Stratistics MRC¿¡ µû¸£¸é ¼¼°èÀÇ AI Ĩ ½ÃÀåÀº 2025³â¿¡ 1,703¾ï ´Þ·¯·Î ÃßÁ¤µÇ°í, ¿¹Ãø ±â°£ µ¿¾È CAGRÀº 22.9%·Î ¼ºÀåÇÒ Àü¸ÁÀ̸ç, 2032³â¿¡´Â 7,215¾ï ´Þ·¯¿¡ À̸¦ °ÍÀ¸·Î ¿¹ÃøµË´Ï´Ù.
AI ĨÀº ¸Ó½Å·¯´×À̳ª µö·¯´× µîÀÇ ÀΰøÁö´É ŽºÅ©¸¦ ó¸®Çϱâ À§ÇØ ¼³°èµÈ Àü¿ë ÇÁ·Î¼¼¼ÀÔ´Ï´Ù. ÀÌ Ä¨Àº ´ë·®ÀÇ µ¥ÀÌÅ͸¦ º´·Ä ó¸®ÇÔÀ¸·Î½á º¹ÀâÇÑ °è»êÀ» °í¼ÓÈÇÕ´Ï´Ù. º¸´Ù °í¼ÓÀ¸·Î È¿À²ÀûÀÎ AI ¸ðµ¨¿¡ ´ëÇÑ ¼ö¿ä°¡ ³ô¾ÆÁö´Â °¡¿îµ¥, ÀÌ·¯ÇÑ Ä¨Àº ÇコÄɾ ±ÝÀ¶À¸·ÎºÎÅÍ ·Îº¿ °øÇÐÀ̳ª ½º¸¶Æ® µð¹ÙÀ̽º¿¡ À̸£±â±îÁö, ¾÷°è Àüü¿¡¼ ºÒ°¡°áÇÑ °ÍÀÌ µÇ°í ÀÖ½À´Ï´Ù.
¿£ºñµð¾Æ¿¡ µû¸£¸é AI ¿öÅ©·Îµå¸¦ Áö¿øÇÏ´Â GPU ÄÄÇ»ÆÃ ¼ö¿ä°¡ ±ÞÁõÇϰí ÀÖÀ¸¸ç, µ¥ÀÌÅͼ¾ÅÍ ¸ÅÃâÀº 2024³âµµ 2ºÐ±â¿¡ 226¾ï ´Þ·¯(Àü³â µ¿±â ´ëºñ 171% Áõ°¡)¿¡ ´ÞÇß½À´Ï´Ù.
¾÷°è¸¦ °¡·ÎÁö¸£´Â AI µµÀÔÀÇ Æø¹ßÀû ¼ºÀå
ÇコÄɾî, ÀÚµ¿Â÷, ±ÝÀ¶, Á¦Á¶ µîÀÇ ºÐ¾ß¿¡¼ ÀΰøÁö´ÉÀÌ ±Þ¼ÓÈ÷ ÅëÇյǰí ÀÖ´Â °ÍÀÌ AI Ĩ ½ÃÀåÀÇ ÁÖ¿ä ÃËÁø¿äÀÎÀÌ µÇ°í ÀÖ½À´Ï´Ù. ÀÚµ¿È, ºÐ¼®, ÀÇ»ç°áÁ¤¿¡ AI¸¦ Ȱ¿ëÇÏ´Â ±â¾÷ÀÌ ´Ã¸é¼ º¹ÀâÇÑ °è»êÀ» ó¸®ÇÒ ¼ö ÀÖ´Â Àü¿ë Ĩ ¼ö¿ä°¡ ±ÞÁõÇϰí ÀÖ½À´Ï´Ù. ÀÌ·¯ÇÑ ±¤¹üÀ§ÇÑ Ã¤¿ëÀº ´ë±â¾÷¿¡¸¸ ±¹ÇÑµÈ °ÍÀÌ ¾Æ´Ï¸ç, Áß¼Ò±â¾÷µµ AI ÁÖµµÀÇ ¼Ö·ç¼ÇÀ» µµÀÔÇϰí ÀÖ½À´Ï´Ù. ¶ÇÇÑ µ¥ÀÌÅͼ¾ÅÍ ¹× Ŭ¶ó¿ìµå ±â¹Ý ¼ºñ½ºÀÇ º¸±ÞÀ¸·Î °í¼º´É AI ĨÀÇ ¼ö¿ä°¡ ³ô¾ÆÁö°í ÀÖ¾î ½ÃÀå È®´ë¿¡ ¹ÚÂ÷¸¦ °¡Çϰí ÀÖ½À´Ï´Ù.
