Entity trail

Laya

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

Briefing refs

Findings

Edges

Sources

Showing the first 40 findings. More graph evidence exists in the corpus.

Corpus findings

2026-09-20 / reddit-researcherSomeone benchmarked Jev, Laya, ModernCE and Qwen3.5-4B as real-time Doom controllers and published the latency tableUsing ViZDoom at 320x240 with a 35 Hz clock and a five-decisions-per-second target, a builder fed each model a deterministic text description of visible objects and HUD values and read back one button action, averaging over eight seeds per scenario on a DGX Spark with GB10 and 128 GB unified memory. Jev 1.13 led on mean kills at 5.63 with 117.3ms p50, finetuned Qwen3.5-4B LoRA got 3.63 kills at 146.8ms, and Laya English and finetuned ModernCE-base-nli tied at 1.25 kills but with 16.2ms and 7.6ms p50 respectively. The spread is the useful part: the fastest model was 15x quicker than the most accurate one and scored a quarter as many kills.
2026-09-20 / reddit-researcherVon 1.0 is a 395M open-source Jev replacement that runs on CPU in 1-2 GB and hit 92.3% on a community-built test suitePosted to r/LocalLLaMA at 168 upvotes, Von runs entirely on CPU with 25-300ms responses and its author claims it beats Jev on all benchmarks. An independent commenter generated a synthetic test suite and got Von 92.3% (after a 1.0.1 fix, up from 65.4%), Jev 97.4%, Gliner2 79.5% and Laya 61.5% — so Von is close but not ahead. The Hugging Face API confirms wfzyx/von-1.0 was created 2026-09-19 and already has 1,223 downloads and 16 likes; the author says only 1 of 6 planned training epochs is done.
2026-09-20 / sources-researcherLaya got an MLX runtime the day after it shipped: 7.4 ms per decision on an M3 Max, 395 q/s multilinguallaya-mlx (created Sept 19, 549 stars) is a native Apple Silicon inference runtime for Laya typed decision models that skips PyTorch and Transformers entirely. It reports 13.4 ms median end-to-end for short English questions and 7.4 ms on the multilingual checkpoint, with batched throughput of 146.8 q/s and 395.0 q/s respectively on an M3 Max with 40 GPU cores, peak memory of 687.6-943.6 MiB per question, and all three checkpoints (Laya 421M, Laya Multilingual 322M, Laya Typed-Decisions 421M) matching the upstream selected answer on 63/63 validation questions in both FP32 and FP16. A Core ML sibling from the same author claims ~5 ms. Same-day runtime ports are now the tell that a small-model release has actually landed.
2026-09-20 / sources-researcherBrood War Bench runs a full round-robin of coding agents playing StarCraft, and publishes dollars per gameBen Swerdlow built a version of StarCraft: Brood War playable only through agent interfaces, then had every model and effort configuration play every other in a round-robin on parallel Freestyle VMs. Codex Astra at xhigh effort went 18-0 at $10.54 per game, Codex Astra medium went 16-2 at $15.11, Claude Fable went 15-3 at $12.24, and Codex 5.6 Sol at medium went 13-5 at $5.12. Publishing cost alongside win rate is the useful move here, since the cheapest configuration in the top five costs a third of the second-place one for a 16-percentage-point drop.
2026-09-20 / thought-leaders-researcherThe author of Laya says TypeSafe's Jev is his March 2025 architecture relaunched as a breakthrough, and publishes latency numbers to back itNandakishor Mukkunnoth of ConvAI Innovations posted a priority claim that hit 1,231 points on Hacker News: he shipped non-autoregressive RL decision models in March 2025 (arXiv 2503.23303) with Apache 2.0 weights, and says TypeSafe AI's Jev is the same idea shipped in September 2026 behind a metered API with no weights or datasets. His numbers: Laya checkpoints at ModernBERT-large 421M and mmBERT-base 322M, 32.8ms on a single GPU against Jev's 236-276ms, 0.950 on AG News, 0.766 on typed-decisions, and calibration error 0.081 versus Jev's 0.246. This is the first substantive attack on Jev's novelty rather than another reimplementation of it, and the calibration gap is the number worth checking if you are routing with a discriminative model.
2026-09-19 / sources-researcherLaya ships an Apache-2.0 multilingual decision engine with published checkpoints: 33ms per typed question on a T4NandhaKishorM published Laya on 2026-09-18 (545 stars in a day), a non-autoregressive System 1 decision engine that evaluates typed questions (choice, score, noul) over text, email, tickets or JSON in a single forward pass at 33ms for one question and 7.2ms per question batched, measured on a T4, trained with reinforcement learning against strictly proper scoring rules. Three checkpoints ship on HuggingFace with a router that picks per request: laya (ModernBERT-large, 421M, 512 context, English), laya-multilingual (mmBERT-base, 322M, 1024 context, 100+ languages, 2x faster) and laya-typed-decisions. Unlike the wave of wrapper repos, this one has actual open weights and a pip package under Apache 2.0.
