Emerging Tech Research: Artificial Intelligence & Machine Learning

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AI semiconductor and language processing innovation drive record venture investment

The pandemic pushed data-driven enterprise operations to adopt AI & ML across industries. However, AI development is a costly affair, and its usage remains uneven, immature and limited within organizations. 

Our Q2 update of AI & ML Emerging Tech Research includes spotlights on private companies, including Databricks, DataRobot and Samsara. The report also tracks major industry trends—covering developments in natural language processing, AI chip optimization and intelligent robotic systems.

Key takeaways include:
 

• AI venture funding set a third consecutive quarterly record in Q2, with $31.6 billion invested in the vertical. The number includes 11 deals closing at more than $500 million during the quarter. 
• Data science companies continue to outperform AI-as-a-service companies, suggesting that scaling data science capabilities is a prerequisite to more widespread use of AI & ML analytics. 
• VC exits in the vertical continued to boom in Q2, with $68.1 billion in disclosed exit value. Of the 13 IPOs during the quarter, notable exits include enterprise automation software provider UiPath, information security vendor SentinelOne and TuSimple, an autonomous vehicle maker.
• Natural language AI adoption is becoming mainstream for several use cases, including text classification, chatbots, translation, call center automation and survey analysis.
• Intelligent robotics startups are achieving high valuation growth at a relatively early stage by applying computer vision innovations to warehouse and factory robots.