#MPC
14 related articles
·3 min
Implementing Zanzibar in Lean4: A Formally Verified Permission Engine for AI Projects
Deep dive into a Datalog permission DSL built on Google Zanzibar using Lean4 theorem prover. How formal verification strengthens AI permission management.
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·3 min
Formally Verifying 3D CSG: Trusting 93 Lines of Specification Over Thousands of Lines of AI Code
Exploring how formal verification solves the trust crisis of AI-generated code. Through a 3D CSG project, learn why reviewing 93 lines of specification beats checking thousands of lines of AI code.
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·3 min
Greenhouse Controller Showdown: Why Reinforcement Learning Lost to a Rule-Based Baseline
An open benchmark in GreenLight-Gym2 compares four greenhouse controllers, revealing why model-free RL (PPO) underperforms hand-tuned rules and how MPC and hybrid RL-in-MPC approaches can help.
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Distributed Secret Storage: A Deep Div…
·2 min
Distributed Secret Storage: A Deep Dive into Threshold Cryptography and Robust Security Architectures
A deep dive into robust secret storage in distributed networks, covering Shamir Secret Sharing, VSS, Proactive Secret Sharing, and real-world applications in blockchain KMS and MPC.
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·2 min
DecisionRL: An Open-Source Reinforcement Learning Library Built for Operational Decision-Making
DecisionRL is an open-source RL library for operational decision-making, with six built-in scenarios (inventory, pricing, energy), OR baselines, and support for DQN, PPO, SAC, and more.
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·6 min
Multimodal and Embodied Intelligence: A Comprehensive Look at Progress, Pitfalls, and Opportunities
At the Microsoft Research India summit, top experts explore the real progress of multimodal AI and embodied intelligence: fusing classical robotics with large models, healthcare AI deployment challenges, perceptual bottlenecks in reasoning, and possibilities beyond scaling.
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·2 min
JEPA World Model Deep Dive: Promise and Controversy
JEPA is LeCun's world model architecture that predicts in abstract embedding space rather than pixels. This article analyzes JEPA's core ideas, differences from generative world models, and key controversies including representation collapse, decodability, and lack of empirical results.
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·2 min
Quadruped Robot Becomes a Wheelchair: How Bionic Legs Are Reimagining Accessible Mobility
YouTube creator JLaservideo built a "bionic legs" wheelchair for his father using Unitree's B2 quadruped robot. Explore the tech, challenges, and real-world impact of robotic assistive mobility.
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Brazil's 55-Year Slavery Case: Can AI …
·3 min
Brazil's 55-Year Slavery Case: Can AI Detect the Invisible Exploitation of Modern Slavery?
A woman in Brazil was enslaved by one family for 55 years, shocking the world. This article explores from a technical angle whether AI data analysis, satellite remote sensing, and machine learning can detect modern slavery.
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·4 min
DIY Robot Lamp Full-Body Motion Test: A Firsthand Account from Components to Coordinated Movement
A maker builds a DIY robot lamp with Robstride actuators, completing its first full-body joint motion test. This article breaks down hardware selection, trajectory planning, PID tuning, and more.
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·6 min
DINOv2 vs SigLIP: Why the Huge Gap in k-NN Classification? A Guide to Avoiding Vision Encoder Selection Pitfalls
Experiments show DINOv2 Giant scores just 41% on k-NN classification, while SigLIP2 reaches 92%. This article dives into the embedding-space differences between contrastive and self-supervised learning to guide vision encoder selection.
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Leanstral 1.5: AI-Assisted Formal Proo…
·3 min
Leanstral 1.5: AI-Assisted Formal Proofs, Making Lean Theorem Verification Accessible to All
Leanstral 1.5 combines LLMs with Lean theorem proving to lower the barrier to formal proofs. Explore its core value, technical approach, and how AI can make formal mathematics accessible to all.
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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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