½ÃÀ庸°í¼­
»óÇ°ÄÚµå
1452979

¼¼°èÀÇ ¸ÖƼ¸ð´Þ AI ½ÃÀå(2024-2031³â)

Global Multimodal AI Market 2024-2031

¹ßÇàÀÏ: | ¸®¼­Ä¡»ç: Orion Market Research | ÆäÀÌÁö Á¤º¸: ¿µ¹® 175 Pages | ¹è¼Û¾È³» : 2-3ÀÏ (¿µ¾÷ÀÏ ±âÁØ)

    
    
    




¡Ø º» »óÇ°Àº ¿µ¹® ÀÚ·á·Î Çѱ۰ú ¿µ¹® ¸ñÂ÷¿¡ ºÒÀÏÄ¡ÇÏ´Â ³»¿ëÀÌ ÀÖÀ» °æ¿ì ¿µ¹®À» ¿ì¼±ÇÕ´Ï´Ù. Á¤È®ÇÑ °ËÅ並 À§ÇØ ¿µ¹® ¸ñÂ÷¸¦ Âü°íÇØÁֽñ⠹ٶø´Ï´Ù.

¼¼°è ¸ÖƼ¸ð´Þ AI ½ÃÀåÀº ¿¹Ãø ±â°£(2024-2031³â) µ¿¾È 14.9%ÀÇ ³ôÀº CAGR·Î ¼ºÀåÇÒ °ÍÀ¸·Î ¿¹»óµË´Ï´Ù. ÅؽºÆ®, À̹ÌÁö, À½¼º µî ´Ù¾çÇÑ ¸ð´Þ¸®Æ¼¿¡ °ÉÄ£ µ¥ÀÌÅÍ »ý¼ºÀÇ Çâ»ó°ú ÇÔ²² ¸ÖƼ¸ð´Þ »ý¼ºÇü AI ¸ðµ¨ÀÇ Ã¤ÅÃÀÌ Áõ°¡ÇÔ¿¡ µû¶ó ¼¼°è ½ÃÀå ¼ºÀåÀ» À̲ô´Â ÁÖ¿ä ¿äÀÎÀ¸·Î ÀÛ¿ëÇÏ°í ÀÖ½À´Ï´Ù. »ý¼ºÀû ¸ÖƼ¸ð´Þ AI ¼Ö·ç¼Ç µµÀÔ¿¡ ÁýÁßÇÏ´Â ½ÃÀå ±â¾÷ÀÌ Áõ°¡Çϸ鼭 ½ÃÀå ¼ºÀåÀ» ´õ¿í ÃËÁøÇÏ°í ÀÖ½À´Ï´Ù. ¿¹¸¦ µé¾î, 2023³â 3¿ù AWS¿Í ¿£ºñµð¾Æ´Â ´ë±Ô¸ð ML ¸ðµ¨ ÈÆ·Ã ¹× »ý¼ºÇü AI ¾ÖÇø®ÄÉÀÌ¼Ç ±¸ÃàÀ» À§ÇÑ Â÷¼¼´ë ÀÎÇÁ¶ó¸¦ À§ÇØ Çù·ÂÇß½À´Ï´Ù. ÀÌ Çù¾÷Àº °¡Àå È®Àå °¡´ÉÇÑ ¿Âµð¸ÇµåÇü AI ÀÎÇÁ¶ó °³¹ß¿¡ ÃÊÁ¡À» ¸ÂÃá °ÍÀ¸·Î, »ý¼ºÇü AI ¾ÖÇø®ÄÉÀÌ¼Ç °³¹ß°ú ±× ¾î´À ¶§º¸´Ù º¹ÀâÇÑ ´ë±Ô¸ð ¾ð¾î ¸ðµ¨(LLM)ÀÇ ÇнÀÀ» Áö¿øÇϵµ·Ï ¼³°èµÇ¾ú½À´Ï´Ù. AI ±â¼ú¿¡ ´ëÇÑ ÅõÀÚ Áõ°¡´Â ½ÃÀå ¼ºÀå¿¡ À¯¸®ÇÑ ±âȸ¸¦ Á¦°øÇÒ °ÍÀ¸·Î ±â´ëµË´Ï´Ù.

