At a time when we are questioning the need for currency, given the explosion of Artificial Intelligence (AI), China, Brazil, and several other countries are seeking to replace the US dollar with Krypto.
Artificial intelligence poses serious threats to humanity, & to fix the challenge, we may have to revolutionize human systems today. This Society was never built to facilitate #AI. Since we moved away from the barter/exchange system to currency, which helped to maintain & extend privilege and power in the development of human civilization. The invention of currency was revolutionary, as it completely replaced the dynamic of human relations and production and created an economic system of value that resolved unfair exchanges in the Barter System. Moreover, the need for a currency system in its conception was necessary to facilitate a rapidly expanding world that was developing sophistication and science in work leading to the various revolutions – Agrarian, Industrial. As the world sped towards becoming Industrial moving from the Agrarian to the Industrial, currency may have been proven useful. But with the explosion of technology and its capabilities through AI, we are faced with another problem, how does the working class obtain it without the possibility of work? To answer this question critically may lead us to several probabilities that are not possible. This is a deep point here that we will flesh out later. Ultimately, we may have to get rid of money or currency. The dialectic of whether we live to work or work to live becomes whether we live to consume and consume to live, as technology replaces the working-class work and therefore their ability to consume and essentially to live in the new consumer society today and worse tomorrow. Social welfare will not be enough to deal with the loss of human labor and thus any currency they can obtain in order to consume and live. Already politicians politicize social programs and are busy mopping up liquidity. If you want to see how technology can upend lives and society, just visit Kensington Philadelphia. It is unlike any place you will notice in a 1st world country. De-industrialization has affected the lives of those whom society has now rendered obsolete through technology replacement that has left many dependents on opioids for escape.
Further, China, Brazil and several other countries today are ditching the US dollar for Cryptocurrency. That was always the plan, but the US caught wind of it and made a wise chess move to dismantle Bitcoin which was investing in Krypto and Silicon Valley Bank collapsed as The Chinese and the US rivals were investing in Krypto and through social media promoted Krypto. Many Americans, new investors with no sound knowledge of geo-politics and Wall-Street, started using their stimulus money and hard earned savings to invest in Krypto and bitcoin. Krypto was booming. The Chinese, Brazil, Russia, India and some other countries were hoping to weaken the US by replacing the demand and dominance of the US dollar and were even getting the support of people in the US. Little did they know how krypto was the currency that was supposed to upend the US dollar as the main and a major exchanged currency in the world. But the US acted, mopping up liquidity, cutting social programs, slowing aid, etc. limiting Americans with excess cash to invest in Krypto and forcing them back to work after COVID. Bitcoin and Krypto collapsed, and several businesses were called before the US Capitol. Many investment businesses closed, and the currency plunged. Yet China, Brazil et al are still proposing a move to replace the US dollars as their main exchange for the Krypto. Furthermore, China has been lending monies to not just low-income countries but middle-income countries such as Argentina, Turkey etc. It is hard to imagine that borrower-countries may now have to use the Cryptocurrency to repay these loans and to trade with China and other countries ditching the US dollar. However, the US dollar remains the strongest, most backed and reputable currency in the world. Nevertheless, at a time when we are questioning the need for currency, given AI, China, Brazil, and several other countries are seeking to replace the US dollar with Krypto.
Artificial Intelligence is becoming normal talk in everyday language as society becomes more sophisticated thanks to advances in technology. According to Bergur Thormudsson of Statista.com in an article entitled: Artificial Intelligence (AI) worldwide – Statistics & Facts, dated March 2, 2022 in Statista,
Artificial intelligence (AI), once the subject of people’s imaginations and the main plot of science fiction movies for decades, is no longer a piece of fiction, but rather commonplace in people’s daily lives whether they realize it or not. AI refers to the ability of a computer or machine to mimic the competencies of the human mind, which often learns from previous experiences to understand and respond to language, decisions, and problems. These AI capabilities, such as computer vision and conversational interfaces, have become embedded throughout various industries’ standard business processes. The most prominent industries for AI adoption in organizations include high tech and telecommunications, financial services, and healthcare and pharmaceuticals.
The AI ecosystem
The current AI ecosystem consists of machine learning, robotics, artificial neural networks, and natural language processing. In machine learning, programs learn from existing data and apply this knowledge to new data or use it to predict data. The field of robotics is concerned with developing and training robots. Usually, the ability of a robot to interact with people and the world follows general rules and is predictable. However, current efforts also revolve around using deep learning to train robots to act with a certain degree of self-awareness. For more on the AI ecosystem, trends, drivers, and applications, please take a look at the Statista in-depth artificial intelligence report.
Number of startup companies working in the artificial intelligence (AI) market worldwide, as of March 2016, by category
AI investment and startups
The global AI market, valued at 142.3 billion U.S. dollars as of 2023, continues to grow driven by the influx of investments it receives. From 2020 to 2022, the total yearly corporate global investment in AI startups increased by five billion U.S. dollars, nearly double its previous investments, with much of it coming from private capital from U.S. companies. The most recent top-funded AI businesses are all machine learning and chatbot companies, focusing on human interface with machines.
Where is AI heading?
