西安品茶论坛 – 第 13 页 – 西安夜生活网论坛,西安耍耍网,西安品茶网

The Premier League champion was born! Arsenal lost 0-1 to win the championship, and Manchester City completed the Premier League’s three consecutive championships!

Early this morning, the Premier League was the firstthreesevenA focus battle was staged.Arsenal away0-1Lost to Nottingham Forest, completely missed the championship, Manchester City in the case of this round, ahead of schedule.threeWin the league championship and complete the great cause of three consecutive Premier League titles! Nottingham Forest finished relegation one round ahead of schedule after winning!

Arsenal fell behind Manchester City before the game.4 points, one game less than the opponent, this round of Arsenal is ahead of Manchester City, and it is necessary to win to keep the hope of winning the championship. Once losing, Manchester City will win the championship three games in advance. Nottingham Forest ranks first in the league.sixBit, leading the relegation zone3 points, there is still some relegation pressure, and we will definitely strive to win at home.

First halfonenineMinutes later, Odegard’s passing error was intercepted, and the home team White scored the ball. Avonii seized the opportunity to complete the goal.1-0! Arsenal then tried to fight back, but their whole team was in poor condition. Except for Trossat, who shot wide and caused a certain threat, the rest of the time had possession rate, but it was difficult to create too much threat to the opponent’s goal.

In the second half, Artta made many substitutions, but Arsenal’s performance did not improve at all, and finally they went away.0-1Lose the game and hand over the championship to Manchester City! Manchester city in the current round of war, ahead of schedule.threeThe game locked the league title and completed the league.threeAfter winning the championship, Guardiola’s team took the first step in the process of winning the triple crown!

Mr. Laundry helped Haier 2023 Qingdao Marathon, and the official designated care brand strength stole the show.

On April 22nd, Haier 2023 Qingdao Marathon officially started. As the official designated care brand of Haier 2023 Qingdao Marathon, Mr. Laundry is committed to providing runners with a more comfortable and secure care experience, being a clothing care housekeeper around you, and helping every runner to go to the mountains and seas.

The new model meets old friends, and Mr. Laundry is praised by users.

Focusing on the needs of users, the care services provided by Mr. Laundry are not limited to sweatshirts and sports shoes on runners, but also include daily clothes, special fabrics such as silk and cashmere. Mr. Laundry can solve the cleaning, nursing and treatment of various fabrics in life. Mr. Laundry’s innovative business model of "1+N+ Ecology" changes the single service of traditional laundries, and provides users with clothes life cycle solutions for washing, protecting, storing, riding, purchasing and collecting clothes.

Mr. Laundry also met many old friends at this Qingma scene. "It’s the first time to run a green horse, but I’ve been an old user for more than ten years at the laundry man & Jieshen Store at the entrance of my community!" The marathon runner, Ms. Song, who lives in Taizhou Road, said. Since 2021, Mr. Laundry set up a joint venture with Qingdao local brand Jieshen for 30 years, the upgrade speed and achievements of the new-type eco-care store have been well received by users in the island city: "At first, it was washing clothes, and then the store had eco-products, as well as home cleaning and home appliance cleaning services. Now the store can even buy Haier household appliances directly, which really provided us with great convenience. I ran into the new track with Mr. Laundry & Jieshen."

Professional runners prefer professional care, and Mr. Laundry is reliable.

In 2023, it was the fifth year that Haier and Tsing Ma walked hand in hand, and it was also the second time that Mr. Laundry made his debut at Tsing Ma Circuit. As a great achievement of Haier’s transformation on the eco-brand track, Mr. Laundry, under the guidance of eco-brand strategy, relies on the platform-leading IOT technology and ecological resources, and establishes a caring ecology trusted and recognized by consumers with a full-link caring solution, which helps the caring industry to develop towards the goal of being more standardized, orderly, green and environmentally friendly, and upgrading services. As of March this year, Mr. Laundry has covered 1,528 network contacts in 30 provinces across the country, built 12 operation centers, 3 self-owned 6S standard central laundry factories and 37 cooperative factories, and the rapid development is backed by the recognition of national users and the guarantee of professional care ability.

"I usually run a lot, and my shoes are dirty and worn quickly. Many of our runners have the need for professional care of running shoes. They should be clean, but don’t brush them too violently." Mr. Li, who specially came to Qingdao from other places to participate in the marathon, said that he was very interested in Mr. Laundry’s treatment mode of "washing, drying, ironing, sterilization and disinfection" and the exclusive care service mode of "one customer, one cylinder and one disinfection".

