Experts Say it is Getting Harder to Measure AI Advancement

Measuring the rate at which AI is developing is becoming difficult because of the rapid pace at which advancements in the industry are happening, experts say. These observations came to light as a closely watched graph by a nonprofit that is focused on tracking AI progress was updated yet again.

The research institute, known as METR, analyzes the software capabilities of the different artificial intelligence models that currently exist. Based on the test results, the experts place dots on a graph to reflect how quickly these models are becoming better at doing what developers designed them to do.

Recent findings reveal that the abilities of AI models to perform tasks are doubling every 7 months, and that pace of improvement is accelerating so fast, almost exponentially, that researchers are finding it harder to keep up.

The tests conducted by METR are designed to see how well AI models can execute increasingly complex tasks that humans previously undertook. The recent graph update was based on tests conducted on Claude Opus 4.6, an AI model recently released by Anthropic. The model surpassed all the previous records that had been set by existing AI models.

These massive leaps in the capabilities of AI models prompted many experts to draw parallels with the way in which Covid-19 spread. Data revealed that the virus could shift from being detected in just a few people to having entire communities in its deadly grip at a very swift pace. That kind of exponential growth is now happening in the way AI models are improving, and this has lots of people worried.

Many tech CEOs, including Dario Amodel, CEO of Anthropic, have sounded the alarm about how quickly AI is developing in an environment where policymakers aren’t equipped to understand the implications of these advances in order to design appropriate regulations to guide developers and users of these technologies.

For example, statistics from the U.S. and the UK show AI hasn’t had a large impact on employment, but the data used is often lagging and doesn’t reflect current realities. Many knowledge-based professionals, such as software engineers, accountants and writers are finding it harder to access employment opportunities due to the growing switch to AI tools.

If AI is doubling its capabilities every 7 months and collapsing that timeframe in real-time, it is hard to imagine how good it will be in a year or two, and what good or risks will emerge as a result of that improved capacity of AI to perform tasks that have traditionally been done by humans. You can be sure that leading tech companies like Apple Inc. (NASDAQ: AAPL) are putting their AI capex to good use and the impact is being seen in the products they release, but there is a likelihood of unintended consequences that experts are currently struggling to figure out.

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