Artificial intelligence (AI) technology is on its way to enter into the processors of computers and smartphones. From robotics to transportation, AI is prevailing in every sector in the world. Today’s computer programs have vast user data and it becomes a laborious task to handle the data using traditional chips.
However, incorporation of AI chips offered novel methods such as pattern recognition to analyze the data. With the use of AI chips, the simple tabletop speaker can be transformed into a smart home assistant and mobile into a smart camera, which increased the demand for AI chips. According to a research firm, Allied Market Research, the rise in demand for AI chips and the emergence of autonomous robotic technology is expected to boost the growth of the AI chip market. Moreover, the rivalry between tech giants such as Google, Intel, and Tesla to deliver the fastest computing chip supplemented the growth of the market.
Tesla To Lunch Self-Driving AI Chip
Elon Musk, the Co-founder, and CEO of Tesla, recently announced that Tesla’s super-advanced AI chip will unveil in the next four to six months. These chips will take over the existing Nvidia Drive PX 2 that are currently operating in the self-driving cars. Moreover, Musk confirmed that the users of pre-ordered “full self-driving” feature will get the upgraded chip for free.
According to the company, Tesla’s AI chip can process up to 2,000 frames per second, unlike the PX processors that compute 20 frames per second. Pete Bannon, the leader of the design team, stated that the AI chip supports the existing machine learning (ML) networks “with a lot of idle cycles to spare”.
Tesla has thus far relied on Nvidia’s Drive Platform. However, to focus on the particular operations and to improve efficiency, Musk decided to develop in-house AI chips that can boost the performance of the self-driving cars. He recently declared, “We have been in a semi-stealth mode in developing AI chips since last 2-3 years. However, it is time to let cats out of the bag.” According to Musk, in the next four to six months, the world will witness the fastest AI chip in the market, catering to the specific requirement of Tesla’s autonomous cars.
Nvidia Unstoppable In AI Chips Business
The inventor of the graphics processing unit (GPU), Nvidia, is using AI chips to offer a more realistic gaming experience. Moreover, AI can help to tackle the challenge of creating lifelike light and shadow effects in the game. Recently, Nvidia unveiled a new graphics chip, Nvidia Turing, that fuses together real-time ray tracing, artificial intelligence, and programmable shading. Making illusions such as lifelike reflection, refractions, and other effects require high computing power, which traditional chips fail to deliver. On the other hand, AI chips can speed up the process. Nvidia’s AI-based approach involves creating an image by overlaying multiple elements to achieve illusions of tackling lights and shadows. The traditional approach increases efficiency by rendering part of an image and AI predicts and fills in the remaining light effects, which offers a lifelike experience in gaming. Apart from that, AI chips favored the revenue generation of Tesla. Since the launch of Turing, the company shares have skyrocketed, making it unstoppable in the AI chip market.
Surge In AI Chips Start-Ups
For decades, leading tech companies ignored start-ups that manufactured AI chips, questioning their ability to compete with the goliath such as Intel and Google. However, the innovations in AI and ML reopened the question of how to build computers and start-ups offered ground-breaking ideas and technologies to build a faster computer. Today, there are at least 45 start-ups that are on the verge of redefining the AI chip industry. Furthermore, there are about five companies that successfully raised more than $100 million from investors. For instance, Venture capitalists invested more than $1.5 billion in AI chips start-ups in 2017, nearly doubling the investments of 2016.
It is a challenging task to go toe-to-toe with Intel and Nvidia in the AI chip business, which would require at least billion dollars of investment. However, these start-ups help to develop dedicated chips that provide a particular kind of computing power to support ML and get acquired by the existing tech giants. Due to the increasing hunger for new and fast processing power, start-ups have gained a rare chance against the entrenched companies in building faster AI chips.
Swamini Kulkarni holds a bachelor’s degree in Instrumentation and control engineering from Pune University, and works as a content writer at Allied Market Research. She is deeply fascinated by the impact of technology on human life, and loves to talk about science and mythology. When she is not glued to the computer, she loves to read, travel, and day dream about her areas of interest.