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Chinese team develops intelligent vision sensor that turns light signals into AI-ready tokens, reducing use of energy_我的网站

A |     新安江上桨板热“想不到新安江还有这么一个地方！”“江浙沪玩水被这里拿捏了！”“夏天到新安江去划桨板！”气温直逼40℃，17℃建德新安江桨板这段时间成了社交平台上的清凉“爆款”，上海、杭州、安徽等长三角游客纷至沓来，一跃成为建德最热门的打卡项目。“平时数百人甚至上千人，尤其一到周末，这段约2公里的路，源源不断的车流会从紫金家园一路堵到新安江电厂门口。    

    The new ultra-low-power intelligent vision sensor chip "LightTok" developed by a research team from Nanjing University. Photo: from Science and Technology Daily
A Chinese research team from Nanjing University has developed a new ultra-low-power intelligent vision sensor chip, dubbed "LightTok," that can convert light signals into tokens within the sensor, significantly reducing the high energy consumption caused by frequent transfers of massive amounts of redundant data, the principal investigator told the Global Times.
According to a release from the Institute of Brain-Inspired Intelligence of Nanjing University, tokens generated by the LightTok chip can be directly fed into a Transformer encoder for image recognition.
"Our design idea was to move token generation onto the sensor itself, allowing the chip to directly produce tokens that AI models can process once light reaches the sensor," Miao Feng, director of the Institute of Brain-Inspired Intelligence at Nanjing University, told the Global Times on Thursday. "These tokens contain complete image information."
Physical AI refers to intelligent systems capable of autonomously perceiving, reasoning, acting and receiving feedback in the real world, representing a key pathway for AI to move from the digital realm into the physical world. Vision-based physical AI systems powered by large AI models need to convert visual information from real-world environments into tokens that can be processed by AI models before feeding these tokens into Transformers for subsequent tasks.
In traditional visual perception pipelines, light signals must go through multiple stages, including image sensing, analog-to-digital conversion, data buffering and transfer, digital image patching and embedding, before being transformed into tokens that AI models can process. The frequent transfer of massive amounts of redundant data has resulted in high energy consumption at the edge, according to a report by Science and Technology Daily.
The LightTok chip directly addresses a key challenge in physical AI hardware: how to efficiently acquire and tokenize visual information from the physical world with low energy consumption, Miao said.
The LightTok chip consists of a photosensitive memory array and peripheral circuits. The team built the array based on single-layer molybdenum disulfide (MoS₂) floating-gate phototransistors, with each pixel capable of sensing light, storing information and performing analog computing. By processing optical information directly within the chip, the device can convert captured visual signals into tokens for AI models, according to the research team.
The current LightTok prototype has a resolution of 32×32 pixels, or 1,024 photosensitive pixels, which is still smaller than that of smartphone cameras and industrial imaging systems. However, Miao said the technology is compatible with CMOS manufacturing processes and can be scaled up. With wafer-level growth of molybdenum disulfide materials, the chip could potentially achieve a scale comparable to existing imaging devices.
Miao said the chip also draws inspiration from the information-processing mechanism of human vision. Similar to how the retina extracts key visual information before transmitting it to the brain, the chip also aims to process visual information at an early stage. 
The research was conducted in collaboration with another research team from the National University of Singapore. The findings were published on Wednesday in Nature Sensors, an internationally renowned journal in the field of sensing technology, according to the release.
Potential applications for LightTok include drone systems, autonomous remote sensing and small-scale embodied AI systems, Miao said. In these scenarios, devices need to continuously detect, understand and track targets, generating massive amounts of visual data. By reducing the energy required for visual processing, the technology could extend the operating time of drones, satellites and small robots with limited power supplies, the expert said.    
。”建德市冬泳协会会长高宗训说。这项小众的水上运动，为何偏偏在建德火出了圈？工作日的新安江上也“堵板”了前天下午2点多，我们从杭城出发，导航到“建德新安绿道夏日冬泳基地”，车程大约2小时。到了建德城区，沿着新电路一路向上游开，车速渐渐慢了起来。好不容易找到停车位，还没走到岸边，人声已先于江风扑面而来。工作日的下午4点，江面已是“板满为患”：从高空俯瞰，江面上密密麻麻铺满了桨板，五颜六色，星罗棋布，像是夏日里撒在碧绿绸缎上的一把彩色糖果。

