Looking for dark matter, machines are better than human eyes. A recent paper published in Computational Astrophysics and Cosmology shows that the deep learning AI framework jointly developed by Lawrence Berkeley National Laboratory (hereinafter referred to as Berkeley Laboratory) can explore the signs of dark matter in the universe.

　　In recent years, artificial intelligence has been increasingly applied to astronomical research. Deep learning requires massive amounts of data, and astronomy is the field where AI shows its talents. Machines can find a needle for human beings from the vast ocean and capture new stars, new extraterrestrial planets and even dark matter.

　　Recognizing the "gravitational lens", AI has made contributions.

　　Finding "gravitational lens" is the basic method to study the distribution of dark matter. An object with a huge mass will distort the passing light like a lens, and if we find out this distortion, we can capture the non-luminous mass.

　　The paper shows that CosmoGAN, a deep learning AI framework established by Berkeley Lab, can analyze the relationship between gravitational lens and dark matter. It can create high fidelity and weak gravitational lens convergence diagram.

　　Once upon a time, it was troublesome to find the simulation and data processing needed for the "gravitational lens". Twenty scientists spent months looking at only a small space image. Physical simulation takes billions of computing hours and takes up megabytes of disk space.

　　The progress of neural network provides opportunities. The team led by Berkeley Lab introduced a "generative confrontation network (GANs)". Researcher Mustafa said: "There are other deep learning methods that can get convergence graphs from many images, but compared with competitive methods, GANs generates very high-resolution images while still having the high efficiency of neural networks."

　　Now, astronomers can use CosmoGAN to analyze a much larger sky area, and the speed is faster.

　　CosmoGAN is not the only astronomical deep learning neural network that has made progress. For example, the University of Toronto used deep learning technology to analyze satellite images of lunar craters, and the neural network of P8 supercomputer discovered 6,000 new craters in just a few hours, twice the number of craters discovered by humans in the past decades. The University of Illinois at Urbana-Champaign uses deep learning to detect and analyze gravitational waves of black hole collisions. AI blooms everywhere in astronomy.

　　There is too much data to play without a machine.

　　In the past few years, most directions in the field of astronomy have tried to use artificial intelligence. Considering the amount of data that astronomy has to deal with, this is a natural idea. Let the machine practice to analyze clues, otherwise, astronomy in the future will not work.

　　The 2019 GPU Technology Conference held not long ago attracted artificial intelligence scholars all over the world. Brent Robertson, an astronomer from the University of California, Santa Cruz, was invited to give a speech at the conference. He pointed out: "Astronomy is at the cusp of a new data revolution". Robertson believes that the new generation of astronomical instruments must cooperate with the new generation of software driven by deep learning.

　　For example, the large-caliber all-day patrol telescope (LSST) is expected to run in three years. It toured 37 billion galaxies in the southern half of the universe, generating a ten-year uninterrupted video. LSST is equipped with a 3.2 billion pixel camera, which generates 25TB of data every night, which is equivalent to all the data contributed by the advanced astronomical telescope in a lifetime.

　　Another example is the Square Kilometer Array Radio Telescope (SKA). It is spread all over the world, some antennas are deployed in eight countries in southern Africa, and more than one million antennas are located in Australia and New Zealand. Its raw data reaches 5000 PB every day, and there are about 50 PB after processing.

　　"Dark Energy Survey" compiles star maps of hundreds of millions of galaxies; "Gaia" satellite surveying and mapping stars with galactic coefficient of one billion; The "Zwicky" project can scan 3,750 square degrees of sky every hour. In China, the daily data volume of FAST will reach 150TB；; Guo Shoujing telescope has observed 9.01 million spectra, which is the largest celestial spectrum library in the world … …

　　Capture patterns that humans can’t see.

　　There are more and more data, and scientists try to aggregate them. However, at the GPU conference, Robertson said that in the future, several large astronomical telescopes will produce a large amount of data together, which is too complicated for human beings to directly use after aggregation. Scientists at the University of California, Santa Cruz, tried to solve this problem. Morpheus deep learning framework created by a doctoral student in computer science department can classify celestial bodies pixel by pixel based on the original data of telescope.

