Last week, one of our product managers (PMs) built and shipped a feature. Not spec'd it. Not filed a ticket for it. Built it, tested it, and shipped it to production. In a day. A […]
As Google integrates AI capabilities across its product suite, a new technical entity has surfaced in server logs: Google-Agent. For software devs, understanding this entity is critical for distinguishing between automated indexers and real-time, user-initiated […]
Many people have tried AI tools and walked away unimpressed. I get it — many demos promise magic, but in practice, the results can feel underwhelming. That’s why I want to write this not as […]
NVIDIA researchers introduced ProRL AGENT, a scalable infrastructure designed for reinforcement learning (RL) training of multi-turn LLM agents. By adopting a ‘Rollout-as-a-Service’ philosophy, the system decouples agentic rollout orchestration from the training loop. This architectural […]
Processing 200,000 tokens through a large language model is expensive and slow: the longer the context, the faster the costs spiral. Researchers at Tsinghua University and Z.ai have built a technique called IndexCache that cuts […]
RPA (robotic process automation) is a practical and proven way to reduce manual work in business processes without AI systems. By using software bots to follow fixed rules, companies can automate repetitive tasks like data […]
In the landscape of enterprise AI, the bridge between unstructured audio and actionable text has often been a bottleneck of proprietary APIs and complex cascaded pipelines. Today, Cohere—a company traditionally known for its text-generation and […]
As Large Language Models (LLMs) expand their context windows to process massive documents and intricate conversations, they encounter a brutal hardware reality known as the "Key-Value (KV) cache bottleneck." Every word a model processes must […]
To gain financial data insights, the majority of family offices now turn to AI, according to new research from Ocorian. The global study reveals 86 percent of these private wealth groups are utilising AI to […]
When running LLMs at scale, the real limitation is GPU memory rather than compute, mainly because each request requires a KV cache to store token-level data. In traditional setups, a large fixed memory block is […]
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