© Figure
We knew that the startup Figure was preparing something important by relying on the power of OpenAI's large language models. Its first demo of its humanoid robot Figure 01 is sure to impress. Not that like Boston Dynamics, the robot knows how to do somersaults and other acrobatic figures – we don't even see him walking here.
Figure 01 is in itself a very advanced technical platform, as the firm shows in other videos. But as you will see in the video that we included at the end of the article, the robot is above all impressive in its ability to take advantage of OpenAI's most advanced APIs. To better build an incredible interaction of humanity.
In the demo in question, we see Figure 01 behind a table with some plates, glasses and an apple in front of him. He describes in English in the voice of a man of a certain age, very natural, what he sees in front of him: “ ;I see a red apple on a plate in the center of the table.
The experimenter then asks the robot “can I have something to eat ?”. The robot executes, before explaining why, precisely, it has just carried out the last action: “so, I'll tell you I gave you an apple, because it's the only, uh, edible thing on this table that I could give you.
With this little detail so human, the little hesitation in the middle of a sentence. Of course, for the moment it is, as we told you, only a demo. The precise development schedule for Figure 01, or its effective marketing date, remains a mystery for the moment.
The firm, which foresees applications of its robot in various fields such as warehouses or personal service has already broadly revealed the technical sheet of the final robot. With a height of 1.68 m and a weight of 60 kg, he will weigh as much as a human being with an ideal BMI score.
It will be able to transport loads of up to 20 kg, all with a top speed of 1.2 meters per second and an autonomy of 5 hours. The whole thing will obviously be electric. The implementation of OpenAI APIs is the result of close collaboration, which partly explains the result shown in Figure in the video below:
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