AI adoption in the enterprise 2020
O’Reilly survey results show that AI efforts are maturing from prototype to production, but company support and an AI/ML skills gap remain obstacles.
Research
Analysis of notable trends based on original surveys, usage, and data sets.
5 key areas for tech leaders to watch in 2020
Our annual analysis of the O’Reilly online learning platform reveals Python’s continued dominance and important shifts in infrastructure, AI/ML, cloud, and security.
The state of data quality in 2020
O’Reilly survey highlights the increasing attention organizations are giving to data quality and how AI both exacerbates and alleviates data quality issues.
O’Reilly serverless survey 2019: Concerns, what works, and what to expect
O’Reilly survey results indicate demand for serverless will grow in the near term as a worthwhile infrastructure option for many organizations.
What’s driving cloud native and distributed systems in 2019
Cloud native, security, performance, and SRE are areas of emphasis for the O’Reilly Velocity Conference in Berlin.
Topics to watch at the Strata Data Conference in New York 2019
Machine learning, artificial intelligence, data engineering, and architecture are driving the data space.
How organizations are sharpening their skills to better understand and use AI
To successfully implement AI technologies, companies need to take a holistic approach toward retraining their workforces.
Got speech? These guidelines will help you get started building voice applications
Speech adds another level of complexity to AI applications—today’s voice applications provide a very early glimpse of what is to come.
Managing machine learning in the enterprise: Lessons from banking and health care
A look at how guidelines from regulated industries can help shape your ML strategy.
How O’Reilly Radar spots the next big thing
Roger Magoulas explains how O’Reilly’s Radar methodology identifies emerging tech trends businesses need to know.
AI and machine learning will require retraining your entire organization
To successfully integrate AI and machine learning technologies, companies need to take a more holistic approach toward training their workforce.
AI adoption is being fueled by an improved tool ecosystem
We now are in the implementation phase for AI technologies.
What’s driving open source software in 2019
Cloud native, AI/ML, and data tools and topics are areas of emphasis for the O’Reilly Open Source Software Conference.
Becoming a machine learning company means investing in foundational technologies
Companies successfully adopt machine learning either by building on existing data products and services, or by modernizing existing models and algorithms.
The topics to watch in software architecture
Microservices, serverless, AI, ML, and Kubernetes are among the most notable topics in our analysis of proposals from the O’Reilly Software Architecture Conference.
Sustaining machine learning in the enterprise
Drawing insights from recent surveys, Ben Lorica analyzes important trends in machine learning.
How companies adopt and apply cloud native infrastructure
Survey results reveal the path organizations face as they integrate cloud native infrastructure and harness the full power of the cloud.
Checking in on AI tools
Ben Lorica and Roger Chen assess the state of AI technologies and adoption in 2019.