The innovative care mode and sincere caring service also give Mr. Laundry enough confidence to be qualified as the official designated care brand of Haier 2023 Qingdao Marathon. It is with this confidence and sense of responsibility that Mr. Laundry will base himself on the care needs of runners, bring high-quality and professional care services and bring more surprises to runners!

The Internet is full of flawed content generated by AI. Will AI trained based on this information be outrageous？

1. Yes.

If you answer the question of "yes and no", the answer is obviously "yes".

2. The logic of AI learning can be simply summarized as the following three steps:

2.1. Input data and feature extraction: The first step of AI learning is input data and feature extraction. At this stage, the AI system will receive some input data, which can be images, text, voice or other types of data. Then, the AI system will extract some useful features from these data, which can help the AI system better understand and process the data.

2.2. Model training: The second step of AI learning is model training. At this stage, the AI system will use the input data and features extracted to train a model. This model can be neural network, decision tree, support vector machine, etc. It will learn how to map the input data to the output results according to the features extracted from the input data and features. The goal of model training is to make the model accurately predict the output results.

2.3. Model evaluation and optimization: The third step of AI learning is model evaluation and optimization. At this stage, the AI system will use some test data to evaluate the performance of the model and optimize the model according to the evaluation results. If the performance of the model is not good enough, the AI system will adjust and optimize the model to improve its accuracy and generalization ability. Generally speaking, the logic of AI learning is to continuously improve the performance and ability of AI system through input data and feature extraction, model training and model evaluation and optimization, so as to realize more accurate and intelligent prediction and decision-making.

3. Garbage input and garbage output

The quality of AI-generated content is affected by the quality of data used to train AI models. If the training packet contains defective content, then the artificial intelligence model will also be defective. This is called "garbage input, garbage output". Because the AI system will try to imitate and repeat the existing data when learning, if the data itself has problems, then the AI system may repeat these problems and even aggravate them.

Constructing high-quality data sets is the key, and attention should be paid to the source, quality, scale and diversity of data sets. Miniaturization of language model is also an important research direction.

4. But there is room for optimization and self-evolution.

4.1. The training of AI system does not only depend on the data on the Internet, and the data on the Internet is less than 5% of human information.

4.2. It also includes various artificially designed data sets and algorithms. If these data sets and algorithms are carefully designed and optimized, then the AI system can be prevented from being affected by flawed data on the Internet.

4.3. AI system can also improve itself through self-learning and adaptation, thus improving its accuracy and reliability.

4.4. Although flawed content on the Internet may have some impact on the training and development of AI system, it does not mean that AI system will become more outrageous. On the contrary, with the advancement of technology and the continuous improvement of data sets, AI systems will become more accurate and reliable.

5. Making an AIGC or ChatGPT requires a lot of technology, not just input.

Large-scale model technology accumulation: it is necessary to master the basic knowledge of large models, such as Transformer architecture, self-supervised learning, pre-training and fine-tuning.

Accumulation of natural language processing technology: you need to know the basic knowledge of natural language processing, such as word segmentation, word vector, semantic understanding, emotion analysis, entity recognition and so on.

Data set construction technology accumulation: it is necessary to build high-quality dialogue data sets to improve the quality and effect of the model. The construction of data set needs to consider many factors, such as data source, data quality, data scale, data diversity and so on.

Algorithms and computing power: You need to master reinforcement learning, generative model, attention mechanism and other algorithms, and have enough computing resources to train and optimize the model.

6. Take the manuscript to make an inappropriate analogy.

Copying refers to copying, pasting, modifying and deleting other people’s original articles without authorization, which makes them look different from the original, but in essence they copy the contents and ideas of the original. Editors usually aim to get the content quickly, save time and energy, so as to achieve the purpose of publishing articles quickly, but this behavior seriously infringes on the intellectual property rights of the original author, and also violates academic ethics and professional ethics. Washing manuscripts not only harms the interests of original authors, but also greatly damages the reputation and image of the whole industry, so it is regarded as an immoral and illegal behavior.

However, the manuscript washing should also be level and creative. The awesome manuscript washing often needs to "see" a lot of materials, which is another process from quantitative change to qualitative change.

7. Going back to the nature of AI, is it a tool or decision logic? What do you do with AI?

The process of human receiving information can be divided into the following stages:

Perception: Perception means that we receive external information through sensory organs, including vision, hearing, touch, taste and smell. Perception process is based on the interaction between sensory organs and external stimuli, which transforms external information into neural signals and transmits them to the brain.

