Will ChatGPT become your new voice assistant?
I asked ChatGPT what it could do to break out of the smart home norm and surpass Alexa and other personal assistants. . With its advanced artificial intelligence language model, it tells me there are countless exciting ways to upgrade your smart home.
AI-driven language models have a deeper personality and capabilities than today’s voice assistants because they are powerful and can inject true conversational depth into their responses. For example, AI assistants can combine responses with data directly from the environment. This, in turn, pushes existing smart home devices to a whole new level of innovation.
This is not to say that the functionality of voice assistants will disappear. Alexa is still needed to handle basic commands and responses, such as turning up the heat or providing tomorrow's weather forecast. Smart home voice assistants will continue to be good at handling simple transactions like these in the future.
“AI-driven language models have a deeper personality and capabilities than today’s voice assistants because they have the power to inject real conversational depth into their responses.”
Passive to active
But today’s voice assistants lack some opportunities to expand the value of smart homes. Most communication with voice assistants revolves around simple commands and responses or actions, so there is little room in the smart home to contextualize the data. However, today's smart home devices generate so much data. By using language models powered by artificial intelligence, various devices in the home can be connected to each other and given intelligence.
For example, next-generation smart thermostats and occupancy sensors use millimeter wave technology, which can detect the slightest movement in a room and even infer the vital signs of the people in the room. If the person is having difficulty breathing, it asks them if they would like to feel more comfortable at a lower room temperature. When consumers develop trust in artificial intelligence voice assistants, they may choose to let these assistants automatically adjust their home environment.
More importantly, the artificial intelligence voice assistant is omni-channel. Imagine receiving a text message from a home device informing you that it just discovered a leak, automatically shutting off the water, and asking if it should book you a local plumber. Assistants like ChatGPT can also connect with smart home sensor data and health and fitness information to make just-in-time recommendations when you open your refrigerator door. It provides suggested options that suit your health goals and can order items accordingly so you're always ready.
This illustrates how we can improve the AI language model to become the true brain of the smart home, reasoning, analyzing behavior and proactively responding to add value to people's lives. The former can do a lot more than today's voice assistants, which can only remind you of doctor appointments you've already scheduled.
In some cases, artificial intelligence smart assistants can serve as digital companions for isolated people. For example, ElliQ, a smart device offered by Intuition, is optimized for empathy and becomes a “friendly presence” in the lives of seniors.
Currently ElliQ is a standalone device, but the day is not too far away when it will be possible to use this rich contextual language through a smart assistant.
Making Smart Homes Smarter
One of the reasons I’m excited about AI-powered assistants is that they will simplify every aspect of the setup and interoperability of the smart home devices consumers purchase . Although smart devices offer many features, some users can't overcome the setup challenges.
In my imagination, consumers are able to purchase smart devices and personalize them through their artificial intelligence assistants. As soon as the device is turned on, the assistant takes over to ensure the device blends seamlessly into the home experience. It can identify the room where the consumer places the device and automatically configure other devices in the same room. If the user is confused about the options, the smart assistant can explain each option and optimize it based on the user request, just like we do today with ChatGPT.
Potential Risks
I firmly support artificial intelligence, but there are some things that all smart device product developers and manufacturers need to think about together. In an interview, OpenAI CEO Sam Altman warned that all artificial intelligence can be misused for nefarious purposes. A more common problem is that when users engage in a conversation with a smart assistant, it can inadvertently put them in a bubble that ultimately changes their worldview. We’ve noticed political interests acting through the creation of chatbots that reflect their leanings.
As with all AI, we need to set up some controls to regulate it. At some point, we need to develop some ethics around AI so that smart assistants don’t feed into users’ biases and distort their judgment. But all technology comes with risks, and with the right protections in place, I'm optimistic that AI-powered smart home devices will improve users' lives in a variety of ways.
The above is the detailed content of Will ChatGPT become your new voice assistant?. For more information, please follow other related articles on the PHP Chinese website!

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

AI Hentai Generator
Generate AI Hentai for free.

