Type: Web Article Original link: https://x.com/karpathy/status/1938626382248149433?s=43&t=ANuJI-IuN5rdsaLueycEbA Publication date: 2025-09-04
Summary #
WHAT - The article discusses the competition to develop a “cognitive core” based on large language models (LLM) with a few billion parameters, designed to be multimodal and always active on every computer as the core of LLM-based personal computing.
WHY - This article is relevant for AI business because it illustrates an emerging trend towards lighter and more capable LLM models, which could revolutionize the way artificial intelligence is integrated into personal devices, offering new market opportunities and improvements in the cognitive capabilities of AI applications.
WHO - The main players are researchers and tech companies developing advanced LLM models, with a particular focus on Andrey Karpathy, an influential researcher in the field of AI.
WHERE - This article is positioned within the context of the competition for innovation in the field of large language models, with a specific focus on personal computing and multimodal integration.
WHEN - The discussion is current and reflects an emerging trend in the AI sector, with a potential significant impact in the coming years.
BUSINESS IMPACT:
- Opportunities: Developing lightweight and multimodal LLM models for personal computing can open new markets and improve AI integration in personal devices.
- Risks: The competition is intense, and other companies might develop similar or superior solutions.
- Integration: These models can be integrated into the existing stack to enhance the cognitive capabilities of AI applications.
TECHNICAL SUMMARY:
- Core technology stack: Large language models (LLM) with a few billion parameters, designed to be multimodal.
- Scalability: These models are designed to be lightweight and always active, making them scalable for use on personal devices.
- Technical differentiators: The ability to be multimodal and always active, sacrificing encyclopedic knowledge for greater cognitive capability.
Use Cases #
- Private AI Stack: Integration into proprietary pipelines
- Client Solutions: Implementation for client projects
- Strategic Intelligence: Input for technological roadmaps
- Competitive Analysis: Monitoring AI ecosystem
Resources #
Original Links #
- The race for LLM “cognitive core” - Original link
Article recommended and selected by the Human Technology eXcellence team, processed through artificial intelligence (in this case with LLM HTX-EU-Mistral3.1Small) on 2025-09-04 19:28 Original source: https://x.com/karpathy/status/1938626382248149433?s=43&t=ANuJI-IuN5rdsaLueycEbA
Related Articles #
- Nice - my AI startup school talk is now up! - LLM, AI
- +1 for “context engineering” over “prompt engineering” - LLM, Natural Language Processing
- Huge AI market opportunity in 2025 - AI, Foundation Model