　　Scientists at the University of California, Santa Cruz, also use AI to better study the formation of galaxies. In a study published in early 2019, scientists trained computers with computer-simulated galaxies to learn three key stages of galaxy evolution. Later, computer analysis of galaxy images from the Hubble Space Telescope performed surprisingly well.

　　Artificial intelligence is applied to face recognition. After training with massive data, you can recognize this person’s makeup and old age according to a photo. And many images in the universe can be classified in the same way.

　　"Deep learning can look for patterns, and machines can see very complicated patterns that humans can’t see." David Ku, a scientist involved in the research, said, "We hope to further test this method. In the proof-of-concept study, the machine seems to have successfully found the different stages of galaxy evolution determined in the simulation in the data. "

　　Help astronomers find another solar system

　　A report at the end of 2018 showed that Google artificial intelligence made efforts to find new planets from Kepler’s exoplanet observation database. Planets are hard to find. Kepler satellite in space observes 145,000 sun-like stars, and finds planets from the faint changes of star brightness. The data recorded for four years includes about 35,000 suspected planetary records. Astronomers use machines combined with human eyes to identify, but the darkest and weakest signals are often ignored.

　　With the help of Google AI, we discovered two new planets, Kepler 90i and Kepler 80g. Kepler 90 was also recognized as the first exogalaxy with at least eight planets.

　　Neural network and machine learning processed 14 billion data points, and then successfully screened out candidates.

　　NASA and Google say that new technologies will find more exoplanets in the future. NASA also said that there is no need to worry about astronomers losing their jobs. Jesse Dotson, a scientist at NASA, explained that astronomers need to classify data before they are provided to neural networks, so that artificial intelligence can learn and analyze new information from them.

　　Dotson said: "AI will definitely work with astronomers in the future and become an indispensable tool."

　　Of course, machine learning also brings the risk of "black box": we get the answer, but we don’t know why the machine makes such a judgment, and maybe the answer is wrong. Machines make mistakes. Astronomers will continue to train and adapt to it.

　　Extended reading

　　Expert comments

　　Deep learning does not have "physical intuition"

　　Indeed, artificial intelligence has now penetrated into all branches of astronomy and astrophysics. At present, Lawrence Berkeley National Laboratory in the United States can quickly judge the basic cosmological constants such as dark matter and dark energy according to the three-dimensional density distribution of the universe by using deep learning. They found that after applying artificial intelligence, the statistical error is much smaller than that of the traditional statistical methods. In addition, we also use deep learning to search for hydrogen and carbon elements in the early universe in the spectrum with extremely low signal-to-noise ratio, and find that it is better than the traditional method.

　　At the same time, astronomers are also applying deep learning to help us judge the three-dimensional position and distance of celestial bodies, and then outline the large-scale structure of three-dimensional space. It is found that deep learning may be stronger than the traditional methods we used before in mining data and information. Artificial intelligence has also been applied to the field of detecting exoplanets by Google, and several exoplanets … … It can be said that artificial intelligence is now widely used in the frontier field of astrophysics.

　　But from the physicist’s point of view, artificial intelligence based on deep learning may also have its limitations. This limitation is that it can only play a role in a specific field that has been very clearly defined based on data. Only under the guidance of physicists, we can make the error bar of statistics smaller and estimate a certain quantity more accurately, but at present we can’t guide us to discover the new physical laws behind the data. Nor does it have a "physical intuition" based on beauty, symmetry and simplicity that is unique to humans.

　　To give a simple example, for example, Kepler’s observation data based on Tycho can find Kepler’s third law, and even the best machine learning and artificial intelligence algorithms at present may be difficult to repeat this discovery based on the same data.

　　Therefore, I think that the essence of the application of deep learning in astronomy is still limited to doing better statistics and fitting.

