Last week, Ovid Cloud.com collaborated with Tencent to launch the "Ovi Viewpoint" column, sparking a heated debate on the topic of "Is the 'Smart' in Smart TVs really deceptive?" Industry experts weighed in, mostly painting a rosy picture of the future. They emphasized that smart home appliances are the wave of the future, with boundless potential.
After AlphaGo ignited the AI craze, the entire business world began to view artificial intelligence with both awe and enthusiasm. Some see it as the next big disruptor after the internet, while others question if it’s merely hype or a sign of technological stagnation. This article isn’t meant to dampen excitement but rather to encourage a clear understanding of where AI home appliances stand today and where they’re headed.
What is the entry point for AI home appliances? In the internet age, we often discuss the concept of "entry points." Think of it as the door to a house or the gateway to a castle.
Yahoo coordinated the internet's content portal, Google opened up the search portal, Facebook and Tencent focused on social media, Amazon and Alibaba pioneered e-commerce, and today, Toutiao has become a major traffic portal for content distribution.
So, what’s the entry point for the AI era? Generally speaking, AI comprises two main parts: "front-end interaction technology" and "back-end AI technology." Front-end interactions include voice, tactile, and visual recognition. Back-end AI involves core algorithms and semantic understanding. Currently, the most familiar front-end interaction technology is voice recognition, which has become the primary mode of human-computer interaction and the largest entry point for AI.
The home appliance sector is undoubtedly one of the most promising fields for AI. From large smart TVs to small smart sockets and the recent trend of smart speakers, AI is everywhere. Apple and Google have launched smart home platforms like HomeKit and Brillo, connecting all smart home devices.
All home appliances revolve around our daily lives, making them prime candidates for frequent interactions. These interactions are vital for AI—providing data collection and training opportunities. Voice interaction fits perfectly with these needs, making it the preferred entry point for most AI home appliances.
For instance, both internet TV makers and traditional color TV brands like Skyworth, TCL, and Storm are incorporating "smart voice" technology to enhance TV functionality.
However, speech interaction presents significant challenges. Speech recognition remains a challenging frontier for many research teams and companies. Despite efforts by domestic institutions like Unicom Telecom, Baidu, and Shanda, only a few can truly claim to be AI companies. Understanding natural language is still a work in progress, as it took tens of thousands of years of human evolution to reach its current state.
Using smart TVs as an example, the current method of collecting voice data relies on external USB devices equipped with microphone arrays and cameras. Typically, only four-microphone arrays are used, which limits effectiveness in noisy environments or when users are far from the TV.
Moreover, voice output standards vary widely. Not everyone speaks standard Mandarin, and many dialects remain incomprehensible to AI systems. Additionally, semantic understanding is still far from human-level. Current smart voice assistants, like those on TVs, primarily handle tasks such as searching for movies, adjusting volume, and checking the weather.
Translating speech into text is just the beginning of speech recognition. The ultimate goal is for computers to understand the meaning of words and provide appropriate responses. While progress is slow, advancements in deep neural networks and visual recognition offer new possibilities. The brain’s ability to process auditory content using visual imagery improves speech recognition accuracy.
Recent reports show that Microsoft’s Switchboard dialogue speech recognition task achieved a 5.9% error rate under ideal conditions. However, practical applications face challenges such as noise, long-distance recordings, dialects, and limited training data.
AI home appliances can be envisioned in three stages. First, the networking control stage: think of smart light bulbs, smart sockets, and smart kettles—all controlled remotely. Second, the platform feedback stage: adding sensors to appliances to deliver scenario-specific data to a smart platform via cloud computing, enabling feedback-driven actions. Third, the human-computer integration stage, where appliances anticipate user needs—like the hypothetical washing machine described earlier. The ultimate stage is machines with feelings and thoughts.
Today’s smart home industry, led by IoT initiatives, is still in the second stage. Platforms like Apple’s HomeKit and Google’s Brillo are opening APIs, allowing users to control home appliances from their phones. Huawei’s HiLink also focuses on inconsistent connection protocols.
These platforms are still in their infancy. Significant development requires collaboration across the supply chain to establish standards. Human-computer integration is hindered by current limitations in artificial neural network technology, particularly deep learning, as seen in AlphaGo.
Hardware performance improvements are crucial, as this model requires vast amounts of data and computational power. If neural networks and computing power continue to advance rapidly, human-computer integration could become a reality.
The fourth stage envisions AI with independent consciousness. Although we’ve been training "weak AI," the idea of machines with emotions and thoughts remains speculative.
In conclusion, AI represents a leap in productivity, but we’re still at the starting line of natural language processing. Yet, capital is rushing in, labeling nearly every appliance as "smart." But as the saying goes, when the wind stops, pigs fall.
For more insights on smart TVs and boxes, visit Sofa Butler (http://), a leading Chinese site for TV boxes and smart TVs, offering news, communication, reviews, and resources for smart TV enthusiasts.
Substation Transformer,Prefabricated Substation,High Quality Prefabricated Substation,European Type Substation
Hangzhou Qiantang River Electric Group Co., Ltd.(QRE) , https://www.qretransformer.com