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New Stanford University Report Shows Rapid Progress of AI and Expanding Costs New Stanford University Report Shows Rapid Progress of AI and Expanding Costs
A recent report from Stanford University’s Institute for Human-Centered Artificial Intelligence reveals that AI systems now almost match or surpass human... New Stanford University Report Shows Rapid Progress of AI and Expanding Costs

A recent report from Stanford University’s Institute for Human-Centered Artificial Intelligence reveals that AI systems now almost match or surpass human abilities in areas such as reading comprehension, image classification, and competitive math.

The 2024 edition of the Artificial Intelligence Index Report, released on April 15, underscores the swift advancements in AI capabilities, which have led to the obsolescence of many existing benchmarks for evaluating these technologies.

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Nestor Maslej, a social scientist at Stanford and the report’s editor-in-chief notes the accelerated pace of AI development: “A decade ago, benchmarks would serve the community for 5–10 years, but now they often become irrelevant in just a few years.”.

The report advocates for newer methods to assess AI systems, particularly in complex tasks that require higher levels of abstraction and reasoning. Partially important as the scale of progress with many of these systems is rapidly expanding.

But there is a problem with the costs to get these systems to continue to improve.  So while AI technology is still growing in terms of power and ability, the costs associated with developing these systems are skyrocketing.

For instance, OpenAI’s GPT-4, launched in March 2023, had a development price tag of $78 million. Similarly, Google’s Gemini Ultra, which debuted in December, cost $191 million. These figures highlight concerns regarding not only the economic but also environmental aspects of AI development, such as high energy consumption and extensive water use for cooling data centers.

The report also addresses increasing ethical concerns about AI. With a significant rise in AI-related regulation, the U.S. saw 25 new regulations last year alone, compared to just one in 2016. Maslej highlights the importance of standardized benchmarks that can evaluate AI tools on metrics like truthfulness, bias, and likability to ensure responsible usage.

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As AI systems become more integrated into scientific research, the report underscores their use in innovative applications such as rapid weather forecasting and materials discovery. However, the looming possibility of running out of high-quality training data by as early as this year poses new challenges, necessitating more sustainable approaches to AI development.

Overall, the Stanford report sheds light on the technical advancements and challenges of AI. While it also provides a great overview of the trajectory and implications of these rapidly evolving technologies.

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ODSC Team

ODSC gathers the attendees, presenters, and companies that are shaping the present and future of data science and AI. ODSC hosts one of the largest gatherings of professional data scientists with major conferences in USA, Europe, and Asia.

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