AI Models Built From Rat Brains Just Got Closer to Reality
AI Models Built From Rat Brains Just Got Closer to Reality
基于大鼠脑细胞构建的 AI 模型离现实更近了一步
A biological computing startup that uses neural patterns from rat brain cells to build artificial intelligence just got a major boost from Amazon. Starting Tuesday, select Amazon Web Services customers will gain access to The Biological Computing Company’s “rat brain” AI model as part of a limited preview. The startup’s technology is specifically designed to improve AI for generating videos. Both Amazon and The Biological Computing Company, which goes by the acronym TBC, says they expect the tech to roll out to all AWS enterprise customers soon.
一家利用大鼠脑细胞神经模式构建人工智能的生物计算初创公司刚刚获得了亚马逊的大力支持。从周二开始，部分亚马逊云科技（AWS）客户将作为有限预览的一部分，获得访问 The Biological Computing Company (TBC) “大鼠大脑” AI 模型的权限。该初创公司的技术专门用于改进视频生成 AI。亚马逊和 TBC 公司均表示，预计该技术很快将向所有 AWS 企业客户推出。
“We figured out a way to code information, like images for example, to the biological material,” says TBC cofounder Alexander Ksendzovsky. “We then observe how the biology processes that information, and then we build a tool that mimics that process.”
“我们找到了一种将信息（例如图像）编码到生物材料中的方法，”TBC 联合创始人 Alexander Ksendzovsky 说。“然后我们观察生物体如何处理这些信息，并构建一个模拟该过程的工具。”
This is not the first biologically-derived computing platform that Amazon has made available in its marketplace, says Deap Ubhi, global director of technology for startups at Amazon Web Services. Ubhi says the cloud-computing giant also works with Cortical Labs, an Australia-based company that combines lab-grown neurons with silicon chips to help companies process data. (It calls its products WAAS, or “wetware as a service.”) Cortical Labs also sells a multi-thousand dollar “biological computer,” a low-power device designed for use in laboratories that can supposedly keep neurons alive for six months.
亚马逊云科技初创企业技术全球总监 Deap Ubhi 表示，这并不是亚马逊在其市场上提供的第一个生物衍生计算平台。Ubhi 称，这家云计算巨头还与总部位于澳大利亚的 Cortical Labs 公司合作，该公司将实验室培育的神经元与硅芯片相结合，以帮助企业处理数据。（他们将其产品称为 WAAS，即“湿件即服务”。）Cortical Labs 还销售一种价值数千美元的“生物计算机”，这是一种专为实验室使用而设计的低功耗设备，据称可以让神经元存活六个月。
TBC takes a “pragmatic approach,” says Ubhi, which is part of why the company appealed to Amazon. Rather than taking big swings or trying to reinvent the transformer, the core architectural unit of large language models, “they’re working within existing standards of the generative AI space and saying, ‘How can we make the current visual models more efficient?’” he explains.
Ubhi 说，TBC 采取了一种“务实的方法”，这也是该公司吸引亚马逊的部分原因。他解释说，他们没有进行大规模的冒险，也没有试图重塑大语言模型的核心架构单元 Transformer，而是“在生成式 AI 领域的现有标准内工作，并思考：‘我们如何让当前的视觉模型更高效？’”
As AI companies race to find ways to make their models more efficient, a once-fringe field known as biological computing has begun gaining traction. Researchers have long envisioned a world where computer software performs more like the neural networks inside human brains instead of relying solely on math-based algorithms.
随着 AI 公司竞相寻找提高模型效率的方法，一个曾经处于边缘的领域——生物计算——开始受到关注。研究人员长期以来一直设想这样一个世界：计算机软件的表现更像人脑内部的神经网络，而不是仅仅依赖基于数学的算法。
But biological computing comes with unique challenges. The field requires running actual biology labs, not just computer labs, in which brain cells, stem cells, or synthetic biomaterials must be kept alive or preserved, carefully monitored, and somehow translated into meaningful digital information. While some startups have made progress in the field, bridging the divide between nature and code remains complicated.
但生物计算面临着独特的挑战。该领域需要运营真正的生物实验室，而不仅仅是计算机实验室，其中脑细胞、干细胞或合成生物材料必须保持存活或保存完好，经过仔细监测，并以某种方式转化为有意义的数字信息。虽然一些初创公司在该领域取得了进展，但弥合自然与代码之间的鸿沟仍然很复杂。
The Biological Computing Company was founded in Baltimore, Maryland four years ago by two neuroscientists and neurosurgeons: Ksendzovsky, now the company’s CEO, and Jon Pomeraniec, who serves as president and COO. Earlier this year, TBC raised $25 million from a group of investors led by Primary Venture Partners, its first significant round of funding. Shortly after that round closed in March, the company secured an additional $25 million, bringing its funding total to more than $50 million. This new round of capital has not been previously reported.
