students added them to GLUE in February 2019, they lasted just a few months before a BERT-based system from Microsoft beat them.Īs of this writing, nearly every position on the GLUE leaderboard is occupied by a system that incorporates, extends or optimizes BERT. BERT was getting numbers on many of the tasks that were close to what we thought would be the limit of how well you could do.” Indeed, GLUE didn’t even bother to include human baseline scores before BERT by the time Bowman and one of his Ph.D. “The general reaction in the field was incredulity. “That was definitely the ‘oh, crap’ moment,” Bowman recalled, using a more colorful interjection. On this brand-new benchmark designed to measure machines’ real understanding of natural language - or to expose their lack thereof - the machines had jumped from a D-plus to a B-minus in just six months. In October of 2018, Google introduced a new method nicknamed BERT (Bidirectional Encoder Representations from Transformers). If you can tell that “President Trump landed in Iraq for the start of a seven-day visit” implies that “President Trump is on an overseas visit,” you’ve just passed. The test was designed as “a fairly representative sample of what the research community thought were interesting challenges,” said Bowman, but also “pretty straightforward for humans.” For example, one task asks whether a sentence is true based on information offered in a preceding sentence. In an April 2018 paper coauthored with collaborators from the University of Washington and DeepMind, the Google-owned artificial intelligence company, Bowman introduced a battery of nine reading-comprehension tasks for computers called GLUE (General Language Understanding Evaluation). But Bowman wanted measurable evidence of the genuine article: bona fide, human-style reading comprehension in English. Sure, they had become decent at simulating that understanding in certain narrow domains, like automatic translation or sentiment analysis (for example, determining if a sentence sounds “mean or nice,” he said). I have also included a set-up explanation video so you can try these games out, and then learn the proper set-up if things don’t go so well.In the fall of 2017, Sam Bowman, a computational linguist at New York University, figured that computers still weren’t very good at understanding the written word. Rather than simply including all of the “weird” LSAT games that appeared in the very early years of the test, or the weird games of recent years, I tried to mix things up. I have compiled a list of some logic games that I believe are amongst the most difficult ever. What used to be medium games are the new easy games, what used to be hard games are today’s medium games, and today’s hard games can be new and weird.Īll this means is that you should pay a little more attention to difficult logic games. It appears that the LSAC is intentionally making the logic games section harder. Logic games skills can and should be improved with efficient test-prep, but gone are the days of a stress-free section. After a couple of months of good LSAT prep, test-takers could be sure that they’d walk into their official exam and get almost all of the questions right.īut things have changed in recent years. Although test-takers usually performed poorly on this section during their first initial diagnostic LSAT, logic games skills could easily be improved with some efficient practice. The logic games section used to be the easiest section of the LSAT for most test-takers.
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