search
HomeTechnology peripheralsAIIs the future direction of AI computing 'water chips”?

The future of neural network computing may be worse than we expected - not solid chips that use electricity, but soaked in water.

Recently, a team composed of the Harvard School of Engineering and Applied Sciences (SEAS) and the startup DNA Script successfully developed a processor based on the movement of ions in an aqueous solution.

Physicists believe that such devices could be the next step in brain-inspired computing because they are closer to the way the brain transmits information.

"Ionic circuits in aqueous solutions use ions as charge carriers for signal processing," the researchers said in the paper. "We propose a water-based ion circuit... This functional ion circuit capable of analog calculations is a step towards more complex water-based ionics."

The research was published in the latest issue of the materials science journal Advanced Materials.

Is the future direction of AI computing water chips”?

##Paper: https://onlinelibrary.wiley.com/doi/epdf/10.1002/adma.202205096

We know that chips in everything from smartphones to cloud servers handle computing tasks by manipulating electrons through solid semiconductors, which is different from the way biology works.

A major part of signal transmission in the brain is the movement of electrically charged molecules called ions in a liquid medium. Although the brain's incredible processing power is difficult to replicate artificially, scientists think computers could use a similar system: carrying ions in a water solution.

This approach will be slower than traditional silicon-based computing because of the changed medium, but it could have some interesting advantages. For example, ions can be produced from a variety of molecules, each with different properties that can be exploited in different ways.

But first, scientists need to show that it actually works.

A team led by Harvard University physicist Woo-Bin Jung has been working in this direction. The first step in building a computer is to design a functional ion transistor, a device that switches or enhances a signal. Their latest advance involves combining hundreds of transistors into an ionic circuit.

The transistor consists of a "bullseye" arrangement of electrodes, with a small disc-shaped electrode in the center and two concentric ring-shaped electrodes surrounding it. This comes into contact with an aqueous solution of quinone molecules. When used, a voltage applied to the central disk generates a hydrogen ion current in the quinone solution. At the same time, two ring electrodes adjust the pH of the solution, thereby increasing or decreasing the ionic current.

Is the future direction of AI computing water chips”?

The chip (left) has an array of hundreds of transistors (right) in the center (middle).

Quinones are a class of organic compounds containing conjugated cyclohexadienedione or cyclohexadienedimethylene structures. Based on this substance The transistor performs the physical multiplication of the weight parameter and the disk voltage set by the ring pair gating, producing the answer to the ionic current.

You may know the concept of "biological computer", which refers to the use of biological Materials to replace the semiconductor chips and storage media currently used in computers are considered to be another major direction for the future of computers in addition to quantum computing. But much previous research has focused on individual ion diodes and transistors, rather than circuits containing many such devices.

Current neural networks that require extremely high computing power rely heavily on matrix multiplication operations, which involve multiple multiplications. So the team designed a 16-by-16 array of transistors, each capable of multiplication, to produce an ionic circuit that could perform matrix multiplication. They are implemented on the surface of and operated by complementary metal-oxide semiconductor (CMOS) electronic chips.

The researchers demonstrated the utility of this array-scale ion circuit by performing physical or simulated multiply-accumulate (MAC) operations. Analog MAC operations based on physical phenomena - In contrast to digital MAC operations based on many digital logic gates and Boolean algebra, new methods bring direction towards reducing the power consumption of artificial neural networks.

Is the future direction of AI computing water chips”?

Schematic diagram of an ion transistor.

Since each crosspoint conductance acts as a network synaptic weight, the input voltage fed into the array rows is multiplied by the weight by Ohm's law and according to the basis Erhoff's law accumulates the resulting current in each column. Therefore, each column current is physically produced as a dot product between the input data vector and the column's synaptic weight vector.

In each ion transistor, the current Iout of the applied voltage Vin is gated by Ig, we can find a region of Vin where Iout = W × Vin, the proportionality constant or weight W can be adjusted by Ig, i.e. the region in which the ion transistor physically multiplies between the weight and the input voltage.

Is the future direction of AI computing water chips”?

Multiply and accumulate operations.

"Matrix multiplication is the most commonly used calculation in artificial intelligence neural networks, and our ionic circuit performs matrix multiplication in water in a completely electrochemical-mechanical simulation. ”, said Woo-Bin Jung.

Of course, this technology currently has significant limitations, including that operations must be performed sequentially rather than simultaneously, which greatly slows down the method.

However, the research team believes that the next step is not to increase the speed, but to introduce a wider range of molecules into the system. So far, the team has used only three or four ionic species, such as hydrogen and quinone ions, to achieve gating and ion transport in aqueous ion transistors. This research attempts to complete more complex ion calculations and let the circuits process more complex information.

The research team pointed out: The ultimate goal of this research is not to use ion technology to compete with or replace electronic products, but to use hybrid technology to complement each other's strengths.

The above is the detailed content of Is the future direction of AI computing 'water chips”?. For more information, please follow other related articles on the PHP Chinese website!