ºÎ¹®º° Àü¸Á

ML ÇÏÀ§ ºÎ¹®ÀÌ Àü ¼¼°è ¸ÖƼ¸ð´Þ AI ½ÃÀå¿¡¼­ »ó´çÇÑ Á¡À¯À²À» Â÷ÁöÇÒ °ÍÀ¸·Î ¿¹»ó

±â¼ú Áß¿¡¼­µµ ML ÇÏÀ§ ºÎ¹®Àº ¼¼°è ¸ÖƼ¸ð´Þ AI ½ÃÀå¿¡¼­ »ó´çÇÑ Á¡À¯À²À» Â÷ÁöÇÒ °ÍÀ¸·Î ¿¹»óµË´Ï´Ù. ÀÌ ºÎ¹®ÀÇ ¼ºÀåÀº NLP¿Í ÄÄÇ»ÅÍ ºñÀüÀ» Æ÷ÇÔÇÑ ¸ÖƼ¸ð´Þ AI¸¦ ÈÆ·ÃÇϱâ À§ÇÑ ML ±â¹Ý °³¹ß ½Ã½ºÅÛÀÇ Ã¤ÅÃÀÌ Áõ°¡ÇÔ¿¡ µû¶ó ÀÌ ºÎ¹®ÀÇ ¼ºÀå¿¡ ±âÀÎÇÕ´Ï´Ù. ´ë±Ô¸ð AI ¸ðµ¨ °³¹ß ¹× ÇнÀÀ» Áö¿øÇϱâ À§ÇØ AI ÀÎÇÁ¶ó¸¦ äÅÃÇÏ·Á¸é °íµµ·Î º´·ÄÈ­µÈ ¼ÒÇÁÆ®¿þ¾î »ýÅ°èÀÇ ¼³Á¤, ±¸¸Å ¹× À¯Áöº¸¼ö¸¦ Æ÷ÇÔÇÑ ¿©·¯ ´Ü°è°¡ ÇÊ¿äÇÕ´Ï´Ù. 2022³â 4¿ù, ÈÞ·¿ÆÑÄ¿µå ¿£ÅÍÇÁ¶óÀÌÁî(HPE)´Â HPEÀÇ »õ·Î¿î ML °³¹ß ½Ã½ºÅÛÀ» ¹ßÇ¥Çß½À´Ï´Ù. ÀÌ »õ·Î¿î ½Ã½ºÅÛÀº ¸ÖƼ¸ð´Þ AI¸¦ À§ÇØ Æ¯º°È÷ ¼³°èµÈ ¿£µåÅõ¿£µå ¼Ö·ç¼ÇÀ¸·Î, ³×Æ®¿öÅ·, °¡¼Ó±â, ÄÄÇ»ÆÃ, ML ¼ÒÇÁÆ®¿þ¾î Ç÷§ÆûÀ» °áÇÕÇÏ¿© º¸´Ù Á¤È®ÇÑ AI ¸ðµ¨À» º¸´Ù ºü¸£°í ´ë±Ô¸ð·Î »ý¼ºÇÏ°í ÈÆ·ÃÇÒ ¼ö ÀÖµµ·Ï Áö¿øÇÕ´Ï´Ù. ÀÌ·¯ÇÑ Á¦Ç° Ãâ½Ã´Â ÀÌ ½ÃÀå ºÎ¹®ÀÇ ¼ºÀåÀ» ´õ¿í ÃËÁøÇÏ°í ÀÖ½À´Ï´Ù.

Áö¿ªº° Àü¸Á

¼¼°è ¸ÖƼ¸ð´Þ AI ½ÃÀåÀº ºÏ¹Ì(¹Ì±¹, ij³ª´Ù), À¯·´(¿µ±¹, ÀÌÅ»¸®¾Æ, ½ºÆäÀÎ, µ¶ÀÏ, ÇÁ¶û½º, ±âŸ À¯·´ Áö¿ª), ¾Æ½Ã¾ÆÅÂÆò¾ç(Àεµ, Áß±¹, ÀϺ», Çѱ¹, ±âŸ ¾Æ½Ã¾Æ Áö¿ª), ±âŸ ¼¼°è Áö¿ª(Áßµ¿ ¹× ¾ÆÇÁ¸®Ä«, ¶óƾ¾Æ¸Þ¸®Ä«) µî Áö¿ªº°·Î ¼¼ºÐÈ­µË´Ï´Ù. ÀÌ Áß ¾Æ½Ã¾ÆÅÂÆò¾çÀº ¿¹Ãø ±â°£ µ¿¾È °¡Àå ³ôÀº CAGRÀ» º¸ÀÏ °ÍÀ¸·Î ¿¹»óµÇ¸ç, E-Commerce, ÇコÄɾî, ±ÝÀ¶ µîÀÇ ºÐ¾ß¿¡¼­ ¸ÖƼ¸ð´Þ AIÀÇ Ã¤ÅÃÀÌ È®´ëµÇ°í ÀÖ´Â °ÍÀÌ ÀÌ Áö¿ª ½ÃÀåÀÇ ¼ºÀåÀ» °ßÀÎÇÏ°í ÀÖ½À´Ï´Ù.