³ôÀº ¿¬±¸°³¹ß ¹× Á¦Á¶ ºñ¿ë
÷´Ü AI ĨÀÇ °³¹ß°ú Á¦Á¶´Â ¿¬±¸ °³¹ß, Àü¹® ÀηÂ, ÃÖ÷´Ü Á¦Á¶ ¼³ºñ¿¡ ¸¹Àº ÅõÀÚ¸¦ ÇÊ¿ä·Î ÇÏ´Â °í°¡ÀÇ º¹ÀâÇÑ ÇÁ·Î¼¼½ºÀÔ´Ï´Ù. Ĩ ¼³°èÀÇ º¹À⼺Àº ÁøÈÇÏ´Â AI ¾Ë°í¸®Áò¿¡ ´ëÀÀÇϱâ À§ÇÑ ²÷ÀÓ¾ø´Â ±â¼ú Çõ½ÅÀÇ Çʿ伺°ú ¸Â¹°·Á ³ôÀº ÁøÀÔ À庮À» ¸¸µé¾î³»°í ÀÖ½À´Ï´Ù. °Ô´Ù°¡ °ø±Þ¸ÁÀÇ È¥¶õÀ̳ª Áß¿äÇÑ ¿øÀç·áÀÇ ºÎÁ·Àº ºñ¿ëÀ» ´õ¿í »ó½Â½Ãų °¡´É¼ºÀÌ ÀÖ½À´Ï´Ù. ÀÌ·¯ÇÑ ¿äÀÎÀº ƯÈ÷ ½Å±Ô Âü°¡ ±â¾÷ ¹× ¼Ò±Ô¸ð ±â¾÷¿¡ ÀÖ¾î¼, ÃÑüÀûÀ¸·Î ½ÃÀåÀÇ ¼ºÀåÀ» Á¦¾àÇØ ¾÷°èÀÇ ±â¼ú Áøº¸ÀÇ ÆäÀ̽º¸¦ ´ÊÃâ °¡´É¼ºÀÌ ÀÖ½À´Ï´Ù.
AI ¾Ë°í¸®Áò ¹× ¸ðµ¨ Áøº¸
AI ¾Ë°í¸®Áò°ú ¸ðµ¨ÀÇ Áö¼ÓÀûÀΠȹ±âÀûÀÎ º¯È´Â Å« ±âȸ¸¦ Á¦°øÇÕ´Ï´Ù. ¸ðµ¨ÀÌ º¸´Ù ¼¼·ÃµÇ°í ¸®¼Ò½º¸¦ ´ë·®À¸·Î ¼ÒºñÇÏ°Ô µÊ¿¡ µû¶ó ÀÌ·¯ÇÑ ¿öÅ©·Îµå¸¦ È¿À²ÀûÀ¸·Î ó¸®ÇÒ ¼ö ÀÖ´Â Çϵå¿þ¾îÀÇ Çʿ伺ÀÌ ³ô¾ÆÁö°í ÀÖ½À´Ï´Ù. °Ô´Ù°¡ ¿¡Áö ÄÄÇ»ÆÃÀÇ ÁøÈ¿Í ·Îº¿ °øÇÐ, IoT, ÀÚÀ² ½Ã½ºÅÛ¿¡¼ »õ·Î¿î AI ¾ÖÇø®ÄÉÀ̼ÇÀÇ ÃâÇöÀÌ Çõ½ÅÀûÀΠĨ ¾ÆÅ°ÅØÃ³ ¼ö¿ä¸¦ ÃËÁøÇϰí ÀÖ½À´Ï´Ù. ¾÷°è°¡ ¼º´É°ú ¿¡³ÊÁö È¿À²¿¡ ¸ðµÎ ÃÖÀûÈµÈ Çϵå¿þ¾î¸¦ ¿ä±¸ÇÏ´Â °¡¿îµ¥, ÀÌ·¯ÇÑ Áøº¸¸¦ Àß ÀÌ¿ëÇÏ´Â ±â¾÷Àº ä¿ë È®´ë¿¡ µû¸¥ ÀÌÀÍÀ» ´©¸®°Ô µË´Ï´Ù.
