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Machine Heart
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Machine Heart

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Machine Heart
Machine Heart
May 29, 2026 · Artificial Intelligence

Why Vendors Bet on Step 3.7 Flash: An Agent‑Optimized Model for High‑Cost AI

Step 3.7 Flash is an open‑source, sparse‑MoE flash model built for real‑world Agent workflows, offering 11 B active parameters, 400 TPS, 256 K context, multimodal perception and tool use, and achieves top‑tier scores on benchmarks such as ClawEval‑1.1, Toolathlon and SimpleVQA, while dramatically reducing token‑costs that have plagued large‑scale AI deployments.

AgentCostFlash
0 likes · 10 min read
Why Vendors Bet on Step 3.7 Flash: An Agent‑Optimized Model for High‑Cost AI
Machine Heart
Machine Heart
May 29, 2026 · Artificial Intelligence

How Meta’s AI Consumed 183 Billion Tokens to Build a Massive Lean Math Library

Meta’s ATLAS project uses the AutoformBot pipeline to automatically translate 26 undergraduate and graduate math textbooks into a Lean codebase of over 630,000 lines, consuming more than 183 billion tokens, while exposing coverage statistics, adversarial dynamics, and model‑level performance trade‑offs.

ATLASAutoformBotLean
0 likes · 11 min read
How Meta’s AI Consumed 183 Billion Tokens to Build a Massive Lean Math Library
Machine Heart
Machine Heart
May 28, 2026 · Artificial Intelligence

How Legato Gives Robots Legato‑Style Smooth Motion

Legato, a new training method for action‑chunking flow policies, teaches robots to generate native continuous motions, eliminating hesitation and improving task speed and trajectory smoothness across five real‑world manipulation tasks, as demonstrated in the RSS 2026 paper.

Embodied AILegatoaction chunking
0 likes · 16 min read
How Legato Gives Robots Legato‑Style Smooth Motion
Machine Heart
Machine Heart
May 28, 2026 · Artificial Intelligence

Claude Opus 4.8 Arrives with Higher Honesty and Record‑Breaking Valuation

Anthropic unveiled Claude Opus 4.8, a flagship LLM that improves benchmark scores, introduces honesty training and dynamic workflows, offers unchanged pricing with a cheaper fast mode, and announced a $65 billion financing round that lifted its valuation to $965 billion.

AI alignmentAnthropicClaude Opus 4.8
0 likes · 9 min read
Claude Opus 4.8 Arrives with Higher Honesty and Record‑Breaking Valuation
Machine Heart
Machine Heart
May 28, 2026 · Artificial Intelligence

Domestic Supercomputer Hits 2.16 EFLOP/s, Enabling 10,000× Remote‑Sensing Compression

The D2AR generative compression framework leverages historical Earth‑observation priors and a dual‑decoupled asymmetric design to achieve exascale training at 2.16 EFLOP/s on a domestic Armv9 CPU supercomputer, scaling to 20,480 nodes and delivering up to 10,000× data reduction while preserving scientific utility.

Armv9 supercomputerdata reductionexascale AI
0 likes · 8 min read
Domestic Supercomputer Hits 2.16 EFLOP/s, Enabling 10,000× Remote‑Sensing Compression
Machine Heart
Machine Heart
May 28, 2026 · Artificial Intelligence

Why Google’s AI Can’t Count the Letters in Its Own Name

The article examines why the newly AI‑powered Google Search fails at simple letter‑count questions like “how many P’s are in Google,” tracing the issue to token‑based language models, illustrating it with examples, and discussing both short‑term prompts and long‑term architectural solutions such as byte‑level models.

Google SearchJagged IntelligenceLLM
0 likes · 13 min read
Why Google’s AI Can’t Count the Letters in Its Own Name
Machine Heart
Machine Heart
May 28, 2026 · Artificial Intelligence

How AutoMoT Leverages Large‑Model Understanding for End‑to‑End Driving Decisions and Trajectory Planning

AutoMoT introduces a unified Vision‑Language‑Action model that combines a 4B Qwen3‑VL understanding expert with a 1.6B action expert via layer‑wise shared attention and asynchronous inference, achieving state‑of‑the‑art results on Bench2Drive and nuScenes while preserving general VLM capabilities.

Asynchronous InferenceAutoMoTAutonomous Driving
0 likes · 10 min read
How AutoMoT Leverages Large‑Model Understanding for End‑to‑End Driving Decisions and Trajectory Planning