nickreese

This is 100% my experience. I rarely reach for Astra as we speak.

Fun fact I learned in Spain recently. They block Cloudflare Edge IPs during soccer games. Took me a long time to figure out why I was having intermittent outages.

I had the same experience. Moving back to Sol for actual implementation.

I think people undervalue skills on the cross repo boundaries and how systems interact with other systems.

For instance… how to deploy a service or new service’a docker container. Get secrets in value blind, manage secrets value blind. Those sorts of things have been wildly valuable. Also due to the nature of skills and how they are pulled in by your harness they can really prime the context in a way that is really useful to agent autonomy if that is your thing.

This is 100% smoke and mirrors. Prove the bucket is empty and nothing was transferred out and I'll believe they deleted it.

Some people use hooks for that. I just avoid CC and use Codex.

Where would one get the dataset for this. This would be awesome to build in realtime.

This is 80% of the reason I have an apple watch. I whisper to it for reminders, timers, calendar stuff all day.

It isn't open... but drop me an email and I can send you it. Basically just tracks a list of known lmstudios on the network, queries their models every 15 seconds and routes to the ones who have the requested models loaded in a FIFO queue tracking the number of tokens/model (my servers are uniform... m4 max 128gb studios but could also track the server) and routes to the one that has just finished. I used to have it queue one just as it was expected to finish but was facing timeout issues due to an edgecase.

Exactly. Using lmstudio you can get structured output like with openai... I have everything in a zod schema then wrote an adapter to both openai and lmstudio instance.

I run lmstudio for ease of use on several mac studios that are fronted by a small token aware router that estimates resource usage on the mac studios.

Lots of optimization left there, but the systems are pinned most of the time so not focused on that at the moment as the gpus are the issue not the queuing.

I'm just now moving my main workflows off openai over to local models and I'm starting to find that these smaller models main failure mode is that they will accept edgecases with the goal of being helpful.

Especially in extraction tasks. This appears as inventing data or rationalizing around clear roadblocks.

My biggest hack so far is giving them an out named "edge_case" and telling them it is REALLY helpful if they identify edgecases. Simply renaming "fail_closed" or "dead_end" options to "edge_case" with helpful wording causes qwen models to adhere to their prompting more.

It feels like there are 100s of these small hacks that people have to have discovered... why isn't there a centralized place where people are recording these learnings?

Wow, weird to see Kuppy on this platform. Thought it was a mistake haha.

Is there a framework for this?

This is such a needed addition! Huge duckdb fan, congrats team!

Is it just me or is having the AI help you self sensor (as shown in the demo live stream: https://www.youtube.com/watch?v=cfRYp0nItZ8)... pretty dystopian?

Note: Running out the door, here is a brief summary that hasn't been deeply considered.

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Example: I casually commented at the gym that I thought Trump would win about a week ago and went into a very long conversation/debate with several people in the gym.

I asked each of them to show me their filter bubbles... once I had explained it to them. 2 Spaniards, 2 Andorran, 1 French guy. The general consensus seemed to be that Trump was a major step back socially and would pollute the environment, not care about climate change, etc.

Their information came from traditional news, Instagram/Tiktok and one from Reddit/HN/X. The only one that was even open to hearing my views during the conversation was the guy who read Reddit/HN/X. Everyone else had their minds made up.

Today at the gym, I had the 2nd part of this conversation with 3 of the guys that were there this morning. The general take away that the guy who read Reddit/HN/X summed up is one of: "Europe has yet to reach "peak tolerance" where it appears the US is already there." This realization was came to due to the issues of immigrants in both Spain/France who don't assimilate which was a hot button issue for them.

I kinda agree with this sentiment. I think that Europe (at least the part I'm in) doesn't seem to have a great immune system for people who abuse the system and generally punishes tall poppies both socially and economically. The US is completely different, tall poppies are celebrated and if you fail or get sick you have no safety net.

