Category: Artificial Intelligence (AI)
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In today’s enterprise landscape, the word “agentic” is everywhere. Vendors tout “AI agents” that promise to revolutionise workflows, cut costs, and accelerate decision-making. Yet despite millions in investment, most corporate AI initiatives remain stuck in pilot stage—demonstrating novelty but failing to deliver measurable, scalable return on investment. The problem isn’t the technology. It’s the terminology—and…
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We’re drowning in AI optimism. Goldman Sachs says it could lift global GDP by 7%. McKinsey calls it “the next productivity frontier.” ARK Invest, Morgan Stanley, and JPMorgan all agree: AI is transformative. And yet—only 5% of companies are actually capturing measurable value from AI, according to BCG. Why this chasm between promise and performance?…
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Looking back, this year began not with fireworks, as usual, but with a golden sunrise at Annapurna Base Camp, 4,130 meters above sea level in Nepal. After three strenuous days of trekking, reaching the base camp felt like a quiet achievement, especially with minimal acclimatization. There is a saying: to truly know yourself, climb a…
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A research breakthrough from Samsung’s SAIL Montréal is challenging the core assumption that more powerful AI requires more parameters. Led by Alexia Jolicoeur-Martineau, the team has released the Tiny Recursive Model (TRM), an open-source model that dramatically outperforms both massive LLMs and the previously state-of-the-art Hierarchical Reasoning Model (HRM) on hard puzzle and reasoning benchmarks,…
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If you’re building products with Large Language Models (LLMs), you’ve likely encountered their biggest limitation: their knowledge is static, frozen at the point of their training. To solve this, Retrieval-Augmented Generation (RAG) has become a go-to solution, enabling dynamic access to external knowledge. But what if your application needs more than just accurate retrieval? What…
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