daily work. Growing organization-wide familiarity with AI has enabled Klarna to move faster, launch internal initiatives more efficiently, and continuously refine the customer experience. By investing early Why it matters: Improved accuracy By training on your unique data—such as product 
 catalogs or internal FAQs—the model delivers more 
 relevant, on-brand results. Domain expertise Fine-tuned models better employee productivity and gives them access to deep, detailed research on any topic in minutes. In an internal evaluation by experts across domains, deep research saved an average of 4 hours per complex task

Steam Engines Telegraph Electrification Mass Steel Production Mass Production & Assembly Lines Internal Combustion Engine Flight Synthetic Fertilizer Transistors PCs Internet Smartphones Cloud12 interact with digital systems – from customer support and onboarding to research, scheduling, and internal operations. Enterprises are leading the charge; they’re not just experimenting with agents, but Revenue is driven by compute sales – whether in the form of AI APIs, enterprise platform fees, or internal productivity gains. But payback periods are often long, especially for vertically-integrated players

we evaluate it on a series of benchmarks in English and Chinese. Our evaluation is based on our internal evaluation framework integrated 13 in our HAI-LLM framework. Included benchmarks are categorized LLaMA3 70B (AI@Meta, 2024), and Mixtral 8x22B (Mistral, 2024). We evaluate all these models with our internal evaluation framework, and ensure that they share the same evaluation setting. Overall, with only Comparison among DeepSeek-V2 and other representative open-source models. All models are evaluated in our internal framework and share the same evaluation setting. Bold denotes the best and underline denotes the

● Git and review servers ● Forums and issue tracker ● Public mailing lists and IRC channel ● Internal Jira project restricted to Linaro members ● Three sub-projects: ○ Arm Compute Library ○ Arm NN