Memories AIがウェアラブルとロボティクスのための視覚的記憶層を構築中

Shawn Shen believes that AI will need to remember what it sees in order to succeed in the physical world. Shen’s company Memories.ai is using Nvidia AI tools to build the infrastructure for wearables and robotics to be able to remember and recall visual memories.

Memories.ai announced a collaboration with semiconductor giant Nvidia at its GTC conference on Monday. Through this partnership, Memories.ai uses Nvidia’s Cosmos-Reason 2, a reasoning vision language model, and Nvidia Metropolis, a reference architecture for video search and summarization, to continue to develop its visual memory technology.

Shen (pictured above left) told TechCrunch that he and his co-founder and CTO, Ben Zhou (pictured above right), got the idea for the company while building the AI system behind Meta’s Ray-Ban glasses. Building the AI glasses got them thinking about how people would actually use the tech in real life if users couldn’t recall the video data they were recording.

They looked around to see if they could find anyone already building that type of visual memory solution for AI. When they couldn’t, they decided to spin out of Meta and build it themselves.

“AI is already doing really well in the digital world. What about the physical world?” Shen said. “AI wearables, robotics need memories as well. … Ultimately, you need AI to have visual memories. We believe in that future.”

The ability for AI systems to remember, in general, is relatively new. OpenAI updated ChatGPT to start to remember past chats in 2024 and fine-tuned that feature in 2025. Elon Musk’s xAI and Google Gemini have also launched their own memory tools in the past two years.

But these advancements have largely focused on text-based memory, Shen said. Text-based memory is much more structured and easier to index but isn’t as helpful for physical AI applications that largely interact with the world through sight and visuals.

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Memories.ai was launched in 2024 and has raised $16 million thus far, through an $8 million seed round in July 2025 and an $8 million extension. The round was led by Susa Ventures and included Seedcamp, Fusion Fund, and Crane Venture Partners, among others.

Shen said successfully building this visual memory layer required two things: building the infrastructure needed to embed and index videos into a data format that can be stored and recalled, and capturing the data needed to train the model to do just that.

The company launched its large visual memory model (LVMM) in July 2025. Shen said it could be compared to a smaller version of Gemini Embedding 2, a multimodal indexing and retrieving model, that was released earlier this month.

For data collection, the company created LUCI, a hardware device worn by the company’s “data collectors” that records video used to train the model. Shen said they don’t plan to become a hardware company, nor sell these devices, but, rather, that they built their own because they weren’t satisfied with off-the-shelf video recorders that focused on high-definition and battery-eating video formats.

The company released the second generation of this LVMM and signed a partnership with Qualcomm to run on Qualcomm’s processors starting later this year.

Memories.ai is also working with some of the large wearable companies already, Shen said, but declined to disclose which ones. Despite some demand now, Shen sees even bigger opportunities in wearables and robotics yet to come.

“In terms of commercialization, we are more focused on the model and the infrastructure, because ultimately we think the wearables and robotics market will come, but it’s probably just not now,” Shen said.

Becca is a senior writer at TechCrunch that covers venture capital trends and startups. She previously covered the same beat for Forbes and the Venture Capital Journal.

You can contact or verify outreach from Becca by emailing rebecca.szkutak@techcrunch.com.

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