NVIDIA Nemotron 3 Nano Omni on Clarifai Reasoning Engine: Zero Day Support at 400 Tokens Per Second
Benchmarking Gemma-3-4B, MiniCPM-o 2.6, and Qwen2.5-VL-7B-Instruct for latency, throughput, and scalability.
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What leaked “SteamGPT” files could mean for the PC gaming platform’s use of AI
These days, it seems like every tech company and their corporate parent is looking to squeeze AI tools and features into their products, whether they’re wanted or not. So when files with names and functions referencing a “SteamGPT” appeared in a recent Steam client update, Valve watchers took quick notice. From the outside, it’s hard
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Run Gemma 4 Locally: Deploy Frontier AI on Your Hardware with Public API Access
Run Google’s Gemma 4 models on your own hardware while exposing them via public API using Clarifai Local Runners. Apache 2.0 licensed, multimodal support, and production-ready.
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Ai2: Building physical AI with virtual simulation data
Virtual simulation data is driving the development of physical AI across corporate environments, led by initiatives like Ai2’s MolmoBot. Instructing hardware to interact with the real world has historically relied on highly expensive and manually-collected demonstrations. Technology providers building generalist manipulation agents typically frame extensive real-world training as the basis for these systems. For some
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How to Choose the Right Open-Source LLM for Production
A practical guide to choosing the right open-source LLM for production based on workload type, infrastructure limits, cost, and real-world performance.
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Anthropic: Claude faces ‘industrial-scale’ AI model distillation
Anthropic has detailed three “industrial-scale” AI model distillation campaigns by overseas labs designed to extract abilities from Claude. These competitors generated over 16 million exchanges using approximately 24,000 deceptive accounts. Their goal was to acquire proprietary logic to improve their competing platforms. The extraction technique, known as distillation, involves training a weaker system on the
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Alibaba Qwen is challenging proprietary AI model economics
The release of Alibaba’s latest Qwen model challenges proprietary AI model economics with comparable performance on commodity hardware. While US-based labs have historically held the performance advantage, open-source alternatives like the Qwen 3.5 series are closing the gap with frontier models. This offers enterprises a potential reduction in inference costs and increased flexibility in deployment
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AI forecasting model targets healthcare resource efficiency
An operational AI forecasting model developed by Hertfordshire University researchers aims to improve resource efficiency within healthcare. Public sector organisations often hold large archives of historical data that do not inform forward-looking decisions. A partnership between the University of Hertfordshire and regional NHS health bodies addresses this issue by applying machine learning to operational planning.
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How to Access Ministral 3 models with an API
Learn how to access Ministral 3 via the Clarifai API. Explore open-weight 3B and 14B reasoning models, benchmark performance, and integrate them using Python and Node.js.
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Access Trinity Mini with an API
Explore NVIDIA GH200 Grace Hopper superchip—architecture, AI use cases, benchmarks, and a decision guide for large-scale LLMs, HPC, and enterprise AI.
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