Anyone who played with this toy will also remember the sound it made. Once you slid the power button to the On position, you heard a constant whirring sound of plastic gears turning and twisting. And if you tried to push it past its boundaries, it twitched and protested with a jarring "CLICK … CLICK … CLICK." It wasn't just kids who found the Armatron so special. It was featured on the cover of the November/December 1982 issue of Robotics Age magazine, which noted that the 31.95

A new report from the International Energy Agency digs into the details of energy and AI, and I think it's worth looking at some of the data to help clear things up. Here are four charts from the report that sum up the crucial points about AI and energy demand. This point is the most obvious, but it bears repeating: AI is exploding, and it's going to lead to higher energy demand from data centers. "AI has gone from an academic pursuit to an industry with trillions of dollars at stake," as the IEA report's executive summary puts it. Data centers used less than 300 terawatt-hours of electricity in 2020.

This highly scalable approach may finally open the skies to a host of commercial drone applications that have yet to materialize. Amazon Prime Air launched in 2022 but was put on hold after crashes at a testing facility, for example. On any given day, only 8,500 or so unmanned aircraft fly in US airspace, the vast majority of which are used for recreational purposes rather than for services like search and rescue missions, real estate inspections, video surveillance, or farmland surveys. One obstacle to wider use has been concern over possible midair drone-to-drone collisions. This prevents most collisions but also most use cases, such as delivering medication to a patient's doorstep or dispatching a police drone to an active crime scene so first responders can better prepare before arriving.

As AI systems that learn by mimicking the mechanisms of the human brain continue to advance, we're witnessing an evolution in models from rote regurgitation to genuine reasoning. This capability marks a new chapter in the evolution of AI--and what enterprises can gain from it. But in order to tap into this enormous potential, organizations will need to ensure they have the right infrastructure and computational resources to support the advancing technology. "Reasoning models are qualitatively different than earlier LLMs," says Prabhat Ram, partner AI/HPC architect at Microsoft, noting that these models can explore different hypotheses, assess if answers are consistently correct, and adjust their approach accordingly. "They essentially create an internal representation of a decision tree based on the training data they've been exposed to, and explore which solution might be the best."

While large language models that generate text have exploded in the last three years, a different type of AI, based on what are called diffusion models, is having an unprecedented impact on creative domains. By transforming random noise into coherent patterns, diffusion models can generate new images, videos, or speech, guided by text prompts or other input data. The best ones can create outputs indistinguishable from the work of people, as well as bizarre, surreal results that feel distinctly nonhuman. Now these models are marching into a creative field that is arguably more vulnerable to disruption than any other: music. Music models can now create songs capable of eliciting real emotional responses, presenting a stark example of how difficult it's becoming to define authorship and originality in the age of AI.

"There's a new kind of coding I call'vibe coding', where you fully give in to the vibes, embrace exponentials, and forget that the code even exists," he said. "I'm building a project or webapp, but it's not really coding--I just see stuff, say stuff, run stuff, and copy paste stuff, and it mostly works." If this all sounds very different from poring over lines of code, that's because Karpathy was talking about a particular style of coding with AI assistance. His words struck a chord among software developers and enthusiastic amateurs alike. In the months since, his post has sparked think pieces and impassioned debates across the internet. But what exactly is vibe coding?

In their proposal, the group had listed several "aspects of the artificial intelligence problem." The last item on their list, and in hindsight perhaps the most difficult, was building a machine that could exhibit creativity and originality. At the time, psychologists were grappling with how to define and measure creativity in humans. The prevailing theory--that creativity was a product of intelligence and high IQ--was fading, but psychologists weren't sure what to replace it with. The Dartmouth organizers had one of their own.

They "needed a vision" for the anticipated growth, Ford says. The two convened a group of volunteers with experience in eight areas: economic development, talent, housing, public health, quality of life, tourism, storytelling, and infrastructure. They built a plan to use Pol.is to help write a 25-year plan for the city. The platform is just one of several new technologies used in Europe and increasingly in the US to help make sure that local governance is informed by public opinion. After a month of advertising, the Pol.is portal launched in February.

In 2021, the Maryland Department of Health and the state police were confronting a crisis: Fatal drug overdoses in the state were at an all-time high, and authorities didn't know why. Seeking answers, Maryland officials turned to scientists at the National Institute of Standards and Technology, the national metrology institute for the United States, which defines and maintains standards of measurement essential to a wide range of industrial sectors and health and security applications. There, a research chemist named Ed Sisco and his team had developed methods for detecting trace amounts of drugs, explosives, and other dangerous materials--techniques that could protect law enforcement officials and others who had to collect these samples. And a pilot uncovered new, critical information almost immediately. This story is from the next edition of our print magazine.

As I also write in my story, this push raises alarms from some AI safety experts about whether large language models are fit to analyze subtle pieces of intelligence in situations with high geopolitical stakes. It also accelerates the US toward a world where AI is not just analyzing military data but suggesting actions--for example, generating lists of targets. Proponents say this promises greater accuracy and fewer civilian deaths, but many human rights groups argue the opposite. With that in mind, here are three open questions to keep your eye on as the US military, and others around the world, bring generative AI to more parts of the so-called "kill chain." Talk to as many defense-tech companies as I have and you'll hear one phrase repeated quite often: "human in the loop."