Founded by Professor Princeton and veterans of AI hardware, the AI startup is developing in-analog memory computing chips to reduce energy consumption and expand AI beyond cloud data centers.
EnCharge AI has raised $100 million in a Series B funding round led by Tiger Global, with participation from Samsung Electronics’ VC ARM, HH-CTBC (Foxconn and CTBC Venture Capital partnership) and RTX Ventures. Masu. With this funding, AI will tailor AI to provide the market with its first AI accelerator solution and meet the unique needs of its partners. The startup will also deploy the first AI accelerator solutions designed to meet the specific needs of their partners using fresh capital injections, the accusations said in an announcement Thursday.
Princeton-backed founder and industry expertise
Anchare AI is Naveen Verma, Kailash Gopalakrishnan, and Ph.D. , and Echere Iroaga, Ph.D. was co-founded. Verma, CEO, is a professor of electrical and computer engineering at Princeton University, and has conducted basic research on Encharge’s chips.
Chief Product Officer Gopalakrishnan is an IBM Fellow and previously led IBM’s AI hardware and software efforts. Chief Operating Officer Iroaga brings more than 25 years of experience in the semiconductor industry and has a leadership role at Macom and Qualcomm.
The AI team will include engineers and executives from Nvidia, AMD, Waymo, Intel, Meta, Sambanova and Cerebras, bringing deep expertise in AI semiconductor development.
Solve AI growth energy problems
AI workloads, particularly the generation AI, are pushing energy consumption to unsustainable levels as companies rely on power-hungry data center clusters. Eliminating AI’s noise-resistant analog-login memory computing architecture dramatically reduces the power requirements for running both traditional AI inference workloads.
By integrating analog processing directly into memory, EnCharge’s AI accelerators consume up to 20 times less energy than the leading AI chips currently available in a wide range of applications. This efficiency breakthrough makes AI more viable beyond the cloud. Process AI processing directly to laptops, smartphones, and even devices such as defense and aerospace applications.
Extend AI beyond data centers
EnCharge AI technology is supported by a comprehensive software platform designed to maximize efficiency, performance and accuracy, ensuring seamless deployment of AI models in hardware. The ability to run AI workloads within tight power constraints is a game changer for industries with size, weight and power limits, such as defense and aerospace.
“We are pleased to announce that Dan Ateya, president and managing director of RTX Ventures,” said: “Continuing collaboration with AI will allow for advances in previously inaccessible environments, taking into account current processor technology limitations.”
Samsung Ventures highlighted the startup’s extensive research foundation, highlighting its ability to bring sophisticated AI to consumer devices beyond the cloud.
The managing director of Samsung Ventures said: “Based on multiple generations of chips, including seven years of peer-reviewed research, Naveen and his team are commercializing a complete hardware and software solution that can bring advanced AI from the cloud to consumer devices. I’m ready to turn it into something.”
As AI adoption continues to surge, AI has established itself as a key player in energy-efficient AI inference, bridging the gap between high-performance computing and sustainable AI deployment across industries.
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