The Biological Computing Company 于四年前在马里兰州巴尔的摩成立，由两位神经科学家兼神经外科医生创立：现任公司首席执行官的 Ksendzovsky 和担任总裁兼首席运营官的 Jon Pomeraniec。今年早些时候，TBC 从以 Primary Venture Partners 为首的一组投资者那里筹集了 2500 万美元，这是其第一轮重大融资。在 3 月份该轮融资结束后不久，该公司又获得了 2500 万美元的额外资金，使其融资总额超过 5000 万美元。这轮新的融资此前未被报道过。
Last year, the startup opened offices and a small research and development lab in San Francisco. TBC now has about 35 employees, some of whom work directly with rat brain cells as well as human stem cells in the lab. The living cells are placed on multi-electrode silicon arrays made by 3Brain, a Swiss biotech company. Researchers use the arrays to send electrical stimulation patterns into the neurons and record how they respond. TBC then analyzes that neural activity for computational patterns that can be translated into software and used to improve existing AI models, specifically video generation models.
去年，这家初创公司在旧金山开设了办事处和一个小型研发实验室。TBC 目前拥有约 35 名员工，其中一些人在实验室直接处理大鼠脑细胞和人类干细胞。这些活细胞被放置在由瑞士生物技术公司 3Brain 制造的多电极硅阵列上。研究人员利用这些阵列向神经元发送电刺激模式，并记录它们的反应。随后，TBC 会分析这些神经活动，寻找可以转化为软件并用于改进现有 AI 模型（特别是视频生成模型）的计算模式。
The decision to focus on video out of the gate was both scientific and practical, says Ksendzovsky. One factor was the physical layout of the multi-electrode silicon arrays Biological Computing Company uses. The place where each electrode sits affects how it interacts with the neurons. The company realized images were a natural place to start, since visual information could be mapped onto the grid more readily than text or language. From there, a potential business use case emerged. The startup theorized that by modeling how the neurons process images, the insights could be used to improve AI models for generating video.
Ksendzovsky 说，决定从视频入手既是科学的，也是务实的。一个因素是 TBC 使用的多电极硅阵列的物理布局。每个电极所在的位置会影响它与神经元的交互方式。该公司意识到图像是一个自然的起点，因为视觉信息比文本或语言更容易映射到网格上。由此，一个潜在的商业用例出现了。该初创公司推测，通过模拟神经元处理图像的方式，这些见解可以用于改进视频生成 AI 模型。
Pomeraniec says that Jeff Dean, a prominent AI researcher and TBC investor, was the person who first suggested that the company try fine-tuning video generation models before trying to apply its neural tech more broadly. Because there’s already accepted industry benchmarks for video models, the startup could show early on whether its tech represented a meaningful scientific advancement by testing its performance on problems that have been solved already. “Jeff said if we could do that, there’s the promise of doing more complex, interesting things with our AI models down the line,” Pomeraniec explains.
Pomeraniec 表示，著名 AI 研究员兼 TBC 投资者 Jeff Dean 是第一个建议该公司在尝试更广泛地应用其神经技术之前，先尝试微调视频生成模型的人。由于视频模型已经有了公认的行业基准，该初创公司可以通过在已解决的问题上测试其性能，尽早展示其技术是否代表了有意义的科学进步。“Jeff 说，如果我们能做到这一点，未来就有希望用我们的 AI 模型做更复杂、更有趣的事情，”Pomeraniec 解释道。
Previously, TBC’s technology was only available through a neocloud provider called Bluesky Compute. The startup is claiming that its AI model, when compared against the open-source AI model it runs on, is up to five times faster at video generation and significantly lowers the cost of inference, the processing or “thinking” part of an AI model versus the training of it. (The company won’t say which open-source AI it is using as a comparison, but claims it’s one of the “frontier” video generation models.)
此前，TBC 的技术仅通过一家名为 Bluesky Compute 的新型云服务提供商提供。该初创公司声称，与它所运行的开源 AI 模型相比，其 AI 模型在视频生成速度上快达五倍，并显著降低了推理成本（即 AI 模型处理或“思考”的部分，而非训练部分）。（该公司未透露其使用哪种开源 AI 进行比较，但声称它是“前沿”视频生成模型之一。）
Now that Amazon is distributing TBC’s software, the ambitious startup could potentially reach a much larger customer base. Amazon’s Ubhi says he’s excited about The Biological Computing Company’s potential.
随着亚马逊开始分发 TBC 的软件，这家雄心勃勃的初创公司可能会接触到更庞大的客户群。亚马逊的 Ubhi 表示，他对 The Biological Computing Company 的潜力感到兴奋。