À±¸®Àû ¿ì·Á ¹× ±ÔÁ¦ ¸ð´ÏÅ͸µ
AI ĨÀº À±¸®Àû ¹è·Á¿Í ±ÔÁ¦ °¨µ¶¿¡ ÀÇÇÑ °úÁ¦°¡ »êÀûÇϰí ÀÖ½À´Ï´Ù. µ¥ÀÌÅÍ ÇÁ¶óÀ̹ö½Ã, ¾Ë°í¸®Áò ÆíÇâ, AI ±â¼ú ¾Ç¿ë °¡´É¼º°ú °°Àº ¹®Á¦´Â Á¤ºÎ¿Í ±ÔÁ¦±â°ü¿¡ º¸´Ù ¾ö°ÝÇÑ °¡À̵å¶óÀÎ µµÀÔÀ» Ã˱¸Çϰí ÀÖ½À´Ï´Ù. ÀÌ·¯ÇÑ ±ÔÁ¦ÀÇ ÁøÀüÀº ÄÄÇöóÀ̾𽺠ºñ¿ëÀ» Áõ´ë½ÃÄÑ Á¦Ç°ÀÇ Ãâ½Ã¸¦ ´ÊÃâ °¡´É¼ºÀÌ ÀÖ½À´Ï´Ù. °Ô´Ù°¡ ¼¼°£ÀÇ °¨½ÃÀÇ ´«ÀÌ ¾ö°ÝÇØÁö¸é¼ ¼ÒºñÀÚ ½Å·Ú¿¡ ¿µÇâÀ» ¹ÌÃÄ AI¸¦ Ȱ¿ëÇÑ ¼Ö·ç¼Ç äÅÃÀÌ Áö¿¬µÉ °¡´É¼ºµµ ÀÖ½À´Ï´Ù.
COVID-19ÀÇ ´ëÀ¯ÇàÀº ´çÃÊ ¼¼°è °ø±Þ¸Á°ú Á¦Á¶¾÷¹«¸¦ È¥¶õ½ÃÄÑ AI ĨÀÇ »ý»ê°ú Àü°³¿¡ Áö¿¬À» °¡Á®¿Ô½À´Ï´Ù. ÇÏÁö¸¸ ÀÌ À§±â´Â Á¶Á÷ÀÌ ¿ø°Ý±Ù¹«·Î ÀüȯµÇ°í AI ±¸µ¿Çü ±â¼ú¿¡ ´ëÇÑ ÀÇÁ¸µµ°¡ ³ô¾ÆÁü¿¡ µû¶ó µðÁöÅÐ ÀüȯÀ» °¡¼ÓÈÇϱ⵵ Çß½À´Ï´Ù. ÀÌ ¶§¹®¿¡ ÇコÄɾî, ¹°·ù, ÀüÀÚ»ó°Å·¡ µî ºÐ¾ß¿¡¼ AI Ĩ ¼ö¿ä°¡ ±ÞÁõÇß½À´Ï´Ù. Ãʱâ ÁÂÀý¿¡µµ ºÒ±¸ÇÏ°í ½ÃÀåÀº ºü¸£°Ô ÀûÀÀÇß°í, AI ÀÎÇÁ¶ó¿¡ ´ëÇÑ ÅõÀÚ°¡ Áõ°¡ÇßÀ¸¸ç, ¾÷°è´Â ÆÒµ¥¹Í ÀÌÈÄ °ßÁ¶ÇÑ ¼ºÀåÀ» À§ÇØ ÀÚ¸®¸Å±èÇß½À´Ï´Ù.
