Definition
Frontier model
One of the most capable general-purpose AI models available, at or near the leading edge of the field.
How founders on the podcast use it
The largest, most capable general purpose models from the leading labs.
Tokenomics Will Wreck Your Margins: The AI Model Routing Workflow That Cuts SpendThe largest, newest, most expensive closed models.
40,000 Models, One API Key, and a $25M Bet on Open SourceThe most capable current AI models, the ones that keep absorbing yesterday's 'products' as built-in features.
What it do!? The Jujitsu Secret That Scales Companies Without ForceThe largest and most capable current generation models. Expensive, powerful, and often overkill for routine tasks.
Tokens Go to Zero, Energy Goes to Zero: What Do You Build When Intelligence Is Free?Hear it on the podcast4 episodes
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Related terms in AI Fundamentals
Fine-tuningTaking a pre-trained model and training it further on data for a specific task or domain so it performs better there.Foundation modelA large model trained on broad data that can be adapted to many different tasks, serving as the base for many products.Foundation Model Fine-TuningThe process of taking a pre-trained large language model (such as GPT-4, Claude, or Gemini) and continuing its training on a smaller, domain-specific dataset to specialize its behavior for a particular use case without training a model from scratch. Fine-tuning allows companies to capture the reasoning and language capabilities of a foundation model while customizing it for specific vocabularies, response formats, constraints, or domain knowledge. Loman.ai fine-tunes foundation models for the specific context of restaurant phone conversations - teaching them the nuances of taking food orders, handling 86'd items, managing reservation requests, and maintaining the appropriate tone for different restaurant types. Christian's approach: test every major foundation model, identify which performs best for each specific sub-task within the product, and fine-tune for production performance.Frontier labsThe handful of companies training the most capable models, including Anthropic, OpenAI, and Google.GAN (Generative Adversarial Network)A setup where two neural networks compete: a generator creates fake data and a discriminator tries to spot it, which pushes the generator to get more realistic.Generative AIAI that creates new content, such as text, images, music, code, or video, rather than only analyzing existing data.GPT (Generative Pre-trained Transformer)A family of large language models built on the transformer architecture and trained to generate human-like text from a prompt.GPT WrapperA thin AI product built on top of a foundational LLM without proprietary data, unique distribution, or genuine differentiation. The category of AI product most founders are building and fewest investors want to fund as foundational models grow more capable. Lacks the defensible IP or distribution moat required for long-term pricing power.