Chatbots that perform the best on a traditional Turing Test are all extremely specialized 'bag of tricks' approaches. They can be surprisingly convincing, because they often use huge databases of real human responses to construct their own -- if you haven't already, I'd recommend giving Cleverbot a try[2].
However these chatbots often fail when an important continuity of facts is being discussed in context, where their parrot-like nature is exposed. Therefore I think this "TED XPRIZE" will be much easier to fool in this sense, because there's only two questions from the judges. This essentially removes the most difficult AI challenges of a traditional turing test.
Of course, succeeding at the "TED XPRIZE" would without a doubt require legitimate and significant advancements to the field of artificial intelligence and machine learning. Synthesizing a convincing talk/essay with an engaging narrative and central theme is no easy task (though limited successes already exist [3]).
But even now computers can beat humans in very specialized areas (and specialization is a key requirement to this). For example, we already have human level-facial recognition[4] and superhuman character recognition[5]. Similarly, while it would indeed be a legitimate AI advancement to be able to construct such a speech, I do not believe this would be any more a holy grail of AGI than character recognition and facial recognition. Instead, it would be incremental progress disguising itself as having already arrived.
[1] http://www.xprize.org/ted-rules
[3] http://www.geekosystem.com/journal-accepts-nonsense-paper/
[4] https://www.facebook.com/publications/546316888800776/
[5] http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.84.1...