Attention: Attention refers to the process of selecting and processing the perceived information. Because of the diversity and complexity of external information, we can’t handle all the information at the same time, so we need to filter out important information and deal with it through attention.

Understanding: Understanding refers to the process of interpreting and understanding the information we receive. This process needs to rely on our knowledge, experience and language ability to connect and integrate the perceived information with the existing knowledge, thus forming new cognition and understanding.

Memory: Memory refers to the process of storing and processing the received information. Memory can be divided into short-term memory and long-term memory. The former is the ability to temporarily store information for processing, while the latter is the ability to permanently store information in the brain.

Judgment: Judgment refers to the process of evaluating and judging the information we receive. This process needs to rely on our values, beliefs and cognitive abilities, and compare and evaluate information with our existing cognitive and value systems, thus forming our attitudes and views on information.

Action: Action refers to the process of making decisions and taking actions according to the information we receive. This process needs to rely on our willpower, decision-making ability and action ability, and turn our understanding and judgment of information into actual actions and decisions.

What is the purpose of obtaining information with AI? To what stage can AI replace you?

The brand-new Chongqing team appeared in China football! The warm-up match defeated the newly promoted Super League, which made the fans sit up and take notice.

A few days ago, Chongqing football ushered in a brand-new professional league team, which is Chongqing Tonglianglong, which gathered many old Lifan generals. After the dissolution of the Chongqing team, Chongqing Tonglianglong began to play in the China Champions League and began to carry the banner of reviving Chongqing football. Chongqing Tonglianglong performed well in the Champions League last season and got the qualification of Chong B. After Chongqing Tongliang Dragon rushed to China B, it filled the gap that there was no professional team in Chongqing football.

Chongqing lifan used to be a strong football team in China, and it also performed well in the Super League, and once beat Evergrande. Chongqing team has also trained international players like Zhang Chiming and Feng Jin. Unfortunately, before the Super League started last season, the team once again encountered the crisis of unpaid wages. Finally, after comprehensive consideration, Chongqing team decided to quit professional football. Chongqing team quit professional football, which made Chongqing football lose its professional team.

At the critical moment, Chongqing Tonglianglong stood up, started to play in the China Champions League in a team, and recruited the Chongqing football flag Wu Qing. Chongqing Tongliang Dragon has now rushed to China B, attracting the attention of a group of old Lifan generals. Chongqing Tonglianglong can consider introducing Liu Huan whose contract with Guoan expired. After leaving Guoan, Liu Huan went to Dalian for trial training.

Whether Liu Huan can stay in Dalian is a huge unknown. Because Liu Huan’s Dalian team is in a precarious state. Dalian team doesn’t even have the qualification to introduce new aid. If this problem is not solved in the future, Liu Huan will not be able to complete the registration. Therefore, Liu Huan can consider returning to Chongqing. At the same time, Chongqing Tonglianglong chose to play a warm-up match in order to test the training results during this period.

Chongqing Tonglianglong chose to play with Qingdao Manatee, a new Chinese Super League army. Originally, fans thought that Chongqing team would be played by Manatee. Unexpectedly, the Chongqing team was very tenacious in the game and finally defeated its opponent 1-0. The strong play of Chongqing team in the warm-up match made the fans see the hope of rushing to armour. I look forward to Chongqing Tonglianglong’s steady and steady progress in the Chinese B League and achieving the goal of rushing to the first division in the new season.

Paris Saint-Germain is willing to spend 50 million pounds to introduce Maguire？

Paris Saint-Germain is preparing to offer 50 million pounds for Harry Maguire in the summer and bring him to France..

It is reported that Manchester United are willing to break the club record and sign Eduardo Camavinga from Real Madrid for 115 million pounds..

Tottenham Hotspur is facing a struggle to convince Thomas Tuchel to become their new head coach. It is reported that both he and Mauricio Pochettino are the best candidates to succeed Antonio Conte, and Chairman Daniel Levy has reservations about bringing back former head coach Pochettino..

Manchester United has added Mason Mount of Chelsea to the list of attacking midfield targets including ude Bellingham. If Erik ten Hag spends most of his summer budget on bringing in Harry Kane or Victor Osimhen, the summer transfer window will exceed the budget..

The exit of Paris Saint-Germain in the Champions League is likely to prompt the departure of head coaches Christophe Galtier and Sports director Luis Campos..

