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Use case
Innovating AI development workflows
Context

NinjaTech AI harnesses Meta Llama 3 alongside AWS's Trainium & Inferentia2 chips and PyTorch to develop next-generation AI agents (Ninja LLMs).

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4
Use case
Accelerating talent acquisition
Context

LyRise, a recruitment platform connecting companies with AI experts from the Middle East and North Africa, uses Meta's Llama 2 and 3 to implement AI-driven candidate matching. By utilizing Llama's text summarization and RAG capabilities to condense job descriptions and resumes, LyRise reduces time-to-hire by 50%, while ensuring quality talent acquisition.

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2
Use case
Ensuring AI compliance and trust
Context

SAIF CHECK, a company based in Riyadh, Saudi Arabia, uses Meta's Llama 3 to develop a model evaluation system that assesses AI models for compliance with legal, regulatory, privacy, and data security standards. Utilizing a Retrieval Augmented Generation (RAG) framework, the system scans and integrates global regulatory environments into a comprehensive knowledge base, enabling conversational and context-aware evaluations for both technical and non-technical users. This enhances trust in AI models, streamlines the auditing and certification process, and ensures businesses in the Middle East and North Africa can deploy AI solutions confidently and compliantly.

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2
Use case
Automating video post-production
Context

Aive, an AI platform for video post-production, leverages Meta's Llama 3 to automate video summarization and smart clipping. By analyzing long-form content, Aive creates concise, engaging video formats optimized for platforms like Facebook and Instagram. This integration helps brands like LVMH, L'Oréal, and Stellantis streamline video workflows, reduce costs, and maximize content impact across channels within a secure and scalable AI environment.

Models/tools
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1
Use case
Democratizing medical AI tools
Context

Meditron, a suite of open-source large multimodal foundation models tailored for the medical field, leverages Meta's Llama 2 and 3 to assist with clinical decision-making and diagnosis in low-resource settings. Developed by researchers at EPFL and Yale School of Medicine in collaboration with humanitarian organizations like the International Committee of the Red Cross, Meditron provides evidence-based, contextually aware recommendations and diagnostic support. It automates tasks such as generating treatment regimens, determining radiation modalities, and assigning diagnostic codes, thereby enhancing clinical efficiency and improving patient outcomes. With over 30,000 downloads and top performance on medical benchmarks, Meditron democratizes access to advanced medical AI tools, enabling equitable healthcare innovation in underserved regions.

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2
Use case
Advancing open healthcare AI performance
Context

The Barcelona Supercomputing Center has developed Aloe, a family of fine-tuned open healthcare LLMs built on Meta Llama 3. Aloe features advanced training and inference mechanisms, achieving over 10 accuracy points improvement and setting new standards for ethical performance in healthcare AI through policy alignment and Direct Preference Optimization, leading to state-of-the-art results for open healthcare 7B LLMs.

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1
Use case
Automating large-scale code refactoring
Context

ClearPoint integrated Meta's Llama 3 with Google's code scanner lint to perform an automated refactor of over 500 code files in a large Kotlin codebase. With less than 500 lines of automation code, they produced a migration that runs with a single build command without human intervention, saving an estimated 11 engineering weeks and improving efficiency without risking IP or vendor lock-in.

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Use case
Indexing massive digital libraries
Context

Tune AI is a fine-tuning and deployment platform assisting large enterprises. For an information services enterprise, Tune AI selected Meta's Llama 3 to index a massive 7B+ page digital library, reducing costs from $18 to $0.60 per document and processing time from 1 hour to 7 minutes, achieving a 99% accuracy rate, significantly enhancing efficiency and cost-effectiveness.

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