I wish tech writers were more consistently mindful of the distinction between (a) announcing the development of a product and (b) actually shipping that product — and then, if the product ever is shipped, between (a) the claims a company makes for its product and (b) what the product actually does.
Coming soon
Kafka announced to us long ago that the meaning of life is that it stops. True enough. But [Jennifer] Banks walks the reader alongside seven intellectuals who took seriously the bookend of starting: new life, fecundity and generativity — and, in my mind, our many distributed practices of creative midwifery that get new ideas off the ground. Hannah Arendt is one of Banks’s chief companions on natality. She thought our creative beginnings are not just universal but necessary, a strong stance against authoritarianism, a rebuke to brute force power. Natality, for Arendt, embodies the amor mundi, an outwardness and expectation of beginnings, of making room for others. She called it “the miracle that saves the world, the realm of human affairs, from its normal ‘natural’ ruin.” And the amor mundi has to start somewhere. Not just the endless talking about what the world should be like. Prototyping is beautifully restless and insistent: Show me how. Let’s start.
John Siracusa: “The recent Apple Intelligence fiasco has revealed that the company is further away from properly prioritizing software reliability than it has ever been. Apple was seemingly willing to sacrifice everything, including its own reputation, to ensure that it had enough new AI features to announce at WWDC. If we want a different result, it seems like we need different leaders.”
Magnolia season
Half-listening to the NBA game and when someone said “Julius Randle” I heard “Jewish Rambo” and now I want to see that movie.
If you ask any of the LLMs to summarize a book or article, they do so with some accuracy. If you ask them to provide relevant quotations from the text along with the summary, they make the quotations up.
The current energized narratives around AGI and Superintelligence seem to be fueled by a convergence of three factors: (1) the fact that scaling laws did apply for the first few generations of language models, making it easy and logical to imagine them continuing to apply up the exponential curve of capabilities in the years ahead; (2) demos of models tuned to do well on specific written tests, which we tend to intuitively associate with intelligence; and (3) tech leaders pounding furiously on the drums of sensationalism, knowing they’re rarely held to account on their predictions.
While media attention remains focused, as always, on elite universities, this story is a sobering reminder of the reality at less selective and less famous schools.