

        <cite>Bryce</cite>
      <time>0:00</time>
      <p>
          Um,   I   have   done   more   matrix   multiplying   than   you.   Um   uh   does   not   make   you   efficiently   learn   it.
      </p>

        <cite>Conor</cite>
      <time>0:09</time>
      <p>
          Last   time   it   was   the   blenders.   This   time   I   mentioned   matrix   multiply.   Bryce&#39;s   response,   Connor.   I   just   like   you   to   know   that   I   have   done   more   matrix   multiplication   than   you   have   in   your   lifetime.   Welcome   to   ADSP   the   podcast,   episode   62,   recorded   on   January   8th,   2022.   My   name   is   Connor,   and   today   with   my   co-host   Bryce,   we   continue   and   finish   part   two   of   our   2021   retro.
      </p>

        <cite>Bryce</cite>
      <time>0:44</time>
      <p>
          Yeah,   well,   we   uh   we   haven&#39;t   we&#39;ve   done   my   2021   retrospective.   What   about   your   2021   retrospective?
      </p>

        <cite>Conor</cite>
      <time>0:51</time>
      <p>
          Mine   is   mine&#39;s   mostly   outside   of   work.   So   my   my   work   highlight,   I   worked   on   a   really   big   project   on   the   Rapids   ecosystem   called   basically   decimal   128.   I&#39;m   not   gonna   go   into   the   details,   but   it&#39;s   it&#39;s   like   fixed   point   uh   arithmetic,   and   it   was   a   pretty   big   deal   because   there   was   compiler   work   that   was   done   in   order   to   support   uh   120.
      </p>

        <cite>Bryce</cite>
      <time>1:10</time>
      <p>
          And   a   bunch   of   work   a   bunch   of   work   that   uh   ended   up   that   my   team   ended   up   having   to   do.   Uh   thanks   uh   128-bit   integers   work.   So   thanks   uh   thanks   to   Wesley   and   my   team   for   making   that   happen.
      </p>

        <cite>Conor</cite>
      <time>1:22</time>
      <p>
          Yeah,   there   was   compiler   folks,   there   was   sort   of   on   the   standard   library   side,   uh   a   bunch   of   stuff.   So   yeah,   that   was   an   awesome   project.   But   my   top   three,   starting   number   three,   uh   there   was   a   trip   I   took   in   August   uh   that   was   in   went   to   both   Vancouver   and   then   also   to   Winnipeg,   I   believe,   to   visit   some   friends   and   then   family.   That   was   the   first   time   I&#39;d   been   on   a   plane   in   over   a   year   and   a   half,   and   more   importantly,   the   first   time   I&#39;d   seen   my   family.   So   that   was   a   big   deal.   Yeah,   obviously,   because   of   the   pandemic.   I   basically   didn&#39;t   want   to   hop   on   a   plane   until   I   had   my   vaccines.   Anyway,   so   that   was   awesome.   Number   two,   what   did   I   write   down?   Oh   yeah,   both   the   podcasts   and   my   book   meetup.   Uh,   we   finished   category   theory   for   programmers.   Like,   this   is   like   podcasting   is   like   my   substitute   for   conferences   because   you   don&#39;t   get   I   was   just   at   like   the   Denver   C   meetup   a   couple   days   ago.
      </p>

        <cite>Bryce</cite>
      <time>2:13</time>
      <p>
          Virtually.   He   was   not   at   person   at   the   Denver   C   plus   plus   meetup.
      </p>

        <cite>Conor</cite>
      <time>2:17</time>
      <p>
          Yeah,   virtually,   and   um,   yeah,   man,   I   just   it&#39;s   it&#39;s   a   very   privileged   statement,   but   I   just   I   miss   I   miss   the   conferences   so   much.   Like   you   you   don&#39;t   get   to   see   like   my   my   like   socializing,   like   my   my   most   happy   favorite   socializing   is   like   at   those   conferences.
      </p>

        <cite>Bryce</cite>
      <time>2:34</time>
      <p>
          Well,   you   know,   it&#39;s   one   of   the   things   that   I   realized   a   few   months   into   the   pandemic   is   and   a   couple   months   into   the   pandemic,   this   was   something   that   like   I   thought   was   a   fear.   It   was   a   it   was   a   or   it&#39;s   it   was   something   that   was   a   fear   of   mine,   but   that   I   now   have   recognized   that   like   it   is   you   know   reality.   And   and   it   was   like   I   I   I   had   this   thought   of   like,   oh   wow,   10   or   20   years   from   now   are   we   gonna   look   back   at   the   at   the   you   know   2011   to   2019   as   this   like   golden   age   of   tech   conferences   and   this   golden   age   of   C   conferences,   and   that   things   never   really   went   back   to   the   way   they   were.   And   I&#39;m   now   fairly   convinced   that   that&#39;s   that   that&#39;s   the   case.
      </p>

        <cite>Conor</cite>
      <time>3:19</time>
      <p>
          So   like,   you   know,   like   you   and   I   it   sort   of   like   peaked   in   2019,   you   know,   you   and   I   both   went   where   I   went   to   the   that   was   my   first   conference,   so   I   basically   got   the   tail   end   of   the   golden   age.
      </p>

        <cite>Bryce</cite>
      <time>3:29</time>
      <p>
          Well,   well,   like   you   remember   like   November   2019,   I   went   for   like   four   weeks.   I   went   to   like   no,   it   was   like   six   weeks.   I   went   to   a   committee   meeting   and   then   Belfast.   Yeah,   yeah.   It   was   the   Belfast   committee   meeting,   then   there   was   ACCU   Belfast,   and   then   there   was   also   C   Russia,   and   then   there   was   Meeting   C.   And   then   I   fli   and   then   like   like   halfway   through   the   trip,   I   had   to   like   rebook   to   fly   to   supercomputing   because   one   of   my   VPs   was   like,   you   need   to   go   to   supercomputing.   Um,   and   so   I   had   just   like   five   or   six   weeks   of   back-to-back   conferences.   Um,   and   it   was   just   in   in   in   like   that   that   summer   too,   I   was   in   Prague   and   then   like   Paris,   and   then   uh   we   were   in   Germany   for   the   committee   meeting.   Um   and   like   earlier   in   that   year   there   was   a   ton   of   travel   too,   and   like   there   was   it   was   just   like   that   that   fall,   I   spent   like   eight   weeks   at   conferences.   Um,   and   then   like   COVID   hit,   and   then   uh   you   know,   it   was   all   over.   And   I   just   like   I   I   I   doubt   that   I&#39;ll   I&#39;m   sure   I&#39;ll   go   to   conferences   again   in   the   future.   I   I   sort   of   doubt   that   there   will   ever   again   be   a   situation   where   we&#39;ll   have,   you   know,   six   or   eight   weeks   of   conferences   back   to   back   like   that.
      </p>

        <cite>Conor</cite>
      <time>4:49</time>
      <p>
          Yeah,   that&#39;s   the   thing,   is   that   I   completely   agree.   There   was   a   a   talk   given   at   Strange   Loop   2021   in   October.   I   believe   her   name   was   Krista.   Actually,   let   me   get   her   name   because   it&#39;s   in   a   spreadsheet   that&#39;s   right   here.   Krista   Lopes.   Christina   Lopes,   although   she   goes   by   Krista   Lopes.
      </p>

        <cite>Bryce</cite>
      <time>5:04</time>
      <p>
          Wait,   wait,   when   you   say   spreadsheet,   is   it   the   spreadsheet?
      </p>