The increase in AI investment is coupled with the increasing need for AI talent. Many companies have posted job opportunities for those with AI talent across IT departments, as well as in other business areas. Organizations worldwide struggle to hire for AI-related positions, emphasizing the critical demand for workers with such skills. The AI talent shortage goes hand in hand with the overall global rise in AI and machine learning use cases throughout companies. Popular applications for AI and machine learning include improving customer experience and generating customer insights, as well as the newcomer of generative AI. Given the considerable and continuous expansion of the industry, we can expect to see more of AI in the coming years.
This text provides general information. Statista assumes no liability for the information given being complete or correct. Due to varying update cycles, statistics can display more up-to-date data than referenced in the text.
Deep learning – Statistics & Facts
What is it?
Deep learning is a subset of machine learning, which is in turn a subset of artificial intelligence (AI). Machine learning is a simpler tool, wherein the programmer gives the AI a set of parameters that it follows. Increased utilization of deep learning has the potential to greatly reduce the manual work of programming parameters for AI. Across several industries, greater use of deep learning algorithms is likely to enable more efficient expenditure of programmers’ time and energy. Deep learning is most often found in virtual assistance, voice-enabled remotes, and emerging technologies such as self-driving cars. Its application requires substantial processing power, using GPUs with a high-performance capacity to handle the enormous number of calculations needed. The deep learning chip market is growing quickly, and is forecast to exceed 21 billion USD by 2027.
Revenues from the artificial intelligence (AI) software market worldwide from 2018 to 2025 (in billion U.S. dollars)
How is it different from Machine Learning?
Machine learning operates on more simplified data than deep learning, and uses structured data for its algorithms. Deep learning, however, eliminates much of the pre-processing involved with machine learning by being capable of ingesting unstructured data, such as texts, and extracting the necessary data. This also means that there is a difference in the skills required to code deep learning and machine learning. Coding capabilities for deep learning algorithms are some of the most sought-after by large organizations around the world.
What is the current state of affairs?
There are a number of real-world, deep learning applications; however, they are often hidden behind the scenes, and the average user is unaware of the complexity of the automation at work. Deep learning is used in various fields, such as financial services, customer service, and healthcare. For example, financial services rely on a large amount of analytics to predict stock trading, monitor for fraud, and aid clients in building their investment portfolios. The most prevalent sign of deep learning in customer services is in the number of AI-enabled assistants or chatbots. These are more specialized than the average chatbot that cycles through manual responses. Deep learning chatbots seek to understand if there are multiple responses to ambiguous questions. Depending on the analysis of the chatbot, it will then provide a response or route to a human agent. Healthcare is another field where deep learning has seen significant growth. Digitizing hospital records and images allows for much swifter organization and categorization of affairs, speeding up and increasing the efficiency of hospital work.
This text provides general information. Statista assumes no liability for the information given being complete or correct. Due to varying update cycles, statistics can display more up-to-date data than referenced in the text.
The worldwide market revenue for artificial intelligence is forecast to grow significantly from 2018 to 2030, although different studies suggest variations in just how much the global market size will increase by. The market research firm IDC projected that the global AI market will reach a size of over half a trillion U.S. dollars by 2024. Precedence research suggest the market will grow to over 1.5 trillion U.S. dollars by 2030.
IBM’s position in the AI market
The current AI market race is led by IBM, which holds a global market share of more than nine percent. IBM is also the leading company in terms of active machine learning and AI patents worldwide with more than 5,500 patent families as of November 2020. Next to IBM in the global AI patent race are Microsoft and Samsung, each within 500 patent families from IBM.
Artificial Intelligence (AI) market size/revenue comparisons 2018-2030 Published by Bergur Thormundsson, Jun 27, 2022
AI startups
The enthusiasm in AI technologies and their applications worldwide is leading to a growing number of AI startup and kindling existing companies’ interest in the field. The number of AI startup acquisitions has increased steadily since 2010, growing by almost fourfold between 2015 and 2018. Increases in AI startup acquisitions have been met by increases in funding of AI startups – global funding increased from over a billion U.S. dollars in 2013 to 8.5 billion U.S. dollars in the first quarter of 2020 alone.
Companies with the most machine learning & AI patents worldwide 2012-2021
As of December 2021, Tencent was the largest owner of active machine learning and artificial intelligence (AI) patent families worldwide with 9,614 families owned. In 2020, the company had claimed the leading position from Microsoft now ranked sixth with 5,821 active families owned. Baidu ranked second with just over 9,500 patent families. The statistic is based on data provided by PatentSight. The two leading companies had a lead of more than 2,100 patent families over IBM who owned 7,343 active patent families in this technology field.
References:
1. Nils-Gerrit Wunsch, Companies with the most machine learning & AI patents worldwide 2012-2021, Statista, June 2022.
2. Bergur Thormundsson, Jun 27, 2022, Companies with the most machine learning & AI patents worldwide 2012-2021, Statista.
3. – – – – – – – – – – – – – – – , Jan 11, 2023, What is the current state of affairs? Statista.
4. ———————————-, Mar. 3, 2023, Artificial Intelligence (AI) worldwide Stats and Fact, https://Statista.com
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