What Are the Popular AI Products? — Part2
From the last article, we can see that the intelligent customer service robot can answer all kinds of simple and repetitive questions. It provides users with round-the-clock consultation and problem-solving services. Its wide application also greatly reduces the manual cost for enterprises.
Now let’s have a look at some other popular AI products.
Intelligent Outbound Robot
An intelligent outbound robot is a typical application of AI in speech recognition. It can automatically initiate outbound phone calls and actively introduce products to user groups in the synthesized human voice.
During an outbound call, it can use speech recognition and natural language processing technology to obtain customer intent and then use targeted speech techniques to conduct multiple rounds of interactive conversations. Finally, the outbound robot classifies the user group, records automatically each call’s key points, and completes outbound work.
Smart outbound robots have shown a blowout-like rise starting from the beginning of 2018. It can respond, sort out, record, and track automatically without emotional fluctuations during the interaction process, helping companies complete some tedious, repetitive and costly tasks. The timely operation and liberating labor allow employees to focus on target customer groups, thereby creating higher business value. Of course, the intelligent outbound robot also brings side effects. That is, it would cause frequent interruptions to users.
Smart speakers are electronic product applications and carriers of AI technologies such as speech recognition and natural language processing. With the rapid development of smart speakers, they are also regarded as the future entrance of smart homes. In its essence, a smart speaker is a machine with voice interaction capabilities. Through direct dialogue, Consumers can control home equipment and “evoke” other services and operations at home.
The pre-foundation supporting the interactive functions of smart speakers includes:
- Automatic Speech Recognition (ASR) technology converts human voices into text
- Natural Language Processing (NLP) analyzes components of speech, sentence structure, and the semantics of text.
- Test to Speech(TTS) technology converts text into synthesized human voices
With the blessing of AI technology, smart speakers have gradually created more applications in home scenarios with various natural voice interaction methods.
A personalized recommendation is an AI application based on clustering and collaborative filtering technology. It is based on massive data mining. It builds a recommendation model by analyzing users’ historical behaviors and actively providing information that matches their needs and wants, such as product recommendations, news recommendations, etc.
A personalized recommendation can quickly locate the desired products for users, weaken users’ passive consumption awareness, increase user interest and retention, help businesses attract traffic quickly, identify user groups and positioning, and succeed in marketing.
Personalized recommendation systems widely exist on various websites and apps. In essence, it considers multiple factors such as the user’s browsing information, content preference and relies on recommendation engine algorithms to classify indicators. The information content which is consistent with the user’s target factors is clustered. The collaborative filtering algorithm is used to achieve accurate, personalized recommendations.
The demand for data labeling continues to increase
At present, the research community is doing unsupervised, small-sample deep learning work. Through three-dimensional synthetic data, the machine is trained with synthetic data, so as to minimize the data collection and labeling process. In this way, the machine can learn and evolve independently. However, as there is a lack of theoretical technology breakthroughs, although the technology is growing fast, the overall level is still relatively low. The current deep learning still relies on the big data model based on statistical significance, which requires scalable data.
ByteBridge, a human-powered and ML-powered data labeling tooling platform
- ML-assisted capacity can help reduce human errors by automatically pre-labeling
- The real-time QA and QC are integrated into the labeling workflow as the consensus mechanism is introduced to ensure accuracy.
- Consensus — Assign the same task to several workers, and the correct answer is the one that comes back from the majority output.
- All results are thoroughly assessed and verified by a human workforce and machine
In this way, ByteBridge can affirm the data acceptance and accuracy rate is over 98%.
In addition, clients can iterate data features, attributes, and workflow, scale up or down, make changes based on what they are learning about the model’s performance in each step of test and validation.
Configure Your Own 2D Images Annotation Project
- Developers can control the labeling project from setting labeling instructions to output review on a pay-per-task model with a clear estimated time and price
- Real-time management and monitoring of project
- Real-time Outputs: clients can get real-time output results through API. (We support JSON, XML, CSV, etc. And we can provide customizable datatype to meet your needs)
These labeling tools are available: Image Classification, 2D Boxing, Polygon, Cuboid.
We can provide personalized annotation tools and services according to customer requirements.
A collaboration of the human-work force and AI algorithms ensure a 50% lower price compared to the conventional market.
We provide different types of NLP in E-commerce, Retail, Search engines, Social Media, etc. Our service includes Voice Classification, Sentiment Analysis, Text Recognition and Text Classification(Chatbot Relevance).
Partnered with over 30 different language-speaking communities across the globe, ByteBridge now provides data collection and text annotation services covering languages such as English, Chinese, Spanish, Korean, Bengali, Vietnamese, Indonesian, Turkish, Arabic, Russian and more.
Please feel free to contact us: email@example.com