Governments plan to pour $1.3 trillion into AI infrastructure by 2030 to invest in “sovereign AI,” with the premise being that countries should be in control of their own AI capabilities. The funds include financing for domestic data centers, locally trained models, independent supply chains, and national talent pipelines. This is a response to real shocks: covid-era supply chain breakdowns, rising geopolitical tensions, and the war in Ukraine.   But the pursuit of absolute autonomy is running into reality. AI supply chains are irreducibly global: Chips are designed in the US and manufactured in East Asia; models are trained on data […]

There are many paths AI evolution could take. On one end of the spectrum, AI is dismissed as a marginal fad, another bubble fueled by notoriety and misallocated capital. On the other end, it’s cast as a dystopian force, destined to eliminate jobs on a large scale and destabilize economies. Markets oscillate between skepticism and the fear of missing out, while the technology itself evolves quickly and investment dollars flow at a rate not seen in decades.  All the while, many of today’s financial and economic thought leaders hold to the consensus that the financial landscape will stay the same […]

MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data other than what they were trained on, raising questions about the need to test whenever a model is deployed in a new setting. “We demonstrate that even when you train models on large amounts of data, and choose the best average model, in a new setting this ‘best model’ could be the worst model for 6-75 percent of the new data,” says Marzyeh Ghassemi, an associate professor in MIT’s Department of Electrical Engineering and Computer Science (EECS), a member of the Institute for […]