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End-to-End Multimodal Data Augmentation and Adversarial Robustness Benchmark with AugLy for Images, Text, Audio, and PyTorch

In this tutorial, we build a comprehensive multimodal augmentation and robustness workflow with AugLy for images, text, and audio. We start by addressing modern dependency compatibility issues and generating deterministic synthetic datasets so the experiments remain self-contained and reproducible. We then explore AugLy’s functional and class-based APIs, metadata, and intensity tracking, probabilistic composition, bounding-box-aware transformations, […]

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Liquid AI Releases LFM2.5-VL-3B-DSpark: Speculative Decoding for Vision-Language Models With Up to 3.13x Faster Decoding

Liquid AI has announced LFM2.5-VL-3B-DSpark, an experimental speculative-decoding draft model for its LFM2.5-VL-3B vision-language model. The drafter adds about 280M parameters and speeds up decoding without changing the model’s output. Liquid AI team reports up to 3.13x faster decoding on Apple silicon and up to 2.66x on an NVIDIA H100. Is it deployable? Yes, Weights

Liquid AI Releases LFM2.5-VL-3B-DSpark: Speculative Decoding for Vision-Language Models With Up to 3.13x Faster Decoding Read More »

Aikido Security Releases Altar-1: An Open-Weight Security Model Pruned From GLM-5.3 to 328 GB

Aikido Security has released Altar-1, its first open-weight security model. It is a compressed version of Z.AI’s GLM-5.3, built to run inside infrastructure the customer controls. Altar-1 powers Aikido Machine, the company’s autonomous pentesting appliance for on-prem and air-gapped networks. Is it deployable? Yes, the weights are public on Hugging Face and run with vLLM

Aikido Security Releases Altar-1: An Open-Weight Security Model Pruned From GLM-5.3 to 328 GB Read More »

Perplexity Trains Its Computer Agent on Real Mistakes With Hint-Guided Self-Distillation

Perplexity Research published a new post-training study. It trains a model inside Perplexity Computer on real user sessions, including failed ones. The method pairs rejection sampling fine-tuning with hint-guided self-distillation. In a live A/B test, tool-call failures fell from 2.24% to 1.77% between 2 trained checkpoints. Perplexity team reports this as a statistically significant 21.2%

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Fastino Releases GLiNER2.5-Decide: A 340M Open-Weight Decision Model That Runs on CPU

Fastino Labs has released GLiNER2.5-Decide, a 340M-parameter open-weight decision model. It takes text and a schema of typed questions and returns structured answers. Each answer comes with a probability distribution, a confidence score, and constraint-feasibility metadata. It targets the frequent judgment calls inside agent pipelines: routing, triage, tool selection, and guardrails. Is it deployable? Yes,

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Black Forest Labs Releases FLUX 3 Action: A 7B Open-Weights World Action Model That Tops RoboLab-120

Black Forest Labs (BFL), the lab behind the FLUX image models, has released FLUX 3 Action. It is a 7B open-weights World Action Model (WAM) for robot control. The model reads camera frames, robot state and a text instruction. It then predicts future video frames and the next chunk of actions together. On the RoboLab-120

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BottleCap AI Releases ThinkingCap-Qwen3.8-27B: 37.2% Fewer Thinking Tokens at a 0.86pp Accuracy Cost

BottleCap AI has released ThinkingCap-Qwen3.8-27B, the second model in its ThinkingCap series. It is a fine-tune of the Qwen team’s Qwen3.8-27B with one narrow goal: shorter reasoning traces. Across 12 benchmarks, it spends 37.2% fewer thinking tokens on average. Macro-average accuracy moves from 86.65% to 85.79%, a 0.86pp drop. Deployable? Yes. It drops in for

BottleCap AI Releases ThinkingCap-Qwen3.8-27B: 37.2% Fewer Thinking Tokens at a 0.86pp Accuracy Cost Read More »

Contrastive-LM Releases CLM-8B: An Open System One Model That Scores Agent Actions Up to 9× Faster Than Jev

Contrastive-LM has released CLM-8B, the first open model in a new class called Contrastive Language Models (CLMs). CLM does not generate text. It scores a set of candidate actions against the current state and returns probabilities. Their main baseline is Jev, the proprietary System One model from TypeSafe AI. Is it deployable? Yes. The Apache-2.0

Contrastive-LM Releases CLM-8B: An Open System One Model That Scores Agent Actions Up to 9× Faster Than Jev Read More »

Google Releases Gemini 3.8 Flash TTS and Flash-Lite TTS With Prompt-Based Voice Design

Google has released Gemini 3.8 Flash TTS and Gemini 3.8 Flash-Lite TTS, 2 new text-to-speech models in its Gemini Audio family. Google calls them its most expressive audio generation models yet. Flash TTS targets creative direction and character voices. Flash-Lite TTS targets high-volume, cost-efficient production. Both let developers direct delivery line by line using natural

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NVIDIA Releases Nemotron 3 Diarization: A 100M-Parameter Open-Weight Model That Tracks 8 Speakers in Real Time

NVIDIA has released Nemotron 3 Diarization, an open-weight speaker diarization model on Hugging Face. It answers one question about any conversation: who spoke when. The 100M-parameter model tracks up to 8 speakers, including when voices overlap. One checkpoint handles both offline recordings and real-time streaming. Is it deployable? Yes. The weights are released under the

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