I wrote the blog post a couple months back, and was considering the parts for the "computer" (Pi and adapter board alone) in that $20 estimate—the V3 version of the Pico Micro Mac is an additional $6.But I'm assuming in that setup you have a VGA-capable monitor on a shelf somewhere; not everyone does, of course.In the video I mention the all-in cost, accounting for the monitor, keyboard, mouse, power adapters, etc.This isn't a practical setup by any means, but at least you wind up with a neat co

Oh, this is really interesting to me. This is what I worked on at Amazon Alexa (and have patents on).An interesting fact I learned at the time: The median delay between human speakers during a conversation is 0ms (zero). In other words, in many cases, the listener starts speaking before the speaker is done. You've probably experienced this, and you talk about how you "finish each other's sentences".It's because your brain is predicting what they will say while they speak, and processing an a

I think it all boils down to, which is higher risk, using AI too much, or using AI too little?Right now I see the former as being hugely risky. Hallucinated bugs, coaxed into dead-end architectures, security concerns, not being familiar with the code when a bug shows up in production, less sense of ownership, less hands-on learning, etc. This is true both at the personal level and at the business level. (And astounding that CEOs haven't made that connection yet).The latter, you may be less produ

Well Opus and Gemini are probably running on multiple H200 equivalents, maybe multiple hundreds of thousands of dollars of inference equipment. Local models are inherently inferior; even the best Mac that money can buy will never hold a candle to latest generation Nvidia inference hardware, and the local models, even the largest, are still not quite at the frontier. The ones you can plausibly run on a laptop (where "plausible" really is "45 minutes and making my laptop sound like it is going to

> the stupid way to manage every year has to be x% exponential increase over the previous year, always forgetting that it is physically impossible when everyone goes for the same goal.That's why we have this corporate ritual, which we carry out each year, or even each quarter - a solemn ceremony, where we divide everyone into two groups: the cost centers and the profit centers.Everyone works in harmony for the same organizational goals, but the people of cost centers also bear an additional, sac

You are selling yourself a little short. And unfortunately some of the commenting public here can't see through your self deprecation, and just add insults thinking they're smarter. They're not.Algorithms, the kind you're talking about, are HARD. All of the algorithms you gave as examples were originally research papers that took months to years to develop. All of the algorithms you cited are algorithms that pretty much EVERYONE gets wrong the first time, no matter how good they are or think

It is unfortunate that many young tech companies, in an effort to differentiate themselves, work to invent a new term and cloak it with the appearance of a movement or industry trend. It's further unfortunate when those to whom this term is being marketed recoil with laughter and amusement at its implications, forcing its purveyors to double down and attempt to re-assert control over the meaning of a term which may please analysts and folks with Twitter accounts who fashion themselves "thought l