¿¹Ãø ±â°£ µ¿¾È ±×·¡ÇÈ ÇÁ·Î¼¼½Ì À¯´Ö(GPU) ºÐ¾ß°¡ ÃÖ´ë°¡ µÉ Àü¸Á
±×·¡ÇÈ ÇÁ·Î¼¼½Ì À¯´Ö(GPU) ºÎ¹®Àº ¿¹Ãø ±â°£ µ¿¾È °¡Àå Å« ½ÃÀå Á¡À¯À²À» Â÷ÁöÇÒ °ÍÀ¸·Î ¿¹ÃøµË´Ï´Ù. GPU´Â º´·Ä ó¸® ´É·ÂÀ» ÅëÇØ µ¥ÀÌÅͼ¾ÅÍ, Ŭ¶ó¿ìµå ȯ°æ, °í¼º´É ÄÄÇ»ÆÃ ¾ÖÇø®ÄÉÀ̼ǿ¡¼ º¹ÀâÇÑ AI ¿öÅ©·Îµå¸¦ ó¸®ÇÏ´Â µ¥ °¡Àå ÀûÇÕÇÏ´Ù°í ÁöÁö¹Þ°í ÀÖ½À´Ï´Ù. ¿£ºñµð¾Æ, AMD, ÀÎÅÚ µî ´ë±â¾÷µéÀº Áö¼ÓÀûÀÎ ±â¼ú Çõ½Å°ú µö·¯´×, ÀÚ¿¬¾î ó¸®, ÄÄÇ»ÅÍ ºñÀü µî AI¸¦ Ȱ¿ëÇÏ´Â ¾÷°èÀÇ ¿Õ¼ºÇÑ ¼ö¿ä·Î ÀÌ ºÐ¾ß¿¡¼ È®°íÇÑ ÀÔÁö¸¦ ±¸ÃàÇϰí ÀÖ½À´Ï´Ù. Á¦³×·¹ÀÌÆ¼ºê AI ¹× ´ë±Ô¸ð ¾ð¾î ¸ðµ¨ÀÌ º¸±ÞµÊ¿¡ µû¶ó ÀÌ ¿ìÀ§¼ºÀº Áö¼ÓµÉ °ÍÀ¸·Î º¸ÀÔ´Ï´Ù.
¿¹Ãø ±â°£ µ¿¾È °¡ÀåÀÚ¸® ºÎ¹®ÀÇ CAGRÀÌ °¡Àå ³ôÀ» °ÍÀ¸·Î ¿¹»ó
¿¹Ãø ±â°£ µ¿¾È °¡ÀåÀÚ¸® ºÎ¹®ÀÌ °¡Àå ³ôÀº ¼ºÀå·üÀ» º¸ÀÏ °ÍÀ¸·Î ¿¹ÃøµË´Ï´Ù. ÀÚÀ²ÁÖÇàÂ÷, ½º¸¶Æ® µð¹ÙÀ̽º, »ê¾÷ ÀÚµ¿È¿¡ ÀÖ¾î¼ ½Ç½Ã°£ µ¥ÀÌÅÍ Ã³¸® ¹× Àú·¹ÀÌÅϽà AI ¾ÖÇø®ÄÉÀ̼ÇÀÇ ¿ä±¸ °íÁ¶°¡, ¿§Áö AI ĨÀÇ ¼ö¿ä¸¦ ÃËÁøÇϰí ÀÖ½À´Ï´Ù. ÀÌ·¯ÇÑ Ä¨Àº ·ÎÄà 󸮸¦ °¡´ÉÇÏ°Ô Çϰí Ŭ¶ó¿ìµå ÀÎÇÁ¶ó¿¡ ´ëÇÑ ÀÇÁ¸µµ¸¦ ÁÙÀÌ¸ç ¼Óµµ, ÇÁ¶óÀ̹ö½Ã, ¿¡³ÊÁö È¿À²À» Çâ»ó½Ãŵ´Ï´Ù. IoT äÅÃÀÌ È®´ëµÇ°í ¿Âµð¹ÙÀ̽º ÀÎÅÚ¸®Àü½º¸¦ ÇÊ¿ä·Î ÇÏ´Â µð¹ÙÀ̽º°¡ ´Ã¾î³²¿¡ µû¶ó ¿§Áö ºÎ¹®Àº ´ëÆø °¡¼ÓµÉ °ÍÀ¸·Î º¸ÀÔ´Ï´Ù.
