24. With the addition of Smart Reply to Gmail on Android and iOS, we’re using machine learning to make responding to emails easier for more than a billion Gmail users.

25. New Cloud TPUs—the second generation of our custom hardware built specifically for machine learning—are optimized for training ML models as well as running them, and will be available in the Google Compute Engine.

26. And to speed up the pace of open machine-learning research, we’re introducing the TensorFlow Research Cloud, a cluster of 1,000 Cloud TPUs available for free to top researchers.

27. Google for Jobs is our initiative to use our products to help people find work, using machine learning. Through Google Search and the Cloud Jobs API, we’re committed to helping companies connect with potential employees and job seekers with available opportunities.

28. The Google Cloud Jobs API is helping customers like Johnson & Johnson recruit the best candidates. Only months after launching, they’ve found that job seekers are 18 percent more likely to apply on its career page now they are using Cloud Jobs API.

29. With Google.ai, we’re pulling all our AI initiatives together to put more powerful computing tools and research in the hands of researchers, developers and companies. We’ve already seen promising research in the fields of pathology and DNA research.

30. We must go deeper. AutoML uses neural nets to design neural nets, potentially cutting down the time-intensive process of setting up an AI system, and helping non-experts build AI for their particular needs.

31. We’ve partnered with world-class medical researchers to explore how machine learning could help improve care for patients, avoid costly incidents and save lives.

32. We introduced a new Google Cloud Platform service called Google Cloud IoT Core, which makes it easy for Google Cloud customers to gain business insights through secure device connections to our rich data and analytics tools.