        <cite>Conor</cite>
      <time>5:07</time>
      <p>
          Yes,   portfolio   of   words   on   the   uh   videos   tab.   I   watched   that   talk   on   uh   December   30th,   2021.   And   yeah,   she   gave   a   talk,   it   was   a   keynote   actually   called   The   Future   of   Conferences,   and   it&#39;s   a   fantastic,   it   sounds   like,   oh,   that&#39;s   not   going   to   be   very   exciting.   It&#39;s   one   of   my   it&#39;s   a   very   good   talk   and   talks   about   how   there&#39;s   trade-offs   in   that   it   increases   the   accessibility,   reduces   the   you   know,   carbon   footprint   if   you   know   things   are   happening   virtually,   but   there&#39;s   also   a   ton   of   pros   to   you   know   having   them   in   person.   And   so   I   I   do   think   there   still   will   be   in-person   conferences   that   are   awesome,   but   yeah,   it&#39;s   it&#39;s   never   gonna   go   back   to   the   way   it   was,   I   don&#39;t   think.   Um   and   that&#39;s   the   thing   is   I   I   say   it&#39;s   like   it&#39;s   my   it&#39;s   the   the   best   socializing   or   my   favorite   socializing,   but   like   it&#39;s   it&#39;s   more   than   that.   Like   you   the   intellectual   growth   or   like   the   ideas   that   you   come   away   with,   and   like   that&#39;s   the   thing,   is   this   you   know   the   Denver   C   plus   plus   meetup,   it   was   great.   We   did   this   live   code   review,   but   then   there   were   sort   of   two   hours   of   casually   casual   chatting.   Inevitably,   it   was   like   80   minutes   of   that   120   minutes   was   just   talking   about   people   that   know   people   that   got   the   virus   and   COVID,   and   it&#39;s   like   it&#39;s   not   really   technical   in   nature.   Not   that   not   that   the   conversation   has   to   be   technical,   but   like   when   you&#39;re   at   C   now,   like   80%   of   what   you&#39;re   talking   about   is   just   like   you&#39;re   nerding   out   on   nerd   stuff.   You&#39;re   not   talking   about,   you   know,   oh,   I   just   got   the   virus   or   I&#39;m   going   to   get   my   booster   vaccine.   And   so   it&#39;s   it&#39;s   both   socializing,   but   like   I   I   learned   so   much   every   single   time   I   was   at   some   conference,   and   also   too,   like   giving   a   talk,   you   always   get   a   bunch   of   people   afterwards   that   come   up   and   they&#39;re   excited   and   want   to   talk   about   like   that   doesn&#39;t   happen   as   much   at   virtual   conferences.
      </p>

        <cite>Bryce</cite>
      <time>6:48</time>
      <p>
          Yeah,   I   mean   there&#39;s   there&#39;s   an   atmosphere   and   a   chemistry   to   to   it   to   you   know   in   person   versus   you   know   um   virtual.   Um   I   I   think   like   like   I   think   it   is   a   reality   that   there&#39;s   like   a   loss   of   chemistry   when   things   are   you   know   solely   virtual.   And   I   don&#39;t   think   that   that&#39;s   something   that   you   can   ever   really   fully   replace.
      </p>

        <cite>Conor</cite>
      <time>7:08</time>
      <p>
          We&#39;ll   see.   We&#39;ll   see   with   uh   you   know   ready   player   one,   two,   three,   four   haptic   suits.   Uh   not   that   I   want   a   haptic   suit   to   go   to   a   conference.
      </p>

        <cite>Bryce</cite>
      <time>7:15</time>
      <p>
          As   good   as   the   metaverse   is   for   uh   our   stock   for   us.
      </p>

        <cite>Conor</cite>
      <time>7:19</time>
      <p>
          Umniverse.   Not   the   metaverse.
      </p>

        <cite>Bryce</cite>
      <time>7:22</time>
      <p>
          I&#39;m   I&#39;m   I&#39;m   I&#39;m   I&#39;m   very   sorry,   Jensen.   Very   sorry,   Jensen.   Omniverse.   We   were   first!   We   were   first,   we   were   first.
      </p>

        <cite>Conor</cite>
      <time>7:29</time>
      <p>
          I   mean,   metaverse,   isn&#39;t   that   from   like   the   snow   snow   capture   piercing?
      </p>

        <cite>Bryce</cite>
      <time>7:37</time>
      <p>
          As   good   as   Omniverse   has   been   for   the   company&#39;s   stock   price,   um   uh   uh   you   know,   I   think   it&#39;s   it&#39;s   one   of   those   technologies   that   um   that   is   important   and   foundational   and   will   be   transformative,   but   because   it&#39;s   important   and   transfer   transformational   um   uh   it   will   be   overhyped.   Um   like   I   I   saw   the   thing   about   like   you   know   the   Walmart   like   VR   like   shopping   experience.   Um   it&#39;s   like   the   whole   the   whole   idea   of   like   um   uh   of   like   grocery   delivery   is   that   like   you   don&#39;t   have   to   walk   through   the   store   to   like   pick   out   the   groceries,   like   you&#39;re   paying   a   premium   to   just   like   you   know   like   have   a   better   shopping   experience   than   like   walking   through   an   actual   storefront   and   like   find   things.   Um   and   so   like   that&#39;s   just   clearly   like   a   wrong   use   of   the   technology.   I   I   I   do   think   that   like   omniverse   is   actually   very   cool.   Um   what   one   of   my   NVIDIA   colleagues   who&#39;s   who&#39;s   in   the   city   works   on   Omniverse,   and   him   and   I   have   chatted   about   it   a   couple   times,   and   I&#39;m   always   very   impressed   with   him.   Um   if   you   go   and   look   at   some   of   Jensen&#39;s   GTC   keynotes   or   some   of   the   talks   about   Omniverse   before   you   know   Facebook   made   its   its   like   metaverse   announcement.   So   like   if   you   go   look   at   like   some   of   the   talks   from   like   2019,   like   early   2020,   um,   I   think   that   really   gets   to   um   it   that   really   does   a   good   job   of   showcasing   some   of   the   the   use   cases   that   um   can   be   really   transformative.   Um   like   one   of   the   things   that   I   always   thought   was   very   clever   was   this   idea   that   uh   you   know   if   you   look   at   like   the   self-driving   car   problem,   um   to   get   the   amount   of   data   that   you   would   need   to   um   to   really   like   train   um   uh   uh   self-driving   car   software   sufficiently   to   be   um   you   know   road   safe,   you   would   need   like   orders   of   magnitude   more   hours   on   the   actual   road   than   you   have   today.   Um   and   so   like   it   may   just   like   not   be   practical   to   go   and   like   gather   that   data   just   like   driving   around   on   the   road.   Um   and   so   you   know   one   of   the   ideas   with   the   Omniverse   was   okay,   well,   what   if   we   built   a   simulation   environment   where   we   could   um   uh   you   know   simulate   the   real   world   and   then   train   the   neural   nets   in   that   simulated   environment.   And   not   just   for   self-driving   cars.   Like   the   the   idea   I   think   the   actual   use   case   that   was   shown   in   one   of   the   keynotes   was   doing   this   for   robotics,   um,   of   like   you   know,   train   training   the   robots   in   this   virtual   um   simulated   uh   reality.   And   and   that&#39;s   just   like   when   I   saw   that,   that&#39;s   really   when   it   clicked   for   me.   Um   and   I   just   like   you   know,   I   saw   that   and   I   was   like,   wow,   this   is   really   cool,   um,   and   I   think   it   has   a   ton   of   potential.   And   one   of   the   reasons   is   that   you   know,   before   I   worked   at   NVIDIA,   um   one   of   the   things   I   did   was   computational   science,   um,   which   is   more   or   less   the   the   same   idea.   Um   you   know,   I   worked   on   uh   doing   these   uh   simulations   of   white   dwarf   mergers.   Um   and   one   of   the   reasons   why   we   want   to   do   those   simulations   is   like   we   want   to   understand,   we   want   to   get   more   data   than   we   can   possibly   get   today   because   um   they   are   these   very   rare   events   that   happen   very,   very   far   away.   Um   and   so   one   of   the   things   that   like   we   do   with   these   simulations   is   we   we   want   to   run   these   simulations   um   and   uh   with   with   our   understanding   of   how   the   physics   of   them   work,   and   then   compare   the   simulated   results   to   like   actual   observational   results   to   make   sure   that   the   simulation   actually   reflects   reality.   Um   and   that&#39;s   sort   of   you   know   that   that   that&#39;s   become   the   basis   of   a   ton   of   science   today.   Um   I   I   I   think   that   you   could   argue   in   some   ways   that   um   that   a   lot   of   HPC   is   in   some   ways   some   form   of   the   omniverse.   Now   the   big   difference   with   something   like   omniverse   is   that   you   know   it&#39;s   visual.   Um   uh   you   know,   for   something   like   you   know,   training   um   self-driving   cars   or   a   robot   that   needs   to   see   things,   you   need   an   actual   visual,   um,   real-time   environment.
      </p>