　　(Professor Cai Wei, Department of Astronomy, Tsinghua University)

1905 movie network news The fantasy action adventure film directed by a series of directors and supervised by the producer is being shown in the country, with a cumulative box office of 756 million. With the fermentation of the film’s good reputation and the heated discussion on the hidden details, it has become a craze for the audience to brush the film twice, three times or even n times.

Many viewers chose IMAX version in the second brush, which better felt the visual feast of blood and light in the different world and the auditory impact called "intracranial massage". Under the blessing of the big screen and the immersive sound system, the audience shared, "IMAX 3D version is completely the feeling of exploding the audience. The modeling and scenes are spectacular, and the sound effects are superb. It is simply a great value to enjoy such an audio-visual feast."

9 brush audience certification, IMAX version of excellent audio-visual

Netizen: Various sound effects are simply the gospel of sound control.

The excellent audio-visual effect praised as "domestic ceiling" in the film attracts the audience to enter the cinema again and again, and the sound effects with great sense of design and penetration have also become the focus of audience discussion. The sound effect of wiping the knife with empty words by teenagers and wielding the knife when Black Armor fights the mob are all called "voice-controlled gospel" by netizens, and they said excitedly, "No one can refuse such a sound, and I am willing to watch the movie ten times for this sound effect."

Not only that, but the drums when Kongwen entered the Red-haired Ghost Palace were also impressive. "I can feel that people around me dare not breathe, and I was completely brought into the movie by that voice." And a netizen who has brushed 5 in various cinemas will get a better audio-visual experience in IMAX cinemas. "It will be more obvious for Lu Kongwen to hear the looming" Song of Little Oranges "in the field. A 9-brush audience also excitedly said that" IMAX effect is really different! Be sure to see IMAX! " .

"Two faces" is full of surprises

Audience comment: Please ask Dong Zijian to film every day for 365 days.

In the film, Dong Zijian plays the novelist Lu Kongwen and the juvenile Kongwen. Faced with the role challenge of one article and one martial art, Dong Zijian also handed over the answer sheet that satisfied the audience. "The subtle similarities and differences in the characteristics of the two roles are vividly displayed, and the acting skills are so good that Dong Zijian is invited to film every day for 365 days." There is also the audience’s subtle observation, and they feel the acting skills from their eyes. "Dong Zijian’s pure, angry and resentful eyes make the role full, and hit the floor".

In addition, the novelist’s strong sense of belief also deeply touched the audience. "Dong Zijian brought the seemingly decadent novelist who is actually strong in heart to life", "Seeing him stubbornly say,’ No matter what others say, I believe I can do it’, I feel my eyes are wet".

"The decade since the 18th National Congress of the Communist Party of China has witnessed the greatest scientific and technological progress and the fastest improvement in scientific and technological strength. China’s scientific and technological undertakings have undergone historic, holistic and structural changes, successfully entered the ranks of innovative countries and fully integrated into the global innovation network, showing the overall layout and development trend with the characteristics of the new era."

On May 12th, Tommy, Vice Minister of Science and Technology, made the above summary on the development of science and technology at the press conference on the theme of "China this decade" held by the Propaganda Department of the CPC Central Committee.

In the past ten years, from innovation as the first driving force for development, to fully implementing the innovation-driven development strategy, to insisting on putting scientific and technological innovation at the core of the overall national development, and to taking scientific and technological self-reliance as the strategic support for national development, the road of independent innovation with China characteristics has become wider and wider.

The strength of science and technology has risen rapidly.

Statistics show that the total R&D expenditure in China is 2.7 times that in 2012, and the basic research expenditure is 3.4 times that in 2012. China’s global innovation index has risen by 22 places in ten years, making it the only country in the world that keeps rising rapidly.

All-round development, outstanding characteristics and quality improvement … In the past decade, science and technology have become the first driving force to support and lead China’s high-quality economic development and improve people’s livelihood.

