Blog
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TechSaving Organizations from Key Person Dependency: LLM Wiki v2
When a key teammate departs a company, almost everyone has experienced the resulting operational friction. The reality is that most organizations already possess more than enough data to smooth over handovers, scattered across tools like Notion, Confluence, and project meeting notes. The fundamental problem lies in fragmentation: information remains isolated, and the underlying tacit knowledge […]
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TechBeyond RT-2, 4 Criteria Driving the Evolution of Physical AI
In our previous article, we explored how the high-level intelligence of Vision-Language Models (VLMs) translates directly into physical movement through Google DeepMind’s RT-2. We also highlighted key challenges that remain to be overcome, such as movement coarseness stemming from quantization errors and latency limitations in real-time control. Post-RT-2, modern robotics stands at a massive inflection […]
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TechHow Did Physical AI Start Learning to Act?
“Bring me the red mug on the table.” When you say this to a robot, its camera activates and begins observing its surroundings. Knowing already what “red” and “mug” mean, the robot relies on state-of-the-art vision-language models to identify the correct object with remarkably high accuracy, even when several similar-looking items are scattered nearby. At […]
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TechThe Core of AI Agents in 2026, Harness Engineering
What would happen if you mounted a 1,000-horsepower Formula 1 engine capable of exceeding 350 km/h onto the frame of a compact city car? The moment the ignition turns on, the chassis would likely collapse under the overwhelming force before the vehicle even begins to accelerate. Without a reinforced structure designed to handle that level […]
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TechContext Entropy: The Hidden Challenge of the AI Agent Era
When interacting with AI systems over extended periods, there often comes a moment when something begins to feel subtly off. At first, the AI agent seems remarkably sharp. It understands intent with precision, generates sophisticated code, and follows complex instructions with impressive consistency. But as conversations grow longer and projects become more complicated, the system […]
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TechTurboQuant: The End of AI Memory Bottlenecks
Last week, the global tech industry turned its attention to an announcement from Google Research. The reason was the unveiling of TurboQuant, a new optimization technology capable of dramatically improving AI efficiency by overcoming one of the industry’s most stubborn hardware limitations. Modern large language models (LLMs) can process hundreds of pages of context in […]
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TechBreaking Through Edge AI Limitations with Knowledge Distillation
We are living in the era of “bigger is better” AI. Every day, massive large language models (LLMs) with hundreds of billions of parameters continue to break new records, outperforming humans across increasingly complex tasks. But the moment we try to deploy these impressive models into real-world environments, we run into a harsh reality. There […]
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TechGraphRAG Awakening Dormant Data
When using generative AI like ChatGPT or Claude in work or daily life, we sometimes hit a wall. When asked about the latest information the AI hasn’t learned, it might give nonsensical answers known as Hallucination, or it may struggle to understand complex internal company documents, repeating only superficial responses. To solve these problems, a […]
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TechWhy Did Qwen3.5 Choose Gated DeltaNet?
The release of Qwen3.5 in mid February 2026 sent shockwaves through the AI industry. Beyond mere performance gains, it proved the potential of a new architecture to solve the chronic issue of efficiency in AI. At the heart of its ability to achieve both overwhelming speed and accuracy lies an innovative technology called Gated DeltaNet […]
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