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Press releaseGlobeNewswire· February 23, 2026

Deep Learning Market Size to Surpass $296B by 2031 as Autonomous Systems and Robotics are Set to Grow at 37.2% CAGR, Says a 2026 Mordor Intelligence Report

View original at globenewswire.com
Deep Learning Market Size to Surpass $296B by 2031 as Autonomous Systems and Robotics are Set to Grow at 37.2% CAGR, Says a 2026 Mordor Intelligence Report Hyderabad, India, Feb…
Opening lines of the source · GlobeNewswire · short snapshot — read the full document at the original

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  • Mexico is increasingly positioning itself as a near-shore manufacturing hub for AI hardware

    80% confidence
  • Canada fosters AI start-ups emerging from its research institutions

    80% confidence
  • Autonomous systems and robotics segment is set to grow at 37.2% CAGR

    80% confidence
  • The United States is strengthening chip production capacity to reduce supply chain dependence

    80% confidence
  • Organizations are transitioning from pilot AI initiatives to full-scale production deployments, positioning deep learning as a foundational technology pillar in global digital transformation strategies

    80% confidence
  • Businesses are increasingly shifting from delayed batch processing to low-latency inference models, improving responsiveness and operational efficiency

    80% confidence
  • Asia-Pacific is emerging as one of the fastest-growing regions in the deep learning market, driven by national AI strategies, digital transformation, and industrial automation

    80% confidence
  • India is supporting start-ups through public AI initiatives

    80% confidence
  • The mobile learning market size is estimated at USD 95.77 billion in 2026 and is projected to reach USD 200.24 billion by 2031, registering a CAGR of 15.89% during 2026–2031

    80% confidence
  • The digital education market size in 2026 is estimated at USD 30.36 billion, growing from USD 23.98 billion in 2025 and projected to reach USD 98.58 billion by 2031, at a CAGR of 26.57% during 2026–2031

    80% confidence
  • Organizations are facing a surge in unstructured data from sources such as video feeds, audio inputs, satellite imagery, and social media streams, driving adoption of neural processing technologies and edge computing solutions

    80% confidence
  • The deep learning market was valued at USD 47.89 billion in 2025 and is projected to grow from USD 64.92 billion in 2026 to USD 296.23 billion by 2031, registering a CAGR of 35.48% during 2026–2031

    80% confidence
  • Major semiconductor players are rolling out new accelerator platforms that deliver significantly stronger performance than earlier generations, enabling businesses to train and deploy large-scale AI models without depending on complex distributed setups

    80% confidence
  • North America continues to play a leading role in the deep learning market, supported by expanding domestic semiconductor manufacturing and a strong ecosystem of AI research and innovation

    80% confidence
  • Growing energy demands from large-scale data centers are pushing utilities to accelerate renewable power integration to sustain AI infrastructure expansion

    80% confidence
  • The rapid expansion reflects increasing enterprise adoption of artificial intelligence (AI), generative AI applications, and advanced data analytics across industries

    80% confidence
  • The Digital Badges Market is expected to grow from USD 237.29 million in 2025 to USD 278.07 million in 2026 and is projected to reach USD 613.43 million by 2031, registering a CAGR of 17.18% during 2026–2031

    80% confidence
  • Japan and South Korea are integrating AI into robotics, smart factories, and advanced connectivity networks

    80% confidence

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Both facts record the same metric (shares_outstanding) for ING Group at the identical observation date (2025-12-31). FACT A states 2,902,437,688 shares; FACT B states 2,902 million shares (2,902,000,000). The difference is 437,688 shares (~0.015%). This is a genuine value conflict, though the discrepancy appears to result from FACT B rounding to the nearest million while FACT A provides the precise count.
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