Google new trillion-parameter AI language model.
                     GOOGLE’S NEW 
TRILLION-
PARAMETER AI 
LANGUAGE 
MODEL
• Google Brain has developed an art ifi cial  intel l igence 
language model with some 1.6 tri l l ion parameters. This is  
nine t imes the size of OpenAI's 175 bi l l ion GPT-3 
parameter. 
INTRODUCTION
Source: aibusiness.com
• Language models  can accompl ish a range of  ro les,  but the 
generat ion of  novel text may be the most common ones.  
• To try to fi x whatever you ask i t ,  you must contact  a language 
prototype of  «the phi losopher AI»,  i .e .  you may come here and 
discuss i t  (with numerous notable except ions).
BACKGROUND
Source: thenextweb.com
• While these amazing AI  models ex ist  at  the top stage of  
machine learning technology,  i t  is  v i ta l  to note that they are 
u lt imately merely t r icks in the analysis .  
• Those appl icat ions don't  understand voice,  they're just  r ight -
tuned to make i t  seem l ike they do.
MACHINE 
LEARNING 
TECHNOLOGY
Source: aibusiness.com
• The Brain group has learnt that the model i tsel f can be 
made as transparent as possible by consuming the brush 
of electrical  design force you may obtain a larger amount 
of measuring parameters possible.  
WHAT GOOGLE 
HAS DONE?
Source: aibusiness.com
• Google’s 1.6-tri l l ion-parameter model,  which appears to 
be the largest of i ts size to date, achieved an up to 4 
t imes speedup over the previously largest Google-
developed language model (T5-XXL).
GOOGLE-
DEVELOPED 
LANGUAGE 
MODEL 
Source: venturebeat.com
• Large-scale preparat ion i s  an important  t ra i l  for  good models .  Easy 
arch i tectures backed up by mass ive data sets  and numerous code 
numbers are way around many more advanced too ls .  
• Eff ect ive,  large-sca le tra in ing i s ,  however ,  h ighly  intens ive in  
computat ions .
LARGE-SCALE 
TRAINING 
Source: venturebeat.com
• The swi tch  t ransformer ,  an  A I  model  parad igm fi rst  in t roduced in  the  
ear ly  1990s ,  re l ies  on  a  d ivers i ty  o f  exper ts .  
• The cha l leng ing pr inc ip le  is  to  re ta in  numerous  pract i t ioners ,  and  
ideas  engaged in  separate ly  ro les ,  wi th in  an  expanded pro jec t  and  
make a  compact  network se lect  wh ich  profess iona ls  to  requested  
in format ion .
SWITCH 
TRANSFORMER
Source: venturebeat.com
• The researchers claim their 1.6-tr i l l ion-parameter model 
with 2,048 experts (Switch-C) exhibited no training 
instabi l i ty at al l ,  in contrast to a smal ler model (Switch-
XXL) containing 395 bi l l ion parameters and 64 experts.  
MODEL 
COMPARISION
Source: venturebeat.com
• Several  of  the most common models have observed elevated 
rates of  theoret ical  bias,  including Google’s BERT and XLNet,  
OpenAI’s  GPT-2, and Facebook’s RoBERTa. 
• Malicious actors might exploit  this  prejudice to st imulate 
divis ion by transmitt ing mistakes, weaknesses and cruel  bias.
STEREOTYPICAL 
BIAS
Source: venturebeat.com
• Google's pol icy for reported machine learning may have 
played a role here. 
• Researchers at the company are now expected to consult 
with legal,  pol icy,  and public relations teams before 
pursuing topics such as face and sentiment analysis and 
categorizations of race, gender, or polit ical affi liation.
GOOGLE'S 
POLICY 
Source: venturebeat.com