Systems | Development | Analytics | API | Testing

This is the most fertile time for mobile app development since the launch of the App Store. Our industry is in the grip of several simultaneous revolutions, each of them bending, flexing and moulding to the others. 5G promises to make our apps 10 times faster; wearable technology lets them wrap themselves around our bodies; artificial intelligence enables them to learn from us and get smarter every day. But this torrent of innovation brings challenges, too.

In this post, we’ll see how ChatGPT can be used to reinvigorate APIs by creating an OpenAPI specification for an existing API that has existing documentation.

The misconception that product led growth implies a business neglects sales couldn’t be further from the truth. In reality, product led growth (PLG) involves integrating sales later in the customer journey, placing the purchasing power back in the hands of your users. This self-service approach is highly effective, especially when paired with insightful user data to streamline and target growth. For AI-centric companies, this product-led strategy serves as a fundamental pillar for success.

Commercializing an AI-based product requires turning technology into a marketable product, navigating challenges from development to market entry. Appealing to enterprise buyers is crucial for sustainable, continuous growth, as their interest not only validates your product’s value but also lays the foundation for long-term success and scalability. More specifically, the larger the businesses of your potential customers are, the more of a monopoly your product likely has in the market.

In recent years, governments across the globe have recognized the transformative potential of artificial intelligence (AI) and have embarked on initiatives to harness this technology to drive innovation and serve their citizens more effectively. These government-led efforts have had a profound impact on the development and adoption of AI solutions in the public sector, paving the way for a future where data-driven decision-making and automation are the norm.

GenAI depends on data maturity, in which an organization demonstrates mastery over both integrating data – moving and transforming it – and governing its use.

Amazon Simple Storage Service (Amazon S3) is a cloud-based object storage service from Amazon Web Services that collects data from anywhere on the internet. In today's data-driven world, businesses rely heavily on seamless data integration and transformation processes to unlock the full potential of their vast data resources. But what happens if you want to move data from Amazon S3 to a data warehouse for analysis?

Amazon S3 is a standout storage service known for its ease of use, power, and affordability. When combined with Apache Kafka, a popular streaming platform, it can significantly reduce costs and enhance service levels. In this post, we’ll explore various ways S3 is put to work in streaming data platforms.

On October 30, 2023, President Joe Biden issued a landmark Executive Order on Safe, Secure, and Trustworthy Artificial Intelligence (AI). The Executive Order represents a comprehensive statement of intent for AI regulation, mandating transparency from firms that use AI and establishing safety and security standards. Moreover, it compels AI developers to disclose the outcomes of safety evaluations to the U.S. government, especially if the results indicate a potential threat to national security.