Tommy summed up the important characteristics of China’s scientific and technological development in the past ten years-

The level of scientific research and the overall strength of the discipline have greatly increased. Several disciplines have reached the international leading level, and the research and development capabilities of scientific research institutions, universities and leading scientific and technological enterprises have obviously increased in the global position. There were less than 50,000 high-tech enterprises ten years ago, but now there are 330,000. Beijing, Shanghai and Guangdong-Hong Kong-Macao Greater Bay Area, three major international science and technology innovation centers, have all entered the top 10 in the ranking of global science and technology innovation clusters.

Produce a number of world-class scientific and technological achievements in the fields of basic research and strategic high technology. The exploration of Mars by Tian Wen, the landing of Chang ‘e on the moon, the successful docking of the core modules of Shenzhou XIII and Tianhe have made a great leap in China’s deep space exploration. The successful development of "Deep Sea Warrior", "Struggler" and "Haidou No.1" indicates that China has the ability to detect the depth of 10,000 meters in the whole sea. In the field of quantum science and technology, China has become the only country in the world that has reached the milestone of "the superiority of quantum computing" in two physical systems.

Independent research and development of a large number of advanced technical equipment and systems into practical use has become a "sharp weapon" to promote rapid industrial upgrading. Supercomputing, high-speed railway, smart grid, fourth-generation nuclear power and UHV transmission technology have all entered the world’s advanced ranks. In particular, the deep expansion of 5G R&D and application scenarios, and the initial establishment of China’s characteristic ecology for the development of artificial intelligence are accelerating the empowerment of all industries. With the support of large computing power and supercomputing, the digital economy is booming, and a number of smart cities, smart factories, intelligent medical care and intelligent transportation are taking shape.

At the same time, the number of original new drugs developed has increased significantly compared with ten years ago, and a variety of COVID-19 vaccines, detection reagents and therapeutic drugs have strongly supported the prevention and control of the COVID-19 epidemic; In the front line of poverty alleviation and rural revitalization, a large number of science and technology commissioners played an important role; The application of more than 200 achievements of "Science and Technology Winter Olympics" has strongly supported the high-quality hosting of the Beijing Winter Olympics …

"Of course, we are also clearly aware that compared with the world’s leading countries, China’s scientific and technological innovation still has a long way to go." Tommy said that facing the future, China’s scientific and technological circles will face up to problems, face up to difficulties and make unremitting efforts to build a world science and technology power.

System reform was accelerated.

Since the 18th National Congress of the Communist Party of China, the CPC Central Committee has placed innovation at the core of the overall development of the country, unswervingly followed the road of independent innovation with China characteristics, and made full efforts to reform the scientific and technological system.

"The reform of the science and technology system has always been regarded as the focus of comprehensively deepening reform." Tommy said that in the decade since the 18th National Congress of the Communist Party of China, the Central Committee for Comprehensively Deepening Reform has considered more than 20 major reform programs in the field of science and technology. So far, the 143 tasks deployed in the implementation plan for deepening the reform of the science and technology system proposed by the central government have been fully completed, and the institutional and basic framework for supporting comprehensive innovation has been basically established. Substantial progress has been made in the reform of key areas and key links, and breakthroughs have been made in some key difficulties and blocking points that have not been solved for a long time. China has set up the National Science and Technology Advisory Committee for the first time, established the National Science and Technology Ethics Committee, reconstructed the science and technology planning system, solved the problem of closed and scattered allocation of science and technology resources, and the science and technology governance mechanism is more suitable for the needs of science and technology development. The national laboratory has been built, the reorganization of the national key laboratory system has been initiated, the autonomy of universities and research institutes has been expanded, the main position of enterprise innovation has been basically established, the national strategic scientific and technological strength has been further strengthened, and a strong synergy has been formed to promote scientific and technological innovation.

In the aspect of scientific research funds, the distribution policy oriented by knowledge value is implemented, the management system of scientific and technological projects and funds based on trust is established, the evaluation orientation centered on quality, performance and contribution is established, and the incentive for scientific researchers is greatly enhanced. Through the reform of "three evaluations", the reform of project evaluation, talent evaluation and institutional evaluation has been carried out in an orderly manner, and many localities and units have explored the realization path of classified evaluation.