ºÏ¹Ì, Àü ¼¼°è ¸ÖƼ¸ð´Þ AI ½ÃÀå¿¡¼­ Å« ºñÁßÀ» Â÷Áö

¸ðµç Áö¿ª Áß ºÏ¹Ì´Â ¼¼°è ½ÃÀå¿¡¼­ »ó´çÇÑ Á¡À¯À²À» Â÷ÁöÇÏ°í ÀÖ½À´Ï´Ù. ÀÌ Áö¿ªÀÇ ½ÃÀå Á¡À¯À²Àº ¸ÖƼ¸ð´Þ AI ¼Ö·ç¼ÇÀÇ ½ÃÀå °³Ã´°ú µµÀÔÀÌ È°¹ßÈ÷ ÀÌ·ç¾îÁö°í Àֱ⠶§¹®ÀÔ´Ï´Ù. ÀüȯÀ²ÀÌ ³ôÀº µðÁöÅÐ ¸ÅÀåÀ» ±¸ÃàÇϱâ À§ÇÑ ´Ü°èº° Áö¿øÀ» Á¦°øÇÏ°í, Áö¿ª ³» ¿©·¯ »óÇ° Ä«Å»·Î±× µ¥ÀÌÅÍ °ü¸®¿Í °°Àº º¹ÀâÇÑ ÀÛ¾÷À» ÀÚµ¿È­Çϱâ À§ÇÑ ¸ÖƼ¸ð´Þ AI¿¡ ´ëÇÑ ¼ö¿ä°¡ Áõ°¡Çϸ鼭 ÀÌ Áö¿ªÀÇ ½ÃÀå Á¡À¯À²ÀÌ ´õ¿í È®´ëµÇ°í ÀÖ½À´Ï´Ù. 2023³â 9¿ù, ¼¼ÀÏÁîÆ÷½º´Â »õ·Î¿î »ý¼º AI ±â¹Ý ´ëÈ­ µµ¿ì¹Ì ¾ÆÀν´Å¸ÀÎ ÄÚÆÄÀÏ·µ(Einstein Copilota)À» ¹ßÇ¥Çß½À´Ï´Ù. ¾ÆÀν´Å¸ÀÎ ÄÚÆÄÀÏ·µÀº ÀÚ¿¬¾î ÇÁ·ÒÇÁÆ®¸¦ »ç¿ëÇÏ¿© ¿ÏÀüÇÑ ´Ù±¹¾î, °³ÀÎÈ­ µÈ Á¦Ç° ÇÁ·Î¸ð¼Ç, SEO ¸ÞŸ µ¥ÀÌÅÍ »ý¼ºÀ» Á¦°øÇÏ¿© ÀüȯÀ» ÃËÁøÇÏ°í ÀÚ¿¬¾î ÇÁ·ÒÇÁÆ®¸¦ ÅëÇØ ¸ÅÀå Àü¸é ±¸¼º ¿ä¼Ò¸¦ »ç¿ëÀÚ Á¤ÀÇÇÏ°í ¼³°èÇÕ´Ï´Ù. ÀÌ·¯ÇÑ Á¦Ç° Çõ½ÅÀº Áö¿ª ½ÃÀå ¼ºÀå¿¡ ´õ¿í ±â¿©ÇÏ°í ÀÖ½À´Ï´Ù.