        <cite>Conor</cite>
      <time>12:09</time>
      <p>
          Yeah,   I&#39;ll   try   and   find   um   a   couple   of   the   videos   that   show   the   robot   simulation   training.   Because   yeah,   it&#39;s   there&#39;s   a   couple   ones.   There&#39;s   one   like   a   golf   one,   there&#39;s   like   a   mini   robot   and   sort   of   a   factory   thing,   and   yeah,   it&#39;s   it&#39;s   very   uh   mind-opening   watching   it   and   being   like,   oh   yeah,   that&#39;s   a   thing.
      </p>

        <cite>Bryce</cite>
      <time>12:28</time>
      <p>
          Yeah.   You   know,   it   it&#39;s   it&#39;s   funny   with   with   things   like   machine   learning   and   omniverse   um   and   data   science.   Um,   you   know,   like   I   think   I   feel   like   oftentimes   some   of   us   who   are   working   in   or   adjacent   to   those   fields,   because   there&#39;s   so   much   hype   around   it,   um   we   sometimes   um   we   sometimes   have   like   a   pessimistic   outlook.   It&#39;s   like,   oh,   it&#39;s   like,   you   know,   everybody&#39;s   excited   about   machine   learning,   everybody   thinks   that   machine   learning   is   gonna   solve   all   their   problems.   Every   company&#39;s   got,   you   know,   uh   a   data   science   and   a   machine   learning   uh   division   now.   Um   and   you   know,   it&#39;s   a   gold   rush   and   and   you   know,   everybody&#39;s   overhyped.   But   like   every   now   and   then   you   you   get   reminded   of   the   fact   that   like   the   reason   that   these   things   are   overhyped   is   because   they   are   actually   amazing   transformational   technologies,   um,   which   are   having   a   huge   impact   on   the   world.
      </p>

        <cite>Conor</cite>
      <time>13:24</time>
      <p>
          Yeah.   Yeah,   it&#39;s   it&#39;s   you   say   that   and   it   makes   me   think   about   the   fact   that   technically   Rapids   sits   under   the   AI   infra,   so   AI   infrastructure.   And   um   technically,   I   could   go   around   saying   that,   yeah,   I   work   on   artificial   intelligence   infrastructure,   um,   which   is   like   it&#39;s   not   false,   but   I   just   I   never   say   that.   Like   when   people   ask   me   what   I   do,   I   just   you   know   say,   ah,   I   walk   work   on   the   C   back   end   for   uh   the   accelerated   Python   library,   because   I   just   feel   like   such   a   like   saying   that   I   work   on   AI   infrastructure,   like   I   know   that   there&#39;s   an   equivalent   team   at   Facebook   and   they   have   they   have   jackets   that   say   AI   infra   on   them,   like   you   know,   uh   Patagonia   jackets,   and   I   just   like   I   just   can&#39;t   do   it   because   um   I   just   like   the   I   know   that   the   semantic   attachment   that   people   have   to   AI.   It&#39;s   like   you   know,   the   Hollywood   movies   and   and   stuff,   and   I&#39;m   just   like   it&#39;s   not   that   sexy   what   I   do.   Like   it&#39;s   awesome,   it&#39;s   really   cool,   but   it&#39;s   not   it&#39;s   a   good   thing.
      </p>

        <cite>Bryce</cite>
      <time>14:16</time>
      <p>
          Well,   I   think   one   of   the   one   of   the   reasons   is   that   to   some   degree   um   the   the   AI   or   I   really   prefer   to   just   say   machine   learning   because   I   I   think   AI   is   much   more   of   a   public-facing   term.   Um   like   AI   is   a   very   broad   field.   Um   and   uh   the   majority   of   the   AI   that   we&#39;re   doing   today   is   machine   learning.   Um   uh   so   you   know,   I   I   I   I   like   I   like   you   know   often   say   to   like   people   like   I   you   know   I   know   nothing   about   ML,   which   is   not   entirely   untrue.   Um   and   like   I   certainly   wouldn&#39;t   like   say   that   like   I   work   on   like   you   know   core   infrastructure   for   ML   and   AI,   although   that   is   kind   of   like   true.   But   I   I   think   one   of   the   reasons   that   there&#39;s   perhaps   some   um   hesitance   there   is   that   it   is   true   that   the   ML   Gold   Rush   has   um   I&#39;m   thinking   about   how   to   say   this   nicely   has   the   ML   Gold   Rush   has   shifted   priorities   in   ways   that   have   left   certain   um   certain   domains   of   computational   science   and   software   engineering   uh   feeling   like   they&#39;ve   sort   of   been   abandoned   at   the   prom   for   another   another   date.   Um   you   know,   like   traditional   HPC,   um   traditional   compute   has   sort   of   taken   a   backseat   to   the   needs   of   ML   and   and   uh   DL   over   the   past   few   years.   Um   and   so   certainly   from   like   the   HPC   perspective,   you   know,   a   lot   of   the   hardware   innovation   that   gets   done   uh   has   been   around   accelerating   um   uh   ML.   Now   we   we&#39;ve   a   lot   of   that   hardware   acceleration   can   be   leveraged   by   HPC,   and   a   lot   of   traditional   HPC   is   starting   to   use   machine   learning   um   techniques.   Um   but   I   think   it&#39;s   a   little   bit   natural   for   there   to   be   some   reaction   of   like,   ah,   that&#39;s   like   like   all   that&#39;s   nonsense,   and   it&#39;s   just   shifting   priorities   away   from   like   the   real,   you   know,   the   real   science   or   the   real   thing   that   we&#39;re   doing.   Um   but   I   I   will   say   I   I   am   I   am   always   proud   to   say   that   I   um   uh   you   know   that   I   work   on   enabling   data   science   um   uh   uh   you   know   frameworks.   Um   because   I   don&#39;t   know,   some   something   about   data   science   feels   more   uh   noble   to   me.
      </p>

        <cite>Conor</cite>
      <time>17:00</time>
      <p>
          Yeah,   I   mean   it&#39;s   uh   it   is   weird   to   think.   Well,   didn&#39;t   Jensen,   wasn&#39;t   he   man   of   the   year,   time   time   of   the   year   person   or   whatever,   person   of   the   year?   Um   and   like   it   the   whole   profile   was   uh   the   you   know   NVIDIA   is   the   company   leading   the   AI,   whatever,   Frontier,   yeah,   something   something   like   that.
      </p>

