Ellison’s net worth second to Musk’s amid Oracle’s rise
Oracle’s shares outperform S&P 500 this year
Oracle’s AI cloud business drives stock surge
Sept 11 (Reuters) – Oracle (ORCL.N), opens new tab shares retreated on Thursday after a record AI-driven surge in the previous session that put the company closer to the trillion-dollar mark and co-founder Larry Ellison within striking distance of the world’s richest person title.
The enterprise software maker’s remarkable rise, fueled by a wave of multi-billion-dollar cloud deals, puts the spotlight on the scramble for computing power from companies that are pouring billions to become leaders in the AI race.
Oracle’s shares fell about 4% after climbing as much as 35.9% on Wednesday. The company’s market valuation rose to a record $933 billion, as of last close, but is set to fall to around $894 billion if losses hold.
Ellison’s net worth stood at around $371.7 billion, largely driven by his 41% stake in Oracle, compared with Tesla (TSLA.O), opens new tab CEO Elon Musk’s $441.2 billion fortune that tops Forbes’ global wealth rankings.
“A bit of buyer exhaustion here. I think the “buy the dip” crowd is likely to re-emerge,” said Dennis Dick, chief strategist at Stock Trader Network.
“The guidance was so incredible, hard to think that this story is over.”
Oracle said on Tuesday its order backlog is on track to hit half a trillion dollars in the coming months.
The Wall Street Journal also reported on Wednesday that OpenAI has signed a $300 billion deal with Oracle for computing power, among the biggest in history.
Oracle trounces gains made by S&P 500 this year
Oracle’s stock has nearly doubled in value this year, making it among the top performers in the S&P 500 index (.SPX), opens new tab, trouncing gains made by the so-called Magnificent Seven stocks.
The median price target of $342 represents an upside of around 9% to the company’s stock price of $314.45, according to LSEG data.
The shares were trading at a premium compared to its cloud services peers. Their 12-month forward price-to-earnings multiple was 45.3, compared with Amazon’s 31.3 and Microsoft’s 31.
While AI was popularised during the OpenAI era of 2018, its roots stretch back to the 1920s. The history of AI is divided into many eras, starting from the groundwork in 1920 and the birth of AI in 1956 which created a base for what we have today.
What is AI?
Artificial intelligence (AI) is a technology that enables computers to simulate human intelligence and problem-solving capabilities on their own or combine them with other technologies.
It all began in the early 1900s, as the concept of artificial humans emerged and scientists started to question if it is possible to create artificial intelligence or what they referred to as “artificial brain”.
The term “artificial people” was first used in 1921 by the Czech playwright Karel Čapek in a science fiction play named “Rossum’s Universal Robots”, where the concept of artificial people was introduced for robots.
The father of artificial intelligence
One of the greatest innovators in the field of AI was John McCarthy who got the title of Father of Artificial Intelligence for his contribution to the field of Computer Science and AI.
John McCarthy used the term Artificial Intelligence for the first time in 1956 when he organised the Dartmouth Conference, which is considered the birth of AI as a field of study.
Who was John McCarthy?
John McCarthy (1927–2011), an American computer scientist and cognitive scientist, often hailed as the “father of artificial intelligence” (AI), made significant contributions to both AI and computer science.
One of McCarthy’s most notable contributions to computer science is the development of the programming language LISP (List Processing), which was specifically designed for AI research and became one of the most important languages in the field. He also proposed the concept of time-sharing in computers, which laid the groundwork for modern interactive computing.
The timeline of AI
The timeline of AI from 1950 to 2024 and onwards
Early Contributions and Milestones of the 50’s
After the foundation of artificial intelligence was laid by pioneers Karel Čapek and John McCarthy in 1956, the field of AI and information technology rapidly gained traction. This newfound interest spurred numerous individuals to contribute to its advancement.
The next key figure in this field, who envisioned machines approaching human intelligence and capable of performing tasks like humans, was Alan Turing, who introduced the Turing Test to evolve machine intelligence. AI made a significant leap in symbolic reasoning with Newell and Simon’s Logic Theorist in 1955. However, their progress was constrained by the limited computing power of the technology at that time.
The Rise of Machine Learning 80’s-90’s
The main breakthrough that happened in the 1980s and 1990s was the transition to machine learning, where the systems made the transition to learning patterns from the data available to them, and stopped relying on explicit programming. This was inspired by the structure of the human brain.
This was made possible by people like Geoffrey Hinton and Yann LeCun who made a huge advancement in network research and developed backpropagation algorithms to be able to train the networks. This was possible because of the increase in computation power and machine learning. Moreover, the vector machine and cluster algorithms were developed and contributed to the growing and evolving AI power and capabilities.
The Big Data Revolution 00’s
At the beginning of the 21st century, the era of big data emerged, providing massive datasets that allowed for more efficient training of machine learning models and significantly improving AI performance. Simultaneously, deep learning became a prominent subset of machine learning, making substantial contributions to speech and image recognition.
Furthermore, advancements in powerful computers and GPUs accelerated the development of machine learning. A notable milestone was achieved by Alex Krizhevsky, in collaboration with Ilya Sutskever and Geoffrey Hinton, who created AlexNet, a convolutional neural network. Their work won the ImageNet competition, showcasing the practical applications of deep learning.
An AI assistant trained on your content
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The AI we have now is useful in all aspects of personal and professional life, from virtual assistants like Siri to e-commerce search like Amazon search or business and enterprise AI Search and Chat. AI applications are now benefiting a wide range of industries, from healthcare to finance, and even extending to innovations like self-driving cars. This marks just the beginning of integrating AI into our daily lives.
The future of AI
Looking to the future, the ethical implications of AI are increasingly important. Ensuring that AI systems are fair, transparent, and accountable is crucial to maximising benefits and minimising potential harm. Researchers and policymakers are collaborating to create frameworks that guide the responsible development and deployment of AI technologies.