¿¹Ãø ±â°£ µ¿¾È ºÏ¹Ì°¡ °¡Àå Å« ½ÃÀå Á¡À¯À²À» Â÷ÁöÇÒ °ÍÀ¸·Î ¿¹ÃøµË´Ï´Ù. ÀÌ ¿ìÀ§¼ºÀº, ÁÖ¿ä Å×Å©³î·ÎÁö ±â¾÷ÀÇ Á¸Àç, °°íÇÑ À̳뺣ÀÌ¼Ç ¿¡ÄÚ ½Ã½ºÅÛ, AI ¿¬±¸ °³¹ß¿¡ ´ëÇÑ °í¾×ÀÇ ÅõÀÚ¿¡ ±âÀÎÇÕ´Ï´Ù. ÀÌ Áö¿ª¿¡¼´Â ÇコÄɾîºÎÅÍ ÀÚµ¿Â÷¿¡ À̸£´Â ´Ù¾çÇÑ ºÐ¾ß¿¡¼ AI ±â¼úÀÌ Á¶±â¿¡ äÅõǰí ÀÖ¾î ¼ö¿ä¸¦ ´õ¿í µÞ¹ÞħÇϰí ÀÖ½À´Ï´Ù. ¾Æ¿ï·¯ Á¤ºÎÀÇ Áö¿øÃ¥°ú º¥Ã³Ä³ÇÇÅÐÀÇ ÀÚ±ÝÁ¶´Þ·Î AIĨ Çõ½Å°ú »ó¾÷È¿¡ À¯¸®ÇÑ È¯°æÀÌ Á¶¼ºµÅ ºÏ¹Ì ¸®´õ½ÊÀÌ È®°íÇØÁö°í ÀÖ½À´Ï´Ù.
¿¹Ãø ±â°£ µ¿¾È ¾Æ½Ã¾ÆÅÂÆò¾çÀÌ °¡Àå ³ôÀº CAGRÀ» ³ªÅ¸³¾ °ÍÀ¸·Î ¿¹ÃøµË´Ï´Ù. ±Þ¼ÓÇÑ µðÁöÅÐÈ, »ê¾÷ ÀÚµ¿È È®´ë, AI ÀÎÇÁ¶ó ÅõÀÚ Áõ°¡°¡ ÀÌ Áö¿ªÀÇ ÁÖ¿ä ÃËÁø ¿äÀÎÀÔ´Ï´Ù. Áß±¹, ÀϺ», Çѱ¹°ú °°Àº ±¹°¡µéÀº Á¤ºÎÀÇ °·ÂÇÑ Á¤Ã¥°ú ÇÏÀÌÅ×Å© ½ÅÈï ±â¾÷ÀÇ ¼ºÀå »ýŰ迡 ÈûÀÔ¾î AI Ĩ Á¦Á¶¿Í Àü°³ÀÇ ÃÖÀü¼±¿¡ ÀÖ½À´Ï´Ù. ½º¸¶Æ® µð¹ÙÀ̽º ¹× IoT ¾ÖÇø®ÄÉÀ̼ÇÀÇ º¸±ÞÀº Àú·ÅÇÑ °¡°ÝÀÇ AI ¼Ö·ç¼Ç¿¡ ´ëÇÑ ¼ö¿ä Áõ°¡¿Í ¸Â¹°·Á ¾Æ½Ã¾ÆÅÂÆò¾ç Áö¿ªÀ» °¡Àå ±Þ¼ºÀåÇϰí ÀÖ´Â Áö¿ªÀ¸·Î ÀÚ¸®¸Å±èÇϰí ÀÖ½À´Ï´Ù.