        <cite>Bryce</cite>
      <time>17:20</time>
      <p>
          So   so   to   me,   one   of   the   reasons   why   like   I   I   like   I&#39;m   I&#39;m   happy   to   say   that   I   I   work   with   people   that   build   data   science   frameworks   um   uh   and   like   have   this   like   gut   reaction   that   data   science   is   more   noble,   is   that   um   I   think   a   lot   of   people   pick   up   ML   and   think,   or   like   a   lot   of   people   and   a   lot   of   organizations   have   picked   up   ML   and   have   like   sort   of   treated   it   as   like   a   hammer.   Um   like,   oh   yeah,   we&#39;ll   just   like   we&#39;ll   just   throw   some   machine   learning   into   like   our   thing   and   it&#39;ll   be   great.   Um   and   the   reality   is   that   like   not   everybody   necessarily   has   the   amount   of   data   um   to   to   to   like   you   know   to   do   that   and   to   like   it.
      </p>

        <cite>Conor</cite>
      <time>18:00</time>
      <p>
          If   it   fits   in   a   spreadsheet,   guess   what?   It&#39;s   not   big   data.
      </p>

        <cite>Bryce</cite>
      <time>18:03</time>
      <p>
          Yeah,   yeah.   But   um,   but   you   know,   data   science   is   really   just   this   field,   like   data   science   is   just   like   the   field   of   using   like   techniques   and   algorithms   and   and   uh   systems   to   get   insights   out   of   data,   you   know,   potentially   noisy   data.   Um   so   like   it&#39;s   not   necessarily   you   know   using   machine   learning.   It&#39;s   just   like   we   have   data,   like   you   know,   how   do   we   extract   knowledge   out   of   that   data?   Um   and   that   to   me,   like   like   that&#39;s   the   sort   of   hammer   that   I   think   is   one   that   almost   anybody   can   pick   up   and   get   something   useful   out   of.   Um   like   if   you   have   data,   um,   you   know,   almost   any   quantity   of   data,   um,   yeah,   you   can   probably   use   data   science   to   learn   something   from   that   data.
      </p>

        <cite>Conor</cite>
      <time>18:54</time>
      <p>
          Yeah.   All   right.   Well,   we   just   went   on   a   huge   we   went   from   podcasts,   and   my   meetup   is   uh   number   two   to   I   miss   conferences   to   omniverse   to   we   work   at   NVIDIA   and   we   know   AI,   except   we   don&#39;t.   But   yeah.
      </p>

        <cite>Bryce</cite>
      <time>19:10</time>
      <p>
          Um   we   do   we   do   kind   of   know   data   science.
      </p>

        <cite>Conor</cite>
      <time>19:13</time>
      <p>
          Um   we   know   people   that   know   stuff.
      </p>

        <cite>Bryce</cite>
      <time>19:15</time>
      <p>
          Yeah,   we   do   we   know   we   do   know   people   that   know   stuff,   yeah.
      </p>

        <cite>Conor</cite>
      <time>19:18</time>
      <p>
          Mostly   I   just   use   thrust   parallel   algorithms   and   yeah.
      </p>

        <cite>Bryce</cite>
      <time>19:22</time>
      <p>
          We   also   don&#39;t   know   graphics,   like   like   the   group   of   like   engine   like   of   all   the   NVIDIA   C   people,   with   a   couple   exceptions,   most   of   the   NVIDIA   C   people   don&#39;t   know   graphics   and   don&#39;t   really   know   machine   learning.   Which   is   funny   because   like   if   you   meet   if   like   those   are   the   two   things   that   NVIDIA   is   kind   of   known   for.
      </p>

        <cite>Conor</cite>
      <time>19:41</time>
      <p>
          I   do,   I   mean,   I   don&#39;t   I   don&#39;t   know   machine   learning,   but   I   didn&#39;t   do   a   lot   of   matrix   multiplication   when   I   was   studying   to   be   an   actuary,   so   I   hear   that&#39;s   like   80%   of   it.
      </p>

        <cite>Bryce</cite>
      <time>19:49</time>
      <p>
          So   um   I   have   done   more   matrix   multiplying   than   you.   Um   uh   does   not   make   you   a   machine   learning.
      </p>

        <cite>Conor</cite>
      <time>20:00</time>
      <p>
          Last   time   it   was   the   blenders.   This   time   I   mentioned   matrix   multiply.   Bryce&#39;s   response,   Connor.   I   just   like   you   to   know   that   I   have   done   more   matrix   multiplication   than   you   have   in   your   lifetime.
      </p>

        <cite>Bryce</cite>
      <time>20:13</time>
      <p>
          Like   I   have   written   optimized   matrix   multiplication   algorithms.
      </p>

        <cite>Conor</cite>
      <time>20:17</time>
      <p>
          I   feel   like   why   are   you   saying   you   don&#39;t   know   machine   learning   then?   That&#39;s   like   I&#39;ve   heard   that&#39;s   like   basically   all   it   is.
      </p>

        <cite>Bryce</cite>
      <time>20:22</time>
      <p>
          No,   no,   like   that&#39;s   that&#39;s   linear   algebra.   That&#39;s   a   different   field.   Like   machine   learning   is   like   a   specific   field   of   like   of   like   applying   these   techniques.   I   think   I   probably   took   in   in   my   undergrad   my   my   my   my   math   education   at   LSU,   the   department   was   very   um   uh   very   theory   focused,   or   at   least   the   program   I   was   in   was   very   theory   focused,   although   it   was   it   was   called   applied   math,   um,   but   it   was   very   focused   on   um   uh   like   graph   theory.   Um   it   was   not   not   really   a   very   computational   program,   which   is   actually   why   I   liked   it.   I   think   I&#39;ve   said   this   on   the   podcast   before.   I   did   not   get   a   computer   science   degree   um   because   uh   I   at   the   time   I   knew   I   was   a   little   shit   um   and   like   a   little   arrogant   shit.   And   I   thought   that   I   I   thought   that   if   I   was   gonna   be   in   a   computer   science   degree,   I   would   think   that   I   was   smarter   than   my   professors   and   I   would   clash   with   them   and   then   I   would   be   miserable.   Um   and   also   I   hated   school,   and   so   I   figured   like   if   the   thing   that   I   loved,   which   is   programming   and   computer   science   and   software   engineering,   if   that   was   like   what   I   had   to   like   study   in   school,   that   I   was   just   gonna   be   miserable   and   it   would   make   me   hate   those   things.   So   that&#39;s   why   I   ended   up   getting   a   math   degree,   and   I   like   intentionally   picked   the   the   math   course,   the   math   course   and   the   math   degree   program   at   LSU   that   was   like   the   least   um   it   might   it   wasn&#39;t   the   least   computational,   but   it   was   like   the   second   least   computational,   um,   which   was   the   applied   math   program.   Um   uh   it   was   like   the   one   where   you   did   not   have   to   take   any   CS   courses.   Like   I   intentionally   picked   that   one.   And   I   I   don&#39;t   know   that   we   ever   took   any   machine   learning   or   neural   net   uh   uh   courses   at   the   time   because   that   that   was   like   2011,   2014.   And   you   know,   it   wasn&#39;t   as   prominent   as   it   is   now.   We   did   there   was   definitely   a   lot   of   like   applicable   graph   theory   that   I   learned   that   was   you   know   applicable   to   uh   uh   machine   learning   techniques   that   are   used   today,   although   most   of   that   knowledge   has   um   drained   out   of   my   head.   There   are   still   like   a   handful   of   like   graph   proofs   that   I   had   to   like   learn   for   like   some   test   that   I&#39;m   fairly   certain   that   if   under   pressure   um   and   like   presented   with   like   the   need   to   produce   these   proofs,   I   could   probably   like   crank   out   like   one   one   of   these   like   three-page   ridiculous   proofs.
      </p>

        <cite>Conor</cite>
      <time>22:54</time>
      <p>
          Sounds   like   a   challenge.
      </p>

