Meta Introduces a Big New AI Model for the Agentic Age


Meta on Thursday announced the next version of its multimodal Spark AI model, Muse Spark 1.1, calling it a significant upgrade from its predecessor. The model is built specifically for agentic tasks and has promises major gains in areas such as computer use, coding and multimodal understanding.

Spark 1.1 follows the launch of Muse Image, its new image-generation tool, which already has some Instagram users opting out. (You can learn how to do that here.)

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With the likes of OpenAI and Anthropic storming headlines with new and advanced AI models, Meta’s announcement is a sign that the company is jumping back into the AI race after lagging behind for more than a year and undergoing extensive reorganization. The model was released by what Meta calls its Superintelligence Labs, an outfit led by former Scale AI CEO Alexandr Wang. 

Meta also launched a public preview of its Meta Model API, in which the new Spark 1.1 will be accessible to developers. The model is now available in the “Thinking” mode within the Meta AI app and on meta.ai.

Enhanced agentic capabilities

Meta says that Spark 1.1 can complete complex projects significantly faster than its predecessor. It’s trained to “orchestrate multiagent systems to optimize end-to-end latency,” according to the company’s blog post. Agentic AI refers to models that can take actual actions on your behalf, rather than just providing answers to a prompt.

This multiagent system features a main agent and subagents. The main agent will make a plan and delegate its execution across parallel subagents. Those subagents will stick to their assigned tasks, use available tools and escalate back to the main agent when necessary. 

Spark 1.1 also actively manages its 1-million-token context window by remembering actions, retrieving information from earlier work and compacting context in a way that keeps the important steps needed for later, according to the blog. That means you should be able to ask it to do more complicated tasks without running into the limits of how much the model can handle at once.

Computer use and coding

The new model might also be able to take control of your computer for certain tasks, if that’s something you’re willing to give a try. 

Meta says its new AI model has received a boost in its computer use workflows across multiple applications. It can maintain context across long sessions and can navigate unfamiliar interfaces with minimal interaction from the user. It can understand when to automate certain tasks and when to navigate through the computer manually. 

On the coding front, Spark 1.1 promises significant improvements, particularly in tasks involving complex databases. It can diagnose and fix bugs, add new features in enterprise-grade systems and perform large code migrations. 

Truly multimodal

Spark 1.1’s multimodal capabilities allow it to see and hear to complete tasks. This isn’t unlike existing AI models we’ve seen today, like Gemini Live’s camera experience. It can ingest imagery and audio, and provide “ultra-descriptive” captions from the sources. Combining this with its agentic computer use abilities, it can interpret what’s on the screen and take action to perform tasks. 

Safety

Meta is touting its extensive safety evaluations for the model, which follows the Advanced AI Scaling Framework. The model is said to show a strong resistance to jailbreaks, prompt injection and other common attacks. 





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NotebookLM is one of the most interesting AI tools out there, with little competition to speak of. While it can be used by anyone, Google’s put a large focus on tools students can take advantage of, and it may receive a new feature to make it even more powerful for those looking to learn. 

The Gemini-powered AI research assistant tool is different because it only uses the sources you provide it with as its data. Compare this to something like the standard Gemini AI chatbot, which will scour the entire internet to find an answer to your question — and the internet is full of conflicting information. If your sources don’t have the answer, NotebookLM won’t attempt to make one up for you. 

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According to a Threads post from AI-focused tech site Testing Catalog on Wednesday, NotebookLM may get a new source that you can add: Textbooks. If and when it arrives, this could open up an entire world of ways students can use the tool as a study buddy. 

Textbooks will join a growing number of source options for NotebookLM. You can already add files, websites, audio clips, Google Play Books and more. Now, adding in an academic textbook for a test you need to cram for? That sounds like a win for all students. 

Testing Catalog shared a screenshot that shows textbooks as an option to be a source, but little else is known about what it truly entails. Given that you could essentially scan the pages of any book and add them as a source, it seems that there may be some sort of partnership in play here. 

Last year, Google partnered with OpenStax, a provider of free, peer-reviewed textbooks, when it introduced Public Notebooks. Whether the new source option is limited to OpenStax textbooks or if there’s another partnership in the works remains to be seen. 

Google did not immediately respond to a request for comment. 





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