Considering the cost of living crisis, the soaring business income of Chelsea, the performance of the club this season and the possible impact of the rising ticket fees on the atmosphere of the match day at Stamford Bridge, Chelsea fans warned the club president Todd Boehly that if he decided to raise the ticket price after a bad season at Stamford Bridge, it would cause "irreversible harm" to the fans..

Before Saturday’s game against Brighton, Leeds may get unexpected good news, and striker Rodrigo may play only one month after ankle surgery..

Wolves hope to beat Premier League rivals Tottenham Hotspur and West Ham United and plan to sign Alex Scott of Bristol City for 20 million pounds..

Daniel Levy, chairman of Tottenham Hotspur, will consider a series of candidates to change coaches, including Mauricio Pochettino, who may return to the club, and Luis Enrique, who was fired by Spain after the World Cup. Celtics coach Ange Postecoglou, Brighton coach Roberto De Zerbi and Neapolitan coach Luciano Spalletti..

Laundry technology sharing： can ChatGPT make autonomous driving faster？

Recently, the hottest topic in the science and technology circle is "ChatGPT". However, ChatGPT is only an external manifestation, and what deserves more attention is the development of AI technology behind it and its future application.

Some people even describe the changes brought by ChatGPT optimistically: Before ChatGPT, AI was only a module of existing scene products at most. Then, after ChatGPT, AI will redefine the product framework of existing scenarios.

Whether it is as optimists say remains to be seen, but whether autonomous driving, as one of the important scenes of AI landing, will have further development in this wave has still aroused many people’s discussion.

Some people think that autonomous driving needs more graphics, images and data processing ability, requires higher image algorithm, and has little correlation with natural language processing ability. It is not possible to realize autonomous driving with ChatGPT’s ability at present.

Of course, some people think that the appearance of ChatGPT shows us a possibility, that is, trained AI will make high-level autonomous driving expected to appear in a few years.

Why does the progress of AI technology make people pay attention to whether autonomous driving is affected?

Observing the development history of autonomous driving, it is not difficult to find that every major breakthrough of autonomous driving is synchronized with the development of AI technology.

We know that,AI is actually imitating the brain neural network and learning some very humanized skills by analyzing a large amount of data.In 1980s, the first practical application of neural network happened in the field of automatic driving.

In 1987, researchers at Carnegie Mellon Artificial Intelligence Laboratory tried to make a truck that could drive automatically. They manually write codes for all driving behaviors and write as detailed instructions as possible for various situations encountered by trucks on the road, so as to make the vehicles run automatically. But unfortunately, this way can only make the car achieve a speed of several inches per second.

Manual code writing failed, and another doctoral student named Dean pomerleau chose another way: neural network.

He named his system ALVINN. After adopting this system, trucks use the images taken by the roof camera to track what drivers are doing, so as to observe how to learn to drive on the road. In 1991, ALVINN drove from Pittsburgh to Erie, Pennsylvania at a speed of nearly 60 miles per hour.

However, a more direct and broader impact occurred in 2012.

Jeff Hinton, a professor at the University of Toronto, and two of his students, Alex Krzyzewski and Ilya Satsky, won the first prize in the ImageNet image recognition competition, and published a paper introducing the algorithm AlexNet. This paper is not only the turning point of artificial intelligence, but also the turning point of global technology industry.

As the key technology of autonomous driving, target detection and image recognition are highly benefited from the breakthrough of computer vision algorithm. Therefore, with the recognition accuracy of Li Feifei team, director of Stanford Artificial Intelligence Laboratory, surpassing humans for the first time on ImageNet open data set in 2015, autonomous driving, as one of the most important landing scenes of AI, has also entered the fast lane of development.

So, will the appearance of ChatGPT become the Milestone of autonomous driving again?

Generally speaking, AI can be divided into three parts: voice, vision and natural language understanding.The last wave of AI was mainly based on the breakthrough of visual image recognition technology, and this time ChatGPT is a natural language processing technology based on GPT-3 model, which can effectively simulate human language understanding ability, thus helping people better understand and analyze natural language text data.

When we want to discuss what impact ChatGPT will have on autopilot, we think that we should first find out whether autopilot here refers to mass-produced low-level autopilot (assisted driving) or high-level L4 autopilot. Secondly, does ChatGPT refer to a language model or a more generalized generation model?

From the perspective of natural language understanding, ChatGPT has a more direct impact on human-computer interaction in the assisted driving part, but it may not have a great impact on L4-level automatic driving.

