AI APPLICATIONS Gilberto Rodriguez
AI APPLICATIONS Gilberto Rodriguez
TITLE : DIRECTOR OF PRODUCT MANAGEMENT - ARTIFICIAL INTELLIGENCE AND ETHERNET CONNECTIVITY
COMPANY : IMAGINATION TECHNOLOGIES
Gilberto Rodriguez has over 20 years leading global teams and organisations . With this experience , he brings expertise in multidisciplinary product development in areas of telecommunications , video processing and artificial intelligence to Imagination Technologies .
With self-driving vehicles , Rodriguez explains : “ The data needed comes from information captured from surroundings . This can be dynamic coming from sensors such as Radar , LIDAR , cameras , Infrared or static from 3D maps in combination with GPS . As all sensor data is processed , the car is placed into a virtual replica of the world , giving it a frame of reference for positioning and for what is happening dynamically around it ( cars , trucks , motorcycles , pedestrians ). AI will help work out the safest path through the road using path planning algorithms . This is then converted into controls for the car ’ s acceleration , brakes , steering and so on .”
Overcoming challenges to fully commercialise the technology Although many companies are developing and testing driverless technology , including Audi , Tesla , Google and BMW , there are still significant technical challenges the industry will face .
Testing these systems is crucial to the development of the technology and algorithms within autonomous vehicles . Bringing a financial challenge to the table , some believe technology and automotive companies could spend up to $ 10 billion to test and perfect their technology .
With the huge expense that comes with developing this technology , Rodriguez says it is important that “ OEMs understand where they fit in the value chain . Driverless car technology can go from capturing data to full validation / certification of a vehicle .”
“ With the neural network accelerator performing most of the computer , it ’ s important to pick the right one . However , machine learning is evolving very quickly , so flexible programmable hardware is also a requirement ,” he added . aimagazine . com 105