双语新闻：美国科学家用实验室培养的脑组织创造了“生物计算机”

American researchers have combined lab-grown human brain tissue with computer hardware to create a working biocomputer.

美国研究人员将实验室培养的人脑组织与计算机硬件相结合，创造了一台可工作的生物计算机。

The scientists say brain cells used in the experiment were able to recognize speech and complete simple math problems.

科学家表示，实验中使用的脑细胞能够识别语音并完成简单的数学问题。

The team made brain-like tissue that took the form of what they called a "brain organoid." Harvard University's Stem Cell Institute explains that an organoid is a collection of individualized, complex cells that can be grown from stem cells in a lab.

该团队制造了类似大脑的组织，他们称之为“类大脑器官”。哈佛大学干细胞研究所解释说，类器官是一组个性化的复杂细胞，可以在实验室中从干细胞中培养出来。

Under the right laboratory conditions, organoids can be made to look and even work similarly to real human tissue and organs. In this process, stem cells "can follow their own genetic instructions to self-organize," the Stem Cell Institute says.

在适当的实验室条件下，类器官可以被制成与真正的人体组织和器官相似的外观甚至工作原理。干细胞研究所说，在这个过程中，干细胞“可以按照自己的遗传指令进行自我组织”。

So far, scientists have been able to produce organoids that look like, or resemble, some organs. These organs include the brain, kidney, lung, stomach and liver. Such lab-created organoids are generally used to study how organs work without needing to experiment on actual organs.

到目前为止，科学家们已经能够制造出看起来像或类似某些器官的类器官。这些器官包括脑、肾、肺、胃和肝。这种实验室制造的类器官通常用于研究器官如何工作，而无需在实际器官上进行实验。

In the biocomputer experiment, the team said stem cells were able to form neurons similar to those found in the human brain. Neurons are electrically charged cells that transport signals to the brain and other parts of the body.

在生物计算机实验中，研究小组表示，干细胞能够形成类似于人类大脑中发现的神经元。神经元是一种带电细胞，负责向大脑和身体其他部位传递信号。

Feng Guo led the experiment. He is a bioengineer and professor of Intelligent System Engineering at Indiana University Bloomington. His team recently published their research results in a study in Nature Electronics.

冯国领导了这项实验。他是印第安纳大学布卢明顿分校的生物工程师和智能系统工程教授。他的团队最近在《自然电子》杂志上发表了他们的研究结果。

The researchers attached the brain organoid to a set of traditional electronic computing circuits. The researchers call this system Brainoware. The system was used to establish communication between the organoid and electronic circuits. An artificial intelligence (AI) tool was used to help read the neural activity of the organoid.

研究人员将大脑类器官连接到一组传统的电子计算电路上。研究人员称这个系统为“大脑意识”。该系统被用来建立类器官和电子电路之间的通信。人工智能(AI)工具被用来帮助读取类器官的神经活动。

The scientists aim to build "a bridge between AI and organoids," Guo explained to Nature. Guo believes that combining organoids and computer circuits could provide additional speed and energy to improve the performance of AI computing systems.

郭向《自然》杂志解释说，科学家们的目标是在“人工智能和类器官之间架起一座桥梁”。郭认为，将类器官和计算机电路结合起来可以提供额外的速度和能量，以提高人工智能计算系统的性能。

The study notes that adding human brain power might be able to help machines with the things they do not do as well as people. For example, the researchers said humans generally have a faster learning ability and use less energy thinking than computers do.

该研究指出，增加人类的脑力可能会帮助机器做一些它们做得不如人好的事情。例如，研究人员表示，与计算机相比，人类通常具有更快的学习能力，并且使用更少的精力进行思考。

During one part of the experiment, the team tested the Brainoware system's voice recognition ability. The team trained the system on 240 recordings of eight different voices. The researchers said the organoid produced different neural signals in reaction to the different voices. The accuracy level of the system reached 78 percent, Guo said.

在实验的一部分，研究小组测试了brainware系统的语音识别能力。该团队用8种不同声音的240段录音对该系统进行了训练。研究人员表示，这种类器官会对不同的声音产生不同的神经信号。郭说，该系统的准确率达到了78%。

"This is the first demonstration of using brain organoids [for computing]," Guo told MIT Technology Review. He added, "It's exciting to see the possibilities of organoids for biocomputing in the future."

“这是使用脑类器官(用于计算)的首次演示，”郭告诉《麻省理工科技评论》。他补充说:“看到类器官在未来用于生物计算的可能性是令人兴奋的。”

Guo said these results persuaded his team that a brain-computer system can work to improve computing performance, especially for some AI jobs. But he noted the best accuracy rates recorded by the Brainoware system were still below the accuracy rates of traditional AI networks. Guo said this is one of the things his team plans to try to improve.

郭说，这些结果说服了他的团队，脑机系统可以提高计算性能，特别是对于一些人工智能工作。但他指出，Brainoware系统记录的最佳准确率仍低于传统人工智能网络的准确率。郭说，这是他的团队计划尝试改进的事情之一。

Lena Smirnova is a developmental neuroscientist at Johns Hopkins University in Baltimore, Maryland. She told Nature that more research will be needed to improve such systems. But she said, "The study confirms some key theoretical ideas that could eventually make a biological computer possible."

莉娜·斯米尔诺娃是马里兰州巴尔的摩市约翰·霍普金斯大学的发育神经科学家。她告诉《自然》杂志，需要更多的研究来改进这些系统。但她说，“这项研究证实了一些关键的理论观点，这些观点最终可能使生物计算机成为可能。”

Smirnova noted that in earlier experiments, researchers have used other kinds of neuron cells to perform similar computational activities. But the latest study, she said, was the first to demonstrate this kind of performance in a brain organoid.

斯米尔诺娃指出，在早期的实验中，研究人员已经使用其他种类的神经元细胞来执行类似的计算活动。但她说，最新的研究是第一次在脑类器官中证明了这种表现。