Fine-tuning large language models (LLMs) is where experimentation meets real-world impact. It’s the moment you can teach a model your company’s domain knowledge, calibrate it for specific use cases, or even adjust the tone and format of its responses to better suit your audience. But none of this magic happens without the right hardware. The … Read more
Companies of all sizes are discovering that cloud-managed AI services offer a practical path to innovation in the cloud without the complexity of building solutions from the ground up. These platforms enable everything from intelligent chatbots and AI agents to automated document processing, predictive analytics, computer vision applications, and natural language processing—all through managed APIs … Read more
When it comes to building and running AI models, one of the first questions to answer is where to put your graphics processing units (GPUs): Should they live on-premise in your own data center, or should you tap into the cloud? On-premise GPUs give you speed, control, and the comfort of keeping sensitive data in-house, … Read more
If you’ve ever wanted to put your coding skills, creativity, and problem-solving chops to the test, an AI hackathon might be the perfect playground. These collaborative events bring together developers, students, designers, researchers, and innovators to build AI-powered projects. Whether you’re looking to experiment with the latest tools, meet like-minded peers, or even launch the … Read more
DigitalOcean’s 2025 Currents research report found that 79% of organizations are already integrating AI, a sharp rise from 49% just a year earlier. While adoption is growing, many teams and individuals are still searching for structured ways to build practical skills—32% remain in exploration mode and 66% of developers experiment with AI through passion projects. … Read more
Whether you’re a working professional looking to advance your career or a student preparing for tomorrow’s opportunities, learning AI skills can expand your professional prospects. DigitalOcean’s 2025 Currents research report found that 38% of businesses surveyed struggle to justify AI spending because they lack in-house expertise to leverage AI technologies. This skills gap creates an … Read more
Companies wanting AI/ML capabilities traditionally needed on-premise GPUs, which required expensive hardware purchases, specialized IT staff, and complex infrastructure management. Even with cloud GPUs, you still often need to handle some tasks like selecting instance types, installing software, configuring environments, and manual scaling. Serverless architecture is one way to run applications and services without managing … Read more
Note: Pricing and features are accurate as of 12, September 2025 and are subject to change. Behind every AI project like building a chatbot solving user’s queries, an image generator creating lifelike art, or a recommendation engine predicting your next favorite song, is a graphics processing unit (GPU) working at scale. These processors calculate billions … Read more
CoreWeave was founded in 2017 as Atlantic Crypto by three commodities traders. It initially focused on Ethereum mining using graphics processing units. Following the 2018 cryptocurrency crash, the company pivoted in 2019 and rebranded to CoreWeave. It used its GPU inventory to provide GPU cloud services for AI and machine learning workloads. Their platform enables … Read more
As demand for affordable, on-demand GPU compute has exploded, Vast.ai has become a popular choice for developers, researchers, and startups looking to rent powerful hardware at competitive prices. Its peer-to-peer marketplace and flexible pricing have made it a go-to for AI training, rendering, and other compute-intensive tasks. But as the GPU ecosystem matures and new … Read more