¸ñÂ÷

Á¦1Àå º¸°í¼­ °³¿ä

  • ¾÷°è ÇöȲ ºÐ¼®°ú ¼ºÀå °¡´É¼º Àü¸Á
  • Á¶»ç ¹æ¹ý°ú Åø
  • ½ÃÀå ³»¿ª
    • ºÎ¹®º°
    • Áö¿ªº°

Á¦2Àå ½ÃÀå °³¿ä¿Í ÀλçÀÌÆ®

  • Á¶»ç ¹üÀ§
  • ¾Ö³Î¸®½ºÆ®ÀÇ ÀλçÀÌÆ®¿Í ÇöÀç ½ÃÀå µ¿Çâ
    • ÁÖ¿ä Á¶»ç °á°ú
    • Ãßõ»çÇ×
    • °á·Ð

Á¦3Àå °æÀï »óȲ

  • ÁÖ¿ä ±â¾÷ ºÐ¼®
  • Google LLC
    • °³¿ä
    • À繫 ºÐ¼®
    • SWOT ºÐ¼®
    • ÃÖ±ÙÀÇ µ¿Çâ
  • Meta Platforms, Inc.
    • ±â¾÷ °³¿ä
    • À繫 ºÐ¼®
    • SWOT ºÐ¼®
    • ÃÖ±ÙÀÇ µ¿Çâ
  • Microsoft Corp.
    • °³¿ä
    • À繫 ºÐ¼®
    • SWOT ºÐ¼®
    • ÃÖ±ÙÀÇ µ¿Çâ
  • ÁÖ¿ä Àü·« ºÐ¼®

Á¦4Àå ½ÃÀå ¼¼ºÐÈ­

  • ¸ÖƼ¸ð´Þ AI ¼¼°è ½ÃÀå : ÄÄÆ÷³ÍÆ®º°
    • ¼ÒÇÁÆ®¿þ¾î
    • ¼­ºñ½º
  • ¸ÖƼ¸ð´Þ AI ¼¼°è ½ÃÀå : µ¥ÀÌÅÍ ¸ð´Þ¸®Æ¼º°
    • À̹ÌÁö µ¥ÀÌÅÍ
    • ÅؽºÆ® µ¥ÀÌÅÍ
    • À½¼º µ¥ÀÌÅÍ
    • ºñµð¿À¡¤¿Àµð¿À µ¥ÀÌÅÍ
  • ¸ÖƼ¸ð´Þ AI ¼¼°è ½ÃÀå : ±â¼úº°
    • ML
    • NLP
    • ÄÄÇ»ÅÍ ºñÀü
    • CA
    • IoT
  • ¸ÖƼ¸ð´Þ AI ¼¼°è ½ÃÀå : ÃÖÁ¾»ç¿ëÀÚº°
    • ¹Ìµð¾î¡¤¿£ÅÍÅ×ÀθÕÆ®
    • BFSI
    • IT¡¤Åë½Å
    • ÇコÄɾî
    • ÀÚµ¿Â÷¡¤¼ö¼Û
    • ±âŸ(°ÔÀÓ)

Á¦5Àå Áö¿ª ºÐ¼®

  • ºÏ¹Ì
    • ¹Ì±¹
    • ij³ª´Ù
  • À¯·´
    • ¿µ±¹
    • µ¶ÀÏ
    • ÀÌÅ»¸®¾Æ
    • ½ºÆäÀÎ
    • ÇÁ¶û½º
    • ±âŸ À¯·´
  • ¾Æ½Ã¾ÆÅÂÆò¾ç
    • Áß±¹
    • Àεµ
    • ÀϺ»
    • Çѱ¹
    • ±âŸ ¾Æ½Ã¾ÆÅÂÆò¾ç
  • ¼¼°è ±âŸ Áö¿ª

Á¦6Àå ±â¾÷ °³¿ä

  • Adobe Inc.
  • Affectiva, Inc.
  • Amazon.com, Inc.
  • Baidu, Inc.
  • Clarifai, Inc.
  • Cogniac Corp.
  • Deepgram, Inc.
  • IBM Corp.
  • iMerit Inc.
  • Indico Data Solutions, Inc.
  • Levity AI GmbH
  • Modzy, Inc.
  • NeuraFlash
  • Nvidia Corp.
  • OpenAIOpCo, LLC
  • Salesforce, Inc.
  • Shanghai SenseTime Intelligent Technology Co., Ltd.
  • Turing AI
  • UBIAI LLC
ksm 24.04.30

