On super intelligence – Cal Newport in The New Yorker:

‘Suddenly, the theoretical idea of artificial general intelligence, which performs as well as or better than humans on a wide variety of tasks, seemed tantalizingly close. If the scaling law held, A.I. companies might achieve A.G.I. by pouring more money and computing power into language models. Within a year, Sam Altman, the chief executive at OpenAI, published a blog post titled “Moore’s Law for Everything,” which argued that A.I. will take over “more and more of the work that people now do” and create unimaginable wealth for the owners of capital. “This technological revolution is unstoppable,” he wrote. “The world will change so rapidly and drastically that an equally drastic change in policy will be needed to distribute this wealth and enable more people to pursue the life they want.”’

(…)

‘Then, last week, OpenAI finally released GPT-5, which many had hoped would usher in the next significant leap in A.I. capabilities. Early reviewers found some features to like. When a popular tech YouTuber, Mrwhosetheboss, asked it to create a chess game that used Pokémon as pieces, he got a significantly better result than when he used GPT-o4-mini-high, an industry-leading coding model; he also discovered that GPT-5 could write a more effective script for his YouTube channel than GPT-4o. Mrwhosetheboss was particularly enthusiastic that GPT-5 will automatically route queries to a model suited for the task, instead of requiring users to manually pick the model they want to try. Yet he also learned that GPT-4o was clearly more successful at generating a YouTube thumbnail and a birthday-party invitation—and he had no trouble inducing GPT-5 to make up fake facts. Within hours, users began expressing disappointment with the new model on the r/ChatGPT subreddit. One post called it the “biggest piece of garbage even as a paid user.” In an Ask Me Anything (A.M.A.) session, Altman and other OpenAI engineers found themselves on the defensive, addressing complaints. Marcus summarized the release as “overdue, overhyped and underwhelming.”’

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‘Last week, researchers at Arizona State University reached an even blunter conclusion: what A.I. companies call reasoning “is a brittle mirage that vanishes when it is pushed beyond training distributions.” Beating these benchmarks is different from, say, reasoning through the types of daily problems we face in our jobs. “I don’t hear a lot of companies using A.I. saying that 2025 models are a lot more useful to them than 2024 models, even though the 2025 models perform better on benchmarks,” Marcus told me. Post-training improvements don’t seem to be strengthening models as thoroughly as scaling once did. A lot of utility can come from souping up your Camry, but no amount of tweaking will turn it into a Ferrari.’

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‘If these moderate views of A.I. are right, then in the next few years A.I. tools will make steady but gradual advances. Many people will use A.I. on a regular but limited basis, whether to look up information or to speed up certain annoying tasks, such as summarizing a report or writing the rough draft of an event agenda. Certain fields, like programming and academia, will change dramatically. A minority of professions, such as voice acting and social-media copywriting, might essentially disappear. But A.I. may not massively disrupt the job market, and more hyperbolic ideas like superintelligence may come to seem unserious.’

(…)

‘The whole enterprise of teaching computers to think remains mysterious. We should proceed with less hubris and more care.’

Read the article here.

Less hubris, more care.

What else is new?

We have been waiting for the paradigm shift, maybe in vain.

In the meantime, the armies are playing with AI for their war games and hoping that superintelligence will bring total victory closer.