Technology

For sure, it seems like 90% of ai startups are nothing more than front end wrappers for a gpt instance.

As someone who was working really hard trying to get my company to be able use some classical ML (with very limited amounts of data), with some knowledge on how AI works, and just generally want to do some cool math stuff at work, being asked incessantly to shove AI into any problem that our execs think are “good sells” and be pressured to think about how we can “use AI” was a terrible feel. They now think my work is insufficient and has been tightening the noose on my team.

TSMC doesn't really have official opinions, they take silicon orders for money and shrug happily. Being neutral is good for business.

Altman's scheme is just a whole other level of crazy though.

"When you're rich, they let you do it."

It's useful.

I keep Qwen 32B loaded on my desktop pretty much whenever its on, as an (unreliable) assistant to analyze or parse big texts, to do quick chores or write scripts, to bounce ideas off of or even as a offline replacement for google translate (though I specifically use aya 32B for that).

It does "feel" different when the LLM is local, as you can manipulate the prompt syntax so easily, hammer it with multiple requests that come back really fast when it seems to get something wrong, not worry about refusals or data leakage and such.

I receive alerts when people are outside my house, using security cameras, Blue Iris, CodeProject AI, Node-RED and Home Assistant, using a Google Coral for local AI. Entirely local - no cloud services apart from Google's notification system to get notifications to my phone while I'm not home (which most Android apps use). That's a good use case for AI since it avoids false positives that occur with regular motion detection.

The AI ecosystem is flooded, we need a good bubble pop to slow down the massive waste of resources that our current info-remix-based-on-what-you-will-likely-react-positively-to shit-tier AI represents.

He wants money/power, and he is getting it. The rest of the AI field will forever be haunted by his greed.

I don’t love it for summarization. If I read a summary, my takeaway may be inaccurate.

Brainstorming is incredible. And revision suggestions. And drafting tedious responses, reformatting, parsing.

In all cases, nothing gets attributed to me unless I read every word and am in a position to verify the output. And I internalize nothing directly, besides philosophy or something. Sure can be an amazing starting point especially compared to a blank page.

It's good for coding if you train it on your own code base. Not great for writing very complex code since the models tend to hallucinate, but it's great for common patterns, and straightforward questions specific to your code base that can be answered based on existing code (eg "how do I load a user's most recent order given their email address?")

https://web.archive.org/web/20240930204245/https://www.nytimes.com/2024/09/25/business/openai-plan-electricity.html

When Mr. Altman visited TSMC’s headquarters in Taiwan shortly after he started his fund-raising effort, he told its executives that it would take $7 trillion and many years to build 36 semiconductor plants and additional data centers to fulfill his vision, two people briefed on the conversation said. It was his first visit to one of the multibillion-dollar plants.

TSMC’s executives found the idea so absurd that they took to calling Mr. Altman a “podcasting bro,” one of these people said. Adding just a few more chip-making plants, much less 36, was incredibly risky because of the money involved.

It's selling an anticompetitive dystopia. It's selling a Facebook monopoly vs selling the Fediverse.

We dont need 7 trillion dollars of datacenters burning the Earth, we need collaborative, open source innovation.

The first part is true .... no one cares about the second part of your statement.