For me the difference in world views is best summed up by what people are focusing on. Climate, equality, and tolerance are the key issues I see pushed heavily in Europe... I see this as stemming from the "tall poppy" syndrome that is prevalent in both Spain/France. In the US, people care about other things and are generally focused on things that directly impact them. That is what this election was about. Less focus on perceived injustices or injustices of the past and more focus on making the future better with something different.

Is Europe a great place? For sure... but it has wildly different problems and world views than the US does. I think it is hard to appreciate that until you've bene immersed in both cultures long enough.

In general, I'd just say there is more nuance to everything than our brains can handle. My little mission has been to try and bring back nuance into the conversation. Black and white thinking is lazy. Nuance exists, find it and challenge your filter bubble.

I'm excited to see how this casual gym conversation continues.

As an American living in Europe, it is fun to see the filter bubble Europeans live in with regards to how the US is framed in the media here and even in common coversation. I was talking to my French buddy about it and we were comparing our filter bubbles. Please realize that there is a filter bubble that all of us live in.

I just bought the EU version of this in 55inch and candidly wish I got the 65. The 55 I have to run it scaled and my mac crashes daily to it.

Nate - We discussed the issues extensively on discord and you even did a video call with me and my team. The entire core theming structure changed multiple times and worked with Eshan (which you represented as being a great developer and contributor to Tamagui) to solve the issues… just to have them break again on a minor version for you to release takeout. Having donated over $1,000 to the project and spent a ton of time in the discord and messaged with you more than a handful of times I feel like this comment isn’t genuine but is to save face on HN.

We were an early adopter and sponsor of Tamagui. Impressive tech but massively unstable even on minor version bumps. We even had a core team member working on the project and the breakage was every version. Lost more than 6 months of time relying on it. Ultimately we killed the project because of the decision to go with Tamagui. Just an FYI for those considering this. Abstractions on unstable abstractions is a good way to hate your project.

Kinda hijacking the thread but... My hypothesis is that we will look back and see that Streetview imagery is a goldmine for AI and will be a path to being able to answer HARD questions about the real world.

The insane thing is there are only like 7 companies that actually have meaningful datasets.

I spent 1.5 years studying the geospatial space and went so far as buying a Mosaic51 and scanning the entire country of Andorra as a test before looking at buying the camera manufacture.

Ultimately I walked away from buying the company after issues with the family office I was working with... but long story short I believe streetview imagery will be a gold mine in the future.

If anyone is working in the space. Feel free to ping me, happy to chat and even make intros to the space. If you are training an AI, ping me as well. Happy to open my images up to the right person to make something "country scale" (160k images... every 3 meters with RTK labeled gnss data).

Claude, GPT, Llama3.1 directly. The models are really capable if you prompt correctly.

Yeah, not open source.

Definitely look into cursor if you like Claude dev. It isn't apples to apples, but their chat mode is very similar.

I've been using AI models to do frontend design and candidly this doesn't hold a candle to just working directly with the base models.

With the base models you can ask: Hey, make me 5 designs that fit xyz requirements and it will go to work. If you already know front end design, you can take that up a level and pass it an emmet abbreviation of the rough code you want and say only use tailwind colors of sky, zinc, and blue.

I am decidedly not your audience, but if anyone on HN is thinking about how to speed up frontend dev and they are a frontend dev, I'd suggest just messing with the base models more.

Once you get the hang of it, it can be like working with a designer who's feelings don't get hurt... which I love.

"Meh, I don't like those designs, generate me 5 more and feel free to increase the model's temperature up quite a bit to see if you can come up with something cool."

Thank you for this explanation. A few things just clicked for me.

For those looking for something more robust... this is where I'd look: https://github.com/kitajs/html.

Also Honojs (hono.dev) has a built in HTML function which is quite good and I've used extensively.

Using this pattern has been a gift. It is really freeing to write templates without a framework and worrying about SSR.

Years back I dove completely in on Svelte and even wrote my own SSG that helped kick off the Islands/partial hydration crazy... Elder.js. It was fun, but burnt me out of open source.

Today, I only pull for a template language and deal with SSR/Hydration for pages that really need it.

I want JS projects that don't break 6 months after the last build. The way you get that is by not adding more dependencies and not chasing the latest craze.