Hardware that consumes less power will reduce artificial intelligence's appetite for energy. But transparency about its carbon footprint is still needed.
Naveen Verma, Ph.D., is the Co-founder and CEO of EnCharge AI. At Encharge, he leads a team of engineering veterans from NVIDIA, Intel, Qualcomm, IBM, and AMD who are commercializing a revolutionary AI chip that solves the energy, scalability, and cost constraints of existing AI compute technologies.
New collaboration to yield full-stack computing solution capable of supporting large-scale public- and private-sector advancements in AI through $18.6 million grant
In the realm of advancing technology, the demand for Artificial Intelligence (AI) solutions is surging. Yet, a major hurdle hindering widespread adoption is the high cost of AI computing. Overcoming these barriers is essential for scaling AI deployment effectively.
The past year has been one of exciting growth for EnCharge AI and the broader AI industry. The release of generative AI tools like ChatGPT fueled demand for AI applications with the potential to enhance high-value functions across a wide range of industries.
EnCharge AI, the company developing advanced AI chips and full stack solutions, today announced it has closed a second institutional round of funding from strategic partners including.
Following years of research and development at Princeton University, EnCharge AI emerges from stealth led by a world-class, multi-disciplinary team from Meta, NVIDIA, Qualcomm, and IBM.
Former Intel Edge AI GM Ram Rangarajan joins EnCharge as its Senior Vice President, Product and Strategy. Ram will work alongside the EnCharge leadership team to advance the company to its next phase of growth and bring its revolutionary in-memory compute-based AI solutions to market, unlocking unprecedented capabilities for large scale automation.
Princeton University — A startup based on Princeton research is rethinking the computer chip with a design that increases performance, efficiency and capability to match the computational needs of technologies that use AI. Using a technique called in-memory computing...
