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first_img The Wall Street Journal: AI infrastructure may become the largest economic bet in American history

According to a report by The Wall Street Journal, the construction of artificial intelligence is becoming the largest economic bet in American history, surpassing investments in railroads, highway systems, and internet infrastructure. The report states that spending on data centers has exceeded the combined expenditures on canals, railroads, and power grid construction, and this related construction is driving inflation while creating jobs and wealth.Economist Stijn van Nieuwerburgh, in estimates published by the Brookings Institution, shows that total investment in data centers and related artificial intelligence infrastructure is expected to reach $10.3 trillion from 2025 to 2032, averaging about 3.6% of GDP annually. The report states that the U.S. economy has never been so dependent on the construction of a single industry. Goldman Sachs estimates that by 2026, U.S. investment in artificial intelligence will reach 1.9% of GDP; the last time a single new industry accounted for a larger share of the economy was during the railroad boom in the late 19th century.The estimates list the average annual infrastructure spending as a percentage of GDP as follows: canals from 1836 to 1841 at 0.66%, railroads from 1870 to 1890 at 2.24%, electrification from 1905 to 1925 at 0.5%, highways from 1956 to 1973 at 1.13%, telecommunications and fiber optics from 1996 to 2003 at 1.1%, and artificial intelligence from 2025 to 2032 at 3.63%. The report also states that this investment is transforming various sectors of the economy, creating hundreds of thousands of jobs and producing new billionaires, while also carrying significant risks, as a large portion of it is supported by debt.

Tether released a dataset of 191.4 billion Token STEM, betting on the "explanatory ability" of local small models

The stablecoin giant Tether's Tether AI Research today released QVAC Genesis III, a synthetic training dataset aimed at the fields of science, technology, engineering, and mathematics, with a scale of 19.143 billion tokens, covering 159.6 million documents.It is reported that Tether hopes to enhance the reasoning and teaching capabilities of small AI models, allowing more AI assistants to run directly on laptops, mobile phones, and local servers, reducing the ongoing reliance on large cloud models.Genesis III continues the data lineage of Genesis I and Genesis II, covering 19 curriculum-related fields including biology, chemistry, physics, mathematics, computer science, medicine, electrical engineering, and machine learning, aimed at high school, university, and professional applications. Tether states that the dataset will focus on training models to explain problem-solving paths, identify erroneous reasoning, and provide corrections, rather than just outputting final answers.According to Tether's disclosed test results, a 1.7 billion parameter model trained with Genesis III option-level data achieved an effective answer rate of 99.45% in relevant benchmark tests. Compared to the Cosmopedia-v2 training model of similar token scale, Genesis III improved scores on the ARC-Easy, ARC-Challenge, and MMLU STEM benchmarks by 28.57, 21.35, and 15.03 percentage points, respectively.
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