The bill, which aimed to regulate shipments of AI GPUs to adversaries and prioritize U.S. buyers, as proposed by U.S. senators earlier this week, made quite a splash in America. To a degree, Nvidia issued a statement claiming that the U.S. was, is, and will remain its primary market, implying that no regulations are needed for the company to serve America.

“The U.S. has always been and will continue to be our largest market,” a statement sent to Tom’s Hardware reads. “We never deprive American customers in order to serve the rest of the world. In trying to solve a problem that does not exist, the proposed bill would restrict competition worldwide in any industry that uses mainstream computing chips. While it may have good intentions, this bill is just another variation of the AI Diffusion Rule and would have similar effects on American leadership and the U.S. economy.”

OpenAI has sharply raised its projected cash burn through 2029 to $115 billion, according to The Information. This marks an $80 billion increase from previous estimates, as the company ramps up spending to fuel the AI behind its ChatGPT chatbot.

The company, which has become one of the world’s biggest renters of cloud servers, projects it will burn more than $8 billion this year, about $1.5 billion higher than its earlier forecast. The surge in spending comes as OpenAI seeks to maintain its lead in the rapidly growing artificial intelligence market.

To control these soaring costs, OpenAI plans to develop its own data center server chips and facilities to power its technology.

The company is partnering with U.S. semiconductor giant Broadcom to produce its first AI chip, which will be used internally rather than made available to customers, as reported by The Information.

In addition to this initiative, OpenAI has expanded its partnership with Oracle, committing to a 4.5-gigawatt data center capacity to support its growing operations.

This is part of OpenAI’s larger plan, the Stargate initiative, which includes a $500 billion investment and is also supported by Japan’s SoftBank Group. Google Cloud has also joined the group of suppliers supporting OpenAI’s infrastructure.

OpenAI’s projected cash burn will more than double in 2024, reaching over $17 billion. It will continue to rise, with estimates of $35 billion in 2027 and $45 billion in 2028, according to The Information.

The PromptLocker malware, which was considered the world’s first ransomware created using artificial intelligence, turned out to be not a real attack at all, but a research project at New York University.

On August 26, ESET announced that detected the first sample of artificial intelligence integrated into ransomware. The program was called PromptLocker. However, as it turned out, it was not the case: researchers from the Tandon School of Engineering at New York University were responsible for creating this code.

The university explained that PromptLocker — is actually part of an experiment called Ransomware 3.0, which was conducted by a team from the Tandon School of Engineering. A representative of the school told the publication that a sample of the experimental code was uploaded to the VirusTotal platform for malware analysis. It was there that ESET specialists discovered it, mistaking it for a real threat.

According to ESET, the program used Lua scripts generated on the basis of strictly defined instructions. These scripts allowed the malware to scan the file system, analyze the contents, steal selected data, and perform encryption. At the same time, the sample did not implement destructive capabilities — a logical step, given that it was a controlled experiment.

Nevertheless, the malicious code did function. New York University confirmed that their AI-based simulation system was able to go through all four classic stages of a ransomware attack: mapping the system, identifying valuable files, stealing or encrypting data, and creating a ransomware message. Moreover, it was able to do this on various types of systems — from personal computers and corporate servers to industrial controllers.

Should you be concerned? Yes, but with an important caveat: there is a big difference between an academic proof-of-concept demonstration and a real attack carried out by malicious actors. However, such research can be a good opportunity for cybercriminals, as it shows not only the principle of operation but also the real costs of its implementation.