The road ahead
The forthcoming era of generative AI models offers a plethora of intriguing opportunities and unparalleled progression, yet it is interspersed with numerous uncertainties. As discussed in this book, many breakthroughs have been accomplished in recent months, but successive challenges continue to linger, mainly pertaining to precision, reasoning ability, controllability, and entrenched bias within these models. While grandiose claims of superintelligent AI on the horizon may seem hyperbolic, consistent trends predict sophisticated capabilities sprouting within a few decades.
On a technical level, generative models like ChatGPT often function as black boxes, with limited transparency into their decision-making processes. A lack of model interpretability makes it difficult to fully understand model behavior or to control outputs. There are also concerns about potential biases that could emerge from imperfect training data. On a practical level, generative models require...