Following the law of scientific exploration and technological innovation, we have implemented the system of "revealing the list and taking the lead" and "horse racing" for major tasks, implemented the chief scientist responsibility system for frontier exploration projects, and set up subversive technical projects to support scientists’ bold exploration. In the "14th Five-Year Plan" national key R&D plan, young scientists are generally set up, so that more young scientists can take the lead and take the lead, which has been widely welcomed. In addition, it also gives scientists greater decision-making power on technical routes and the right to use funds, freeing researchers from the cumbersome and unnecessary institutional constraints.

In order to solve the long-standing problem of the transformation of scientific and technological achievements, an important orientation of scientific and technological system reform in recent years is to speed up the establishment of the transfer and transformation system of scientific and technological achievements and open up channels among science and technology, industry and finance. To this end, the reward for the transformation income of scientific and technological personnel has been greatly increased, the right to use, dispose of and benefit from scientific and technological achievements has been fully decentralized, and a pilot project has been carried out to give scientific and technological personnel ownership and long-term use rights.

Established a relatively complete inclusive policy and institutional arrangement to encourage enterprise innovation. The deduction ratio of R&D expenses of enterprises has increased from 50% in 2012 and 75% in 2018 to 100% in the fields of technology-based SMEs and manufacturing, which reflects the orientation of supporting technology-based SMEs. At present, more than 3/4 of China’s total social R&D investment is invested by enterprises, and 79% of the national key R&D plans are led or participated by enterprises.

The technology trading market continues to grow, and the activity of the technology trading market reflects the activity of the transfer and transformation of achievements. Last year, the national technology contract transaction volume reached 3.7 trillion, far exceeding the R&D investment of the whole society in that year and 5.8 times that of 2012.

In the capital market, the establishment of science and technology innovation board, the reform of the Growth Enterprise Market, the establishment of the North Stock Exchange, and the smooth channels for direct listing and financing of hard technology enterprises are forming a virtuous circle of mutual shaping of science and technology, industry and finance. In the past, weak ties, where science, technology and economy were amplified by the participation of financial and capital markets, has become a strong coupling now.

"To achieve high-level scientific and technological self-reliance and self-improvement, China depends on high-level innovative talents in the final analysis." Tommy said that in the next step, the Ministry of Science and Technology will, in accordance with the deployment of the CPC Central Committee, take the implementation of the three-year plan for tackling key problems in scientific and technological reform as the main line, pay close attention to implementation, stimulate the innovative vitality of all kinds of talents, and make more researchers with real talents and practical knowledge available.

　　Recently, Gamma Data released the Monthly Report of China Game Industry in January 2024 (hereinafter referred to as the report). The report shows that in January 2024, the actual sales revenue of China mobile game market was 17.687 billion yuan, down 4.17% from the previous month and up 0.39% year-on-year. Wang Xu, chief analyst of China game industry, said that there are two main reasons for the year-on-year growth this month. First, some old products that have been online for several years have achieved revenue growth. Second, some new tours launched this month have brought increments.

　　In January, 2024, the number of mobile game products increased, with some products increasing by over 1 billion yuan, and the share of self-propelled chess in TOP50 increased by 217% year-on-year. Wang Xu said that competitive products are an important source of market revenue growth this month, and such products are more likely to grow during long holidays, such as the cold and summer holidays, the Spring Festival holidays and the time periods before and after.

　　In January, the share of self-propelled chess games in TOP50 mobile games increased by 5.8%, up by 217% year-on-year. The growth was mainly driven by some products. At the same time, some self-propelled chess products entered the gamma data flow calculation list TOP2 this month, which is also the highest ranking of this product so far. Its growth is mainly due to the fact that this kind of products update their seasonal activities in January and update the collection and shopping mall simultaneously. In addition, Wang Xu emphasized that the share of interactive drama has also increased this month. This type has sprung up in recent years, and the sales volume on steam has also continued to grow. In the future, more similar products will be put into the market. The deeper reason is the change of user demand.

