Artificial Intelligence chip race fueled by $34billion marketMatt Grant
The race is certainly on to try out different ideas and architectures and see what meshes best with AI technologies and developers.
AI chip sales will rise by a projected 52% annually, from $4.27 billion in 2018 to $34.3 billion by 2023. This total is comprised of chips from the IoT enabled devices, personal computing, and data-center markets, all of which are great news for Antistat.com who supply ESD technology consumables to these markets. The silicon brain, that can give rise to thought, emotion and behavior in a machine is firmly within reach. There have been seismic advances in software and hardware that are paving the way for next-gen computational systems equipped cognitive abilities modeled on the human brain.
Wells Fargo Securities believes the market for artificial intelligence chips will surge over the next five years. Facebook is currently developing its own artificial intelligence chips that go far beyond what’s currently on the market, according to a report from The Financial Times that’s based on an interview with Yann LeCun, Facebook’s chief AI scientist.
The idea is the chips will be able to provide the faster computing that Facebook needs in order to achieve new AI breakthroughs including digital assistants with common sense added in. During the interview, Facebook indicated they are already developing its own custom ASIC (application-specific integrated circuit) chips to support its AI software. “We are in the very early stages of beginning to consider the long-term importance that customized AI silicon will play in the overall semiconductor industry,” said a representative from the company.
Neuromorphic computing and chips bring the much-needed evolution in computer hardware, allowing us to enhance machine intelligence for the complex problems that need to be solved for the future of humanity.
AI workloads are more specialized, which is expanding the market for custom chips. Amazon.com (AMZN) and Alphabet ’s (GOOGL) Google are also developing semiconductors internally. Systems have achieved improved AI performance by infusing machine learning capabilities with high-bandwidth CPUs and GPUs, specialized AI accelerators, and high-performance networking equipment.
To maintain this trajectory, new thinking is required to accelerate AI performance scaling to ever-expanding AI workload complexities – and we are confident with our global manufacturer network and logistics framework, that Antistat will continue to be the experts in provision of electrostatic discharge consumables and high-end technology-led packaging solutions to serve these dynamic businesses.