Categories: Samsung

Samsung Focuses on Developing More Sophisticated AI Memory Chips

Although Samsung initially lagged behind its competitors in the development of fifth generation high bandwidth memory (HBM3E) chips, the company has managed to narrow and effectively close that gap with the introduction of its sixth generation HBM4 technology. Reports indicate that Samsung has officially started large scale production of HBM4 and intends to supply Nvidia with these chips later this month. Meanwhile development efforts are already underway for future, more sophisticated HBM technologies.

At the Semicon Korea 2026 expo, an event expected to feature more than 550 global companies showcasing the latest advancements in semiconductor technology, Samsung Electronics CTO Song Jai-hyuk voiced strong confidence in the company’s leading position within the HBM4 segment. He emphasized Samsung’s ongoing efforts to strengthen its position in this advanced memory category. He said “Samsung which has been responding (to the market) with the world’s top technology, is just showing its true self.”

Song also stated that Samsung has streamlined and optimized its supply chain to more efficiently design and manufacture the chips needed for the rapidly expanding artificial intelligence (AI) sector. He noted that these improvements have fostered greater collaboration and synergy among the company’s internal teams.

According to Song, key chip clients including Nvidia have expressed approval of Samsung’s HBM4 offerings. Moving forward Samsung plans to keep advancing its memory portfolio through the development and large scale manufacturing of seventh generation HBM4E and eighth generation HBM5 chips.

Riding the wave of rapid growth in the AI market, Samsung Electronics which holds the position of the world’s biggest memory chipmaker recently announced record high revenue and profits. The company is widely expected to deliver even stronger results this year as shipments of its HBM4 chips ramp up and begin reaching key customers such as Nvidia in larger volumes.

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