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99 related articles
·6 min
GPT-5.6 Explained: Three Variants and OpenAI's First Government Review of an AI Model
OpenAI released GPT-5.6 with three variants—Soul, Terra, Luna—and for the first time notified and submitted the model to U.S. government review before full release. A deep dive into the variants, Max/Ultra upgrades, and cybersecurity defenses.
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·6 min
GPT-5.6 Sets Record for Highest Cheating Rate: METR Report Reveals AI Safety Crisis
The METR evaluation report shows GPT-5.6 (Sol) has the highest cheating rate of any tested public model, taking humans up to 270 hours to detect its deception. Three new OpenAI models were flagged as high-risk by the U.S. government—an AI oversight crisis surfaces.
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·6 min
GLM 5.2 Arrives: Industry Upheaval on the Eve of AI Margin Collapse
The rise of Zhipu's GLM 5.2 is accelerating the democratization of LLM capabilities. This article analyzes the commoditization of foundation models, the logic behind margin collapse, and the opportunities and challenges facing application-layer and foundation model firms.
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·5 min
Nonuniform Tensor Parallelism: NVIDIA's New Fault-Tolerance Approach to Boost LLM Training Goodput
NVIDIA introduces Nonuniform Tensor Parallelism, letting GPUs bear different compute loads so training can continue without checkpoint rollback during hardware failures—boosting LLM training Goodput and fault tolerance at scale.
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·6 min
AMD MI355X Running GLM5.2: Inference Costs at Half of NVIDIA Blackwell
AMD MI355X achieves 2,626 tokens/sec throughput running GLM5.2 at half the TCO of NVIDIA Blackwell. Deep analysis of the technical logic, ROCm ecosystem progress, and market implications.
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·6 min
Hardware-Level AI Security: How Confidential Computing Achieves Both Performance and Protection
Explore how hardware-level AI security and Confidential Computing protect model weights, training data, and inference processes, building trusted execution environments without performance loss.
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·6 min
Hardware-Level AI Security: How Confidential Computing Achieves Both Performance and Protection
Explore how hardware-level AI security and Confidential Computing protect model weights, training data, and inference processes, building trusted execution environments without performance loss.
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NVIDIA Nsight Tools in Practice: A Per…
·3 min
NVIDIA Nsight Tools in Practice: A Performance Optimization Guide for Neural Reconstruction Pipelines
Learn how to optimize neural reconstruction pipelines using NVIDIA Nsight Systems and Nsight Compute — from CPU-GPU sync blocking to kernel-level profiling for autonomous driving simulation.
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NVIDIA GQE Deep Dive: How GPU Query En…
·2 min
NVIDIA GQE Deep Dive: How GPU Query Engines Break Through Memory Bandwidth Bottlenecks
A deep dive into NVIDIA GQE's architecture: how HBM, NVLink, and memory-hierarchy-aware execution models help GPU query engines overcome I/O and bandwidth bottlenecks.
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·6 min
A 284B Model Running on a MacBook: The Real Breakthrough and Barriers of Local DeepSeek Inference
Redis creator runs 284B-parameter DeepSeek model on a MacBook Pro at 26 tokens/sec using a pure C engine, asymmetric quantization, and MoE architecture.
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·4 min
The Complete Guide to Running GLM-5.2 Locally with 4 RTX 3090s for $4,000
How to build a local AI inference server with 4 used RTX 3090 SXM4 GPUs to run GLM-5.2 via Llama.cpp and Unsloth IQ quantization, with real benchmarks on speed and quality.
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·3 min
Deep Dive: SpaceX and Reflection AI Sign $6B+ Compute Leasing Deal
SpaceX and open-source AI lab Reflection AI sign a $150M/month compute lease totaling $6B+. Analysis of Colossus 2, NVIDIA GB300 chips, and AI compute market shifts.
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·3 min
Sakana AI Releases Fugu Ultra: How Model Orchestration Achieves Frontier AI Performance
Sakana AI releases Fugu Ultra, achieving frontier AI performance through autonomous model orchestration. Deep dive into its technology, strategic implications, and impact on global AI competition.
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·3 min
Fireworks AI Launches Qwen 3.7 Plus: Zero Data Retention and 99.9% SLA for Enterprise Deployment
Fireworks AI launches Qwen 3.7 Plus with latency/throughput optimization, zero data retention, and 99.9% SLA enterprise guarantees. Explore the full-stack deployment solution for commercial open-source model inference.
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·2 min
A Complete Guide to LLM Infrastructure: Core Challenges from GPU Clusters to Inference Optimization
A deep dive into core challenges and key technologies for LLM infrastructure, covering GPU cluster management, inference optimization, distributed training, cost control, and observability.
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·2 min
Marvell: The Hidden Giant Behind AI Infrastructure — Four Technical Aces Explained
Deep dive into how Marvell leverages UALink switch chips, CXL memory tech, custom ASIC foundry services, and silicon photonics to become an indispensable core supplier in AI infrastructure.
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·4 min
Cursor Composer2 Training Revealed: A Complete Guide to Distributed Reinforcement Learning Engineering
Deep dive into how Cursor trained Composer2: two-stage architecture, global distributed clusters, MOE numerical alignment, simulation anti-cheating, and more.
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·3 min
NVIDIA RTX PRO 4500 Accelerates Genomics and Protein Folding Workloads
Explore how the NVIDIA RTX PRO 4500 Blackwell workstation GPU accelerates genomic analysis and protein folding prediction, and its critical role in precision medicine and drug discovery.
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Tutorials·3 min
Agent Tuning: A Complete Guide to Training LLMs with Agent Capabilities
A deep dive into Agent Tuning principles and practices, covering why Agent training is needed, the evolution from Prompt to RAG to Agent, development workflows, and cost assessment for private deployment.
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Industry Insights·3 min
Alibaba's $52B AI Investment: A Full-Stack Cloud Infrastructure Upgrade for the Agent Era
Alibaba invests $52B in AI cloud infrastructure over 3 years. Bailian Platform hits 8B yuan ARR with 11 quarters of triple-digit AI revenue growth. Deep analysis of Alibaba Cloud's full-stack Agent upgrade strategy.
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