Statement
This article is reproduced at:51CTO.COM. If there is any infringement, please contact admin@php.cn delete
ai合并图层的快捷键是什么ai合并图层的快捷键是什么Jan 07, 2021 am 10:59 AM

ai合并图层的快捷键是“Ctrl+Shift+E”,它的作用是把目前所有处在显示状态的图层合并,在隐藏状态的图层则不作变动。也可以选中要合并的图层,在菜单栏中依次点击“窗口”-“路径查找器”,点击“合并”按钮。

ai橡皮擦擦不掉东西怎么办ai橡皮擦擦不掉东西怎么办Jan 13, 2021 am 10:23 AM

ai橡皮擦擦不掉东西是因为AI是矢量图软件,用橡皮擦不能擦位图的,其解决办法就是用蒙板工具以及钢笔勾好路径再建立蒙板即可实现擦掉东西。

谷歌超强AI超算碾压英伟达A100!TPU v4性能提升10倍,细节首次公开谷歌超强AI超算碾压英伟达A100!TPU v4性能提升10倍,细节首次公开Apr 07, 2023 pm 02:54 PM

虽然谷歌早在2020年,就在自家的数据中心上部署了当时最强的AI芯片——TPU v4。但直到今年的4月4日,谷歌才首次公布了这台AI超算的技术细节。论文地址:https://arxiv.org/abs/2304.01433相比于TPU v3,TPU v4的性能要高出2.1倍,而在整合4096个芯片之后,超算的性能更是提升了10倍。另外,谷歌还声称,自家芯片要比英伟达A100更快、更节能。与A100对打,速度快1.7倍论文中,谷歌表示,对于规模相当的系统,TPU v4可以提供比英伟达A100强1.

ai可以转成psd格式吗ai可以转成psd格式吗Feb 22, 2023 pm 05:56 PM

ai可以转成psd格式。转换方法:1、打开Adobe Illustrator软件,依次点击顶部菜单栏的“文件”-“打开”,选择所需的ai文件;2、点击右侧功能面板中的“图层”,点击三杠图标,在弹出的选项中选择“释放到图层(顺序)”;3、依次点击顶部菜单栏的“文件”-“导出”-“导出为”;4、在弹出的“导出”对话框中,将“保存类型”设置为“PSD格式”,点击“导出”即可;

GPT-4的研究路径没有前途?Yann LeCun给自回归判了死刑GPT-4的研究路径没有前途?Yann LeCun给自回归判了死刑Apr 04, 2023 am 11:55 AM

Yann LeCun 这个观点的确有些大胆。 「从现在起 5 年内,没有哪个头脑正常的人会使用自回归模型。」最近,图灵奖得主 Yann LeCun 给一场辩论做了个特别的开场。而他口中的自回归,正是当前爆红的 GPT 家族模型所依赖的学习范式。当然,被 Yann LeCun 指出问题的不只是自回归模型。在他看来,当前整个的机器学习领域都面临巨大挑战。这场辩论的主题为「Do large language models need sensory grounding for meaning and u

ai顶部属性栏不见了怎么办ai顶部属性栏不见了怎么办Feb 22, 2023 pm 05:27 PM

ai顶部属性栏不见了的解决办法:1、开启Ai新建画布,进入绘图页面;2、在Ai顶部菜单栏中点击“窗口”;3、在系统弹出的窗口菜单页面中点击“控制”,然后开启“控制”窗口即可显示出属性栏。

强化学习再登Nature封面,自动驾驶安全验证新范式大幅减少测试里程强化学习再登Nature封面,自动驾驶安全验证新范式大幅减少测试里程Mar 31, 2023 pm 10:38 PM

引入密集强化学习,用 AI 验证 AI。 自动驾驶汽车 (AV) 技术的快速发展,使得我们正处于交通革命的风口浪尖,其规模是自一个世纪前汽车问世以来从未见过的。自动驾驶技术具有显着提高交通安全性、机动性和可持续性的潜力,因此引起了工业界、政府机构、专业组织和学术机构的共同关注。过去 20 年里,自动驾驶汽车的发展取得了长足的进步,尤其是随着深度学习的出现更是如此。到 2015 年,开始有公司宣布他们将在 2020 之前量产 AV。不过到目前为止,并且没有 level 4 级别的 AV 可以在市场

ai移动不了东西了怎么办ai移动不了东西了怎么办Mar 07, 2023 am 10:03 AM

ai移动不了东西的解决办法:1、打开ai软件,打开空白文档;2、选择矩形工具,在文档中绘制矩形;3、点击选择工具,移动文档中的矩形;4、点击图层按钮,弹出图层面板对话框,解锁图层;5、点击选择工具,移动矩形即可。

See all articles

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

AI Hentai Generator

AI Hentai Generator

Generate AI Hentai for free.

Hot Tools

SublimeText3 Chinese version

SublimeText3 Chinese version

Chinese version, very easy to use

WebStorm Mac version

WebStorm Mac version

Useful JavaScript development tools

Zend Studio 13.0.1

Zend Studio 13.0.1

Powerful PHP integrated development environment

SublimeText3 Linux new version

SublimeText3 Linux new version

SublimeText3 Linux latest version

Safe Exam Browser

Safe Exam Browser

Safe Exam Browser is a secure browser environment for taking online exams securely. This software turns any computer into a secure workstation. It controls access to any utility and prevents students from using unauthorized resources.