B | 超百块桨板在江面上缓缓滑行、交错穿梭： 有人平衡性好，在板上站得笔直，身体随桨频自然摆动，划起来如履平地，颇有几分“水上漂”的潇洒；家长带娃大多是盘腿坐在板上，优哉游哉地任江水推着走；还有一人一板慢慢划的，享受难得的独处时刻。划累了就坐在桨板上，任其在水面滑行。

C | 这片静水水域，没有固定的滑道，却自有一种松弛，大家各划各的、各乐各的，互不打扰，又共享着同一片清凉。

D | 岸边是安全员来回巡逻，橙色救生衣在阳光下很是醒目。今年刚大学毕业的小张，特地带着朋友从金华开车2小时赶来。“在抖音上刷到视频，没想到工作日人也这么多。”小张甩了甩头发，忙着往岸上走，“划起来还是很简单的，就是水有点冰，又爽又刺激”。“我们隔三差五就来，电瓶车几分钟。

E | ”家住新安江边的沈先生，带着二年级的儿子一口气滑了1个多小时，“泡在水里，比空调房舒服”。一对从南京自驾来的情侣正在岸边整理装备。女孩小周说，她也是小红书上刷到了桨板的视频，被那种“江雾缭绕、人在画中划”的画面击中了。两人开了4个多小时车，上午刚到，下午就直接下水了。“水很凉，划起来一点都不热，而且真的超出片，我刚才随手拍了几张，都不用修图。

F | ”下午5点，夕阳洒落，江面上波光粼粼，17℃新安江水更是带来了阵阵凉风。江面上百舸争流，岸边是另一个沸腾现场：租桨板的摊位前排起小长队，店家拎着打气筒“哼哧哼哧”地给桨板充气；卖冷饮、烤肠、西瓜的小吃车一字排开，草坪上、石阶上、树荫下坐满了歇脚的人……17℃新安江上划桨板为什么会火？现代桨板，学名SUP，全称是“Stand-Up Paddling”，也称立式单桨冲浪。这项运动的源头，要追溯到上世纪60年代的夏威夷。最初是由冲浪教练为了更好地观察学员和涌浪情况，直立站在冲浪板上并使用单面桨进行操作。随着时代的发展，桨板冲浪逐渐成为一种独立的水上运动，其特点是不受束缚的玩法，参与者可以根据自己的喜好选择站立、坐着、趴着或躺着的姿势进行划行。北京亮马河、天津海河、上海苏州河、杭州西溪……各大城市的平缓水域，都能见到桨板爱好者的身影。但为什么偏偏是建德新安江成为夏日顶流？80后桨板爱好者张振华，江湖人称“张大爷”，他从2022年开始自学桨板，是建德桨板运动圈名副其实的“第一人”，参加过大大小小数十场比赛，最好成绩拿过宁波公开赛的前六名。家门口的新安江，是张振华主要的训练场。在他的印象里，这股桨板热，是从去年夏天开始的，到了今年夏天，人数更是迎来爆发式的增长。

G | “桨板其实是冲浪的延伸，如果按照比赛要求，是要站起来划的，但是对于游客体验来说，在宽大的休闲板上坐着或者跪着划，非常容易上手。”在他看来，桨板对新手十分友好，属于“有手就会”的休闲运动。

H | 其次便是全国独一份的清凉。新安江江水，来自千岛湖的70米深层，常年保持14℃至17℃恒温，哪怕烈日当头，只要把脚浸到江水里，一秒就能驱散暑热。“对于年轻人来说，能不能带来情绪价值，美美‘出片’也很重要。”本地桨板爱好者沈菲说，新安江两岸的绿水青山、“水上仙境”般的新安奇雾、美轮美奂的日出日落，在桨板上带来的是独一无二的松弛体验。

I | 去年夏天，她随手在小红书发了一组照片，到现在还有人私信：“这是在哪里，怎么玩？桨板怎么租？”她将这个商机告诉了弟弟沈平，抢先做起了桨板租赁生意。光是微信，沈平一个夏天就加了近2000人，高峰期近三十块桨板全部满租，供不应求。“上海、江苏、杭州……有的凌晨三四点就开车过来了，我也不得不越起越早。

J | ”沈平说。

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