        <cite>Bryce</cite>
      <time>22:55</time>
      <p>
          Yeah.   I   also   got   I   I   I   you   know   it&#39;s   funny   because   I   was   I   was   somebody   that   was   in   you   know   HBC,   but   um   I   I   barely   survived   my   like   partial   differential   equations   coursework.   Um   like   that,   like   um   uh   differential   equations   and   calculus   never   came   naturally   to   me.   Um   like   graph   theory,   you   know,   like   did   graph   theory   and   like   discrete   math,   um,   like   that   was   all   like   very   natural   to   me.   Um   but   like   the   calculus,   nope,   nope,   nope,   nope,   nope,   nope,   nope.
      </p>

        <cite>Conor</cite>
      <time>23:30</time>
      <p>
          Yeah.   I   mean   calculus,   calculus   one   and   two   um   was   fine,   but   as   soon   as   it   hit   multivariate   and   three,   I   just   I   hate   I   hated   the   word   problems.   Um   and   I   used   to   love   word   problems,   but   I   just   remember   there   would   be   like   some   cone   and   water   and   water   leaving   at   a   certain   rate   and   water   being   poured   into   the   cone,   and   you   can&#39;t   that   wasn&#39;t   even   my   my   problem.
      </p>

        <cite>Bryce</cite>
      <time>23:52</time>
      <p>
          My   problem   was   that   like   like   once   you   get   to   like   once   you   get   to   like   partial   differential   equations,   like   you   to   like   solve   these   problems,   like   you   just   had   to   have   an   intuition   about   like   how   to   do   it.   Like   literally,   my   professors   would   tell   me   that   like   you   just   have   to   have   the   right   intuition   about   like   how   to   approach   this.   Um   and   like   I   don&#39;t   know,   I   just   lacked   that   intuition.
      </p>

        <cite>Conor</cite>
      <time>24:14</time>
      <p>
          Yeah,   I   never   took   PDE   or   ODE.
      </p>

        <cite>Bryce</cite>
      <time>24:16</time>
      <p>
          So   I   still   have   like   I   have   right   here   on   this   shelf   like   my   uh   these   actually   aren&#39;t   even   my   my   coursework   PDE   books.   These   were   like   the   graduate   level   PDE   books   that   I   had   to   pick   up   to   like   learn   how   to   do   my   job.   Um   like   to   like   learn   like   to   to   learn   the   like   the   things   that   I   needed   to   um   to   do   the   computational   astrophysics   and   other   stuff   that   I   uh   that   I   was   doing.
      </p>

        <cite>Conor</cite>
      <time>24:43</time>
      <p>
          Alright,   well   enough   enough   with   uh   boring   our   listeners   with   or   boring   the   listener,   sorry,   uh   uh   with   our   mathematics   um   uh   not   even   successes.   It   sounds   like   we   both   struggle   towards   the   end.
      </p>

        <cite>Bryce</cite>
      <time>24:55</time>
      <p>
          Um   I   mean   I   like   I   think   it&#39;s   a   good   thing   for   people   to   know.   Um   like   you   know,   like   I   I   um   I   think   I   think   I&#39;m   good   at   math.   I   actually   think   that   I&#39;m   strong.   Uh   my   verbal   and   my   like   communication   skills   are   stronger.   Um   like   I   remember   when   I   when   I   took   the   SATs,   which   are   like   the   the   college   like   entrance   exams   in   in   the   US,   um   I   got   like   like   the   the   math   section   was   like   always   like   hard   for   me,   which   was   weird   because   like   I   was   like   a   science   kid.   You   know,   like   like   like   my   parents   were   like   convinced   I   was   gonna   like   get   get   a   STEM   degree   and   whatnot.   Like   that   was   always   what   interested   me.   Um   but   like   the   math,   like   um   just   because   I   liked   science   doesn&#39;t   mean   didn&#39;t   mean   I   was   good   at   math,   which   you   need   to   be   to   like   go   far   in   science.   But   like   the   math   section   I   struggled   with,   I   ended   up   doing   pretty   good,   but   the   like   verbal   section   of   the   like   SATs,   like   I   didn&#39;t   have   to   study   for   and   I   got   like   a   perfect   score.
      </p>

        <cite>Conor</cite>
      <time>25:52</time>
      <p>
          Um   we&#39;re   like   opposites.
      </p>

        <cite>Bryce</cite>
      <time>25:54</time>
      <p>
          Uh   yeah,   yeah,   yeah,   yeah.   But   like   it&#39;s   like   people   don&#39;t   expect   that   from   like   me.   Um   when   they   meet   me,   they&#39;re   like,   oh   like   you&#39;re   a   software   engineer,   you   have   a   math   degree,   like   you   know,   writing   can&#39;t   be   your   strong   suit.   But   like   the   reality   is   like   writing   and   communicating,   um,   like   that   is   like   just   natural   to   me.   Whereas   math   is   something   that   I   had   to   struggle   with.   And   to   some   degree,   that&#39;s   why   I   chose   to   get   a   math   degree.   Um,   you   know,   I   as   part   of   it   was   that   sort   of   like   reason,   like   I   didn&#39;t   want   to   like,   I   didn&#39;t   want   to   um   get   a   CS   degree   because   I   thought   I   would   argue   with   my   professors   and   because   I   I&#39;d   never   enjoyed   school   and   I   enjoyed   programming   and   I   didn&#39;t   want   to   like   combine   I   didn&#39;t   want   to   come   to   hate   programming   through   studying   it   in   a   school.   But   like   the   other   reason   was   like   I   I   thought   about   like,   you   know,   I   know   how   to   program   right   now.   I   don&#39;t   think   I   need   to   go   to   school   to   learn   that,   but   the   thing   that   I   don&#39;t   know   is   math.   Um,   and   so   I&#39;m   gonna   go   to   get   a   degree   in   math   to   hopefully,   you   know,   learn   more   about   it.   So   it   I   guess   that&#39;s   maybe   not   something   that   a   lot   of   people   think   to   do.   That   like   a   lot   of   people   think,   like,   I&#39;m   gonna   go   to   college   in   the   field   that   I&#39;m   good   at.   I   consciously   chose   to   get   a   degree   in   the   field   that   I&#39;m   bad   at   so   that   I   could   learn   more   about   it.
      </p>

        <cite>Conor</cite>
      <time>27:06</time>
      <p>
          This   is   actually,   man,   it&#39;s   we   we   have   these   back   and   forths   on   uh   how   similar   we   are,   except   for   furnishing   our   apartments,   which   is   where   we   really   differ.   But   it&#39;s   actually   that&#39;s   crazy   that   we&#39;ve   talked   about   university   quite   a   bit   on   this   podcast   or   like   our   past   experiences,   but   I   basically   had   the   exact   same   decision.   Like,   so   I   I   always   had   a   whatever   predisposition   towards   math,   but   at   one   point   in   my   third   semester,   I   had   taken   two   computer   science   courses,   the   two   intro   ones,   and   because   they   had   projects   with   bonus   marks   and   stuff,   I   got   a   hundred   percent   above   a   hundred   percent   um   in   both   of   those   classes,   and   I   loved   it.   And   I   I   was   already   working   towards   the   acturail   math,   and   so   I   had   a   choice.   And   at   the   time,   I   and   I   consider   this   a   mistake.   At   the   time,   I   didn&#39;t   know   that   like   computer   science,   I   didn&#39;t   know   anything   about   software   engineering   and   Google   and   stuff,   and   that   it   was   like   a   you   know   growing   industry.   My   view   was   just   that   like,   oh,   computer   science   is   this   super   fun   thing.   I   love   coding   in   Python,   but   I   decided   to   continue   with   the   actual   math   thing   because   I   figured   I   was   gonna   get   bored   with   computer   science   because   it   was   just   so   easy.   At   least,   I   mean   it   that   was   a   naive,   ignorant   view,   uh,   because   I   didn&#39;t   know   you   know   that   it&#39;s   gonna   get   harder   at   the   200,   300,   400   level.   I   just   figured   it   was   I   was   gonna   continue   to   be   able   to   do   well.   Whereas   I   knew   acturail   math,   even   though   I&#39;m   good   at   math,   it   it   was   an   extremely   competitive   and   difficult,   like   the   the   introductory   actual   course   that   you   have   to   take   in   order   to   get   into   the   program.   I   think   I   got   like   a   B   minus   or   a   C   plus,   and   and   uh   it   was   a   very,   very   Actually,   no,   I   got   it   I   got   higher   than   a   C   plus   because   you   needed   a   certain   minimum   grade,   but   like   I   had   studied   harder   for   that   course   than   any   other   course   up   to   that   point   in   university   and   and   done   very,   very   poorly.   And   that   the   course   had   like   a   50%   dropout   rate.   Like   so   the   point   being   is   I   was   like,   I&#39;ll   I&#39;ll   do   this,   it&#39;ll   be   more   challenging.   In   hindsight,   I   think   it   was   a   mistake,   but   it&#39;s   just   interesting   that   we   both   made   the   same   decision   to   try   something   that   was   more   challenging.
      </p>

