Apple’s Ferret Multimodal LLM Getting New Attention
Back in October, a team of researchers from Apple and Columbia University subtly released its own large language model named Ferret, an open-source multimodal LLM, at the time of its release it was available for research purposes with no commercial license option.
According to VentureBeat, the release garnered little attention but with the release of Google’s Gemini model which is expected to be coming to its Pixel Pro and Android, this has refocused attention on Ferret and what it can do the iPhones.
That’s because the company recently released two new research papers that introduced new techniques for efficient language model interfaces and 3d avatars. As one could imagine, these advancements have the potential to help enable a more immersive experience for users while allowing for complex AI systems to run on small consumer devices.
The new attention to Apple’s LLM ramped up before the Christmas holiday as Bart de Witte, head of a European non-profit that is focused on open-source AI in medicine took to X (formally Twitter) to express his excitement at Ferret’s poetical impact in the AI ecosystem.
So what does Ferret exactly do? Well according to Miz Causevic’s Medium post on the LLM, it is “uniquely capable of interpreting both images and text, and allowing for detailed queries within specific areas of an image.”
Making this model open source is also an interesting move by the tech giant. This is because Apple has been known for years as its own enclosure when it comes to research and the tech that runs its products. It has also been reported that the company was far behind Google in terms of generative AI.
So by allowing the LLM to become open source, it could signal that the company hopes to navigate potential ethical concerns with care while at the same time ensuring specific business goals for the company aren’t harmed.
All of this comes as both OpenAI and Anthropic are hoping to supercharge funding for their respective companies going into 2024. With Apple’s quiet arrival onto the large language model scene, it will be interesting to see how they will affect the landscape and how rivals move forward.
Originally posted on OpenDataScience.com
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