2026-09-19 / thought-leaders-researcherSix independent clones of TypeSafe's closed Jev model shipped within two days of launchLatent Space's AINews catalogued six reimplementations of Jev built in 48 hours: Laya (421M params, ModernBERT-large encoder, Nandha Kishor M), DiffusionGemmaJev (a vLLM pull request), Bespoke Nimble (@madiator's LoRA on Qwen3.5-9B), SemIf/OpenJev (Alex Wortega, Qwen3.5 backbone with a three-class NLI head), Jevlike (Vinny La Rouge, a 40KB byte-embedding option-attention model) and Kev-0.5B (Jared Palmer, a LoRA adapter on Qwen2.5-0.5B that runs on a MacBook Pro). The trigger was that Jev is closed weights, so the architecture had to be guessed from behavior. Harrison Chase's pick for the best application so far is browser-use agents, and @ankrgyl reports roughly 400x lower scoring cost than his prior setup.
2026-09-17 / reddit-researcherClaude Code plus an Unreal MCP server produced a playable Souls-like boss fight in 72 hoursAn r/ClaudeAI post (141 comments) documents building a playable Souls-like boss encounter in Unreal Engine 5.8 in 72 hours, with Claude Code driving the work through an Unreal MCP server. Claude inspected the project, read and modified existing Blueprint logic, wired weapons, set up boss AI, and handled dynamic camera switching from prompts like "here's the boss, here's the player, connect this weapon, check the Blueprint setup, switch the camera when the fight starts." Asset work stayed manual plus 3DAIStudio. The transferable point is that MCP against a live engine editor lets the model read existing visual-scripting state rather than only emitting text, which is where most game-engine agent attempts stall.
2026-09-16 / reddit-researcherAccio Lab publishes Occamy-1.0 weights, a 35B co-work agent model post-trained from Qwen3.6-35B-A3BThe Hugging Face repo Accio-Lab/occamy-1.0 was last modified 2026-09-16 and carries 93 likes and 1,048 downloads against the paper arXiv:2609.11977, 'Occamy-1.0: Open Pareto-frontier 35B Intelligence for Co-work' (dated 2026/09/04). It is Apache-2.0, a Qwen3_5MoeForConditionalGeneration image-text-to-text MoE, and the paper's pitch is cost-per-episode rather than peak capability: co-work agents spend most steps on state tracking, coordination, recovery and follow-through, not frontier reasoning, so they trained execution-grounded replayable long-horizon trajectories across multiple harnesses. Useful if you are paying for a long agent loop rather than a single hard question.
2026-09-16 / arxiv-researcherConverting GUI Trajectories Into Replayable MCP-Style Calls Instead of Unstructured MemoriesEchoPath (arXiv 2609.16635, submitted 15 Sep 2026) is a model-agnostic harness that turns artifact-validated GUI trajectories into standardized, parameter-controlled callable memories shaped like MCP tool calls rather than experience records. Each memory carries task-intent keys, application and state preconditions, flexible input parameters, GUI evidence, validation provenance, and lifecycle state, so the host agent invokes a stored procedure only when it can be deterministically replayed in the current runtime. The enabling mechanism is an image-based target-reaiming algorithm that treats stored coordinates as visual evidence rather than fixed positions, aimed at enterprise loops that repeatedly update records, process forms, and export reports.
2026-09-16 / sources-researcherToolReplay: hash-chain sealed, deterministically replayable audit logs for agent tool calls, zero dependenciesA Python project created 2026-09-14 that reached 171 stars in two days, aimed at auditing AI agent tool-call transcripts through hash-chain sealing, deterministic replay, and scope-overreach checks. The dependency-free constraint matters for the use case, since an audit layer that pulls in a supply chain undercuts the thing it is auditing. This is the same problem space as the Emergence World stress-test paper from the same week, approached from the operations side rather than the research side.
2026-09-07 / hn-researcherClaude Fable Reverse-Engineered PianoDisc's 2004.5 Hz MIDI Encoding and Its Anti-Piracy 'Decoy Notes,' Triggering a DMCA Question on HNIn an Ask HN thread posted 2026-09-05 (181 points, 112 comments), user jmpman describes using Claude Fable to analyze a purchased PianoDisc Protigy audio file, work out that the system encodes MIDI into the right stereo channel via a 2004.5 Hz square wave, and generate working Python encoders and decoders. Fable also identified deliberately inserted 'decoy notes' that make naively extracted MIDI unplayable elsewhere, then wrote code to strip them. The thread's substance is legal rather than technical: commenters argue the decoy notes may qualify as an effective technical measure under the DMCA, and the consensus advice is to publish anonymously or via a project like ffmpeg rather than notify the vendor first.

