Amazing. Thanks for your detailed posts on the bake-off between the Mac and GB10, Daniel, and on your learnings. I had trying similar on both compute platforms on my to-do list. Your post should save me a lot of debugs, sweat, and tears.
Whether by design or accident, the way Anthropic is managing the Claude Mythos release is creating a Glomar Trap for customers, competitors, and investors.
Do you want to define the seasons by temperature? Or by lengthening of the day? Because, to me, seasons are tied to weather in general, but temperature specifically. And temperature seems to correlates to length of day, but trails it by about a month. Which makes sense, since it takes time to heat/cool the enormous thermal mass. So, if weather is how you track the changing of the seasons, it’s close enough to correct as-is.
And which temperatures - air, ground, sea? Or qualitative measures such as when lambs are born, crops are harvested, leaves fall, etc?
There's a lot that we associate with seasons. But the quote somewhere above about six seasons with locking before winter and unlocking after does feel like a better fit to me.
Yeah there are "climatological seasons." The Earth heats up over time, as you say, so the longest day of the year is not generally the hottest day. Climatological summer is June/July/August. The Romans and many other northern hemisphere cultures marked summer as starting before the solstice. I'm not sure when we got the idea that Summer was supposed to start on the solstice.
But it's more than just the temperature, or the day length.
There's a big difference between 40-50°F in November, when the trees are brown and barren, and you're looking ahead to winter, and you swear there's a hint of frost in the air...
...and 40-50°F in April, when the leafbuds are coming out, and the geese are flying back north, and is that a crocus coming up over there?
CLaRa (Continuous Latent Reasoning) is an approach Retrieval-Augmented Generation (RAG) that shortens context, reduces double-encoding, and improves quality of responses by compressing documents into a small set of "continuous memory tokens" that preserve the key information in the documents, and optimizes and performs retrieval and generation out of that shared latent space.
Because, the programming languages best matched to a (natural human language-based) declarative programming paradigm (e.g., vibe coding) would be declarative programming languages, not imperative programming languages.
Yes. Logue's are (brilliant) retellings, not translations. His source material were other English translations, since he was not literate in ancient Greek (as the article's author notes).
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See an East African lion
Nose tip to tail tuft ten, eleven feet
Slouching towards you
Swaying its head from side to side
Doubling its pace, its gold-black mane
That stretches down its belly to its groin
Catching the sunlight as it hits
Twice its own length a beat, then leaps
Great forepaws high great claws disclosed
The scarlet insides of its mouth
Parting a roar as loud as sail-sized flames
And lands, slam-scattering the herd.
"People seem to think that having the internet at their fingertips means they no longer need to know anything themselves. But in order to understand things, you need a lot of knowledge readily available in your head. Only then can the mind make the connections between the different points of data and come to new insights. This cannot happen when that knowledge is external, in a book or on some Wikipedia page that you have to look up first."
"Vorrath, who has spent 36 years at Apple, is known for managing the development of tough software projects. She’s also put procedures in place that can catch and fix bugs."
"In the mid-2000s, she was chosen to lead project management for the original iPhone software group and get the iconic device ready for consumers. Until 2019, she oversaw project management for the iPhone, iPad and Mac operating systems, before taking on the Vision Pro software."
Is Apple having a project management/delivery execution problem? Maybe.
But, it seems like they are actually having a deeper product envisioning problem for how Apple should be leverage AI to enhance their "bicycles for the mind". They need to figure out what the right things to build are, before they optimized how to build and deliver it.
