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JevBench

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EVENT TIMELINE

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MODELS · 1 SOURCE · InfoQ AI, ML & Data Engineering

AWS open-sources Strands Decider 2B and launches Strands Box sandbox for agent execution

AWS released Strands Decider 2B, a 2-billion-parameter decision-focused model (based on Qwen3.5-2B with a pointer head and rank-16 LoRA) and published the model weights, training data, and scripts. It also announced Strands Box (developer preview), a kernel-enforced sandbox using the Dogwood policy language to control agent execution (shell, Python, tools, filesystem, network); AWS reports ~115 ms median decision latency on an RTX 3090 and 72.3% accuracy on JevBench for a v19 checkpoint.

7.0

RESEARCH · 1 SOURCE · arXiv cs.AI

LEV (arXiv:2610.20951v1): looped decision models enable variable-depth thinking and higher accuracy

The paper introduces LEV, a decision-model architecture that reruns its layers in a loop and reads options after each loop step so a single checkpoint can be executed at different depths; all loop steps are trained jointly and a small learned ‘stopper’ can set depth per question. The authors report accuracy increasing with depth on three looped backbones (e.g., a 2.6B LEV rises from 63.2% at depth 1 to 76.2% at depth 4 on JevBench), on-demand depth saves roughly 15–24% of compute for under one percentage point of accuracy loss, and 1.4B/3B looped models outperform comparable dense models and cascades by 5.4–8.8 points at latencies below 50 ms.

7.0

CODING · 1 SOURCE · AWS Machine Learning

Deploy llama.cpp decision models on Amazon SageMaker AI with AWS DLC and SemIf

AWS published a how-to showing how to use the AWS Deep Learning Container (DLC) for llama.cpp to serve OpenAI‑compatible chat completions via SageMaker InvokeEndpoint, and how to extend that image with SemIf (formerly OpenJev) to return option probabilities and logits for structured decision tasks. The post includes CPU and GPU deployment options, a child‑image build path using CodeBuild/ECR for SemIf, and a benchmark comparing CPU vs GPU latency for SemIf workloads.

6.0