        <cite>Bryce</cite>
      <time>29:03</time>
      <p>
          I   don&#39;t   I   actually   I&#39;m   gonna   argue   that   I   don&#39;t   think   that   it   was   a   mistake,   Connor.   And   and   I   mean,   you   know,   I   I   think   this   is   probably   not   applicable   to   every   field.   Um,   there&#39;s   probably   other   fields   outside   of   tech,   you   know,   maybe   even   in   tech,   where   you   really   do   need   to   have,   you   know,   a   degree   in   a   particular   field   to   get   a   job   in   that   field.   Um   but   um,   you   know,   in   tech,   like,   you   know,   you   don&#39;t   need   to   have   a   particular   degree   type   to   get   uh   to   become   a   software   engineer.   Um   you   know,   that&#39;s   that&#39;s   not   true   for   like   civil   engineering.   If   you   want   to   become   like   a   civil   engineer,   you   you   need   to   go   get   like   a   civil   engineering   degree.   Um   uh   like   like   ditto   for   like   other,   like,   you   know,   if   you   want   to   be   an   accountant   or   a   lawyer,   like   you   need   to   go   to   law   school,   you   need   to   um   get   an   accountant   accounting   degree.   Um   but   um   I   like   I   I   think   that   if   you&#39;re   planning   on   going   into   a   field,   or   even   if   like   you   don&#39;t   know   what   field   you&#39;re   going   into,   I   think   that   there   is   something   to   be   said   for   um   seeking   uh   seeking   out   the   the   the   courses   and   the   education   and   the   in   the   degree   program   that   uh   does   not   come   naturally   to   you   and   that   challenges   you,   um,   but   that   is   like   something   that   you   think   that   you&#39;ll   need   in   your   career.   Um   so   like,   you   know,   like   I   I   think   that   it   probably   has   helped   you   more   than   you   think   about   it   because   I   think   that   those   like   actuarial   skills   that   you   have   um   they   give   you   um   this   this   background   in   like   math   and   statistics   and   um   and   to   some   degree   like   data   science   that   um   sort   of   like   make   you   like   unique   as   a   software   engineer   um   and   and   give   you   like   a   unique   perspective   um   on   things.   So   like   I   I   think   I   think   that   you   I   think   that   you   would   not   have   as   diverse   a   skill   set   if   you   had   switched   programs.
      </p>

        <cite>Conor</cite>
      <time>31:03</time>
      <p>
          I   think   you&#39;re   definitely   correct   to   an   extent.   And   I   agree   that   like   my   like   I   consider   myself   a   statistician   because   I   took   so   many   stats   courses   and   you   know   at   actual   math,   you   have   to   memorize   all   these   distributions,   Bernoulli,   binomial,   whatever,   weable,   etc.   Or   you   don&#39;t   have   to   memorize   them,   but   you   need   to   know   how   to   use   them.   And   so   I   learned   it   a   a   ton,   but   like   my   the   one   regret   is   that   like   taking   that   path,   I   spent,   and   this   is   not   an   exaggeration,   thousands   of   hours   studying   for   actuarial   exams   because   there&#39;s   eight   of   them.   You   know,   you   fail   some   of   them   sometimes.   Uh   I   failed,   I   think,   three,   four,   even   maybe   five.   And   each   time   you   have   to   study,   you   know,   four   or   five   hundred   hours.   I   spent   so   much   time   spinning   my   wheels   on   these   exams,   and   they&#39;re   terribly   designed   exams,   they&#39;re   not   focused   on   like   you   know   how   much   you   comprehend.   They   give   you   2,000   pages   of   material   and   then   they   only   test   10%   of   it.   Um,   so   it&#39;s   just   like   it&#39;s   luck   of   the   draw   half   the   time.   And   uh   I   just   think   that   there   was   like   there   was   a   number   of   years   that   I   was   working   towards   something   that   like   as   soon   as   I   finished   it,   I   switched.   Although   I   will   say,   out   of   that,   arguably   one   of   the   most   valuable   things   that   I   got   was   like   an   insane   work   ethic,   or   I   shouldn&#39;t   use   the   word   insane,   just   like   a   very,   very   my   my   my   it&#39;s   the   knowledge   that   like   I   can   work   40   hours   a   week   or   50   hours   a   week,   and   then   on   top   of   that   also   study   another   30   or   40   hours.   And   like   like   back   when   I   studied,   I   used   to   wake   up   at   like   6   a.m.   and   I   would   track   15-minute   intervals   like   a   consultant   and   like   down   to   like   showering,   eating,   exercise,   like   everything   had   a   category   in   order   to   maximize   like   how   much   time   I   was   studying.   Um   so,   anyways,   you&#39;re   not   wrong.   But   uh,   there&#39;s   a   few   thousand   hours   I   could   get   back.
      </p>

        <cite>Bryce</cite>
      <time>32:58</time>
      <p>
          Yeah.
      </p>

        <cite>Conor</cite>
      <time>32:59</time>
      <p>
          If   uh   if   uh   I   wasn&#39;t   if   I   wasn&#39;t   doing   that.   All   right,   we   gotta   wrap   the   we&#39;re   we&#39;re   I   think   we&#39;re   past   the   hour   mark   on   episode   61.   I   have   no   idea   how   I&#39;m   gonna   cut   this   up,   and   I   haven&#39;t   even   gotten   to   the   number   one   thing   of   2021,   which   very   quickly,   and   we&#39;re   deferring   2022   Outlook   to   another   episode   because   we&#39;ve   run   out   of   time,   is   uh   my   running.   Running   was   definitely   the   highlight   of   the   what   was   probably   I&#39;d   say   2021   was   the   worst   year   of   my   life.
      </p>

        <cite>Bryce</cite>
      <time>33:28</time>
      <p>
          It&#39;s   the   first   worst   year   why   was   it   the   worst   year   of   your   life?
      </p>

        <cite>Conor</cite>
      <time>33:31</time>
      <p>
          Well,   I   mean   you   you   I   mean   you   know,   okay,   yeah,   yeah,   yeah.   There&#39;s   a   lot   of   stuff   happened.   Plus   two,   2021   was   the   first   year   in   I   don&#39;t   know   how   many   years   that   I   haven&#39;t   left   the   country.   The   last   time.   Yeah.   February   2020   was   the   last   time   I   went   to   a   different   country.   I   was   in   New   York.
      </p>

        <cite>Bryce</cite>
      <time>33:51</time>
      <p>
          I&#39;m   trying   I&#39;m   trying   to   get   Strava   to   tell   me   how   many   miles   or   how   many   kilometers   I   biked   um   last   year.   I   can&#39;t.
      </p>

