Systems | Development | Analytics | API | Testing

The Generative AI Boom: Crafting Tomorrow's Careers Today

Generative AI, once a niche area of artificial intelligence, has exploded into the mainstream, captivating the world with its ability to create everything from stunning images and compelling text to realistic music and functional code. Far from being a job destroyer, this revolutionary technology is proving to be a powerful job creator, forging entirely new career paths and redefining existing ones across virtually every industry. If you're looking to future-proof your career and ride the wave of innovation, understanding how Generative AI is shaping the job market is crucial.

Maximizing GPU Utilization with ClearML's Dynamic Fractional GPUs: Unleashing the Full Power of Your AI Infrastructure

In the world of AI, GPUs have become the undisputed workhorses of innovation. From training deep learning models to accelerating agentic workflows, digital twins, and scientific simulations, these powerful accelerators are indispensable. However, the immense computational power of GPUs comes with a significant investment.

Connect APIs to AI Agents: Expose, Discover and Manage MCP Servers with Bijira

The API landscape is evolving rapidly with some protocols rising in popularity while others fade away. The journey that started with SOAP has now evolved into other protocols like REST, GraphQL, gRPC, AsyncAPIs, and more. With the emergence of large language models (LLMs), we are now in the era of AI agent/assistant integrations with APIs. LLMs are power utilities. However, they operate without contextual awareness.

Cortex Agents | Built[By] Danmei Xu

Cortex Agents are changing how Snowflake customers access insights across structured and unstructured data—but they didn’t build themselves. In this Built spotlight, Senior Software Engineer Danmei Xu shares how her team brought Cortex Agents to life by combining powerful LLMs, retrieval systems, and thoughtful orchestration.

Machines That Learn Vs Machines That Imagine: GenAI Vs ML

Artificial Intelligence(AI) has recently become a hot topic across industries transforming sectors like finance, healthcare, education and research. The two of its subfields are Generative AI and Machine Learning(ML), but both of these terms are often confused for one another. we will explore the difference in purpose, techniques and capabilities and tools like Keploy’s GenAI-powered testing platform makes big difference in software testing.

What Agentic AI Demands from Your Data Strategy

If you’re leading a data, analytics, or AI initiative right now, you know the pressure. AI is no longer a future project - it’s a business imperative. Executives want results, boards want differentiation, and the window to deliver is closing fast. That’s why Salesforce’s intent to acquire Informatica should raise serious questions for data leaders. Not just because of what it means for Informatica, but for what it could mean for your AI roadmap.

Don't Just Hope Your Data Is AI-Ready - Know It

As enterprises double down on AI, there’s a hard truth many leaders are starting to face — they’ve invested in the promise of AI, but they can’t always trust the data behind the predictions. Whether you're training a model, building RAG pipelines, or scaling intelligent automation, AI outcomes are only as reliable as the data feeding them. Yet most organizations still can’t answer a critical question with confidence: Is our data truly AI-ready?

Unified Data And AI: Elevating Telecom Customer Experiences

In this episode, Dana Gardner, Principal Analyst at Interarbor Solutions, is joined by Soren Marklund, Vice President of Global Services, Technology Consulting, and AI Data Strategy at Ericsson. They explore how Ericsson leverages modern data architectures to enhance customer interactions and drive business benefits. The discussion covers the importance of a unified data operating model, challenges faced with data silos, and the role of AI and machine learning in improving customer service.

Developer Experience in the Age of AI: Developing a Copilot Chat Extension for Data Streaming Engineers

Three in 4 programmers have tried artificial intelligence (AI). This factoid comes from a recent Wired survey on the habits of engineers with respect to AI tooling like GitHub Copilot. Though Wired used a pool of only around 700 engineers, Gartner’s prediction from a year ago was that 75% of enterprise software engineers would use AI by 2028. To many of us, it’s starting to feel like that’s already happened.

The Story of Keboola MCP: How We Decided Not to Wait

Sometimes the biggest opportunities come disguised as unproven protocols released on a random Monday. Here’s why we bet on MCP before anyone asked us to. ‍ Two months before anyone knew what MCP was, we made a bet that it would fundamentally transform how people interact with their data infrastructure.