Sep 27, 2024 · Sep 27, 2024 · Sep 27, 2024
diff --git a/pgml-cms/blog/SUMMARY.md b/pgml-cms/blog/SUMMARY.md
 # Table of contents

 * [Home](README.md)
 * [Meta’s Llama 3.2 Now Available in PostgresML Serverless](meta-llama-3.2-now-available-in-postgresml-serverless.md)
 * [Announcing postgresml-django](announcing-postgresml-django.md)
 * [Sudowrite + PostgresML](sudowrite-postgresml.md)
 * [Korvus x Firecrawl: Rag in a single query](korvus-firecrawl-rag-in-a-single-query.md)
diff --git a/pgml-cms/blog/meta-llama-3.2-now-available-in-postgresml-serverless.md b/pgml-cms/blog/meta-llama-3.2-now-available-in-postgresml-serverless.md
 ---
 description: Bringing smaller, smarter models to your data.
 featured: true
 tags: [product]
 image: ".gitbook/assets/Blog-Image_Llama-3.2.jpg"
 ---

 # Llama 3.2 now available in PostgresML serverless

 <div align="left">

 <figure><img src=".gitbook/assets/image.png" alt="Author" width="100"><figcaption></figcaption></figure>

 </div>

 Cassandra Stummer

 September 27, 2024

 Today, we're excited to announce that PostgresML now supports Llama 3.2, a development that not only enhances our capabilities, but also aligns with our core philosophy: bring the models to your data, not the other way around.

 ## The power of smaller models

 The AI market is finally moving away from the "bigger is better" mentality. Size no longer equals capability. While companies like OpenAI pushed the research frontier with massive models, we're now seeing open-source models 225 times smaller achieving capabilities comparable to GPT-4 at launch. This shift challenges the notion that enormous, closed source models are the only path to advanced AI.

 ## Why Llama 3.2 in PostgresML?

 Companies aiming to run their own models face a critical challenge. Data sources for interactive AI are hard to scale. The amount of context models need is growing: text, vectors, images, user history; find the needles in multiple haystacks, on demand. Gathering and sorting through context from growing data sources becomes the bottleneck in the system.

 As models become smaller and datasets grow larger, the traditional approach of moving data to models becomes increasingly inefficient. That’s why we've always believed that the future of AI lies in bringing models directly to your data. The integration of smaller models like Llama 3.2  into PostgresML is a testament to our vision of the future of AI: Big data and small models colocating to deliver the most efficient, scalable AI infrastructure.

 ## What this means for you

 The Instruct variants, LLama 3.2 1B and 3B, are now standard models included with all Serverless Databases at **no additional cost**. You can try them now.

 ## Getting Started

 Integrating Llama 3.2 with PostgresML is straightforward. Here's a quick example:

 ```postgresql
 SELECT pgml.transform(
  task   => '{
    "task": "text-generation",
    "model": "meta-llama/Llama-3.2-3B-Instruct"
  }'::JSONB,
  inputs  => Array['AI is going to']
 );
 ```

 ## The road ahead

 This is just the beginning. We're committed to continually supporting the latest and greatest models, always with the goal of making AI more efficient, and aligned with your data strategy.

 Ready to experience the power of Llama 3.2 in PostgresML? Get started today or contact our team for a personalized demo.

 Stay tuned for more updates as we continue to push the boundaries of what's possible with AI in databases\!
Original file line number	Diff line number	Diff line change
		@@ -1,6 +1,7 @@
		# Table of contents

		* [Home](README.md)
		* [Meta’s Llama 3.2 Now Available in PostgresML Serverless](meta-llama-3.2-now-available-in-postgresml-serverless.md)
		* [Announcing postgresml-django](announcing-postgresml-django.md)
		* [Sudowrite + PostgresML](sudowrite-postgresml.md)
		* [Korvus x Firecrawl: Rag in a single query](korvus-firecrawl-rag-in-a-single-query.md)
Expand Down
Original file line number	Diff line number	Diff line change
		@@ -0,0 +1,56 @@
		---
		description: Bringing smaller, smarter models to your data.
		featured: true
		tags: [product]
		image: ".gitbook/assets/Blog-Image_Llama-3.2.jpg"
		---

		# Llama 3.2 now available in PostgresML serverless

		<div align="left">

		<figure><img src=".gitbook/assets/image.png" alt="Author" width="100"><figcaption></figcaption></figure>

		</div>

		Cassandra Stummer

		September 27, 2024

		Today, we're excited to announce that PostgresML now supports Llama 3.2, a development that not only enhances our capabilities, but also aligns with our core philosophy: bring the models to your data, not the other way around.

		## The power of smaller models

		The AI market is finally moving away from the "bigger is better" mentality. Size no longer equals capability. While companies like OpenAI pushed the research frontier with massive models, we're now seeing open-source models 225 times smaller achieving capabilities comparable to GPT-4 at launch. This shift challenges the notion that enormous, closed source models are the only path to advanced AI.

		## Why Llama 3.2 in PostgresML?

		Companies aiming to run their own models face a critical challenge. Data sources for interactive AI are hard to scale. The amount of context models need is growing: text, vectors, images, user history; find the needles in multiple haystacks, on demand. Gathering and sorting through context from growing data sources becomes the bottleneck in the system.

		As models become smaller and datasets grow larger, the traditional approach of moving data to models becomes increasingly inefficient. That’s why we've always believed that the future of AI lies in bringing models directly to your data. The integration of smaller models like Llama 3.2 into PostgresML is a testament to our vision of the future of AI: Big data and small models colocating to deliver the most efficient, scalable AI infrastructure.

		## What this means for you

		The Instruct variants, LLama 3.2 1B and 3B, are now standard models included with all Serverless Databases at no additional cost. You can try them now.

		## Getting Started

		Integrating Llama 3.2 with PostgresML is straightforward. Here's a quick example:

		```postgresql
		SELECT pgml.transform(
		task => '{
		"task": "text-generation",
		"model": "meta-llama/Llama-3.2-3B-Instruct"
		}'::JSONB,
		inputs => Array['AI is going to']
		);
		```

		## The road ahead

		This is just the beginning. We're committed to continually supporting the latest and greatest models, always with the goal of making AI more efficient, and aligned with your data strategy.

		Ready to experience the power of Llama 3.2 in PostgresML? Get started today or contact our team for a personalized demo.

		Stay tuned for more updates as we continue to push the boundaries of what's possible with AI in databases\!