Private Markets, Angel and Secondary Investing, Sacra

Sacra

Private Markets, Angel and Secondary Investing

Bringing transparency to private markets so investors, founders, and employees can build on conviction. Sacra delivers deeply researched insights on the private companies shaping tomorrow's markets. By surfacing the data, context, and operator perspective that are missing from private markets today, we help secondary buyers and sellers price equity accurately and unlock liquidity for the people building these businesses.

Private Capital Markets

<ul><li>Claude 3.5 Sonnet has blown the doors open for Anthropic's API business, growing 5x this year to date to $664M ARR.</li><li>OpenAI's ChatGPT continues to dominate, growing a Sacra-estimated 2.5x this year to date to $2.9B ARR.</li><li>OpenAI's 4x YoY growth to $4B matches and exceeds Meta, Google & AWS’s.</li></ul>

Claude 3.5 Sonnet has blown the doors open for Anthropic's API business, growing 5x this year to date to $664M ARR.OpenAI's ChatGPT continues to dominate, growing a Sacra-estimated 2.5x this year to date to $2.9B ARR.OpenAI's 4x YoY growth to $4B matches and exceeds Meta, Google & AWS’s.

Cerebras Systems / Private Capital Markets

<ul><li>Cerebras generated $250M of revenue in 2023, up 200% year-over-year, their growth accelerating with the rise in AI compute demand from big enterprises training models on their proprietary data.</li><li>Cerebras (2015) designed its Wafer-Scale Engine chip to vastly accelerate training on the compute-intensive BERT models used in scientific deep learning, finding product-market fit with national labs like Argonne and Livermore working on protein folding, climate prediction, and molecular dynamics.</li><li>With GPTs ascendant (vs BERT models), Cerebras and Groq are both repurposing their chips to move into the $150B and growing market of LLM and AI model training to take on Nvidia.</li></ul>

Cerebras generated $250M of revenue in 2023, up 200% year-over-year, their growth accelerating with the rise in AI compute demand from big enterprises training models on their proprietary data.Cerebras (2015) designed its Wafer-Scale Engine chip to vastly accelerate training on the compute-intensive BERT models used in scientific deep learning, finding product-market fit with national labs like Argonne and Livermore working on protein folding, climate prediction, and molecular dynamics.With GPTs ascendant (vs BERT models), Cerebras and Groq are both repurposing their chips to move into the $150B and growing market of LLM and AI model training to take on Nvidia.

<ul><li>Companies like Ramp, Notion and Databricks take outputs from frontier models like OpenAI’s GPT-4 and use them to fine-tune smaller, cheaper and faster open source models like Mistral and Llama 3.1, reducing their costs by 90% for specific, repetitive tasks.</li><li>Fine-tuning platforms like OpenPipe ($6.7M raised), Predibase (Felicis, $28.5M raised) and Airtrain AI (Y Combinator, $3.2M raised) unbundle fine-tuning from the LLMs and rebundle it with MLOps, combining a software development kit (SDK) for collecting prompt-completion pairs with model training, eval, and deployment to launch and rapidly iterate on fine-tuned models.</li><li>We recognized that fine-tuning could greatly enhance capabilities and reliability, but it typically required having a specialist on staff. We realized that if we built the right workflow tool, we could replace that specialist and make it possible for anyone proficient in prompt engineering to successfully build a fine-tuned model.</li></ul>

Companies like Ramp, Notion and Databricks take outputs from frontier models like OpenAI’s GPT-4 and use them to fine-tune smaller, cheaper and faster open source models like Mistral and Llama 3.1, reducing their costs by 90% for specific, repetitive tasks.Fine-tuning platforms like OpenPipe ($6.7M raised), Predibase (Felicis, $28.5M raised) and Airtrain AI (Y Combinator, $3.2M raised) unbundle fine-tuning from the LLMs and rebundle it with MLOps, combining a software development kit (SDK) for collecting prompt-completion pairs with model training, eval, and deployment to launch and rapidly iterate on fine-tuned models.We recognized that fine-tuning could greatly enhance capabilities and reliability, but it typically required having a specialist on staff. We realized that if we built the right workflow tool, we could replace that specialist and make it possible for anyone proficient in prompt engineering to successfully build a fine-tuned model.

Kyle Corbitt, CEO Of OpenPipe, On The Future Of fine-tuning LLMs

United States

Workflow tool for fine-tuning LLMs using production prompts and user feedback

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OpenPipe (OPENPIPE US)

Anthropic Vs. OpenAI

TL;DR: Claude 3.5 Sonnet has Anthropic's API business surging, hitting a Sacra-estimated $664M ARR this year (up 5x this year to date) and...

Sacra

Cerebras At $250M

TL;DR: Sacra estimates that Cerebras generated $250M of revenue in 2023, up 200% year-over-year, their growth accelerating with the rise in AI...

Sacra

Kyle Corbitt, CEO Of OpenPipe, On The Future Of fine-tuning LLMs

Tell us about OpenPipe—what was the key insight that led you to start the company and focus on fine-tuning...

Sacra

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