Cui Dongshu, secretary-general of the Federation, also wrote in his WeChat WeChat official account that the innovation of human-computer interaction and intelligent cockpit system is very strong, especially the human-computer interaction ability of domestic car companies is very strong. Only China enterprises can understand Chinese more deeply. With the empowerment of the bottom layer in the future, the domestic automobile industry will have more good human-computer interaction effects at the application level.

For example, by using ChatGPT, the vehicle can interact with the driver by voice or text, and provide the driver with real-time feedback on vehicle status and driving information.

Before this, although a large number of in-vehicle interactive systems have appeared, the pain point of the industry mainly focuses on the "understanding" part, and most of the in-vehicle voice interactive systems are not intelligent in "understanding", resulting in a single function and command word of the whole system. ChatGPT’s explosion made the market see the hope of solution.

However, Cui Dongshu, secretary-general of the Federation, also said that,Electrification is the core of new energy vehicles, and intelligence is just icing on the cake. In the future, the core competitiveness of car companies will still be to build electric vehicles, and at the same time make full use of intelligence such as ChatGPT to empower the development of the automobile industry.

Of course, whether it is the core or not, it is not enough to have a technological breakthrough if you want to get on ChatGPT. An AI industry person told Titanium Media that "there are still cost issues, including the use cost, cloud service cost and targeted training cost."

However, from a broader generative model, the generative model with big data and large parameters will help to achieve a higher level of autonomous driving.

He Xiang, a data intelligence scientist at Mimo Zhixing, said in an interview with Titanium Media App that the vehicle-side capabilities mainly include two categories: perception and cognition. The perception ability really relies mainly on image technology, while the cognitive ability relies more on similar generation technology of ChatGPT.

That is to say,ChatGPT’s revolutionary significance lies in: letting AI model enter the era of knowledge and reasoning. At present, the biggest shortcoming of autonomous driving lies in the lack of sufficient intelligence in decision-making planning.

ChatGPT uses a training method called "Human Feedback Reinforcement Learning (RLHF)", and He Xiang, a data intelligence scientist at Mimo Zhixing, explained to Titanium Media APP.GPT is a large-scale universal pre-training language model. GPT1, GPT 2 and GPT 3 mainly improve the parameter scale, while ChatGPT mainly introduces human feedback data for reinforcement learning.

The introduction of this method can ensure the minimum output of useless, distorted or biased information according to human feedback in training.

It happens that there is also a kind of automatic driving decision algorithm called imitation learning, which is to let the machine learn how human drivers do it in different scenarios.

Generally speaking, every takeover by a human driver is an artificial feedback to the autonomous driving strategy; This takeover data can be simply used as a negative sample, which is a record that the autopilot decision is corrected. At the same time, it can also be used as a positive sample to improve cognitive decision-making

"The big model of big data and big parameters can learn more potential knowledge, including different environments and different scenarios, which is equivalent to learning a lot of common sense of autonomous driving. This common sense is very important for autonomous driving decisions." He Xiang, a data intelligence scientist at the end of the year, told Titanium Media App.

That is to say,In the process of autonomous driving research and development, the idea of human feedback reinforcement learning can be used to train a model to verify and evaluate the output of the machine model, so that it can make continuous progress and finally reach the driving level of human beings.

Therefore, it can be said that the improvement of basic ability has brought about the expansion of imagination and applicable scenarios. However, at this stage, we still can’t accurately judge how much change the big model represented by ChatGPT will bring to autonomous driving. An industry person told Titanium Media App that the excellent generalization ability trained by the big model may make there no corner case in the world.

Corner case refers to a small probability event that may occur during driving, but the frequency is extremely low. Although it is rarely encountered at ordinary times, it is likely to lead to a fatal traffic accident when encountering a corner case that cannot make a decision for an autonomous driving system.

The emergence of ChatGPT has made the industry realize that it is possible to gain a higher level of autonomous driving technology by constantly accumulating kilometers and running like this.

In fact, before this, both foreign Tesla and domestic Tucki, Baidu and Mimo Zhixing were already exploring the route of "big model".

In 2020, Tesla announced that it would introduce a large model based on deep neural network into its autonomous driving, and now it has realized a large-scale public beta of pure visual FSD Beta; Tucki expressed the viewpoint of using large models to get through the whole scene of XNGP on the 1024 Science and Technology Day in 2022. Baidu Apollo believes that the Wenxin model will be the core driving force of the elevator’s automatic driving ability.

