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Jan 18 (Reuters) - Semafor is planning to buy out FTX founder Sam Bankman-Fried's roughly $10 million investment in the news startup, the New York Times reported on Wednesday, citing the company's chief executive officer.
"We are planning to repurchase Sam Bankman-Fried's interest in Semafor and to place the money into a separate account until the relevant legal authorities provide guidance as to where the money should be returned," said Semafor's CEO Justin Smith, according to the NYT report.
The news outlet did not immediately respond to a Reuters request for comment.
The U.S. Department of Justice accused Bankman-Fried of causing billions of dollars of losses related to FTX, which a U.S. prosecutor called a "fraud of epic proportions."
Bankman-Fried founded FTX in 2019 and rode a boom in the values of bitcoin and other digital assets to become a billionaire several times over as well as an influential donor to U.S. political campaigns.
In December, non-profit investigative news outlet ProPublica said, in a staff memo, it will return $1.6 million it received from Bankman-Fried's family foundation.
Reporting by Manya Saini in Bengaluru; Editing by Shailesh Kuber
Our Standards: The Thomson Reuters Trust Principles.
AI robot trading is the use of artificial intelligence (AI) and machine learning algorithms to analyze financial markets and execute trades automatically.
AI robots are able to analyze vast amounts of data and make decisions based on that analysis, allowing them to identify trading opportunities that might be missed by human traders.
One key aspect of AI robot trading is machine learning, which is a type of AI that enables systems to learn and improve their performance over time. Machine learning algorithms are able to analyze data and use it to make predictions or decisions without being explicitly programmed to do so. This allows them to adapt and improve their performance as they are exposed to more data.
There are several techniques that can be used in AI robot trading, including:
Decision trees: These are algorithms that use a tree-like structure to make decisions based on multiple conditions.
Neural networks: These are algorithms that are inspired by the structure and function of the human brain, and are capable of learning and adapting based on input data.
Genetic algorithms: These are algorithms that use principles of genetics and natural selection to optimize and improve their performance over time.
Reinforcement learning: This is a type of machine learning that involves an AI agent receiving rewards or punishments for certain actions, and using that feedback to learn and adapt its behavior.
By using these and other techniques, AI robot traders are able to analyze financial data and make informed decisions about when to buy and sell assets. This can help them achieve better returns and outperform human traders in some cases.