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Machine Heart
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Machine Heart

Professional AI media and industry service platform

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Machine Heart
Machine Heart
Jun 10, 2026 · Artificial Intelligence

MINT: Enabling Strong Generalization and One‑Shot Transfer for Vision‑Language‑Action Models

MINT introduces a spectrally disentangled tokenization and intent‑driven strategy that lets Vision‑Language‑Action models generalize compositionally, transfer with a single demonstration, and achieve state‑of‑the‑art performance and robustness across benchmark suites and real‑world robot experiments.

Compositional GeneralizationFew-shot TransferMINT
0 likes · 9 min read
MINT: Enabling Strong Generalization and One‑Shot Transfer for Vision‑Language‑Action Models
Machine Heart
Machine Heart
Jun 10, 2026 · Industry Insights

Tabbit AI Browser: Free, Automated Workflows and Agent-Powered Features

Tabbit 1.0 launches as a free AI‑native browser that embeds large‑model agents to automate web tasks, integrate documents, and generate content, with a free tier covering 1,000 dialogues, 50 image generations and 10 agent runs per week, plus a paid professional edition and a new mobile app.

AI browserAI-native browserAgent automation
0 likes · 12 min read
Tabbit AI Browser: Free, Automated Workflows and Agent-Powered Features
Machine Heart
Machine Heart
Jun 9, 2026 · Artificial Intelligence

Why Code Is the Core of Agent Harness: Deep Insights from UIUC, Meta, and Stanford

Recent coding agents like Claude Code and Codex expose a deeper challenge: beyond generating correct code, agents must manage long‑term tasks by continuously planning, executing, testing, and updating code, making code the executable, inspectable, stateful medium that powers the Agent Harness framework.

AI AgentsAgent orchestrationMulti-Agent Collaboration
0 likes · 13 min read
Why Code Is the Core of Agent Harness: Deep Insights from UIUC, Meta, and Stanford
Machine Heart
Machine Heart
Jun 9, 2026 · Artificial Intelligence

Claude Fable 5 Unveiled: Record-Breaking Performance and New Pricing

Anthropic has launched Claude Fable 5, its most powerful LLM to date, claiming top‑tier results across software engineering, knowledge work, vision and scientific benchmarks, while offering higher token efficiency, new safety layers, and a pricing model of $10 per M input and $50 per M output tokens.

AI safetyAnthropicClaude Fable 5
0 likes · 7 min read
Claude Fable 5 Unveiled: Record-Breaking Performance and New Pricing
Machine Heart
Machine Heart
Jun 9, 2026 · Artificial Intelligence

Can a $10 Million Inference Budget Uncover AI’s Real Upper Limit?

The article argues that as large language models grow more capable, single‑score benchmarks no longer capture true performance; instead, evaluating models across varying inference budgets—measured in tokens, cost, or time—reveals their real capabilities and safety risks, prompting a shift toward performance‑cost curves and new industry standards.

AI evaluationAI safetyBenchmarking
0 likes · 13 min read
Can a $10 Million Inference Budget Uncover AI’s Real Upper Limit?
Machine Heart
Machine Heart
Jun 9, 2026 · Artificial Intelligence

How Linear Attention Learns “Write‑Before‑Think”: Parallel Multi‑Step Memory Writes with PRISM

PRISM demonstrates that linear‑attention models can adopt a “write‑before‑think” paradigm by reconstructing the multi‑step step‑size × residual × direction iteration of Test‑Time Training, achieving Transformer‑level quality while delivering up to 174× higher throughput through parallel scan and fused kernels.

Linear AttentionPRISMParallel Scan
0 likes · 19 min read
How Linear Attention Learns “Write‑Before‑Think”: Parallel Multi‑Step Memory Writes with PRISM
Machine Heart
Machine Heart
Jun 9, 2026 · Artificial Intelligence

OneReason: When Recommendation Systems Learn to Reason

The OneReason report details how Kuaishou’s recommendation team injects reasoning into large‑scale recommender models through a four‑level pre‑training pipeline, chain‑of‑thought (CoT) fine‑tuning, and specialized reinforcement learning, achieving significant offline gains and a 10.33% exposure lift in a live A/B test.

CoTLLMPretraining
0 likes · 31 min read
OneReason: When Recommendation Systems Learn to Reason
Machine Heart
Machine Heart
Jun 9, 2026 · Artificial Intelligence

How PSI Lab’s Three Award‑Winning Papers Define a Systematic Humanoid Robot Learning Framework

The PSI Lab at USC, led by Wang Yue, secured three CVPR 2026 awards—Psi‑0, PhysWorld and Humanoid Everyday—each tackling a distinct stage of humanoid robot learning: large‑scale human video pre‑training, embodiment‑aligned fine‑tuning, and physics‑aware world modeling, together forming a coherent data‑model‑prediction pipeline.

Embodied AIFoundation ModelsWorld Models
0 likes · 14 min read
How PSI Lab’s Three Award‑Winning Papers Define a Systematic Humanoid Robot Learning Framework