The latest News and Information on APIs, Mobile, AI, Machine Learning, IoT, Open Source and more!
The news have been full of coverage: ChatGPT (Generative Pre-trained Transformer), the prototype chatbot released by OpenAI in November 2022 seems to hail in a new era of information sourcing, schooling and learning, and interacting with a computer. The service sprinted to one million users in five days after the launch, with many more following until this date.
As the saying goes, a picture is worth a thousand words. This is especially true when describing your problem to IT support. The good news is that Alloy mobile apps can since now handle attachments, including pictures and documents! Technicians and end-users can attach files when submitting issues or collaborating on tickets—in short, in all their daily operations. The new feature enables uploading an existing file from the device library and taking a picture immediately in the app.
An API, or application programming interface, is a set of protocols and instructions that allows two software applications to communicate with one other. APIs can be implemented in a number of architectural styles. One of the most popular styles is REST (representational state transfer,) which allows server and client interaction in a stateless manner.
On-premises vs cloud MDM deployment With the rise of SaaS application management, mobile device management (MDM) services have gained popularity among IT professionals. Modern computing environments rely on the efficient use and provisioning of resources. But which one is right for your business: on-premise or cloud MDM deployment? While this may seem like a simple question, there are many factors that come into play when deciding which method to go with. This article discusses the differences between on-premises vs. cloud MDM deployment. It will also present examples, use cases, and pros and cons of these two deployment options.
While AI seems to be the topic of the moment, especially in the tech industry, the need to make it happen in a reliable way is becoming more obvious. MLOps, as a practice, finds itself in a place where it needs to keep growing and remain relevant in view of the latest trends. Solutions like ChatGPT or MidJourney dominated internet chatter last year, but the main question is…What do we foresee in the MLOps space this year and where is the community of MLOps practitioners focusing their energy?