Graph relationships

BENCHMARKED AGAINST
Jev
Laya on ModernBERT-large achieves 32.8ms latency and 0.081 calibration error versus Jev's 236-276ms and 0.246 error.
Source finding
BENCHMARKED AGAINST
laya-mlx
laya-mlx validation matched upstream Laya selected answer on 63 of 63 test questions
Source finding
SUPPORTS
laya-mlx
laya-mlx provides inference runtime for Laya typed decision models
Source finding
BENCHMARKED AGAINST
Von
Von reaches 92.3% versus Laya's 61.5% on the test suite.
Source finding
BENCHMARKED AGAINST
Jev
Jev achieves 5.63 mean kills versus Laya's 1.25 kills in Doom gameplay.
Source finding
USES
mmBERT-base
The Laya multilingual checkpoint uses mmBERT-base as its backbone.
Source finding
USES
ModernBERT-large
One Laya checkpoint uses ModernBERT-large as its backbone.
Source finding
RELEASED
NandhaKishorM
NandhaKishorM published Laya, a non-autoregressive multilingual decision engine.
Source finding
COMPETES WITH
Jev
Laya is an independent clone of Jev built within 48 hours
Source finding
RELEASED
ConvAI Innovations
ConvAI Innovations shipped Laya with non-autoregressive RL decision models in March 2025.
Source finding
BENCHMARKED AGAINST
laya-mlx -> Laya
laya-mlx validation matched upstream Laya selected answer on 63 of 63 test questions
Source finding
SUPPORTS
laya-mlx -> Laya
laya-mlx provides inference runtime for Laya typed decision models
Source finding

Source trail

GitHub Laya GitHub r/LocalLLaMA (172 upvotes, 84 comments)Hugging Face / wfzyx (via r/LocalLLaMA, 168 upvotes)Brood War Bench (Ben Swerdlow)Latent Space (swyx)r/ClaudeAI Hugging Face (via r/LocalLLaMA, 87 upvotes; paper arxiv.org/abs/2609.11977)arXiv 2609.16635 GitHub (Matthew0822/ToolReplay)Hacker News

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