This feels like a fair question (perhaps not perfect wording, but no adhominem or disingenuity)
More broadly, we are overbuilding infra on highly inefficient silicon (at a time when designing silicon is easier than ever) and energy stacks _before_ the market is naturally driving it. (with assets that depreciate far faster than railroads). Just as China overbuilt Shenzhen
I have heard (unconfirmed) that the US is importing CNG engines from India for data center buildouts. I loved summers in my youth in Bombay and the parallax background have been great for photography, but the air is no fun to breathe (and does a kicker on life-expectancy to boot)
If we aren't asking these questions here, are they being asked? Don't bite the hand that feeds?
On device models (deepseek-coder, etc) are very good // better than the old way of using stack overflow on the internet. I have been quite productive on long haul flights without internet!
You're an engineer, your goal is to figure stuff out using the best tools in front of you
Humans are resilient, they reliably perform (and throw great parties) in all sorts of chaotic conditions. Perhaps the thing that separates us most from AI is our ability to bring out our best selves when baseline conditions worsen
I know this gets asked all the time, but what is your preferred workflow when using local models? I was pretty deep into it early on, with Tabby and Continue.dev, but once I started using Claude Code with Opus it was hard to go back. I do the same as you, and still use them on flights and whatnot, but I think my implementation could be improved.
Developer here. This was a blast to work on over the past few months in collaboration with the Magenta team. Built using a C++/JUCE foundation and a React frontend
> The researchers used microphones to record healthy and stressed tomato and tobacco plants, first in a soundproofed acoustic chamber and then in a noisier greenhouse environment. They stressed the plants via two methods: by not watering them for several days and by cutting their stems. After recording the plants, the researchers trained a machine-learning algorithm to differentiate between unstressed plants, thirsty plants, and cut plants.
This is interesting but obviously very different from the suffering that animals are experiencing.
My websites have this too with MDX, it's awesome. Reminds me of the old Bret Victor interactive tutorials back around when YC Research was funding HCI experiments
MDX & claude are remarkably useful for expressing ideas. You could turn this into a little web app and it would instantly be better than any word processor ever created.
Waymo has ~1000 cars. Uber has 8 million drivers. Worst case Uber will be acquired or merger or make a deal with one of the many AI driving startups.
I predict Waymo will have their own struggles with profitability. Last I heard the LIDAR kit they put on cars costs more than the car. So they'll have to mass produce + maintain some fancy electronics on a million+ cars.
This (particularly the figure 1 illustration) discounts the "distribution" layer for apps
Single app/feature startups will lose (true long before AI). A few will grow large enough to entrench distribution and offer a suite of services, creating defensibility against competitors
The distributors (eg. a SaaS startup that rapidly landed/expanded) will continue to find bleeding edge ways to offer a 6-12mo advantage against foundation models and incumbents
GitLab is a great example of this model. The equivalent bitter lesson of the web is that every cutting edge proprietary technology will eventually be offered free open source. However, there is a commercial advantage to purchasing the bleeding edge features with a strong SLA and customer service
The mistake is to think technology is a business. Business has always been about business. Good technology reduces the cost of sale (CAC) and cost of goods sold (COGS) to create a 85-90% margin. Good technology does not create a moat
Resilient businesses do not rely on singular technology advantages. They invest heavily in long term R&D to stay ahead of EACH wave. Resting on one's laurels after catching a single wave, or sitting out of the competition because there will be bigger waves later, are both surefire ways to lose the competition
More broadly, we are overbuilding infra on highly inefficient silicon (at a time when designing silicon is easier than ever) and energy stacks _before_ the market is naturally driving it. (with assets that depreciate far faster than railroads). Just as China overbuilt Shenzhen
I have heard (unconfirmed) that the US is importing CNG engines from India for data center buildouts. I loved summers in my youth in Bombay and the parallax background have been great for photography, but the air is no fun to breathe (and does a kicker on life-expectancy to boot)
If we aren't asking these questions here, are they being asked? Don't bite the hand that feeds?
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