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IS AI RACIST?

Plus Does China Dominate AI If They Use US Models?

Is Google’s Gemini AI Racist?

Google’s Gemini AI faced criticism for refusing to show images or achievements of White people, citing concerns about reinforcing stereotypes. The senior director of product management apologized and promised immediate improvement. The AI readily provided images of Black, Native American, and Asian individuals but was hesitant to showcase White individuals. Gemini emphasized the importance of celebrating diversity without segregating achievements by race. Social media users also reported similar responses from the AI. Despite the controversy, Google released Gemini 1.5, claiming enhanced performance surpassing competitors in various benchmarks. The incident highlighted the complexities and challenges of AI representation and diversity.

A Twist on China’s AI Dominance

In China’s race to dominate generative AI, Chinese firms are facing challenges due to their reliance on underlying technology from the United States. Despite efforts to catch up, the country lags by at least a year and may be falling further behind. For example, a Chinese start-up, 01.AI, that rose to prominence used technology from Meta’s model, LLaMA, as its foundation. This dependency on U.S. technology is putting pressure on Chinese companies to innovate and keep up with American advancements. Experts estimate that China is two to three years behind in generative AI development. 

Nvidia Rides High on AI Boom

Nvidia has reported a significant increase in profit and revenue, projecting continued growth due to the increasing demand for artificial intelligence technology. The Silicon Valley chip maker’s revenue more than tripled in the fiscal fourth quarter, reaching $22.1 billion, while profits rose ninefold to $12.3 billion. Nvidia’s CEO, Jensen Huang, attributes this success to the rise of accelerated computing and generative AI, stating that the company is at a tipping point. The company’s valuation has surged to $1.7 trillion, making it one of the most valuable public companies globally. 

AI Saves Tokamak Reactors

Princeton researchers have developed an AI model that can predict and prevent plasma instabilities in donut-shaped tokamak reactors, crucial for generating fusion energy. This breakthrough addresses a major challenge on the path towards unlimited clean fusion energy. The AI model, trained on real data, can anticipate tearing mode instabilities before they occur, providing a small but crucial window for intervention. While this study is still in the early stages, researchers are hopeful that this technology could be applied to other reactors to optimize reactions and energy output.

Intel Jumps Back on the Chipwagon

Intel’s CEO, Pat Gelsinger, announced that Intel is revamping its foundry business to produce chips for other companies, attracting big names like Microsoft. The move is an attempt to compete with Taiwan’s TSMC, the current industry leader. Intel plans to unveil its new 18A manufacturing process, aiming to become the world’s second-largest foundry by 2030. The company’s focus on generative AI chips signals a comeback after missing the mark with mobile computing and machine learning chips. 

AI Boom Sends Japan’s Nikkei Soaring

Japan’s Nikkei hit a record high fueled by strong results from Nvidia amidst an artificial intelligence investment boom. The euphoria also spread to European shares as the Stoxx 600 index reached a fresh high. Nvidia’s forecasted revenue growth of 233% had investors excited, propelling tech stocks globally. This surge in demand for AI chips has positioned Nvidia as a significant player in the market, with the potential to add billions to its market value and reclaim the spot as Wall Street’s third-most valuable company.

AI Hunting for Aliens, One Data Set at a Time

The chief executive of the Seti Institute, Bill Diamond, explains how the use of AI is transforming the search for alien intelligence. Seti Institute, in partnership with the US’s National Radio Astronomy Observatory, is using AI-powered software at the Very Large Array facility in New Mexico to process massive amounts of data captured every second. AI is helping to search for new types of radio signals from alien sources that traditional methods may have missed. Additionally, AI is being used to analyze rock samples from Mars for signs of past life. While promising, the validation of any results by AI is crucial. The collaboration between AI and astronomy is slowly but surely increasing the chances of detecting alien life.

AI Accusation Lands Student on Academic Probation

A college student, Marley Stevens, was placed on academic probation for using Grammarly to proofread her paper, which was flagged as plagiarism by anti-plagiarism software. Her professor accused her of AI use, resulting in a zero on the assignment, loss of scholarship, and academic probation. Stevens denies using AI to generate content, stating that Grammarly was only used for spelling and punctuation. Despite explaining her innocence, she was penalized. The incident has led Stevens to caution other students about the risks of using AI tools in academic settings. The university claimed they couldn’t provide details due to privacy laws, but emphasized that the misuse of AI is against the Student Code of Conduct. Stevens now faces the dilemma of transferring to a new college at a higher cost.

CEOs Discuss AI Race

Intel CEO Pat Gelsinger and OpenAI CEO Sam Altman met in San Jose to discuss AI chip production, following Nvidia’s impressive revenue growth. Altman aims to expand the industry’s manufacturing capacity to meet the growing demand for AI chips, needing more processing power. Meanwhile, Gelsinger outlined Intel’s plans to catch up with Nvidia and predicted Intel to become the world’s second-largest foundry by 2030. Despite Intel’s efforts, Nvidia remains the frontrunner in AI chip production, experiencing significant growth and creating substantial shareholder wealth. Both companies are positioning themselves to capitalize on the AI market’s potential, as evidenced by the U.S. Commerce Department’s plans to invest in increasing manufacturing capacity for processors.

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