Dream Labs raises $90M seed for robot foundation model API
The startup secured funding led by B Capital and Kindred Ventures for its Dream-1 model trained on human video data.
Key points
- Dream Labs raised $90 million in seed funding.
- B Capital and Kindred Ventures led the investment round.
- The company offers an API for the Dream-1 robot foundation model.
Dream Labs has secured $90 million in seed funding, according to a report by Forbes. The investment round was led by B Capital and Kindred Ventures. The startup offers an API for its Dream-1 robot foundation model, which is trained on human videos.
The Dream-1 model is a robot foundation model trained on human videos. Dream Labs provides access to this model through an API. Forbes reported that the cost to use this service is $3 an hour. The report also noted that the voice experience associated with the announcement is generated by AI.
Context and Background
The funding announcement comes from a report by Forbes, which cited John Koetsier. The headline for the report asks if users want to make their "dumb robot smart." The article states that $3 an hour is all it costs to achieve this through Dream Labs' services. The source material does not provide further details on the technical architecture or specific training methodologies beyond the use of human videos.
Who is Affected
The primary subject of the report is Dream Labs and its new funding. The investors involved are B Capital and Kindred Ventures. The service targets users who want to enhance robot capabilities using the Dream-1 model. The source material does not specify other affected parties, competitors, or broader industry impacts beyond the startup and its investors.
What should you do?
Security and technology professionals should monitor the deployment of AI-driven robotics in their environments. As these systems become more autonomous, understanding the data sources and training methods is crucial for risk assessment. Organizations should evaluate how third-party APIs integrate with their internal networks and robotic hardware to ensure secure communication channels.
What to do and how to stay safe: Dream Labs
- Review access controls for any APIs that control physical hardware or robotic systems.
- Audit the data sources used by third-party AI models to ensure compliance with privacy policies.
- Monitor network traffic between robotic devices and external AI services for anomalies.
- Establish clear incident response procedures for potential AI model failures or manipulations.
Step-by-step guide: Prompt Injection Warning Signs: How to Spot AI Manipulation
General security guidance from the Threat Times newsroom. It is not confirmed advice from the organisations named in this story.
Frequently asked questions
How much funding did Dream Labs raise?
Dream Labs raised $90 million in seed funding according to the Forbes report.
Who led the investment round for Dream Labs?
The seed funding round was led by B Capital and Kindred Ventures.
What is the Dream-1 model trained on?
The Dream-1 robot foundation model is trained on human video data.