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics



This site reported on June 27 that Jianying is a video editing software developed by FaceMeng Technology, a subsidiary of ByteDance. It relies on the Douyin platform and basically produces short video content for users of the platform. It is compatible with iOS, Android, and Windows. , MacOS and other operating systems. Jianying officially announced the upgrade of its membership system and launched a new SVIP, which includes a variety of AI black technologies, such as intelligent translation, intelligent highlighting, intelligent packaging, digital human synthesis, etc. In terms of price, the monthly fee for clipping SVIP is 79 yuan, the annual fee is 599 yuan (note on this site: equivalent to 49.9 yuan per month), the continuous monthly subscription is 59 yuan per month, and the continuous annual subscription is 499 yuan per year (equivalent to 41.6 yuan per month) . In addition, the cut official also stated that in order to improve the user experience, those who have subscribed to the original VIP

Improve developer productivity, efficiency, and accuracy by incorporating retrieval-enhanced generation and semantic memory into AI coding assistants. Translated from EnhancingAICodingAssistantswithContextUsingRAGandSEM-RAG, author JanakiramMSV. While basic AI programming assistants are naturally helpful, they often fail to provide the most relevant and correct code suggestions because they rely on a general understanding of the software language and the most common patterns of writing software. The code generated by these coding assistants is suitable for solving the problems they are responsible for solving, but often does not conform to the coding standards, conventions and styles of the individual teams. This often results in suggestions that need to be modified or refined in order for the code to be accepted into the application

Large Language Models (LLMs) are trained on huge text databases, where they acquire large amounts of real-world knowledge. This knowledge is embedded into their parameters and can then be used when needed. The knowledge of these models is "reified" at the end of training. At the end of pre-training, the model actually stops learning. Align or fine-tune the model to learn how to leverage this knowledge and respond more naturally to user questions. But sometimes model knowledge is not enough, and although the model can access external content through RAG, it is considered beneficial to adapt the model to new domains through fine-tuning. This fine-tuning is performed using input from human annotators or other LLM creations, where the model encounters additional real-world knowledge and integrates it

To learn more about AIGC, please visit: 51CTOAI.x Community https://www.51cto.com/aigc/Translator|Jingyan Reviewer|Chonglou is different from the traditional question bank that can be seen everywhere on the Internet. These questions It requires thinking outside the box. Large Language Models (LLMs) are increasingly important in the fields of data science, generative artificial intelligence (GenAI), and artificial intelligence. These complex algorithms enhance human skills and drive efficiency and innovation in many industries, becoming the key for companies to remain competitive. LLM has a wide range of applications. It can be used in fields such as natural language processing, text generation, speech recognition and recommendation systems. By learning from large amounts of data, LLM is able to generate text

Machine learning is an important branch of artificial intelligence that gives computers the ability to learn from data and improve their capabilities without being explicitly programmed. Machine learning has a wide range of applications in various fields, from image recognition and natural language processing to recommendation systems and fraud detection, and it is changing the way we live. There are many different methods and theories in the field of machine learning, among which the five most influential methods are called the "Five Schools of Machine Learning". The five major schools are the symbolic school, the connectionist school, the evolutionary school, the Bayesian school and the analogy school. 1. Symbolism, also known as symbolism, emphasizes the use of symbols for logical reasoning and expression of knowledge. This school of thought believes that learning is a process of reverse deduction, through existing

Editor |ScienceAI Question Answering (QA) data set plays a vital role in promoting natural language processing (NLP) research. High-quality QA data sets can not only be used to fine-tune models, but also effectively evaluate the capabilities of large language models (LLM), especially the ability to understand and reason about scientific knowledge. Although there are currently many scientific QA data sets covering medicine, chemistry, biology and other fields, these data sets still have some shortcomings. First, the data form is relatively simple, most of which are multiple-choice questions. They are easy to evaluate, but limit the model's answer selection range and cannot fully test the model's ability to answer scientific questions. In contrast, open-ended Q&A

Editor | KX In the field of drug research and development, accurately and effectively predicting the binding affinity of proteins and ligands is crucial for drug screening and optimization. However, current studies do not take into account the important role of molecular surface information in protein-ligand interactions. Based on this, researchers from Xiamen University proposed a novel multi-modal feature extraction (MFE) framework, which for the first time combines information on protein surface, 3D structure and sequence, and uses a cross-attention mechanism to compare different modalities. feature alignment. Experimental results demonstrate that this method achieves state-of-the-art performance in predicting protein-ligand binding affinities. Furthermore, ablation studies demonstrate the effectiveness and necessity of protein surface information and multimodal feature alignment within this framework. Related research begins with "S

According to news from this site on August 1, SK Hynix released a blog post today (August 1), announcing that it will attend the Global Semiconductor Memory Summit FMS2024 to be held in Santa Clara, California, USA from August 6 to 8, showcasing many new technologies. generation product. Introduction to the Future Memory and Storage Summit (FutureMemoryandStorage), formerly the Flash Memory Summit (FlashMemorySummit) mainly for NAND suppliers, in the context of increasing attention to artificial intelligence technology, this year was renamed the Future Memory and Storage Summit (FutureMemoryandStorage) to invite DRAM and storage vendors and many more players. New product SK hynix launched last year