As early as 2021, Mimo Zhixing announced that it would improve its data processing ability with the help of a large model. On February 17th this year, Mimo Zhixing officially upgraded the large model of human driving self-monitoring cognition to "DriveGPT", which will continue to introduce large-scale real takeover data, and continuously improve the evaluation effect through intensive learning of human driving data feedback. At the same time, it also uses DriveGPT as a cloud evaluation model to evaluate the driving effect of small models at the vehicle end.

However,The development of high-level self-driving cars is a complex multidisciplinary field, involving a wide range of technical and regulatory challenges. The progress of artificial intelligence technology can bring some impetus, but this is not a short-term problem.

It is reported that GPT3.0 involves 170 billion parameters, with more than 300 GB of memory, and the training process costs more than 12 million US dollars. The above-mentioned industry insiders said that the autopilot algorithm is to run in the car. Can such a large model be deployed to the car? How much computing power does it need to support? In addition, autonomous driving can not be completed by repetitive and simple road data stacking, so how to ensure a large amount of data is also a key issue.

The article is reproduced from the titanium media. The opinions in the article are only for sharing and communication, and do not represent the position of WeChat official account. If copyright issues are involved, please let us know and we will deal with them in time.

About the laundry list technology company

Laundry Technology Co., Ltd. is the world’s leading spatio-temporal intelligent big data service company and the leading location data and industry application solution provider in China. Relying on self-developed patented technology, based on high-precision maps and multi-source spatio-temporal intelligent big data, we will establish city-level and industry-level holographic spatio-temporal digital twin systems, and actively serve smart transportation (autonomous driving, smart highway, vehicle-road coordination), natural resource asset management (carbon neutral and environmental protection remote sensing data service), LBS smart industry applications (mobile Internet local business location service, smart travel, smart logistics, new infrastructure, smart city, emergency rescue) and other fields. For more information, please search for "laundry list technology" and visit the company website.

The Influence of Artificial Intelligence on Modern Society

Artificial Intelligence (AI for short) refers to a technology that computer system simulates human intelligent thinking and behavior through learning, reasoning, perception, understanding, judgment and decision-making. The core of AI technology is machine learning, that is, processing and analyzing a large number of data through training algorithms, and learning and extracting useful information and rules from them, so as to continuously optimize and improve their intelligence.

AI technology covers many different fields and applications, including natural language processing, image recognition, machine vision, speech recognition, robotics, intelligent recommendation, virtual reality and so on. These applications can play a role in many fields, such as health care, finance, energy, manufacturing, transportation, education, entertainment and so on.

In a word, artificial intelligence is a technology that can simulate human intelligent thinking and behavior. It enables computer systems to complete a series of complex tasks and decisions independently through machine learning and pattern recognition.

Artificial intelligence (AI) can bring us many benefits. The following are some of the main benefits:

Automation: AI technology can automate many repetitive tasks, saving time and labor costs.
Intelligent decision-making: AI system can provide more intelligent decision-making for human beings by analyzing a large amount of data and information.
Customer service: AI can improve the quality and efficiency of customer service, such as providing instant service and support to customers through intelligent robots or chat bots.
Health care: AI technology can help doctors and health care professionals make diagnosis and treatment decisions, while improving the efficiency and accuracy of health care services.
Resource management: AI can help enterprises and government agencies to better manage resources, for example, by forecasting and planning energy demand and supply, and optimizing the supply chain.
Education and training: AI can provide a better education and training experience, such as optimizing the learning process through personalized learning paths and real-time feedback.
Safety and security: AI can help protect public safety and personal safety, for example, through automatic monitoring and detection systems to identify security threats and abnormal behaviors.

In a word, AI technology can improve efficiency, accuracy and intelligence, provide better service and support for human beings, and bring more commercial and social value.

Artificial intelligence (AI) has been widely used in various fields, including but not limited to the following aspects:

Natural Language Processing (NLP): transforming human language into computer-readable forms, such as machine translation, speech recognition, text classification and sentiment analysis.
Image recognition and Computer Vision (CV): Computer vision technology enables computer systems to recognize and understand images and videos, such as face recognition, object detection, automatic driving and security monitoring.
Machine Learning (ML): By training algorithms, computer systems can automatically learn and adapt to new data, thus improving the accuracy of prediction and decision-making, such as recommendation system, credit evaluation, risk control and medical diagnosis.
Robotics: Using artificial intelligence technology, robots can accomplish tasks that humans can’t, such as autonomous navigation, cooperative operation, intelligent control and service robots.
Automation and intelligent manufacturing: using artificial intelligence technology to realize the automation and intelligence of production process and supply chain, such as intelligent logistics, intelligent warehousing, intelligent quality control and intelligent equipment.
Virtual reality and augmented reality: through artificial intelligence technology, virtual reality and the real world are combined to realize a more immersive user experience, such as virtual training, virtual fitting, virtual tourism and augmented reality applications.

