catnip to the tech press, the mainstream media, and the conversations of professionals in nearly every
I don’t know. The speed that these things blew up in becoming The Next Big Thing™️ kind of sets off my bullshit detectors.
I’m certainly not an expert in machine learning topics, but I suspect that the output of LLMs will never be able to output complex code that doesn’t require a lot of modification and verification.
See any advancements in automation from farming to manufacturing.
See, this is the kind of thing that makes my bullshit detectors go off. The comparison elevates this new tech to the same level of importance as past revolutionary shifts in industry. But this only seems justified if you can assume the rapid advancements in LLMs will continue at the same rate going forward, which not a given at all. Fundamentally, these models are trained to produce convincing output, not accurate output. There is no guarantee that high accuracy will be achieved with this approach.
For programming, I don’t see these LLMs any differently than previous advancements in tooling and in high level programming languages and frameworks. They will make it easier to rapidly prototype and deploy (shoddy) apps, but they will not be replacing devs who work at a low level high performance, or critical areas, nor will they be drastically reducing the workforce needed - at least not any more than other tooling advancements.
I don’t know. The speed that these things blew up in becoming The Next Big Thing™️ kind of sets off my bullshit detectors.
I’m certainly not an expert in machine learning topics, but I suspect that the output of LLMs will never be able to output complex code that doesn’t require a lot of modification and verification.
While it may not eliminate positions entirely, it will greatly reduce the number of positions needed.
See any advancements in automation from farming to manufacturing.
See, this is the kind of thing that makes my bullshit detectors go off. The comparison elevates this new tech to the same level of importance as past revolutionary shifts in industry. But this only seems justified if you can assume the rapid advancements in LLMs will continue at the same rate going forward, which not a given at all. Fundamentally, these models are trained to produce convincing output, not accurate output. There is no guarantee that high accuracy will be achieved with this approach.
For programming, I don’t see these LLMs any differently than previous advancements in tooling and in high level programming languages and frameworks. They will make it easier to rapidly prototype and deploy (shoddy) apps, but they will not be replacing devs who work at a low level high performance, or critical areas, nor will they be drastically reducing the workforce needed - at least not any more than other tooling advancements.
All just my opinion, of course. We shall see.