According to Stratistics MRC, the Global AI Chips Market is accounted for $170.3 billion in 2025 and is expected to reach $721.5 billion by 2032 growing at a CAGR of 22.9% during the forecast period. AI chips are specialized processors designed to handle artificial intelligence tasks like machine learning and deep learning. These chips accelerate complex computations by processing large volumes of data in parallel. With growing demand for faster, more efficient AI models, these chips are becoming essential across industries, from healthcare and finance to robotics and smart devices.
According to NVIDIA, the demand for GPU computing to support AI workloads has surged, with data center revenue reaching $22.6 billion in Q2 FY2024, a 171% increase year-over-year.
Explosive growth of Ai adoption across industries
The rapid integration of artificial intelligence across sectors such as healthcare, automotive, finance, and manufacturing is a primary driver for the AI chips market. As organizations increasingly leverage AI for automation, analytics, and decision-making, the demand for specialized chips capable of handling complex computations has surged. This widespread adoption is not limited to large enterprises; small and medium-sized businesses are also embracing AI-driven solutions. Furthermore, the proliferation of data centers and cloud-based services has intensified the need for high-performance AI chips, fueling market expansion.
High research & development and manufacturing costs
Developing and manufacturing advanced AI chips is an expensive and intricate process, requiring significant investments in R&D, specialized talent, and state-of-the-art fabrication facilities. The complexity of chip design, coupled with the need for constant innovation to keep pace with evolving AI algorithms, creates high entry barriers. Additionally, supply chain disruptions and the scarcity of critical raw materials can further escalate costs. These factors collectively constrain market growth, particularly for new entrants and smaller firms, and may slow the pace of technological advancement in the industry.
Advancements in Ai algorithms and models
Ongoing breakthroughs in AI algorithms and models present substantial opportunities. As models become more sophisticated and resource-intensive, there is a growing need for hardware that can efficiently process these workloads. Moreover, the evolution of edge computing and the emergence of new AI applications in robotics, IoT, and autonomous systems are driving demand for innovative chip architectures. Companies that successfully harness these advancements stand to benefit from increased adoption, as industries seek hardware optimized for both performance and energy efficiency.
Ethical concerns and regulatory scrutiny
AI chips face mounting challenges from ethical considerations and regulatory oversight. Issues such as data privacy, algorithmic bias, and the potential misuse of AI technologies have prompted governments and regulatory bodies to introduce stricter guidelines. These evolving regulations can increase compliance costs and delay product launches. Additionally, heightened public scrutiny may impact consumer trust and slow the adoption of AI-powered solutions.
The Covid-19 pandemic initially disrupted global supply chains and manufacturing operations, causing delays in AI chip production and deployment. However, the crisis also accelerated digital transformation as organizations shifted to remote work and increased reliance on AI-driven technologies. This led to a surge in demand for AI chips in sectors such as healthcare, logistics, and e-commerce. Despite early setbacks, the market quickly adapted, and investments in AI infrastructure rose, positioning the industry for robust post-pandemic growth.
