tempoponet

If llama 3 70b were available for $400 today, people would make it work. They would have 4 of them working side by side or 1 of them working with a GPU on another model.

To me, it's like imagining if Sonnet 3 was burned into an ASIC 8 years ago and then never changed. It would still be revolutionary, and today we would have an entire ecosystem of tools and services built around it, likely surpassing some of our current workflows.

The frontier is a different beast, but it would likely mean competing on price.

The barrier to entry for tinkering on Linux is so much lower now for anyone with a $20 Claude/Codex plan. What might have been an hours/days of fruitless head-scratching can now be done in minutes while you grab a coffee.

While I haven't tried this yet, I do have a Bazzite box that would be a good fit. I wouldn't treat the rough edges as a deterrent the way we have in the past.

In Bazzite I've had innumerable issues with waking from sleep and display driver crashes, which means a 50 ft walk to press the reset button.

If you're cool with that, this appliance isn't for you.

I bought an irresponsible pile of homelab equipment in 24/25. Hard drives, SSD, memory, GPUs.

I feel bad for people locked out right now, since it's become more interesting and important than ever.

At the time it seemed wasteful, but I'm happy to report that I'm putting it all to use now.

To go further down this pipe dream - Anthropic / OpenAI would buy them all and still price out the consumer. There's no end-run in this scenario.

I can actually use and enjoy Linux. The "year of the desktop" never came for me, but instead I got the "year of the cli".

For 20 years I've used Linux in one form or another, but I've felt like I was kneecapped for the most basic things. Just trying to plug in an external drive or a second display meant hours of stack overflow and pasting commands I didn't understand.

Now I'm using several Linux machines for Steam, NAS, local LLM, development, and what used to derail a weekend project now amounts to a coffee break while Claude figures it out.

It's fine for dense models where you need them in VRAM, less so for MoE where you're offloading layers to ram. But 32/32 is pretty good for both in the popular ~30b range right now.

- You can send any amount of money to anyone in the world very quickly and cheaply, and nobody can stop you.

- No government can dilute it or limit its supply.

Stuff like that. Maybe that matters to you, maybe not, but BTC was created because that didn't exist. And even if you don't use it, you're living in a world where financial institutions have to live alongside an alternative that does these things, for whatever that's worth.

This is where a lot of the crypto scammers on x have moved, selling ai/bots to do this. It seems like the odds slip significantly after these large bets are filled.

For the huge percentage of devs using vscode, switching to Cursor was essentially adding a new color theme and a chat window. The CLI switch was far more radical.

Thank you for the thoughtful reply. I have some smaller 3080's I'm looking to place and this sounds like a good opportunity.

The memory upgrade is $1k on a Macbook Pro. The laptop is ~$5500.

Expect to pay $4k-10k

- Your RTX 6000 is closer to $10k now

- Sparks are creeping into the $4-5k range

- AMD Strix are ~3.5k

- Apple depends on chipset and memory. Sweet spot would be 128gb M3 Ultra, probably $6-8k but admittedly haven't been tracking closely. New M5 might come in the fall. You can get a new 128gb M5 Max laptop for ~5-6k today.

- a 4x3090 rig would take $5-6k

Every platform has tradeoffs, but it's mostly ecosystem, memory bandwidth, and power consumption. They're all slow. The best option is likely to rent hardware on Runpod. The RIO on self-hosting is very low unless you have a specific need or you're ok treating it as a hobby.

Why this entire tool chain instead of building within something like pi code?

I've been exploring this area and a project like https://github.com/itayinbarr/little-coder (not my work) lets me mix and match with my current setup or any plugins built for pi.

It's older, but Hermes Pro 2 (same lab as Hermes agent) is a fine-tune of Mistral 7b for tool calling and structured outputs.

This isn't for agentic loops, though. This is for turning simple requests into API calls.

Similarly, the agentic coding success stories are from orgs that had all of these things out of the gate.

It reads like the inventors of Claude can't get Claude to apply a "human in the loop" workflow.

You can fine-tune a model, but there are also smaller models fine-tuned for specific work like structured output and tool calling. You can build automated workflows that are largely deterministic and only slot in these models where you specifically need an LLM to do a bit of inference. If frontier models are a sledgehammer, this approach is the scalpel.

A common example would be that people are moving tasks from their OpenClaw setup off of expensive Anthropic APIs onto cheaper models for simple tasks like tagging emails, summarizing articles, etc.

Combined with memory systems, internal APIs, or just good documentation, a lot of tasks don't actually require much compute.

Rather, Imagine you have 2-3 of these working 24/7 on top of what you're doing today. What does your backlog look like a month from now?

You're right for the same reason that the original iPhone outranks the iPhone 3Gs.

OpenClaw had a huge viral marketing campaign. It wasn't a coincidence everyone on twitter was talking about it at the same time suddenly. To its credit, it also executed well enough in a few areas that captured people's imagination. Most of the concepts are ideas people have been toying with for years, though.

What kind of small tasks do you find it's good at? My non-coding use of agents has been related to server admin, and my local-llm use-case is for 24/7 tasks that would be cost-prohibitive. So my best guess for this would be monitoring logs, security cameras, and general home automation tasks.

Maybe for a coding agent, but a daily/weekly report on sensitive info?

If it were 2016 and this technology existed but only in 1 t/s, every company would find a way to extract the most leverage out of it.

And here's the blog article describing the widget: https://maurycyz.com/misc/ads/

Remember when Netflix almost split its brand with "Quickster"? It was the dying DVD by mail service, but the whole debacle did nothing but confuse people.

The new Alexa uses Claude under the hood, and it also misinterprets my intent, only with a 2 second longer delay and slightly more approachable tone.

Everyone has their own hill to die on, that's the thing about personal computing. It's the same if you ask why they can't switch mobile OS. It's some seemingly trivial app or feature that almost nobody cares about.

They support their phones for years longer than any vendor. This has been widely understood for probably 10+ years at this point.

There's plenty of room for criticism without a blanket conspiracy that doesn't match what most can observe.

I was really looking for tangible, actionable advice since I'm facing slow adoption in my org. This post seems to hide behind the "secret sauce" that it claims made all of the difference.

Once local models are good enough there will be a $20 cloud provider that can give you more context, parameters, and t/s than you could dream of at home. This is true today with services like groq.