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Microsoft built Phi-4-reasoning-vision-15B to know when to think — and when thinking is a waste of time
Microsoft on Tuesday released Phi-4-reasoning-vision-15B, a compact open-weight multimodal AI model that the company says matches or exceeds the performance of systems many times its size — while co [...]
Why your LLM bill is exploding — and how semantic caching can cut it by 73%
Our LLM API bill was growing 30% month-over-month. Traffic was increasing, but not that fast. When I analyzed our query logs, I found the real problem: Users ask the same questions in different ways.& [...]
AMD Ryzen 9 9950X3D review: A no-compromise CPU for demanding gamers
How can we push CPUs forward? That's the question the computing industry has been asking since the Intel 4004 processor launched in 1971. Chipmakers have tried cranking up clock speeds, adding mu [...]
Nvidia says it can shrink LLM memory 20x without changing model weights
Nvidia researchers have introduced a new technique that dramatically reduces how much memory large language models need to track conversation history — by as much as 20x — without modifying the mo [...]
Phi-4 proves that a 'data-first' SFT methodology is the new differentiator
AI engineers often chase performance by scaling up LLM parameters and data, but the trend toward smaller, more efficient, and better-focused models has accelerated. The Phi-4 fine-tuning methodology [...]
Nvidia’s new technique cuts LLM reasoning costs by 8x without losing accuracy
Researchers at Nvidia have developed a technique that can reduce the memory costs of large language model reasoning by up to eight times. Their technique, called dynamic memory sparsification (DMS), c [...]
New training method boosts AI multimodal reasoning with smaller, smarter datasets
Researchers at MiroMind AI and several Chinese universities have released OpenMMReasoner, a new training framework that improves the capabilities of language models in multimodal reasoning.The framewo [...]
New KV cache compaction technique cuts LLM memory 50x without accuracy loss
Enterprise AI applications that handle large documents or long-horizon tasks face a severe memory bottleneck. As the context grows longer, so does the KV cache, the area where the model’s working me [...]