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ARK Invest, an investment firm, released its annual analytical report titled “Big Ideas 2023” on January 31. The report provides a comprehensive analysis of advanced technologies and their growth prospects up to 2030. Within the report, ARK Invest’s analysts assessed various industries such as robotics and automation, digital wallets and blockchain, electric vehicles and charging infrastructure, as well as space flights and molecular research.
The development of technology and forecasts
Artificial intelligence and neural networks are at the forefront of the company’s future technological advancements. They are expected to act as catalysts for growth in other industries, including autonomous vehicles, intelligent devices, robots, cloud services, and molecular research. A visual representation of this concept is illustrated in the accompanying image, where the size of the circle corresponds to the potential market size, with larger circles representing larger markets. The lines connecting the circles demonstrate how one technology can stimulate the development of another.
An instance of this is the connection between neural networks and autonomous vehicles, where the thick purple line denotes that the advancement of neural networks will play a major role in the progress of autonomous mobility. Conversely, the thin green line in the opposite direction represents that the advancement of autonomous mobility will also have a positive impact on neural networks, albeit to a lesser degree.
A recent breakthrough in the field of artificial intelligence involves the use of neural network-based chatbots. OpenAI, an American company, introduced its universal chatbot, ChatGPT, in November 2022, which is capable of coding, answering queries, generating poetry and scripts. By early February 2023, ChatGPT had garnered 100 million users, making it the fastest growing application in the world, achieving this milestone in just two months. To provide context, TikTok took nine months, while Instagram took two and a half years to reach this level of adoption. A Bloomberg article about the success of ChatGPT calls its performance “indistinguishable from magic.”
The cost of training AI has declined by 90% over the last two years, now amounting to $450,000, and ARK Invest projects that it will further decrease to $30 by 2030, enabling the deployment of this technology universally to enhance labor productivity. With a generative neural network, creating images takes less than a minute, and the cost of a finished image is below 8 cents. On the other hand, a person takes approximately five hours to perform comparable work, and it costs at least $150.
A finished image can be created by a generative neural network in under a minute and at a cost of less than 8 cents. In comparison, a person would require around 5 hours to accomplish the same task, costing at least $150.
Employing a neural network for coding tasks can decrease the time it takes to complete them by 55%. Thanks to the reduction in training expenses, the productivity of programmers is predicted to increase tenfold by 2030. According to ARK Invest’s research, the implementation of artificial intelligence is anticipated to enhance the productivity of knowledge-based workers by more than four times by 2030.
The U.S. Bureau of Labor Statistics forecasts that 19 out of 30 professions that will experience job losses by 2030 will do so due to the adoption of production automation and neural networks.
Job Losses in the US due to AI and Neural Networks
|Employment Change by 2030||Percentage Change from Current Level|
|Office and Administrative Professions||-539,200||-2.8%|
Numerous technology firms are utilizing artificial intelligence and neural networks to enhance the quality of their products and services. For instance, Alphabet employs AI to sift through spam emails for Gmail users and improve search results. Amazon and Netflix use neural networks to recommend suitable products and content to their customers.
Furthermore, several companies are capitalizing on the surging demand for artificial intelligence by vending hardware and software products.
According to projections, the total expenditure on artificial intelligence systems will surge to $97.9 billion by 2023, an increase from $37.5 billion in 2019.
Graphics cards, supercomputers, and processors
Nvidia is a key player vying for dominance in the hardware components sector of artificial intelligence. As a producer of graphics chips and video cards, Nvidia’s offerings have established themselves as the norm for handling data in data centers, machine learning, and operating generative neural networks.
It is projected that by the close of 2022, earnings from data processing centers could potentially exceed those from the gaming industry. Furthermore, Nvidia’s chips are utilized in self-driving cars that need to handle massive quantities of data from numerous sensors and cameras in real-time. These chips facilitate the detection of objects in road infrastructure, pedestrians, other vehicles, and the ability to make intricate decisions. Meeting these requirements necessitates significant computing capability, which Nvidia’s software and hardware solutions offer.
IBM, a pioneering technology company and one of the most established players in the industry, is another significant contender in the field of artificial intelligence. IBM is credited with being the precursor to contemporary neural networks. In 2006, the company unveiled the IBM Watson supercomputer, one of the first cognitive systems worldwide with the ability to comprehend natural language, handle a query, and provide an answer. IBM Watson made history by winning the American TV show Jeopardy in 2011.
The functionalities of IBM Watson are highly versatile and relevant across multiple industries. In 2020, the research firm IDC recognized IBM as a top performer in the AI software platforms domain, with a 13.7% market share, representing a 46% increase from the previous year.
AI Powered Equity ETF
Nowadays, supercomputing capabilities are being leveraged in medicine for treatment selection, drug discovery, and asset management. In October 2017, the United States saw the introduction of the AI Powered Equity ETF, which employs IBM Watson’s analytical prowess to make investment decisions.
Insider.com made a splash in January 2023 with a bold headline stating that an AI-driven investment fund using the IBM Watson supercomputer is outperforming the market by nearly 100%, overshadowing ChatGPT.
