Tinker
PulseAugur coverage of Tinker — every cluster mentioning Tinker across labs, papers, and developer communities, ranked by signal.
4 day(s) with sentiment data
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Qwen3-235B outperforms Inkling as base for fine-tuned models
A Reddit discussion on the r/LocalLLaMA subreddit explores the effectiveness of fine-tuning large language models, specifically questioning whether the base model's architecture is as crucial as its fine-tuning behavior…
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AI accessibility is artificially subsidized and unsustainable, experts warn
The current accessibility of large-scale AI is artificially maintained through significant subsidies, including cheap tokens, subscription discounts, and local government support for data center infrastructure like powe…
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Thinking Machines Lab releases Inkling, a 1T-parameter open-weight multimodal AI model
Thinking Machines Lab has released Inkling, an open-weight AI model with approximately 1 trillion parameters designed for fine-tuning. This model supports multimodal understanding of text, images, and audio, and allows …
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Fireworks AI releases Inkling, a 975B multimodal MoE model
Fireworks AI has released Inkling, a new 975 billion parameter Mixture-of-Experts (MoE) model. This multimodal model, which can process text, image, and audio, is available under the Apache 2.0 license. Inkling is desig…
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Thinking Machines Lab releases Inkling, an open-weights multimodal model
Thinking Machines Lab has released Inkling, an open-weights multimodal model with 975 billion total parameters and 41 billion active parameters. The model is trained on 45 trillion tokens of text, images, audio, and vid…
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thinkingmachines.ai unveils open-source multimodal model Inkling
thinkingmachines.ai has launched Inkling, a new multimodal AI model capable of reasoning across text, image, and audio. The company is releasing the full model weights, making it open-source and fine-tunable on their Ti…
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Ex-OpenAI execs launch Inkling, an open-weight AI model
Thinking Machines Lab, founded by former OpenAI executives, has released its first open-weight model named Inkling. This model is designed to process audio, video, and text, featuring advanced reasoning and coding capab…
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Thinking Machines releases open-weight Inkling model, challenging closed AI giants
Thinking Machines, a startup founded by former OpenAI CTO Mira Murati, has released its first open-weight AI model named Inkling. This model, a mixture-of-experts system with 975 billion parameters, is designed to be ad…
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Developer trains AI to train other AI models using Qwen3.6
A developer has created an AI system that trains other AI models, utilizing a Qwen3.6 model as the primary agent. This agent is tasked with generating complete training jobs, including environments, rewards, datasets, a…
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Open AI ecosystems offer cost advantages through shared R&D
The majority of compute costs for developing frontier AI models are attributed to research and development rather than the final training phase. China's AI ecosystem, characterized by its open-first approach among leadi…
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Mira Murati highlights AI model training infrastructure choices
Mira Murati shared a post from Brydon Eastman discussing the "taste" of AI models and their creators, specifically in relation to training infrastructure. The post humorously suggests that models, like their developers,…
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Mira Murati highlights Mantic's work on calibrated predictions and supports AI education
Mira Murati, CTO of OpenAI, shared support for Mantic's work on calibrated predictions, highlighting their potential to transform decision-making. Mantic's new blog post details their methodology, which aims to build AI…
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Thinking Machines launches Tinker, simplifying LLM fine-tuning for researchers
Thinking Machines has launched Tinker, a platform designed to simplify the process of fine-tuning language models for researchers and developers. The tool offers abstractions for writing experiments and managing distrib…
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Thinking Machines launches Tinker API for flexible, distributed LLM fine-tuning
Thinking Machines has launched Tinker, a new API designed to simplify the fine-tuning of language models. The service allows developers to write training loops on their local machines, which are then executed on distrib…