获得 3 000万美元资金
瑞士机器人启动发布情报今天宣布它有融资3000万美元种子前资金。
首都由包括世界最著名的人工智能研究者之一Yann LeCun在内的财团提供。 Mistral AI SAS首席执行官Arthur Mensch,Hugging Face Inc.联合创始人托马斯·沃尔夫和几家风险投资公司加入了他。
发布，正式的Eta机器人AG，今年早些时候由CEO曼努埃尔·伊夫斯·加利基尔(Manuel Yves Gallikier)担任发布。 执行官早先曾在机器人创业物理情报公司和1X Technology AS担任工程角色。 发布团队还包括Google DeepMind,Amazon.com Inc.的前员工和其他主要行业角色。
发布正在开发优化控制机器人的AI模型。 这种算法在历史上是针对特定的机器人形态因素定制的。 因此，一个为人造机器人制造动力的模型可能无法可靠地操作独立的机器人臂。 相比之下，Prancing的算法旨在支持广泛的机器人设计。
早期的创业企业经常使用开源模型的定制版本来为其软件提供动力。 最近一份职位公告表明，《立法》正在采取不同的做法。 该公司正在聘请一位具有预训专业知识的AI研究员，这是一个从头开始开发AI模型的术语。 这项任务可能比定制开源模型困难得多。
发布称，它不仅正在开发AI模型，而且正在开发物理机器人组件，最显著的是激活器。 这些是机械子系统，发挥机器人的肌肉作用。 起动器将电动机与控制其运动和某些其他辅助部件的芯片结合。
发动器不仅能产生动能，而且能起到传感器的作用。 称公司，他们“感应力和触摸力”，这大概意味着他们测量机器人在接动物体时施加的压力。
法律并未规定科技如何运作。 然而，更早的尝试制造基于激活器的传感器可能会提供线索。 Google有限责任公司和公开交易的芯片制造商Allegro MicroSystems Inc.都是在这些项目中投资的公司。 两家公司都采用名为Back EMF的方法，将触发器转化为压力传感器。
通过动因器运行电流会导致其内置电动机旋转。 电动机的旋转，反过来，产生第二个电流，流回驱动器。 Back EMF技术测量第二电流或最常用的反电动力，以了解主机系统在做什么。
如果机器人臂的驱动器是活跃的，但不会产生任何反电动力，工程师可以推断，臂部持有重物，其驱动器无法移动。 相比之下，强大的反电动力量的存在表明，助动器正在自由旋转。 这往往意味着机器人手臂没有任何东西。 后EMF传感器也可以收集其他一系列机器人活动的数据。
工作公告显示，颁布计划使用可实地编程的门阵列，或FPGA，为其机器人提供动力。 FPGA是一种芯片，用户可以比中央处理单元或图形卡更广泛地定制。 这使得有可能实现更好的业绩和电力效率。
据报告，颁布将利用其供资回合来雇用更多的工程师并加强其技术。
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Robotics startup Enact Intelligence nabs $30M funding round
Swiss robotics startup Enact Intelligence today announced that it has raised $30 million in pre-seed funding.
The capital was provided by a consortium that included Yann LeCun, one of the world’s most prominent artificial intelligence researchers. He was joined by Mistral AI SAS Chief Executive Arthur Mensch, Hugging Face Inc. co-founder Thomas Wolf and several venture capital firms.
Enact, officially Eta Robotics AG, was launched earlier this year by CEO Manuel Yves Galliker. The executive earlier held engineering roles at robotics startups Physical Intelligence Inc. and 1X Technologies AS. The Enact team also includes former employees of Google DeepMind, Amazon.com Inc. and other major industry players.
Enact is developing AI models optimized to control robots. Such algorithms were historically tailored to specific robot form factors. As a result, a model built to power a humanoid robot may not be capable of reliably operating a standalone robotic arm. Enact’s algorithms, in contrast, are designed to support a wide range of robot designs.
Early-stage startups often use customized versions of open-source models to power their software. A recent job posting indicates that Enact is pursuing a different approach. The company is hiring an AI researcher with expertise in pre-training, a term for developing AI models from scratch. That task can be significantly more difficult than customizing open-source models.
Enact says that it’s developing not only AI models but also physical robot components, most notably actuators. Those are mechanical subsystems that act as a robot’s muscles. An actuator combines an electric motor with a chip that controls its motion and certain other auxiliary parts.
Enact’s actuators not only produce kinetic energy but also act as sensors. The company says that they “sense force and touch,” which presumably means they measure the amount of pressure a robot applies to objects when it picks them up.
Enact didn’t specify how the technology works. However, earlier attempts to build actuator-based sensors may offer clues. Google LLC and publicly traded chipmaker Allegro MicroSystems Inc. are among the companies that have invested in such projects. Both companies used an approach called Back EMF to turn actuators into pressure sensors.
Running a current through an actuator causes its built-in motor to spin. The rotation of that motor, in turn, generates a second current that flows back into the actuator. Back EMF technologies measure that second current, or counter-electromotive force as it’s most commonly known, to understand what the host system is doing.
If a robotic arm’s actuator is active but not generating any counter-electromotive force, engineers can deduce that the arm is holding a heavy item its actuator is unable to move. By contrast, the presence of a strong counter-electromotive force indicates that the actuator is spinning freely. That often means the robot arm isn’t holding anything. Back EMF sensors can also collect data about a range of other robot activities.
A job posting indicates that Enact plans to use field-programmable gate arrays, or FPGAs, to power its robots. An FPGA is a chip that users can customize more extensively than a central processing unit or a graphics card. That makes it possible to achieve better performance and power efficiency.
Enact will reportedly use its funding round to hire more engineers and enhance its technology.
Photo: Unsplash
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