Global Multimodal AI Market Size, Share & Trends Analysis Report by Component (Software and Service), by Data Modality (Image Data, Text Data, Speech & Voice Data and Video & Audio Data), by Technology (Machine Learning, Natural Language Processing, Computer Vision, Context Awareness and Internet of Things), and by End User (Media & Entertainment, BFSI, IT & Telecommunication, Healthcare, Automotive & Transportation and Others), Forecast Period (2024-2031)

The global multimodal AI market is anticipated to grow at a significant CAGR of 14.9% during the forecast period (2024-2031). The growing adoption of multimodal generative AI models with the improving producing data across diverse modalities like texts, images, and audio is a key factor supporting the growth of the market globally. The increasing focus of market players on introducing generative multimodal AI solutions is further aiding to the market growth. For instance, in March 2023, AWS and NVIDIA collaborated on next-generation Infrastructure for training large machine-learning models and building generative AI applications. The collaboration focused on developing the most scalable, on-demand artificial intelligence (AI) infrastructure that was designed to support the development of generative AI applications and the training of ever-more-complex large language models (LLMs). The increasing investment in AI technology is expected to offer lucrative opportunity to the market growth.

Private Investment in AI by Geographic Area, 2022

Source:Artificial Intelligence Index Report 2023

Segmental Outlook

The global multimodal AI market is segmented on the component, data modality, technology and end user. Basedon the component, the market is sub-segmented into software and service. Based on the data modality, the market is sub-segmented into image data, text data, speech & voice data and video & audio data. Based on the technology, the market is sub-segmented into machine learning, natural language processing, computer vision, context awareness and internet of things. Further, on the basis of end user, the market is sub-segmented into media & entertainment, BFSI, IT & telecommunication, healthcare, automotive & transportation and others (gaming). Among the end users, the BFSI sub-segment is anticipated to hold a considerable share of the market owing to the increasing adoption of multimodel AI in fraud detection and customer service automation by analyzing textual, vocal, and transactional data.

The Machine Learning Sub-Segment is Anticipated to Hold a Considerable Share of the Global Multimodal AI Market

Among the technology, the machine learning sub-segment is expected to hold a considerable share of the global multimodal AI market. The segmental growth is attributed to the increasing adoption of machine learning-based development systems to train multimodal AI, which includes natural language processing (NLP) and computer vision. Adopting AI infrastructure for supporting AI model development and training at scale, requires a multi-step procedure that includes setting up, buying, and maintaining a highly parallel software ecosystem. In April 2022, Hewlett Packard Enterprise introduced a new HPE machine learning development system.The new system is an end-to-end solution designed specifically for multimodal AI that combines networking, accelerators, computation, and a machine learning software platform to create and train more accurate AI models more quickly and at scale. Such product launches are further aiding to the growth of the market segment.

Regional Outlook

The global multimodal AI market is further segmented based on geography including North America (the US, and Canada), Europe (UK, Italy, Spain, Germany, France, and the Rest of Europe), Asia-Pacific (India, China, Japan, South Korea, and Rest of Asia), and the Rest of the World (the Middle East & Africa, and Latin America. Among these, Asia-Pacific is anticipated to exhibit highest CAGR during the forecast period. The growing adoption of multimodal AI in applications such as e-commerce, healthcare, and finance drives the growth of the regional market.

North America Hols Considerable Share in the Global Multimodal AI Market

Among all regions, the North America holds considerable share in the global market. Regional market share is attributed to the high rate of development and implementation of multimodal AI solutions. The growing demand of multimodal AI to provide step-by-step assistance to build high-converting digital storefronts and automate complex tasks like managing multi-product catalog data across the region is further contributing to the regional market share. In September 2023, Salesforce launched Einstein Copilota new generative AI-powered conversational assistant. Using natural language prompts, Einstein Copilot completely offers multiple languages, personalized product promotions, and SEO metadata generation that drive conversions and customize and design storefront components with natural language prompts. Such product innovations are further contributing to the regional market growth.

Market Players Outlook

The major companies serving the multimodal AI market include Google LLC, IBM Corp., Meta Platforms, Inc., Microsoft Corp., OpenAIOpCo, LLC, and others. The market players are considerably contributing to the market growth by the adoption of various strategies including mergers and acquisitions, partnerships, collaborations, funding, and new product launches, to stay competitive in the market. For instance, in May 2023, Appen Ltd. and Reka AI partnered to build customized multi-modal LLM Applications. For enterprises, Appen and Reka have developed a complete and functional generative AI solution.

