rajesh sinha @ShoulderArms
too old to rock and roll , too young to die. Views Personal, RT != Endorsement - Chief Scientist & Smart Machines Program Head at TCS Research mostly travelling Joined September 2009-
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With a podium finish in the 2017 Amazon Robotics Challenge, TCS Research & @IITKanpur continue to collaborate & develop autonomous #robots for warehouse automation. We also work with IISc Bangalore, IIIT Hyderabad, IIT Delhi, & the University of Tokyo, Japan. @TCS #40andForward
If you don't remember retweeting this, it means that you have leaked your Twitter Access Token in a public GitHub repository. Not the best practice, right? For details, read our latest article: link.medium.com/L1VvZmhb5mb #InfoSec #CyberSecurity #GitHub
Congrats @swagatk231 prof Behera and Samrat on this
Team Aham, (@iiscbangalore, @TCSResearch, & @hansonrobotics) is among the 38 semi-finalist teams for the @FlyANA_official #Avatar @xprize! Our carefully chosen research partnerships remind us that together we can do great things. More - bit.ly/3tL75X7 #buildingonbelief
#Retailers, CPG & #logistics players want to enhance delivery experience by keeping customers informed of their real-time package status. Read about how new technologies combine with the ‘package of the future’ to reshape the #ecommerce delivery experience on.tcs.com/3uPsAa0
My husband is traveling with me to a conference and we’ve been thinking of fake AI subfields for him to claim to be working on. Favorites so far: - Disentangled HairNets - Deep Distraction Networks - Misrepresentation Learning Got any other good suggestions for him?
🤓 Here it is, the 2019 State of AI Report by @soundboy and I. 130 slides covering the most important machine learning research, industry and political developments over the past 12 months. New section on China. 👉 Please RT if you find interesting! stateof.ai
My investment in tax saving instrument for next 5 years #IndiaElections2019 #VoteForIndia
Deep Neural Network Approximation for Custom Hardware: Where We’ve Been, Where We’re Going [37pp] Comprehensive evaluation of approximation methods for high-performance inference with in-depth discussion of their effectiveness for custom hardware arxiv.org/abs/1901.06955
This is what happens when you believe in hype and overestimate capabilities timesnownews.com/amp/the-buzz/a…

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