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VERSION:2.0
PRODID:IEEE vTools.Events//EN
CALSCALE:GREGORIAN
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TZID:Asia/Kolkata
BEGIN:STANDARD
DTSTART:19451014T230000
TZOFFSETFROM:+0630
TZOFFSETTO:+0530
TZNAME:IST
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BEGIN:VEVENT
DTSTAMP:20260204T183721Z
UID:E58EE0F3-863F-492E-BED1-632EC8B251FB
DTSTART;TZID=Asia/Kolkata:20240524T110000
DTEND;TZID=Asia/Kolkata:20240524T120000
DESCRIPTION:Over the past decade\, the confluence of sophisticated algorith
 ms and tools\, computational infrastructure\, and data science has fueled 
 a machine learning revolution across multiple fields\, including speech an
 d handwriting recognition\, natural language processing\, computer vision\
 , social network filtering\, and machine translation. Ensuing advances are
  changing the way we interact with technology in our daily lives. This is 
 particularly salient when it comes to user input on mobile devices\, be it
  speech\, handwriting\, touch\, keyboard\, or camera input. Increased inpu
 t intelligence boosts device responsiveness across languages\, improving n
 ot only basic abilities like tokenization\, named entity recognition and p
 art-of-speech tagging\, but also more advanced capabilities like statistic
 al language modeling and question answering. In this talk\, I will give se
 lected examples of what Apple has been doing to impart input intelligence 
 to mobile devices\, with two overarching themes as sub-text: (i) enhancing
  interaction experience through machine learning\, and (ii) transforming u
 sers' digital lives without sacrificing their privacy.\n\nSpeaker(s): Dr. 
 Jerome R. Bellegarda\, \n\nVirtual: https://events.vtools.ieee.org/m/42171
 0
LOCATION:Virtual: https://events.vtools.ieee.org/m/421710
ORGANIZER:ieee.sps.sb.iitkgp@gmail.com
SEQUENCE:12
SUMMARY:IEEE SPS SBC Webinar: Input Intelligence on Mobile Devices (By Dr. 
 Jerome R. Bellegarda)
URL;VALUE=URI:https://events.vtools.ieee.org/m/421710
X-ALT-DESC:Description: <br /><p>Over the past decade\, the confluence of s
 ophisticated algorithms and tools\, computational infrastructure\, and dat
 a science has fueled a machine learning revolution across multiple fields\
 , including speech and handwriting recognition\, natural language processi
 ng\, computer vision\, social network filtering\, and machine translation.
  Ensuing advances are changing the way we interact with technology in our 
 daily lives. This is particularly salient when it comes to user input on m
 obile devices\, be it speech\, handwriting\, touch\, keyboard\, or camera 
 input. Increased input intelligence boosts device responsiveness across la
 nguages\, improving not only basic abilities like tokenization\, named ent
 ity recognition and part-of-speech tagging\, but also more advanced capabi
 lities like statistical language modeling and question answering. In this 
 talk\, I will give selected examples of what Apple has been doing to impar
 t input intelligence to mobile devices\, with two overarching themes as su
 b-text: (i) enhancing interaction experience through machine learning\, an
 d (ii) transforming users' digital lives without sacrificing their privacy
 .</p>
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