steno132

My first time using Grok. I'd been so used to using AI models that declined to do things I told them, like tagging people in a video feed, helping me "optimize" my taxes or managing my Twitter bot farm.

Grok just did these things for me, no questions asked, no ethical judgments. No woke.

Elon really doesn't get enough credit for Grok. People don't want the most powerful reasoning model or "constitutional AI". They just want a model that does what they say. Elon understood that insight (like he usually does) and no one else really did and that's probably why Grok has been growing rapidly over the last two years or so.

But practically AI inference requires substantial local computing resources. It's not some web app, it's a order of magnitude more compute needed

Agreed. I feel like Alphabet (who wrote this post) has kind of lost track of what they're espousing here.

Self driving cars were the "monkey" 10 years ago but now they are largely derisked. I'd like to see Alphabet working on the next generation of innovations. For me personally, I'd like to see them work on:

- Teleportation. - Talking animals. - A cure for death.

I'm not seeing them work on anything remotely as ambitious these days!

Seems like you tore through some outdated Jira tickets, which is cool, but what was the impact of your work?

Hard doesn't mean impactful. In fact that's one of the biggest mistakes I see junior engineers make! But glad you got that learning experience, as you become more senior you'll definitely develop a better understanding of what drives actual impact.

This is a great initiative. Postgres was written in the 1980s and we can't afford to have our most utilized workloads running on a software written before most of us even existed. LLMs make it possible to rewrite Postgres and we should take that chance.

What I'm saying is that Postgres was built for a long gone age. We need a extensible database written in Rust which can serve as a foundation for any data system. We don't need a relic of the 1980s serving our most critical workloads.

Take a example. You could be a hunter gatherer, you could grow all your own crops from scratch, you could forsake all modern medicine and rely on superstition - would you be considered a wise person? You figured out things a lot of people didn't, you took the harder road - but most people would say this approach is just dumb.

What's wise isn't forsaking technology, it's using technology to improve things, and developing new technology as well. What's wise is using AI as a power user and seeing how you can contribute to the intelligence age.

Celebrating a foregone past where human intelligence was more valuable is hopeless and naive at best.

My view is, if you're going to use the service - you should give the data.

It's like using Gmail and expecting them not to train their AI models on your data - how can you expect that when they're giving you a secure, reliable, highly functional email client completely for free?

The digital economy only works if everyone pays their fair share. If you don't want to give your data then you are really harming everyone by slowing down AI development for everyone else.

Exactly, thank you, we are on the same page! It's great to be able to use our own devices and not have their compute coopted by a third party.

I'd rather not have intensive compute needed shifted onto my personal machine which I want to use for something else.

What's wrong with the data being used for something else? Someone is providing digital intelligence to us, saving us many hours a week, so the least we can do is provide them a little data so they are able to improve their service.

It would be selfish and unethical not to in my view. And ultimately the data is just being used in order to improve the models and benefit us, not for anything nefarious.

GPT1 was released in 2018, so yes, since then.

Practically if you're running a small personal automation project you're not going to want to waste a lot of time configuring and tuning a local model. You want to build the automation and move on.

If you're building a automation as a company you definitely won't want to take on the long term maintenance overhead of running your own models for some automation project.

This is dumb. Don't do hard things, do things which have a high ROI.

I could try to swim across the Pacific Ocean, walk across Siberia or consume a family size portion of McDonalds in a single sitting. All those things are hard. All those things have zero to negative ROI.

Doing hard things won't get you anywhere. Most hard things are useless. And a lot of the most valuable things are not hard at all.

Test driven development is one of the worst ideas nowadays in the LLM age. We have models that can consistently write expert level, usually bug free code for you and rapidly fix even complex bugs in your codebase.

The token cost and tech debt introduced by tests is just not worth it. There's usually no bugs and if there are, you can fix them quickly if and when it's needed.

I don't get this obsession with smaller models. I've been using Claude and GPT models for years and have had zero issues with them.

I see absolutely no benefit to me as a end user for a local model which is going to take up more of my CPU and memory and slow down my machine. I almost always have Internet and if I don't then not having access to a AI model is the least of my concerns.