The graphics processing unit (GPU) segment is expected to be the largest during the forecast period
The graphics processing unit (GPU) segment is expected to account for the largest market share during the forecast period. GPUs are favored for their parallel processing capabilities, making them ideal for handling complex AI workloads in data centers, cloud environments, and high-performance computing applications. Major players such as NVIDIA, AMD, and Intel have established strong positions in this segment, driven by continuous innovation and robust demand from industries leveraging AI for deep learning, natural language processing, and computer vision. This dominance is set to persist as generative AI and large language models become more prevalent.
The edge segment is expected to have the highest CAGR during the forecast period
Over the forecast period, the edge segment is predicted to witness the highest growth rate. The increasing need for real-time data processing and low-latency AI applications in autonomous vehicles, smart devices, and industrial automation is propelling demand for edge AI chips. These chips enable local processing, reducing reliance on cloud infrastructure and improving speed, privacy, and energy efficiency. As IoT adoption expands and more devices require on-device intelligence, the edge segment will experience significant acceleration.
During the forecast period, the North America region is expected to hold the largest market share. This dominance is attributed to the presence of leading technology companies, robust innovation ecosystems, and substantial investments in AI research and development. The region's early adoption of AI technologies across diverse sectors ranging from healthcare to automotive further bolsters demand. Additionally, supportive government initiatives and venture capital funding have fostered a favorable environment for AI chip innovation and commercialization, solidifying North America's leadership.
Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR. Rapid digitalization, expanding industrial automation, and increasing investments in AI infrastructure are key drivers in this region. Countries like China, Japan, and South Korea are at the forefront of AI chip manufacturing and deployment, supported by strong government policies and a growing ecosystem of tech startups. The proliferation of smart devices and IoT applications, coupled with rising demand for affordable AI solutions, positions Asia Pacific as the fastest-growing region.
Key players in the market
Some of the key players in AI Chips Market include NVIDIA Corporation, Intel Corporation, Advanced Micro Devices, Inc. (AMD), Qualcomm Technologies, Inc., Alphabet Inc. (Google LLC), IBM Corporation, Samsung Electronics Co., Ltd., Huawei Technologies Co., Ltd., Baidu, Inc., Apple Inc., Microsoft Corporation, Amazon Web Services, Inc., Broadcom Inc., MediaTek Inc., Graphcore Limited, Rebellions Inc., SK Hynix Inc. and Sapeon Inc.
In June 2025, AMD launched the AMD Instinct(TM) MI350 Series, delivering up to 4 x generation-on-generations AI compute improvement and up to 35x leap in inferencing performance. AMD also showcased its new developer cloud to empowering AI developers with seamless access to AMD Instinct GPUs and ROCm for their AI innovation. The company also previewed its next-gen "Helios" AI rack infrastructure, integrating MI400 GPUs, EPYC "Venice" CPUs, and Pensando "Vulcano" NICs for unprecedented AI compute density and scalability
In May 2025, NVIDIA announced that Taiwan's leading system manufacturers are set to build NVIDIA DGX Spark and DGX Station(TM) systems. Growing partnerships with Acer, GIGABYTE and MSI will extend the availability of DGX Spark and DGX Station personal AI supercomputers - empowering a global ecosystem of developers, data scientists and researchers with unprecedented performance and efficiency. Enterprises, software providers, government agencies, startups and research institutions need robust systems that can deliver the performance and capabilities of an AI server in a desktop form factor without compromising data size, proprietary model privacy or the speed of scalability.
In May 2025, At Embedded World Germany, Qualcomm Technologies, Inc. announced the entry into an agreement to acquire EdgeImpulse Inc., which will enhance its offering for developers and expand its leadership in AI capabilities to power AI-enabled products and services across IoT. The closing of this deal is subject to customary closing conditions. This acquisition is anticipated to complement Qualcomm Technologies' strategic approach to IoT transformation, which includes a comprehensive chipset roadmap, unified software architecture, a suite of services, developer resources, ecosystem partners, comprehensive solutions, and IoT blueprints to address diverse industry needs and challenges.