In short, artificial intelligence technology has been widely used in various fields and industries, which has changed our way of life and work, but also brought great opportunities and challenges for future technological development and innovation.

The impact of artificial intelligence (AI) on employment in modern society is twofold: on the one hand, AI technology can create new employment opportunities, on the other hand, it will also affect the employment of some traditional industries.

New employment opportunities: With the development of AI technology, more and more companies and organizations need professional AI engineers, data scientists, machine learning experts and AI strategists. In addition, AI technology has also created some new professional fields, such as intelligent robot engineers, voice interaction designers and virtual reality developers.
Impact of employment in traditional industries: AI technology will also have a certain impact on employment in traditional industries. For example, AI technology can automate many repetitive tasks and jobs, thus reducing the work that needs to be done by human beings. This may lead to the reduction of jobs in some traditional industries, such as manufacturing, administration and support services.

However, it should be pointed out that AI technology will not completely replace human work. On the contrary, it usually cooperates with human beings to improve efficiency and quality. Therefore, for the job market in modern society, it is important to improve skills and transformation ability to adapt to the rapidly changing technology and job market.

There are so many ai robot outbound calling systems, how to choose the one that suits you？

As the artificial intelligence industry becomes more and more mature, the times are developing and the industry is progressing, and more industries will embrace artificial intelligence; Ai robot outbound system can make enterprises create more profits with less cost and shorten the cycle of finding customers. So, there are so many ai robot outbound call systems, how to choose the one that suits you?

Telephone:

To judge whether an ai robot outbound system is suitable for you, we should first pay attention to several aspects: 1. Connection rate 2. Time required for dialing 3. Speech skills 4. Whether the line is high or not. 5. Where the number belongs …

Constantly compare the function of this robot outbound system with that of the robot outbound, and choose who can meet the actual needs of your company;

It’s just that this choice takes a long time and costs a lot of time, so is there a simpler method?

1. It can be applied to mainstream industries and application scenarios.

Jiadan Technology Intelligent Sales Robot is suitable for covering mainstream industries and application scenarios.

Jiadan Technology intelligent telemarketing robot is equipped with a good platform, and uploads the exclusive speech recorded by a professional sound recorder. Technicians upload it to the system platform, and then they can make their own calls by importing the phone, so as to quickly and effectively screen customers who are interested in the products and push them to WeChat bound to the system platform to arrange professional contact and communication.

Faster and more effective, support interruption, support manual intervention, and improve work efficiency.

2. Automatically determine the intended customers. According to the intended customer label set by the system platform, what kind of customers are divided into: Class A, Class B, Class C and Class D all have clear standards; For example, how much money the customer asks, where the company is, and other keywords, the system will automatically judge it as a class A customer, and the call records can be viewed in real time without missing any intended customers.

3. After professional and intimate after-sales service cooperation, many-to-one guidance will be given to the docking group, and many customer service technicians will solve all kinds of problems encountered in the use process in real time.

If you are interested, please contact the above phone and WeChat to provide you with professional advice.

Google launched PaLM-E, a visual language model with 562 billion parameters.

Recently, it was reported that Robotics at Google, Technical University of Berlin and Google Research team jointly launched the largest visual language model PaLM-E, with the final parameters as high as 562 billion. It is understood that this model has the ability to understand images, understand generation languages and handle complex machine instructions.

In this regard, Google said that the model also has an environmentally adaptive response and has the ability to face possible unexpected situations. It is reported that the model is robust to interference because it is integrated in a control loop.

It is reported that this model is a combination of PaLM-540B language model and Vit-22B visual Transformer model, and its core is its powerful language processing ability. The highlight is that the model can use visual data to enhance its own language processing ability after acquiring and processing visual data. For example, the corresponding traffic rules can be solved by pictures of traffic signs, the production process can be understood by pictures of ingredients, or the robot can be guided to complete relatively complicated actions by inputting instructions.