        <cite>Conor</cite>
      <time>33:58</time>
      <p>
          Have   you   biked   more   than   I   have   run?   That   is   the   question.
      </p>

        <cite>Bryce</cite>
      <time>34:01</time>
      <p>
          Um   well,   so   so   the   problem   is   it   has   year-to-date,   which   is   not   applicable   for   last   year,   and   it   has   um   all   time.   Um   uh   so   I   don&#39;t   know   whether   I   can   actually   get   out   the   information   that   I   would   want.   Um   and   I   haven&#39;t   really   biked   since   like   October   because   it   got   cold.   Um   but   I   started   biking   in   like   November   2020.   Or   I   I   I   I   biked   when   I   was   at   LSU   and   then   like   I   took   like   a   two   or   three   year   when   I   moved   to   California,   I   like   stopped   biking   for   three   or   four   years.   Um   and   then   I   started   again   in   like   late   2020.   Um   I   think   it   Ryan,   if   you&#39;re   listening,   you&#39;re   like   you   and   I   like   went   on   a   bike   ride   together   like   in   like   November   2020,   and   that   was   like   what   motivated   me   to   get   back   into   biking.   So   you   you   get   credit   for   that.   But   um,   but   since   then   uh   Strava   says   I&#39;ve   ridden   uh   4,156   kilometers.   Um   this   is   from   when   to   when?   This   is   from   uh   November   2020   to   now.
      </p>

        <cite>Conor</cite>
      <time>35:14</time>
      <p>
          Oh   damn.   So   it   depends   how   much   did   you   bike   in   November   and   December   of   2020?
      </p>

        <cite>Bryce</cite>
      <time>35:20</time>
      <p>
          I   don&#39;t   think   it   was   like   that   much.   Um   I   think   it   was   maybe   um   hang   on,   we&#39;ll   we&#39;ll   see   if   I   can   find   that.
      </p>

        <cite>Conor</cite>
      <time>35:27</time>
      <p>
          The   numbers   are   gonna   be   super   close.
      </p>

        <cite>Bryce</cite>
      <time>35:30</time>
      <p>
          But   this   this   this   this   does   not   count   um   because   this   does   not   count   everything.   Um   uh   because   when   I   spin   in   indoors,   um   uh   that&#39;s   not   counted   here,   which   is   all   that   I&#39;ve   been   doing   recently.
      </p>

        <cite>Conor</cite>
      <time>35:44</time>
      <p>
          Um,   okay,   so   you&#39;ve   definitely   biked   more   than   I   was   gonna   say   my   my   2021   stats   are   I   ran   3,890   kilometers.
      </p>

        <cite>Bryce</cite>
      <time>35:53</time>
      <p>
          Ow,   that   that   okay,   that   makes   me   feel   bad   though,   because   I   I   should   have   done   a   lot   more,   a   lot   more.
      </p>

        <cite>Conor</cite>
      <time>35:59</time>
      <p>
          You   still   beat   me.   You   still   beat   me.   Anyways,   2022,   episode   62.
      </p>

        <cite>Bryce</cite>
      <time>36:05</time>
      <p>
          How   much   are   you   running   a   day   normally?
      </p>

        <cite>Conor</cite>
      <time>36:08</time>
      <p>
          Uh   it   depends.   I   mean,   my   I   think   I   think   my   my   best   month   was   512   kilometers   in   August.   So   that   works   out   to   like   218   or   something,   17,   I   don&#39;t   know,   13.
      </p>

        <cite>Bryce</cite>
      <time>36:21</time>
      <p>
          See,   I   I   don&#39;t   I   don&#39;t   see   all   that.   Oh   wait,   wait,   but   do   you   run   every   single   day?
      </p>

        <cite>Conor</cite>
      <time>36:27</time>
      <p>
          Uh   basic   in   August,   basically,   I   probably   took   off   one   or   two   days   in   August.
      </p>

        <cite>Bryce</cite>
      <time>36:31</time>
      <p>
          Yeah,   okay.   So   so   I   I   do   yoga   with   my   mom   uh   uh   or   yoga   or   Pilates   with   my   mom   twice   a   week,   and   um   my   normal   bike   ride   is   25   kilometers.   Um   uh   and   I   usually   do   a   40k   once   or   twice   a   week.   Um,   but   but   I   I   haven&#39;t   been   biking   since   October   um   outside   because   it&#39;s   been   cold,   and   I   definitely   had   some   periods   where   I   was   not   biking.   Well,   you   know,   towards   the   start   of   the   year   I   wasn&#39;t   I   was   biking   like   18   kilometers.   It   was   I   only   started   doing   like   25k   a   day,   and   I   only   started   doing   40ks   like   in   the   spring.   So   probably   like   like   probably   next   year,   my   I   will   probably   bike   a   lot   more   than   uh   than   you.   I&#39;ll   have   to   figure   out   a   way   to   to   get   the   data   for   how   long   for   for   my   um   my   biking   uh   my   my   my   spin   uh   bike,   which   I&#39;m   gonna   count   towards   my   my   kilometers.
      </p>

        <cite>Conor</cite>
      <time>37:31</time>
      <p>
          Yeah.   We&#39;ll   we&#39;ll   see   if   we   can   do   a   contest.   We&#39;ll   see   who   uh   who   if   if   you   bike   more   than   that.
      </p>

        <cite>Bryce</cite>
      <time>37:37</time>
      <p>
          I   feel   like   I   should   probably   I   feel   like   it   probably   should   be,   you   know,   like   two   two   times   for   like   if   it&#39;s   like   like   about   the   the   right   the   same   amount   of   exercise,   I   should   probably   be   aiming   to   bike   like   twice   the   distance   that   you&#39;re   running.
      </p>

        <cite>Conor</cite>
      <time>37:52</time>
      <p>
          Okay,   we   can   do   that.   We   can   have   a   bet.
      </p>

        <cite>Bryce</cite>
      <time>37:53</time>
      <p>
          We   can   uh   we   can   like   what   what   how   fast   do   you   run   normally?
      </p>

        <cite>Conor</cite>
      <time>37:57</time>
      <p>
          It   depends.   So   when   I&#39;m   like   yesterday   I   went   for   uh   it   was   yesterday   was   well   let&#39;s   figure   out   it   was   minus   eight   but   felt   like   minus   sixteen.   Minus   sixteen   Celsius   in   Fahrenheit,   which   for   all   of   you   Americans   was   three   degrees   Fahrenheit.   Oh   my   um   who   have   the   four?   So   it   was   very   it   was   very   cold.
      </p>

        <cite>Bryce</cite>
      <time>38:20</time>
      <p>
          I   thought   it   was   cold   here   because   there&#39;s   snow   on   the   ground   and   it   is   um   it   is   26   degrees,   which   is   cold.
      </p>

        <cite>Conor</cite>
      <time>38:27</time>
      <p>
          So   yeah,   it   was   very   cold,   and   I   went   for   a   23k   run   and   I   ran   at   a   um   445,   so   four   minutes   and   forty-five   seconds   per   kilometer.   So   if   we   change   that   to   miles   pace,   it&#39;s   like   seven   and   a   half   minutes   per   mile.   Which   is   like   that&#39;s   like   uh   it&#39;s   not   fast,   but   it&#39;s   also   not   slow.   It&#39;s   just   like   a   decent   pace.
      </p>

        <cite>Bryce</cite>
      <time>38:51</time>
      <p>
          Yeah.
      </p>

        <cite>Conor</cite>
      <time>38:52</time>
      <p>
          Anyways,   we&#39;ll   wrap   up   2021,   2022,   it&#39;s   gonna   be   a   better   year   for   sure.   Hopefully,   we&#39;ll   have   in-person   conferences.   Hopefully,   Bryce   and   I   will   be   able   to   see   each   other   in   person   at   some   point.
      </p>

