Step 1 Google collects a bunch of playlists. Bard classifies them
as "networking", split by sub-topic (queueing theory, congestion handling,
DNS, TCP/UDP, hardware types, wireless vs wired vs quantum, etc.)<p>Step 2 is for Bard to summarize each lecture and create a
1-page summary of the important points as well as a syllabus of
each course.<p>Step 3 is a use the lectures as reinforcement learning from human
feedback (RLHF) so Bard is able to interactively answer questions
about networking before, during, and/or after the lectures.<p>Step 4 is for Bard to create (or find) github repositories related to the
course as well as the whole subject of networking.<p>So now Bard IS the teacher.<p>Iterate by topic.<p>Step 5 is to have Bard create a "canonical version" of network lectures
that it has self-generated, curated by experts in the field.<p>Now you've disrupted all the Universities.<p>I suspect that a small team could have most of this working within the
next year or two using Bard doing voice recognition in lectures as well
as Bard generated voice, video-from-text to illustrate the lectures, and
even generate and correct homework problems unique to a particular
user's weak areas of understanding based on interactions.<p>Bard could be adaptive enough so that when I don't remember Little's
Law it can dynamically insert a quick tutorial at the point in question.<p>Companies could use such courses instead of resumes or interviews.
You need to show a passing grade for a course in their problem area.
People could easily transition from their current job to another job by
taking Bard courses that target the employer. Everybody wins.<p>Having deep control of youtube puts Google ahead of OpenAI.<p>Skate where the puck is going, not where it has been. -- Wayne Gretzky