UK Algoshambles, Neuralink, GPT-3 and Intelligence
Episode 16 of the Machine Learning Street Talk (MLST) podcast, hosted by Machine Learning Street Talk (MLST), titled "UK Algoshambles, Neuralink, GPT-3 and Intelligence" was published on September 7, 2020 and runs 94 minutes.
September 7, 2020 ·94m · Machine Learning Street Talk (MLST)
Summary
This week Dr. Tim Scarfe, Dr. Keith Duggar and Yannic "Lightspeed" Kilcher respond to the "Algoshambles" exam fiasco in the UK where the government were forced to step in to standardise the grades which were grossly inflated by the schools. The schools and teachers are all paid on metrics related to the grades received by students, what could possibly go wrong?! The result is that we end up with grades which have lost all their value and students are coached for the exams and don't actually learn the subject. We also cover the second Francois Chollet interview on the Lex Fridman podcast. We cover GPT-3, Neuralink, and discussion of intelligence. 00:00:00 Algoshambles 00:45:40 Lex Fridman/Chollet: Intro 00:55:21 Lex Fridman/Chollet: Neuralink 01:06:28 Lex Fridman/Chollet: GPT-3 01:23:43 Lex Fridman/Chollet: Intelligence discussion
Episode Description
This week Dr. Tim Scarfe, Dr. Keith Duggar and Yannic "Lightspeed" Kilcher respond to the "Algoshambles" exam fiasco in the UK where the government were forced to step in to standardise the grades which were grossly inflated by the schools. The schools and teachers are all paid on metrics related to the grades received by students, what could possibly go wrong?! The result is that we end up with grades which have lost all their value and students are coached for the exams and don't actually learn the subject. We also cover the second Francois Chollet interview on the Lex Fridman podcast. We cover GPT-3, Neuralink, and discussion of intelligence.
00:00:00 Algoshambles
00:45:40 Lex Fridman/Chollet: Intro
00:55:21 Lex Fridman/Chollet: Neuralink
01:06:28 Lex Fridman/Chollet: GPT-3
01:23:43 Lex Fridman/Chollet: Intelligence discussion
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