　　In the new tour, the report analyzed the advertising of some new tour products, and the advertising of such products was mainly concentrated on the day of launch, and remained at the TOP15 of the best-selling list of iOS games within the statistical date. Some products have also obtained a high ranking in terms of overseas downloads.

　　According to 21st century business herald, the reporter noted that the Tianjin Municipal People’s Government issued the "Proposal on Further Promoting the Construction of Financial Innovation Operation Demonstration Zone" on January 8. The plan points out the overall goal of the future in three time periods: in the next three years, it will continue to maintain the leading position in the financial leasing and commercial factoring industries in China, and at the same time create a number of financial agglomeration symbol areas with themes and characteristics. In the next five years, the added value of the financial industry will account for about 15% of the regional GDP, and the overall asset scale of leasing will reach 2.7 trillion yuan. The scale of leasing and disposal of aircraft, international shipping vessels and offshore platforms will remain above 80% in the whole country, and the total assets and factoring financing balance of the commercial factoring industry will remain the first in the country. In 2035, a world-class national leasing innovation demonstration zone and a national commercial factoring capital will be built in an all-round way, which will provide a practical sample for China’s characteristic financial development.

As a commentator, Mr. Huang appeared on XXTV-5 in the early 1990s, and Huang and Liu and Zhang Sanjianke created the column of World Football, which made us look forward to every Monday when we were studying in Beijing. My last impression was that I co-hosted the 2002 Japan-Korea World Cup with Shen Bing in 2002.

Later, it is said that he joined the media and became the online celebrity of football. With his football level, he should be able to dominate one side, and entertainment football can flourish off the court. Should be blessed, although the age difference is not big, but after all, watching his program has a beard.

Another master’s corner, I really don’t know. I know it by chance because of a technical term of "protective response" That is, online celebrity, who wears sunglasses and bobs his head to catch and scold anyone on the Internet, is said to know the way and know the king better than the beautiful country and Sichuan.

Because of the big sunglasses, I knew that I had a football teenager. Frankly speaking, we are not football professionals. Although big sunglasses preached everywhere that he was engaged in youth training, we always felt that it was at best a football training class and an off-campus training class.

It seems that the relationship between the two is not bad, and they have been entertaining to death, and they are also connected to each other live. I don’t know about it recently, maybe Mr. Huang has seen through the scam; Perhaps the head of the new Football Association named the big sunglasses, and Mr. Huang wanted to raise his arms and shout for the sake of his inner conscience.

Mr. Huang finally decided that junior football is a performance class in online celebrity. Zhan Yan, it’s worse than us, and we also evaluate it as teaching and training.

Big sunglasses know the king, how can you stop? Come on, bully me, no way. Although we are not studying literature, we are studying inorganic materials. We’re not subtle. What do you think you came from? Leave that station, you’re nothing, and you’re a bitch.

Football in China, what is this situation? In a rural phrase, that is: dogs eat dog bones.

China football, when can you get clean and let a certain line really "do it"?

This time, I am optimistic about Mr. Huang, just because I follow my heart and my heart.

Generative AI is getting more and more popular. Is this really a good business?

Recently, AI painting is on fire.

By inputting some words, AI can generate an image that matches the words in a few seconds. These images are wild, and some are even bizarre. For example, people have extra fingers on their hands, and their fingers bend unnaturally. Even, AI can generate some meaningless billboards and alphabets that humans have never seen before.

Although AI painting is outrageous, it has set off a wave of science and technology: the spring of generative AI has come.

David Beisel, a venture capitalist at NextView Ventures, said that in the past three months, the word "generative AI" once became a hot word. Moreover, the generative AI technology has developed rapidly and the market enthusiasm is so high that many people even quit their jobs to start a business in this field.

There is no doubt that AI has been in a prosperous stage in the past five years or so, but most of these past advances have to do with understanding the existing data-for example, the AI model has been able to quickly and efficiently identify whether there are only cats in your mobile phone photos. However, the generative AI model generates something completely new that has never been seen before. In other words, generative AI is not just about analyzing existing data, but creating.

