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Writer at Cate Lawrence @Cate_Lawrence
Berlin, DE
Joined Mar 2017
I'm a freelance tech journo, who writes about IoT, biohacking, robotics, wearable tech and weird things that lead me down rabbit holes. @cate_lawrence is an easy way to connect
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Edge Computing
Enterprise AI
Artificial intelligence (AI) has continued to change the way the world views what is technologically possible. Moving from theoretical to implementable, the emergence of technologies like ChatGPT allowed users of all backgrounds to leverage the power of AI. Now, companies across the globe are taking a deeper dive into their own AI and machine learning (ML) capabilities; they’re measuring the modes of success needed to become truly AI-driven, moving beyond baseline business intelligence goals and expanding to more innovative uses in areas such as security, automation, and performance.In DZone’s Enterprise AI Trend Report, we take a pulse on the industry nearly a year after the ChatGPT phenomenon and evaluate where individuals and their organizations stand today. Through our original research that forms the “Key Research Findings” and articles written by technical experts in the DZone Community, readers will find insights on topics like ethical AI, MLOps, generative AI, large language models, and much more.
Development at Scale
As organizations’ needs and requirements evolve, it’s critical for development to meet these demands at scale. The various realms in which mobile, web, and low-code applications are built continue to fluctuate. This Trend Report will further explore these development trends and how they relate to scalability within organizations, highlighting application challenges, code, and more.
Low Code and No Code
As the adoption of no-code and low-code development solutions continues to grow, there comes many questions of its benefits, flexibility, and overall organizational role. Through the myriad of questions, there is one main theme in the benefit of its use: leveraging no-code and low-code practices for automation and speed to release.But what are the pain points that these solutions seek to address? What are the expected vs. realized benefits of adopting a no- or low-code solution? What are the current gaps that these solutions leave in development practices? This Trend Report provides expert perspectives to answer these questions. We present a historical perspective on no and low code, offer advice on how to migrate legacy applications to low code, dive into the challenges of securing no- and low-code environments, share insights into no- and low-code testing, discuss how low code is playing a major role in the democratization of software development, and more.
Edge Computing and IoT
Edge computing aims to solve cloud computing challenges amidst the continued monumental growth of the Internet of Things. While IoT causes a massive data volume problem, edge computing addresses the classic data locality problem. The latter helps solve the former, but edge computing is a much bigger concept than "IoT data filtration" alone.The intersection of these paradigms is particularly hard to pin down given their immaturity at the implementation level. DZone's recent 2020 Edge Computing and IoT survey served to help better understand the state of the industry, as well as the mind of the practicing IoT programmer and edge-computing user. This Trend Report presents observations and analyses of survey results and an interview with industry leader Muhammad Rehman. Readers will also find content written by DZone community members, including a timely article that illustrates the impactful role that edge and cloud computing played in healthcare over the last year.
