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  4. Palette trains small model to build design decks
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Models & Releases

Palette trains small model to build design decks

Hugging Face: Palette: teaching a small model to build decks in your design language

Designers could save hours on repetitive layout work if AI learns to match their specific visual systems and brand guidelines.

Get smart on it

Palette is a small open-weight model trained to automatically build presentation decks in a specific design language, rather than relying on large frontier models that impose their own house style. Small models traditionally struggle with deck creation because they must simultaneously make editorial decisions about content and perform precise geometric calculations for layout, leading to broken slides with overlapping text and misaligned elements. The researchers addressed this by splitting the task into two specialized stages: a designer that creates a structured plan with design rationale, and a coder that converts each slide specification into executable code, with training data synthesized from a larger teacher model and validated through an automated checking system. This approach allows organizations to maintain ownership of their design assets while keeping confidential content on their own infrastructure.

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Anthropic Releases FlashProve: Cryptographic Proofs That a Reply Came From Committed Weights

Anthropic’s Frontier Red Team has released FlashProve, an open-source research prototype for provable inference. FlashProve is a zkSNARK system from Anthropic that proves a reply came from a committed model. The proof reveals nothing about the model weights. On Llama 4 Maverick, a 400B mixture-of-experts model, it proves about 110 tokens/second on 1 H100. For developers, this targets a real gap: today you cannot check which model actually answered your API call. TL;DR Size: Proves

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42AI comes out of stealth with $62.5M and a world model that can ‘predict human behavior’

Here's a question straight out of sci-fi: What if AI could predict what you were going to do before you decided to, even in a completely new situation?

Also reported by SiliconANGLE

Models & ReleasesOpen story →

Mistral releases weights for its trillion-parameter AI model, targeting cybersecurity

Mistral says its new model can afford organizations a kind of control over its cyber defenses that closed models can't.

Models & ReleasesOpen story →

Deep Principle Releases Hydrogen-1.0: A 753B Open-Weight Model for Scientific Discovery

Deep Principle has released Hydrogen-1.0, an open-weight scientific model for chemistry, materials science and life sciences. It is built by post-training Z.ai’s GLM-5.3 on domain data, laboratory records and agent discovery trajectories. For developers, it offers open weights that report a FrontierScience-Research win over GPT-6-Astra. The weights ship under the MIT License. TL;DR Size: 753B parameters (MoE, ~40B active per the GLM-5.3 base), 1M-token context, 128K max output.

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OpenAI sets new behavioral guidelines for AI models that have already proven hard to control

OpenAI has updated its Model Spec, restructuring its AI behavior guidelines around five core values, including faithfulness to human intent and correctability. GPT models should now draw on conversation history to figure out what users actually want and disclose their own assumptions. Whether the models follow these rules is another matter. The article OpenAI sets new behavioral guidelines for AI models that have already proven hard to control appeared first on The Decoder.

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Soniox STT v6 Adds Agent Text Input and Echo Filtering for Voice Agents

Soniox has released Soniox STT v6, the latest generation of its speech-to-text API. Soniox STT v6 is a speech-to-text model that reads what a voice agent says while hearing the caller. It uses that text to recognize short replies and to drop the agent’s own voice. The release ships as stt-rt-v6 for streaming and stt-async-v6 for files, across 60+ languages. TL;DR Size: Soniox STT v6 is a proprietary hosted model, no parameter count published. Runs on: Soniox cloud API only (WebS