Systems | Development | Analytics | API | Testing

IoT startups serve various purposes such as increased performance, security, comfort, and entertainment. However, implementing IoT projects requires a mix of skills, knowledge, and technologies, including hardware, software, cloud computing, networking, and analytics. Of course, a key element of anу IoT solution is to pick an appropriate programming language that ensures the interaction between IoT devices and apps, processing, data storage, task execution, and user interaction.

We consistently hear from engineering leaders that automated test maintenance is a painful, mindless exercise that takes too much time away shipping code — the main goal of any startup software team. Our vision is to deliver end-to-end test automation that requires no maintenance from your team. With that in mind, we’ve designed Rainforest as an intuitive, no-code platform that anyone can quickly use with no training. This has been an important — but insufficient! — step.

GPU as a Service (GPUaaS) serves as a cost-effective solution for organizations who need more GPUs for their ML and gen AI operations. By optimizing the use of existing resources, GPUaaS allows organizations to build and deploy their applications, without waiting for new hardware. In this blog post, we explain how GPUaaS as a service works, how it can close the GPU shortage gap, when to use GPUaaS and how it fits with gen AI.

Founders of the world’s leading data companies share their insights on the latest trends in their industry and the keys to turning generative AI into business impact.

You can now access Gemini 1.0 Pro from inside the BigQuery console, gaining scale and efficiency to ground LLMs with your business data.

When ChatGPT first hit the market its human-like responses were astonishing, yet somewhat eerie. Many thought, “It communicates just like me.” It follows that the next logical thought was, “It’s going to take over my job.” However, the fear that AI-driven tools will replace human software testers is unfounded. AI will certainly impact testing jobs, including market expectations, skillsets, and required knowledge.

In our latest research, conducted this year with AIIA and FuriosaAI, we wanted to know more about global AI Infrastructure plans, including respondents’: 1) Compute infrastructure growth plans 2) Current scheduling and compute solutions experience, and 3) Model and AI framework use and plans for 2024. Read on to dive into key findings! Download the survey report now →