# Foundational Models Projects at AI Tinkerers > Canonical HTML: https://aitinkerers.org/technologies/foundational-models > Markdown URL: https://aitinkerers.org/technologies/foundational-models.md > Technology record last updated: 2026-03-04T06:10:37Z > Generated: 2026-09-21T06:52:20Z Massive, pre-trained AI models: they serve as the adaptable base (foundation) for numerous downstream applications via transfer learning. Foundation Models (FMs) represent a paradigm shift: a single, massive AI model trained on a vast, general dataset. This pre-training allows FMs to be adapted (via fine-tuning or prompting) for a wide array of specialized tasks: natural language processing (NLP), image generation, and code completion. Key examples include OpenAI's GPT-4, a transformer architecture with an estimated 1.7 trillion parameters, and Google's BERT. The core value is transfer learning: FMs eliminate the need to train task-specific models from scratch, significantly cutting development time and compute resources for new applications. - Official technology site: https://crfm.stanford.edu/ - Public AI Tinkerers demos and talks: 3 - Result page: 1 of 1 ## Recent Public Talks and Demos ### [NParks Camera Trapping Video Animal Recognition, Using Foundational Models' Embeddings for Zero-shot Classification](https://singapore.aitinkerers.org/talks/rsvp_D3CY7_XnQlI) As part of Singapore National Park's Youth Stewards for Nature 2024 volunteer program, we built a system to recognize animals in camera trapping videos. In addition to fine-tuning a supervised trained model, we were able to use Foundational Models' zero-shot learning capability to classify frames. This method is competitive with supervised finetuning on a large amount of in-domain data, while requiring no training, and re-formulating the model training task into a data curation task, making it more accessible to the laymen. - Event context: AI Tinkerers Singapore: 4th Meetup - January 10th, 2025 β€” 2025-01-10 β€” Singapore - Public talk page: https://singapore.aitinkerers.org/talks/rsvp_D3CY7_XnQlI ### [Building Semiconductors in my Apartment](https://toronto.aitinkerers.org/talks/rsvp_ySgNtzKHHaM) Because the future of tech is semiconductorsβ€”but the barrier to entry is massive. πŸ—οΈ So, we are starting a design team Waterloo Hacker Fab building low-cost DIY equipment πŸ› οΈ to manufacture semiconductors devices. πŸ’° With $16,000 in funding already secured, we've just completed the first step of semiconductor manufacturing – Patterning and Coating. Now, we want to take it to the next level, and we’re looking for passionate Waterloo students interested learning more about semiconductors and building this out. - Event context: AI Tinkerers - Toronto - September 2024 Meetup β€” 2024-09-20 β€” Toronto - Public talk page: https://toronto.aitinkerers.org/talks/rsvp_ySgNtzKHHaM ### [AI agents for investment research](https://la.aitinkerers.org/talks/rsvp_WaoS2XyFySY) Using various ai personas to do the aspects of financial analysis based on their personas (fundamental analysis, technical analysis, growth and innovation analysis etc) - Event context: May 21st - LA AI Tinkerers Meetup & Demos β€” 2024-05-22 β€” Los Angeles - Public talk page: https://la.aitinkerers.org/talks/rsvp_WaoS2XyFySY ## Related Technologies - [AI personas](https://aitinkerers.org/technologies/ai-personas) ([Markdown](https://aitinkerers.org/technologies/ai-personas.md)) β€” 1 public demo - [Coating](https://aitinkerers.org/technologies/coating) ([Markdown](https://aitinkerers.org/technologies/coating.md)) β€” 1 public demo - [Data curation](https://aitinkerers.org/technologies/data-curation) ([Markdown](https://aitinkerers.org/technologies/data-curation.md)) β€” 1 public demo - [Embeddings](https://aitinkerers.org/technologies/embeddings) ([Markdown](https://aitinkerers.org/technologies/embeddings.md)) β€” 22 public demos - [function calling](https://aitinkerers.org/technologies/function-calling) ([Markdown](https://aitinkerers.org/technologies/function-calling.md)) β€” 11 public demos - [GPUs](https://aitinkerers.org/technologies/gpus) ([Markdown](https://aitinkerers.org/technologies/gpus.md)) β€” 5 public demos - [Open source models](https://aitinkerers.org/technologies/open-source-models) ([Markdown](https://aitinkerers.org/technologies/open-source-models.md)) β€” 7 public demos - [Patterning](https://aitinkerers.org/technologies/patterning) ([Markdown](https://aitinkerers.org/technologies/patterning.md)) β€” 1 public demo - [Prompt Engineering](https://aitinkerers.org/technologies/prompt-engineering) ([Markdown](https://aitinkerers.org/technologies/prompt-engineering.md)) β€” 28 public demos - [Semiconductors](https://aitinkerers.org/technologies/semiconductors) ([Markdown](https://aitinkerers.org/technologies/semiconductors.md)) β€” 1 public demo - [Supervised learning](https://aitinkerers.org/technologies/supervised-learning) ([Markdown](https://aitinkerers.org/technologies/supervised-learning.md)) β€” 2 public demos - [Zero-shot learning](https://aitinkerers.org/technologies/zero-shot-learning) ([Markdown](https://aitinkerers.org/technologies/zero-shot-learning.md)) β€” 1 public demo