        <cite>Bryce</cite>
      <time>39:04</time>
      <p>
          That&#39;ll   happen.   Not   so   certain   about   in-person   conferences.   And   I   mean,   you   know,   C23   is   gonna   be   finalized   this   year,   which   I   think   is   gonna   be   very   exciting.   Um   uh   and   um   I   think   you   and   I   both   have   some   exciting   so   very   there&#39;s   various   different   exciting   work   projects   that   we&#39;ve   got   going   on   that   I&#39;m   gonna   do.
      </p>

        <cite>Conor</cite>
      <time>39:22</time>
      <p>
          We&#39;ll   we&#39;ll   we&#39;ll   preview   what   we   can   preview   in   in   the   next   episode   of   uh   2022.   And   then   also   we   gotta   have   Dave   Abrahams   back   on   to   finish   up   the   rest   of   his   story,   and   we   gotta   have   uh   Sean   Parent   back   on.
      </p>

        <cite>Bryce</cite>
      <time>39:34</time>
      <p>
          Yeah,   and   like   I   think   we   gotta   we   gotta   expand   our   guest   repertoire.
      </p>

        <cite>Conor</cite>
      <time>39:38</time>
      <p>
          Well,   so   that   that&#39;s   actually   that&#39;s   actually   m   my   last   thing   was   we   mentioned   CPP   North,   we   talked   about   BQN,   and   my   last   note   is   bringing   on   other   PL   people.   So   I   think   because   we&#39;re   on   our   quest   to   become   number   one   in   Slovenia,   and   in   order   to   grow   the   podcast,   I   think   what   we   need   to   do   is   start   bringing   you   know   someone.   We   technically   already   had   Dave   Aberhans   from   Swift,   but   like   bring   on,   let&#39;s   bring   on   uh   someone   from   Rust,   someone   from   Go.   We   can   even   go   to   JavaScript   and   Scala   and   Ruby.
      </p>

        <cite>Bryce</cite>
      <time>40:04</time>
      <p>
          We   should   bring   we   should   bring   on   um   we   should   bring   on   Andre,   um,   of   course,   at   some   point.
      </p>

        <cite>Conor</cite>
      <time>40:09</time>
      <p>
          Um   Alexandrescu?
      </p>

        <cite>Bryce</cite>
      <time>40:12</time>
      <p>
          Yeah,   yeah,   yeah.   He&#39;s   he&#39;s   um   one   of   the   creators   of   D.   And   he&#39;s   just   like,   he&#39;s   he&#39;s   just   an   amazing   and   charismatic   storyteller.
      </p>

        <cite>Conor</cite>
      <time>40:19</time>
      <p>
          Oh   yeah.   We&#39;d   have   a   good   time   with   him.
      </p>

        <cite>Bryce</cite>
      <time>40:20</time>
      <p>
          And   we   should   also   bring   on   Bartush.
      </p>

        <cite>Conor</cite>
      <time>40:22</time>
      <p>
          Um   yeah,   that&#39;d   be   awesome.   Why   why   do   you   want   to   bring   on   Bartosh?
      </p>

        <cite>Bryce</cite>
      <time>40:28</time>
      <p>
          It&#39;s   the   same   thing.   Just   like   like   like   I   think   he   has   the   same   quality   like   Sean   and   Andre,   that   like   he&#39;s   gonna   have   he&#39;s   gonna   be   he&#39;s   a   great   storyteller.   He&#39;s   just   he&#39;s   just   a   great   storyteller.   And   then   well   wait,   so   sorry,   what   there   was   like   four   of   them   that   made   up   like   the   the   Northwest   C   user   group.   Like,   who   was   who   was   the   other   horseman?
      </p>

        <cite>Conor</cite>
      <time>40:46</time>
      <p>
          Um   I   I   I   so   for   those   of   you   that   don&#39;t   know   what   the   heck   Bryce   is   talking   about,   in   my   Better   Algorithm   Intuition   talk   that   I   first   gave   back   in   2019   on   that   little   European   tour   that   we   we   both   went   on,   although   admittedly   yours   was   a   lot   longer   than   mine.   I   uh   I   I   had   talked   to   Eric   Niebler   about   sort   of   his   history,   and   he   talked   about   this   era   where   they   were   in   the   Pacific   Northwest   C   user   group   in   Seattle,   or   maybe   it   was   just   outside   Seattle.   And   um   he,   so   himself,   Eric,   uh,   and   then   three   other   people   would   always,   you   know,   after   these   C   meetups,   they&#39;d   go   up   and   they&#39;d   go   out   and   you   know,   have   a   couple   drinks   and   sometimes   meet   together   on   the   weekends.   And   uh   the   four   of   them   would   always   talk   about   like   functional   programming   and   all   this   awesome,   you   know,   category   theory   stuff,   and   then   they   all   sort   of   went   in   different   directions.   So   those   four   people   were   Eric   Niebler,   Bartaj   Meluski,   who   went   and   did   category   theory   for   programmers,   and   then   uh   Andre   Alexandrescu,   and   the   fourth   one   is   Walter   Bright,   who   is   the   main   creator   of   the   D   language.   And   so   basically,   Walter   and   Andre   went   and   did   D.   Eric   went   and   did   C   ranges,   and   then   Bartaj   went   and   did,   you   know,   category   theory   and   functional   programming.   And   um   yeah,   we   could   potentially   get   them   all   on   in   the   same   time.   That   might   be   a   bit   crazy.
      </p>

        <cite>Bryce</cite>
      <time>42:08</time>
      <p>
          That   would   be   fun.   That   would   be   fun.   And   uh   we   gotta   have   Patricia   and   uh   uh   Chandler   back   at   some   point.   There&#39;s   a   lot   that   well,   we   we   obviously   at   some   point   we&#39;re   gonna   have   Titus   on   this   podcast.
      </p>

        <cite>Conor</cite>
      <time>42:19</time>
      <p>
          Oh,   yeah,   yeah.
      </p>

        <cite>Bryce</cite>
      <time>42:20</time>
      <p>
          Like   I   don&#39;t   know   that   Titus   whether   Titus   knows   this   yet,   but   at   some   point,   at   some   point   we&#39;re   gonna   have   Titus.
      </p>

        <cite>Conor</cite>
      <time>42:24</time>
      <p>
          We   also   have   to   have   Allison,   we   gotta   do   the   the   thrust,   we   gotta   have   Allison   on.   Yeah.
      </p>

        <cite>Bryce</cite>
      <time>42:28</time>
      <p>
          And   um   Although   I&#39;ve   since   I&#39;ve   since   discovered   um   that   the   that   the   thrust   CUDA   backend   has   an   optimized   partition   um   path,   and   uh   it&#39;s   pretty   clever.   I   haven&#39;t   fully   figured   out   how   it   works   yet.   And   also   I   think   I   think   I&#39;ve   determined   that   you   you   need   to   have   it   done   at   least   two.   Well,   no,   I   know   I   you   can   do   it   in   one   pass,   but   it&#39;s   uh   let&#39;s   save   it.
      </p>

        <cite>Conor</cite>
      <time>42:49</time>
      <p>
          Let&#39;s   save   it   for   the   future   episode   where   we   we   have   a   dedicated   time   to   talk   about   this.   Um   anyways,   lots   of   guests.   Yep.   Happy   twenty   happy   new   year.
      </p>

        <cite>Bryce</cite>
      <time>42:59</time>
      <p>
          Happy   New   Year   to   everybody.
      </p>

        <cite>Conor</cite>
      <time>43:01</time>
      <p>
          And   we   will   we   will   preview   twenty   twenty   two   next   time.   Thanks   for   listening.   We   hope   you   enjoyed   and   have   a   great   day.
      </p>