Boris Dayma, founder of Craiyon generative AI, believes that "generative AI is not only creating old images, but also creating many new things, which are completely different from what we have seen before."

Sequoia Capital also said in a blog post on its website: "Generative AI has the potential to create trillions of dollars in economic value." Sequoia Capital predicts that generative AI may change all industries that require human beings to create original works, from games to advertising to the legal profession. It is worth mentioning that Sequoia Capital also pointed out in its blog post that this message was partly written by GPT-3 (GPT-3 is a generative AI capable of generating text).

Working principle of generative AI

In the past, deep learning technology was widely used to train the model on large data sets. When the program understands the relationships in these data, the model can be applied to actual scenes, such as identifying whether there is a dog in a picture or translating text, and so on.

The working principle of the image generator is to reverse this process. For example, instead of translating English into French, it translates English phrases into images. Specifically, it usually has two main parts, one is to process initial phrases, and the other is to convert data into images.

At first, generative AI was based on a method called GAN, that is, the generative adversarial network. In essence, this method is to make two artificial intelligence models compete with each other to better create images that meet the target.

At present, generative AI is usually based on Transformer, such as image generator DALL-E and so on. DALL-E was first created by OpenAI in 2021, and in 2022, OpenAI released DALL-E 2.

Christian Cantrell, a developer who focuses on generative AI, said: "With DALL-E 2, we can really cross uncanny valley." (The Valley of Terror theory is a hypothesis about human perception of robots and non-human objects. It was put forward by Japanese robot expert Masahiro Mori in 1970. )

Another commonly used AI-based image generator is Craiyon (formerly known as DALL-E Mini), where users can enter phrases in the browser and see the illustrations it generates within a few minutes.

According to Dayma, since its launch in July 2021, Craiyon has produced about 10 million unprecedented pictures every day, which adds up to 1 billion. Earlier this year, the use of Crayon soared, and Dayma also took Crayon as its full-time job. In addition, Dayma has created a Twitter account to post the weirdest and most creative pictures generated by Craiyon. For example, ketchup comes out of the tap on the Italian sink.

In addition, Stable Diffusion has also received wide attention. The project was released in August this year and has been open source on GitHub. Developers can run the project on computers, not just in the cloud or through programming interfaces. For example, Stable Diffusion can be integrated into Adobe Photoshop by plug-in, allowing users to generate backgrounds and other parts of images, and use layers and other Photoshop tools to operate in applications.

Cantrell, the developer of the plug-in, said, "I want to meet these creative professionals, so that they can introduce artificial intelligence into their creative work, instead of destroying their work."

It is understood that Cantrell has worked for Adobe for 20 years. After leaving in 2022, Cantrell focused on the direction of generative AI. Cantrell said that Stable Diffusion has been downloaded tens of thousands of times, and artists told him that they used this plug-in in many unexpected places, such as making Godzilla animation or creating pictures of Spider-Man.

Start-up companies get together

Some investors regard generative AI as a potentially transformative change, just like the early development of smart phones or the Internet. This kind of transformation has greatly expanded the potential market of this technology.

"Before that, artificial intelligence was not unprecedented. Before 2007, we were not without mobile devices, "said Beisel, a seed investor." But at this moment, everything came together. The final consumer can experience and see something different from before. "

Cantrell believes that machine learning is similar to a more basic technology: database. "Machine learning is a bit like a database, which opens up a whole new world for network applications. All the applications we have used in our life are built on the database. But no one cares about how the database works. People only know how to use it. "

Michael Dempsey, managing partner of Compound VC, said that in the past, it was "very rare" for laboratory technology to enter the mainstream, but at present, generative AI has attracted wide attention of venture capitalists. Nevertheless, he warned that the current generative AI may be in the "curious stage" near the peak of the hype cycle, and the companies established at this stage may fail because they don’t focus on the specific uses that enterprises or consumers are willing to pay for.

Others in the industry believe that startups that can apply new technologies such as generative AI today may challenge technology giants such as Google, Meta and Microsoft in the future.