The Report Covers:

  • Market value data analysis of 2023 and forecast to 2031.
  • Annualized market revenues ($ million) for each market segment.
  • Country-wise analysis of major geographical regions.
  • Key companies operating in the global multimodal AImarket. Based on the availability of data, information related to new product launches, and relevant news is also available in the report.
  • Analysis of business strategies by identifying the key market segments positioned for strong growth in the future.
  • Analysis of market-entry and market expansion strategies.
  • Competitive strategies by identifying 'who-stands-where' in the market.

Table of Contents

1.Report Summary

  • Current Industry Analysis and Growth Potential Outlook
  • 1.1.Research Methods and Tools
  • 1.2.Market Breakdown
    • 1.2.1.By Segments
    • 1.2.2.By Region

2.Market Overview and Insights

  • 2.1.Scope of the Report
  • 2.2.Analyst Insight & Current Market Trends
    • 2.2.1.Key Findings
    • 2.2.2.Recommendations
    • 2.2.3.Conclusion

3.Competitive Landscape

  • 3.1.Key Company Analysis
  • 3.2.Google LLC
    • 3.2.1.Overview
    • 3.2.2.Financial Analysis
    • 3.2.3.SWOT Analysis
    • 3.2.4.Recent Developments
  • 3.3.Meta Platforms, Inc.
    • 3.3.1.Overview
    • 3.3.2.Financial Analysis
    • 3.3.3.SWOT Analysis
    • 3.3.4.Recent Developments
  • 3.4.Microsoft Corp.
    • 3.4.1.Overview
    • 3.4.2.Financial Analysis
    • 3.4.3.SWOT Analysis
    • 3.4.4.Recent Developments
  • 3.5.Key Strategy Analysis

4.Market Segmentation

  • 4.1.Global Multimodal AI Market by Component
    • 4.1.1.Software
    • 4.1.2.Service
  • 4.2.Global Multimodal AI Market by Data Modality
    • 4.2.1.Image Data
    • 4.2.2.Text Data
    • 4.2.3.Speech & Voice Data
    • 4.2.4.Video & Audio Data
  • 4.3.Global Multimodal AI Market by Technology
    • 4.3.1.Machine Learning
    • 4.3.2.Natural Language Processing
    • 4.3.3.Computer Vision
    • 4.3.4.Context Awareness
    • 4.3.5.Internet of Things
  • 4.4.Global Multimodal AI Market by End-User
    • 4.4.1.Media & Entertainment
    • 4.4.2.BFSI
    • 4.4.3.IT & Telecommunication
    • 4.4.4.Healthcare
    • 4.4.5.Automotive & Transportation
    • 4.4.6.Others (Gaming)

5.Regional Analysis

  • 5.1.North America
    • 5.1.1.United States
    • 5.1.2.Canada
  • 5.2.Europe
    • 5.2.1.UK
    • 5.2.2.Germany
    • 5.2.3.Italy
    • 5.2.4.Spain
    • 5.2.5.France
    • 5.2.6.Rest of Europe
  • 5.3.Asia-Pacific
    • 5.3.1.China
    • 5.3.2.India
    • 5.3.3.Japan
    • 5.3.4.South Korea
    • 5.3.5.Rest of Asia-Pacific
  • 5.4.Rest of the World

6.Company Profiles

  • 6.1.Adobe Inc.
  • 6.2.Affectiva, Inc.
  • 6.3.Amazon.com, Inc.
  • 6.4.Baidu, Inc.
  • 6.5.Clarifai, Inc.
  • 6.6.Cogniac Corp.
  • 6.7.Deepgram, Inc.
  • 6.8.IBM Corp.
  • 6.9.iMerit Inc.
  • 6.10.Indico Data Solutions, Inc.
  • 6.11.Levity AI GmbH
  • 6.12.Modzy, Inc.
  • 6.13.NeuraFlash
  • 6.14.Nvidia Corp.
  • 6.15.OpenAIOpCo, LLC
  • 6.16.Salesforce, Inc.
  • 6.17.Shanghai SenseTime Intelligent Technology Co., Ltd.
  • 6.18.Turing AI
  • 6.19.UBIAI LLC
ºñ±³¸®½ºÆ®
0 °ÇÀÇ »óÇ°À» ¼±Åà Áß
»óÇ° ºñ±³Çϱâ
Àüü»èÁ¦