It is understood that PaLM-E has another outstanding advantage, that is, it has strong positive migration ability. In the relevant test results released by Google, the researchers believe that PaLM-E has the ability of self-learning, so it can perform planning and cross-length tasks on different entities. For example, after the model guides the robot to complete the "color block by color", it can further guide the robot to push the green color block to the ornaments that have never been seen before.

Some people think that although the guidance given by PaLM-E to robots does not seem very complicated at present, with the change of data training, it will give robots more thinking ability, and it is expected to be able to plan and execute the commands issued by humans more reasonably in the future, and make great breakthroughs in industrial application and design.

It is understood that in the artificial intelligence track, Microsoft previously published a similar case mentioned in the above research in February this year, that is, through the program written by ChatGPT to guide drones how to find drinks.

[The picture in this article comes from the network]

To what extent have robots developed in China？

The development of robots in China has made great progress, and various types of robots have been popularized from manufacturing to service. The following is some information about the present situation and development trend of robot industry in China:

China is dominated by industrial production and occupies a leading position in the global market.Logistics, warehousing, processing and other businesses all involve robots.

Consumer robots are becoming more and more popular.For example, home cleaning robots, toy robots and robots that assist the elderly and the disabled.

In 2019, China successfully developed the first conversational AI robot. Its name is Xiaodi, which has the functions of speech recognition, natural language understanding, dialogue generation and emotion recognition. It is widely used in customer service and hotel reception.

Considering the aging population and increasing medical costs, China is actively exploring medical robots. Such as robotic surgery, nurse robots, etc.

In education, artificial intelligence and robots are being used in schools and higher education.For example, educational robots can help children improve their math and science skills.

The market demand is huge.With the transfer of global manufacturing, China has become one of the largest robot markets in the world. According to the data released by the Ministry of Industry and Information Technology, in 2020, the output of robots in China reached 242,000, and the sales revenue reached 51.1 billion yuan, up 8.5% year-on-year.

Low cost advantageCompared with Europe, America and other countries, the production cost of robots in China is lower, especially in the fields of processing and system integration.

Wide range of application scenariosChina robots have a wide range of applications, not only in traditional manufacturing, but also in services, health care and other fields, such as hotel reception, family support, surgery assistance and so on.

A fast-growing industryThe government’s support for the robot industry is one of the favorable factors for the development of robots in China. Policy support and industry innovation have continuously promoted the rapid development of robot industry in China.

The development prospect of robots in China is in a stage of rapid growth and expansion, and it is very likely that this trend will remain in the future. Here are some reasons:

Huge market demandWith the advancement of industrialization and the aging of the population, the demand for robots is increasing in the fields of manufacturing, medical care and service.

High technical levelChina is rising rapidly in science, technology and manufacturing at an alarming rate. With the introduction of advanced technology, the robot industry in China has also developed rapidly.

Comprehensive policy supportThe government is committed to providing all kinds of financial support for enterprises and encouraging more enterprises to invest and participate in the development of robots.

Innovative environmentAt present, the domestic robot industry has formed an innovation ecosystem, including research institutions, manufacturers, integrators, application services and other chains.

Accumulate rich experienceIn recent years, China robot enterprises have developed their business in overseas markets, gathered many excellent technical talents and R&D personnel, and accumulated rich experience and knowledge.

Based on the above reasons, the robot industry in China will develop at a high speed in the future, and at the same time, it will promote the progress of the whole intelligent manufacturing industry, thus comprehensively promoting the transformation and upgrading of China’s economy.

The robot industry in China is one of the most popular investment fields at present, but whether it is worth investing needs specific analysis. Here are some reference factors:

market prospectThe robot market in China is huge and has great potential for future development, which is a long-term and sustainable trend.

policy supportThe state has great support for the promotion of intelligent manufacturing and robot industry, and supports it in various policy forms, such as tax policy and financial subsidies.

Competition patternAt present, the competition in the robot industry in China is fierce, especially the competition between domestic enterprises and foreign brands in the market, which requires careful consideration of their respective advantages and disadvantages.

investment riskThe technology in this industry is changing rapidly, and the market share is uncertain. Therefore, investment needs to consider the sustainability of business model and control the risks.

Generally speaking, when investing in the robot industry in China, we should pay attention to the overall operation and financial situation of the corresponding enterprises, and at the same time pay attention to the impact of the global economic situation on the development and investment of the industry.

In a word, with the continuous promotion of new technologies and innovations in China, the coexistence of robots and humans will become closer in the future. China robot has strong competitiveness and market potential due to its large market demand, low production cost, wide application scenarios and government policy support.

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