However, upon closer examination, the situation is not as optimistic as the article’s authors suggest. While it is true that the AI Powered Equity ETF saw a 10.4% increase in shares in January 2023, outpacing the S&P 500’s growth of 5.67%, the fund has underperformed the general market by almost two and a half times since its establishment in 2017. Specifically, the fund has grown by 24.26%, whereas the index has surged by 58.4%.
Manufacturers of processors and memory chips such as Intel and AMD
In 2017, Intel achieved a significant milestone as the first firm globally to manufacture chips for use in artificial intelligence and machine learning. Intel’s chip sales surpassed the billion-dollar mark, and the company developed a specialized neural network accelerator chip named Gaudi. Additionally, Intel’s most recent AI-specific chip for deep learning is the Intel NCS2 processor.
Meanwhile, AMD concentrates on addressing issues related to the presentation of preprocessed data resulting from neural network operations. The AMD Alveo U50 accelerator for data centers is capable of handling 10 million data sets and executing graphic algorithms in mere milliseconds.
Beyond specialized processors for artificial intelligence and neural networks, significant computational power and advanced cloud infrastructure are essential components of the field. The three largest players in this arena are Amazon, Microsoft, and Alphabet, which hold market shares of 34%, 21%, and 11%, respectively.
Chinese corporations Alibaba and Tencent, on the other hand, control 5% and 2% of the global cloud computing market, respectively. Despite the global economic slowdown, the sector grew by 22% in 2022.
China is the new leader in the field of AI
Based on recent studies, it has been found that the artificial intelligence models developed by Chinese technology giants Alibaba and Tencent have a better understanding of the Chinese language compared to humans.
In the Chinese Language Understanding Evaluation (CLUE) test, a series of tasks created to assess a machine’s ability to comprehend and respond to text in Chinese similar to humans, two rival models have achieved record-breaking scores. Tencent’s Hunyuan AI model secured the top position with an 86.918 score, followed closely by Alibaba’s AliceMind with a score of 86.685. The third position was held by the group of human participants, who scored 86.678. This marks the first time that AI models have surpassed human performance in CLUE.
Chinese companies have been heavily invested in the competition for dominance in the field of artificial intelligence. While the industry was still in its nascent stages five years ago, as of 2021, Chinese companies have emerged as global leaders in terms of the number of patents filed for AI. They hold three of the top five positions in the rankings, with Tencent and Baidu claiming the top two spots.
LexisNexis reports that Microsoft held the top spot for artificial intelligence patents between 2012 and 2019, but its ranking plummeted in 2019 as a result of increased activity from competing companies.
Ping An, the Chinese insurance giant, holds the top spot in this ranking. The company has witnessed an impressive increase in the number of patents related to artificial intelligence over the past five years. They have gone from owning only 46 patents to an astounding 6,410, which are not just theoretical patents but actual technologies integrated into the company’s business.
One of Ping An’s latest developments in artificial intelligence is software designed to analyze microexpressions on the face such as eye blinks and involuntary lip twitches. This tool is utilized by the company to evaluate insurance claims that are sent to them in video format by insurance providers.
Among all Chinese companies, Baidu appears to be the most prepared for a full-scale competition with ChatGPT, as it is China’s largest search engine and is often compared to Google. Baidu is set to launch its own chatbot named “Ernie” in the near future, which will be integrated into the search engine, much like ChatGPT is integrated into Microsoft’s Bing search engine.
The development of the artificial intelligence model that powers Baidu’s “Ernie” chatbot has been ongoing since 2019, and the latest iteration is trained on a massive 260 billion parameters – a scale similar to that of GPT-3, the technology behind ChatGPT. The news about the upcoming launch of its own chatbot has had a significant impact on Baidu’s stock, as its shares have risen by 30% since the start of 2023.
In the end
Artificial intelligence and neural networks are widely regarded as “disruptive” technologies capable of creating new markets and transforming existing ones.
An example of this can be seen in the aftermath of ChatGPT’s success and its integration into Microsoft’s Bing search engine. This development led to a decline in the stock of Google’s parent company, Alphabet. Since February 7th, Microsoft’s shares have increased by 4.7%, whereas Alphabet’s shares have dropped by 5%.
Chinese companies Tencent and Baidu have experienced a significant increase in their shares, with a rise of 15% and 30%, respectively, since the start of the year. This growth has far exceeded the performance of the Hong Kong stock exchange index, which has only seen a 3.7% increase during the same period.
While artificial intelligence does not yet play a major role in the business of Tencent, Baidu, or Microsoft, hardware manufacturers like Nvidia, IBM, Intel, AMD, and others are likely to experience a surge in demand for their products.
Following ChatGPT’s success, Microsoft announced its readiness to invest up to $10 billion in OpenAI, the developer of ChatGPT. Additionally, at the end of 2022, Google invested $300 million in Anthropic, a company founded by former OpenAI employees.
From an investment standpoint, it may be wise to remember the lessons from the gold rush era, during which those who sold shovels made the most money.