At present, many companies applying generative AI technology have already received large amount of financing, and their valuations have also risen. For example, earlier this year, Hugging Face was valued at $2 billion after receiving investments including Lux Capital and Sequoia Capital; OpenAI has also received more than $1 billion from Microsoft and Khosla Ventures.

In addition, according to Forbes, Stability AI, the developer of Stable Diffusion, is negotiating with investment institutions to raise up to $1 billion in venture capital.

Cloud vendors and chip vendors will benefit.

Besides start-ups, cloud service providers such as Amazon, Microsoft and Google can also benefit from it, because generative AI may require a huge amount of computation.

Meta and Google have also taken action and started recruiting talents. In September of this year, Meta released an artificial intelligence application called "Make-A-Video", which can generate videos, which makes the generative AI technology a step further.

"This is a great progress," Zuckerberg, CEO of Meta, posted on his Facebook page. "It is much more difficult to generate videos than photos, because besides correctly generating each pixel, the system must also predict how they will change over time."

Recently, Google matched with Meta and released a program code called Phenaki, which can also convert text into video and generate several minutes of footage.

This craze may also boost chip manufacturers such as Nvidia, AMD and Intel, because the advanced graphics processors produced by these companies are ideal for training and deploying artificial intelligence models.

At a recent meeting, Huang Renxun, CEO of Nvidia, emphasized that generative AI is the key use of the company’s latest chip, and he said that this kind of program may "revolutionize communication" soon.

At present, there are not many uses of generative AI that can generate commercial benefits. Many exciting breakthroughs today come from free or low-cost experiments. For example, some writers have tried to use image generator to generate images for articles. An example of Nvidia is to use a model to generate new 3D images, including people, animals, vehicles or furniture, which can be filled into the virtual game world.

Ethical issues can not be ignored.

While generating AI excites the industry, the ethical issues it brings are also worthy of attention.

The first is employment. Compared with professional illustrators, generative AI is obviously cheaper. Therefore, generative AI is likely to rob artists, video producers and other people engaged in creative work of their "rice bowls".

In addition, there are complex problems in originality and ownership of the content created by generative AI.

Generated AI is trained on a large number of images. Therefore, it is still controversial whether the creator of the original image has copyright requirements for the generated new image.

Some time ago, an artist won an art competition in Colorado, and his winning image was created by a generative AI named MidJourney. After winning, the artist said in an interview that he selected one image from hundreds of images generated by himself and post-processed it in Photoshop.

It is worth mentioning that some images generated by Stable Diffusion are watermarked, which indicates that some of the original data sets are copyrighted. Previously, Getty Images (a picture trading company based in Seattle, USA) announced that it was forbidden for users to upload generated AI pictures to its picture library, because the company was worried that there might be some copyright problems in such pictures. .

With the improvement of image generation software, generative AI may also deceive users, make them believe false information, or display images or videos of events that never happened.

In addition, developers must also deal with the possibility that models trained on a large amount of data may have biases related to gender, race or culture contained in the data, which may cause the models to show such biases in their outputs.

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Source: AI Frontline, author: Kif Leswing. If there is any infringement, please contact to delete it.

In recent years, with the promotion of market demand, AGV handling robot has gradually matured. The continuous maturity of Beidou navigation and the continuous development and application of artificial intelligence in China have greatly improved the efficiency of AGV handling robots, provided great conditions for saving manpower, and made AGV handling robots gradually become the choice for automation upgrading of major factories in various industries.

In today’s era, with the continuous development of world trade, transnational logistics and logistics in various industries can’t do without handling. With the wide application of the Internet, big data and artificial intelligence, intelligent automated unmanned AGV handling robots are constantly developing and innovating, which promotes the continuous upgrading of China’s logistics industry and reforms the current industrial form.

With the growing manufacturing industry in China, China has introduced new measures to promote the development of intelligent industrial robots through the cooperation of Industrial Revolution 4.0 and enterprises, in order to enhance the strength of the manufacturing industry and cultivate competitive advantages. Unmanned AGV handling robot is one of them.