Artificial Intelligence Booming Year Is Behind Us: What's Next in the AI Industry?


Artificial Intelligence, Robot, Booming Year, AI Industry

Artificial intelligence-based tools for image, text, sound and content creation in general marked the year 2022.


The year 2023 brings a handful of opportunities, but also challenges. What artificial intelligence is expected to bring us by the end of 2023, find out below!


More artificial intelligence apps, more problems


After the success of Prisma Labs’ selfie app Lensa, we can probably expect a lot of similar apps.


At least some of them – if not all – will be able to be tricked into creating images that are not for showing colleagues at work, and excessive sexualization and changing the appearance of women will continue to be a problem.


The expected integration of generative artificial intelligence into consumer electronics will only amplify the current good and bad aspects.


However, 2023 should be the year during which generative artificial intelligence will finally shine. But in order for that to be possible, it will have to either start bringing in a lot of money, or have a meaningful impact on the everyday life of the public.


It is to be expected that there will be attempts in both directions, with variable success.


Artists will seek exemptions


DeviantArt has released an AI and Stable Diffusion based art generator, customized for its community’s artwork. The move was met with loud opposition from long-time users of the service, who criticized it for the lack of transparency surrounding the use of works of art to train artificial intelligence systems.


The creators of the most popular systems – OpenAI and Stability AI – say they have taken steps to limit the amount of harmful content their systems produce.


But, judging by what appears on social networks, it seems that there is still a lot of work to be done in that segment, which will require the participation of the people whose work is being used.


Stability AI has already bowed to public pressure and indicated that it will allow artists to be denied permission to use their work when training the next generation of Stable Diffusion.


Those who wish to do so will be able to do so in a few weeks at


OpenAI does not currently offer such an option, preferring to partner with organizations such as Shutterstock to secure licenses to use parts of their catalogs.


But, it wouldn’t be strange if they soon followed the same path as Stability AI.


It is possible that, in the end, they will be forced to do so by court decisions.


In the United States, a joint lawsuit has already been filed against Microsoft, GitHub and OpenAI for copyright infringement by allowing Copilot, GitHub’s service that suggests which lines of computer code should be written, to use parts of licensed code without disclosing who wrote it.


At GitHub – perhaps precisely because they anticipated legal problems – they recently added settings that prevent the display of publicly available computer code in Copilot’s suggestions.


They also plan to introduce a feature that will show where the suggestion came from.


However, both of these measures currently do not guarantee that the failure will not occur.


Open source and decentralization will continue to grow


During the year at the end, only a handful of companies dominated the artificial intelligence stage, led by OpenAI and Stability AI.


However, during the next year, more new challenges could appear because the creation of new systems could become available outside specialized laboratories rich in resources.


If such a development occurs, it is possible that we will witness stricter supervision of the system being built and implemented.


An example of such efforts are, among others, the large language models produced by EleutherAI and Big Science, which is behind the startup Hugging Face.


Stability AI has launched several such communities, such as Harmonai (for music generation) and OpenBioML (biotechnological experiments).


Money and know-how are still needed to train and run sophisticated AI models.


ChatGPT’s chatbot is estimated to cost around US$3 million a day to operate.


But decentralized computing could throw down the gauntlet in the face of traditional data centers as open source computing projects mature.


BigScience has taken a step in this direction with the recently launched Petals project, where people can lend their computing power (similar to Folding@home) to run large language models that would otherwise require an advanced graphics card or web server.


Large laboratories will continue to have an advantage as long as the methods and data remain their property.


Pressure from regulatory bodies will increase


Regulation such as the European Union’s Artificial Intelligence Act could change the way companies develop and implement artificial intelligence systems in the future.


Regulation and increased supervision are necessary because generative artificial intelligence is still prone to errors, so it is not advisable to apply it in areas where it could cost a lot, such as healthcare.


However, artificial intelligence systems are already making decisions with serious moral and ethical implications.


Arguments over the rules and litigation should be expected before the fines and indictments begin.


Artificial intelligence systems are currently divided into four risk categories, which differ in the degree of supervision and requirements they must meet.


High-risk systems (algorithms for robotic operations and determining credit rerating, for example) must be at a certain legal, ethical and technical level before they can enter the European market.


On the other hand, for low-risk systems (spam filters, computer games with artificial intelligence), it is enough to inform users that they are dealing with artificial intelligence.


It is not impossible that there will be companies that will try to push their services and platforms into that category in order to reduce costs, even though they belong to one of the riskier ones.


Will there be investments?

Artificial Intelligence, Robot, Booming Year, AI Industry

So far, investors seem willing to invest in any promising generative artificial intelligence system.


Stability AI has raised $101 million and reached a valuation of over $1 billion from investors such as Coatue and Lightspeed Venture Partners.


OpenAI is estimated to be worth $20 billion after they entered into negotiations with Microsoft for a new round of funding, after the company already invested $1 billion in them in 2019. But are they exceptions?


Apart from autonomous vehicle companies Cruise, Wayve and WeRide, and robotics company MegaRobo, the investments mainly attracted companies dealing with AI software for practical applications.


Contentsquare, which develops software for suggesting content on the web, closed a $600 million investment round in July.


Uniphore (call center software) raised $400m in February, and Highspot (real-time help for sales reps) raised $248m in January.


What Can We Expect Next in the AI Industry?


To begin with, we may anticipate continuous expansion in the usage of AI in a variety of applications.


Businesses and organizations of all sizes will try to harness AI to automate processes, make smarter choices, and enhance productivity as technology advances and becomes more accessible.


This will be especially true in fields such as healthcare, banking, and logistics, where AI can assist in optimizing complex systems and improving results for patients, consumers, and stakeholders.


Some things we may expect in the near future include a better explanation of how AI works to people in order to lessen fear of the unknown.


Numerous new inventors and scientists will undoubtedly generate many new discoveries and ideas in the field of artificial intelligence, resulting in the creation of many new job opportunities.


We may also expect continuing advancements in the development of AI algorithms and systems.


This will be fueled in part by the increased availability of data and computational capabilities, which will enable researchers to test out novel ideas and strategies.


Another issue that must be addressed is the need for more ethical and responsible AI use.


As AI gets more powerful and pervasive, there is a risk that technology will be utilized in harmful or discriminating ways.


To counter this issue, researchers and politicians must collaborate to create rules and standards for the ethical use of AI, as well as means to enforce these norms.


The future approaching us will definitely be as exciting as it is terrifying.


In order to successfully adapt to these upcoming changes, the best idea is to carefully research everything about artificial intelligence, and find a way to turn it to your advantage as soon as possible!


If you are a tech enthusiast and want to know more about the power of artificial intelligence or you want to find out ways how to make money on ai, check for daily insight on the latest developments and most useful information!


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