SEC chief warns it’s ‘almost inevitable’ AI will cause financial collapse

Artificial intelligence in a nutshell Gary Gensler, chairman of the US Securities and Exchange Commission, has warned that the increased use of artificial intelligence systems will almost certainly crash financial markets at some point in the next decade.

Gensler said the current free development of artificial intelligence told the Financial Times that such a collapse was “almost inevitable” unless regulators stepped in to control how the technology was used. He said he was in talks with other regulators and the government about how to remedy a potentially disastrous situation.

I think we will face a financial crisis in the future…[and] In post-op reports, people say, “Aha! Either there was a data aggregator or a model…we relied on it. Maybe it’s in the mortgage market. Maybe it’s in part of the stock market.” Gensler said.

This isn’t the first time computers have had a hell of a time with the financial markets, the most recent being the 2010 flash crash that briefly wiped out nearly a trillion dollars in value. A British trader has been accused of causing the problem with fake orders, which then triggered automated stock sales before human intervention.

Gensler is urging the SEC and other U.S. regulators to take another look at the potential for crash codes to prevent the next code. But this was new and uncharted territory, and he worried that progress might be difficult.

“Frankly, it’s a tough challenge,” Gensler said. This is a hard financial stability issue to address because most of our regulation is about individual institutions, banks, individual money market funds, individual brokers; “It’s just in the nature of what we do.”

Improves Habitat’s meta AI

Employees at Meta’s Fundamental AI Research Labs have advanced software designed to teach AI models how to navigate human environments, such as virtual offices, to help physical robots do the same.

Code Habitat 3.0 essentially brings together the first two versions of the code into one integrated system with an additional robotics module for developers to continue working with the robotics development code.

The first iteration set up a learning model to allow AI agents to navigate virtual environments, with this latest build being upgraded to 3D avatars, while the second iteration set up a dataset of environments and a dataset of It was an object that could be recognized and moved.

“In recent years, the field of embodied AI research has largely focused on the study of static environments—working under the assumption that objects in an environment remain static,” the FAIR team reported.

However, in a physical environment where humans live, this is simply not true. Our vision for intelligent social robots goes beyond the current paradigm by considering dynamic environments.

For his next trick, Meta says he wants to take the lessons learned from version three and apply them to the physical world. If the initial test adheres to technological norms, expect a lot of broken dishes.

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