The top 10 people in artificial-intelligence hardware

Amazon is building its own custom chips as it tries to catch up in the generative-AI boom. Brown, the head of Amazon Web Services, is in charge of that effort. At a recent event at Amazon's Seattle headquarters, Brown said Amazon's own chips — Inferentia and Trainium — have better price performance than competitors, including Nvidia. Amazon hopes the chips will be less expensive and more available, enabling more customers to build and train AI models more efficiently.

Fidler is the vice president of AI research at Nvidia and leads the company's Toronto AI lab which, she said, is now one of the largest research teams at the company. With her name on more than 170 research papers and a particular interest in computer vision and neural graphics, Fidler has explored using generative AI to build 3D worlds. She's also an associate professor at the University of Toronto. In 2016, she and colleagues made headlines for their weird and prescient "neural karaoke" project that used AI to create songs from digital photos.

The intersection of AI and quantum technology isn't talked about as much as buzzy chatbots right now — but it's a future Hidary is trying to prepare us for. His company, SandboxAQ, began life in Alphabet as a research unit nestled in the company's X building, exploring how to run quantum workloads using the same chips as those that power AI. Hidary spun the unit out in early 2022 with a nine-figure round of investment that included the former Alphabet executive chair Eric Schmidt and Marc Benioff, the CEO of Salesforce. SandboxAQ is working across different industries, including using AI simulations for drug discovery and materials science, which could help "to create promising new products, such as better drug therapies or more powerful batteries," Hidary told Insider.

See the full list of 100 people who make AI intelligent here.

Hsiao leads work on Google's Bard chatbot, which the company has been improving at breakneck speed to keep up with OpenAI's ChatGPT. Hsiao also oversees the voice-powered concierge, Google Assistant, which the company is now supercharging with Bard's generative-AI abilities. All told, she's in the pilot seat of two major products that Google is relying on to demonstrate its AI prowess — and which, when the time comes, will include its much-anticipated Gemini model. Hsiao has been with Google for 17 years but said the past few months have been a whirlwind. "It feels like the first one or two years I was at Google," she told Insider. "It feels like the beginning all over again."

As far as smart pivots go, it's hard not to be impressed with what Intrator pulled off. In 2017, after several years of running a natural-gas investment fund, Intrator and his colleague Brian Venturo started buying Nvidia GPUs to feed their crypto-mining hobby. Today, CoreWeave offers companies access to those hard-to-get chips via the cloud for training AI. As the gold rush for GPUs continues, CoreWeave could end up in a fortuitous position. The Nvidia-backed startup was valued at $2 billion in April and has reportedly wooed investment from Microsoft that could be worth billions of dollars over the next several years.

James is the founder and CEO of Ampere, which develops chips for data centers. She has a long history in hardware and software development and in chip manufacturing. Before starting Ampere, James was the president of Intel. Ampere is building energy-efficient processors to reduce power consumption from big data and machine-learning systems. The company has said its chips offer four times the performance for AI inference while using nearly three times less power than competitors' chips. Ampere has raised $340 million from investors including ARM and Oracle.

AI chips are great, but an AI supercomputer is better. Cerebras Systems builds special chips that are much larger than those of rivals such as Nvidia, and — the company claims — capable of training AI systems potentially hundreds of times faster. Lie, Cerebras' cofounder and its chief hardware architect, has been core to those efforts, working on the design of those chips and helping Cerebras attract interest and investment from even OpenAI's Sam Altman.

Luong is the senior director of machine learning and AI at Apple, where she leads the training and development of the company's AI models. Before working at Apple, she was a director for Google's AI research efforts and the software for its Nest home assistant. Apple has been developing conversational AI technology and incorporating it into products such as Siri. Given Apple's incredible reach, her work is likely to have a significant impact on how many of us interact with AI.

As the head of Intel's data-center and AI group, Rivera leads the chip giant's AI strategy and oversees key products, such as the Xeon chip. Intel has been using AI to design, build, and sell its products and plays a crucial role in developing the components that run many of the world's computing systems. Rivera has worked at Intel for over two decades: She started in marketing, led the company's network-platforms group, and most recently served as the company's chief people officer.

Su has been at AMD for over a decade. Under her leadership, AMD's stock has increased in value nearly thirtyfold. It's building chips and software for AI inference and training, as well as signing AI partnerships with companies such as Hugging Face. It's preparing to launch its Instinct MI300X AI chip, which could challenge Nvidia's GPUs. "AI represents a multibillion-dollar growth opportunity for AMD across cloud, edge, and an increasingly diverse number of intelligent endpoints," Su said on a recent earnings call.