Osmo 希望透過 AI 重塑嗅覺視覺的未來

人工智慧公司 Osmo 正在努力工作，以帶回 1960 年 Hans Laube 向世界介紹「Smell-O-Vision」時所承諾的未來。

Artificial intelligence firm Osmo is working hard to bring back the future we were promised in 1960 when Hans Laube introduced the world to “Smell-O-Vision.” Only this time, the goal is to improve the lives of humans everywhere by teaching computers how to interpret scent.

人工智慧公司 Osmo 正在努力實現 1960 年 Hans Laube 向世界推出「Smell-O-Vision」時所承諾的未來。只是這一次，我們的目標是透過教導電腦如何解讀氣味來改善世界各地人類的生活。

Osmo's technology is a complex, multidisciplinary amalgamation of science and engineering at the cutting edge, but its purpose is simple. The company wants to build generative AI that can do for scents what OpenAI’s ChatGPT and Google’s Gemini can do for sounds and images.

Osmo 的技術是複雜的、多學科的前沿科學與工程的融合，但其目的很簡單。該公司希望建立生成式人工智慧，能夠像 OpenAI 的 ChatGPT 和Google的 Gemini 處理聲音和影像一樣處理氣味。

Per the company’s website:

根據該公司的網站：

AI that can smell

能聞氣味的人工智慧

Teaching a computer to smell live odors isn’t as simple as giving it sight or sound. Microphones and cameras have existed for decades and the data they produce can be interpreted by a computer the same as any other input.

教導電腦聞氣味並不像讓它看到或聽到聲音那麼簡單。麥克風和攝影機已經存在了幾十年，它們產生的數據可以像任何其他輸入一樣由電腦解釋。

But there’s no instrumental analogous to what the microphone is for the human ear. We have technologies such as breathalyzers that can analyze the chemical content of certain gases. These are used for purposes such as testing a person’s breath for the presence of ethanol in order to determine their blood alcohol level.

但沒有一種樂器可以與麥克風對人耳的作用相似。我們擁有呼吸分析儀等技術，可以分析某些氣體的化學含量。這些用於測試人們的呼吸中是否存在乙醇等目的，以確定他們的血液酒精含量。

However, these sensory devices have to be fine-tuned to detect a specific set of molecules. Even if a sensor could detect a spectrum of ambient molecules, a computer by itself wouldn’t be capable of classifying and identifying them without assistance from generative AI.

然而，這些感測裝置必須進行微調才能檢測一組特定的分子。即使感測器可以偵測到一系列環境分子，如果沒有產生人工智慧的幫助，電腦本身也無法對它們進行分類和識別。

According to Osmo, that’s where AI comes in. Getting computers to smell involves the seemingly simple task of identifying which molecules are associated with which types of aromas and then training an AI to recognize and identify specific patterns.

根據 Osmo 的說法，這就是人工智慧的用武之地。

It sounds easy enough, but it turns out that there’s no “smell map” for an AI to study. And inventing a dataset containing labeled examples of molecular bond associations from scratch turned out to be a monumental task.

這聽起來很簡單，但事實證明，沒有可供人工智慧研究的「氣味圖」。從頭開始發明一個包含分子鍵關聯標記範例的資料集是一項艱鉅的任務。

Osmo CEO and co-founder Alex Wiltschko, a former Google engineer, told CNBC that the entire detection and identification process required incredible precision.

Osmo 執行長兼聯合創始人、前Google工程師 Alex Wiltschko 告訴 CNBC，整個檢測和識別過程需要令人難以置信的精確度。

“The molecules that carry an odor are present in the air at parts per billion,” said Wiltschko. “The AI has to learn to detect these molecules among millions of others in the background and identify them correctly within milliseconds. It's like finding a needle in a dense and ever-changing haystack.”

「帶有氣味的分子在空氣中的含量為十億分之一，」威爾奇科說。 「人工智慧必須學會在後台數百萬個其他分子中檢測這些分子，並在幾毫秒內正確識別它們。這就像在密集且不斷變化的大海撈針中尋找一根針。

Helping humanity

幫助人類

On the surface, the reemergence of Smell-O-Vision may not sound important. But the company hopes to build a system capable of superhuman feats of smell. These would include the ability to smell the presence of certain diseases such as cancer or symptoms associated with diabetes such as low blood sugar.

從表面上看，Smell-O-Vision 的重新出現聽起來可能並不重要。但該公司希望建立一個能夠實現超人嗅覺能力的系統。這些包括嗅出某些疾病（例如癌症）或與糖尿病相關的症狀（例如低血糖）的能力。

The team also hopes to develop a method to recreate smells using molecular synthesis. This would, for example, allow a computer in one place to “smell” something and then send that information to another computer for resynthesis — essentially teleporting odor over the Internet.

該團隊還希望開發一種利用分子合成來重現氣味的方法。例如，這將允許一個地方的電腦「聞到」某種東西，然後將該訊息發送到另一台電腦進行重新合成——本質上是透過網路傳送氣味。

This also means scent could join sight and sound as part of the marketing and branding world. Organizations and companies may one day need to worry over which particular smells best represent their brands.

這也意味著氣味可以與視覺和聲音一起成為行銷和品牌世界的一部分。有一天，組織和公司可能需要擔心哪種特定氣味最能代表他們的品牌。

This begs the question: which cryptocurrency would smell the best?

這就引出了一個問題：哪種加密貨幣聞起來最好？

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