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Comment by ytxm

14 hours ago

It passed my threshold for not caring to try new models back with DS4, I use it for literally everything. Announcements of new models in the series always feel curious, because it doesn't really feel like there's much left to fix that would improve on what's already there for any task I know of.

It's a bit like obsessing over patch releases of some software after a major upgrade already solved the original problem long ago.

I have quite the opposite experience: I can do any concrete coding change with any model, but the intelligence limit just doesn't go through more complex debugging examples.

And then when I try a smart model, like Astra medium and it solves it (I had a firmware bug in my new laptop where I couldn't charge through USB-C) on the first try (altough with a repo already having lots of information about the hardware/firmware/debugging programs/traces), I realize how much time I'm losing on the few examples that the less intelligent models are just not able to debug and solve.

  • Also they can work in completely new domains, like Astra and Opus 5.5 starting to be able to use something like Blender. Currently they still often do horrible topology and basic UV mistakes, and the animations are really bad, but who knows where they’ll be in 5 years.

    • I don’t think these are completely new domains in training. Like I’ve taken up offers to help code up AI training material just to see what they’re up to and get a sneak peek at how the sausage is made, no idea who these front companies are working for of course, but they pay for all kinds of fringe cases and Blender wouldn’t even be considered fringe in what I saw at the beginning of the year. (I was only there to observe, never submitted anything, so I didn’t betray you guys by helping train your replacements.)

    • I’ve heard about this through vfx artists

      I was really hoping this would be solved since openai said that gpt-6 could paint brushstroke by brushstroke but it’s still shit

  • Very cool!

    Is your laptop something like framework which has open source firmware?

    I(and many other people) have a similar issue with usb-c charging not working consistently. I've been meaning to try one of these new smart models to help me debug the issue.

    • ASUS Zephyrus, but it was able to reverse engineer the ports and I was able to download the firware from the controller itself, write an emulator that emulates running the firmware on multiple controllers with different instruction sets (the USB Power Delivery controller is RISC-V) and the communication between them. Also it found out how to read the communication buffer that was on the devices for debugging, which helped it understand the USB data packets that were doing the handshaking and voltage/current negotiation.

      I had to reboot my laptop a few times though until I got to this, but it was a fun experience anyways.

      At this point open source isn't as much advantage as long as the firmware is not encrypted :)

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Yeah, but for some reason people think they need SOTA to help them work on their side/indie projects.

Like if we needed PhD intelligence for productivity tools and SaaS platforms, why weren't we hiring PhDs to build things before.

99.99% of people do not need SOTA ai.

Speed and price. You should try the 4.1 Flash on one of the fast providers. It's pretty crazy how fast this model works, and it's great for iterative software development because you can steer it fast to where you want to go.

https://www.lithosai.com/

https://www.coralbricks.ai/

  • How are these high-speed providers close to matching the API rates from deepseek?

    • Seems that V4.1 Flash is quite cheap to serve. Especially how it implements the cache, meaning the cache pricing can be very low depending on how you implement it in your inference engine.

      Depends on your use case. But if you do software development with a harness such as oh-my-pi, your cache rates are probably somewhere above 98%. Coralbricks has free cache reads, meaning it's much cheaper than the Deepseek API rates.

      Lithosai is more expensive especially in the ultra tier. It's if you want extremely snappy and fast responses, which is important e.g. for a personal assistant where every second counts.

      If you generate a lot of output, you're better off with the Deepseek API rates.

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  • Where does one even get decent ZDR provider? I'm wary of sending sensitive data but not at a scale where I would build my own machine.

    • You just search around, or heck, just ask Google for inference providers that are ZDR and whatever else you want. Just make sure to read their terms/privacy and review the security center. You will have to request access if you are wanting to get into the deeper details.

      Outside of major players like Amazon/Google which have compatible offerings available, I believe together.ai, fireworks.ai, and deepinfra.com are, as best as I can tell, US-based (if that matters in your situation) SOC2/HIPPA/ZDR. Each of them offer serverless model hosting with caching, which is going to be the cheapest overall. Most of them also offer private AI deployment which is more expensive but your entirely own instance. Some of them more heavily quantize their models (deepinfra) so take that into your workload considerations. I included deepinfra because they tend to have some the new models sooner than others or have models the others don’t (like mimo). IMO, together > fireworks > deepinfra.

      However, you’ll have to keep in mind that for true ZDR you give up caching which increases your inference costs, so it depends on how “Zero” you need the zero to be and on what timeframe. If you just don’t want your data being trained on, normal use is fine imo. If you are working on something actually sensitive (like, because of NDA agreements and such), then they might not be the right choice and you may be looking at more expensive offerings or building a machine.

      One note: you have to pay attention to the source of the inference. Many (similar to open router) offer models that are pass-throughs to a providers API, but they are pretty clearly marked. Just make sure the model is marked as serverless when evaluating new ones. This is where a proxy comes in handy so you can prevent your LLM from accessing a different models from the specific ones you’ve vetted.

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Same. I'm just happy sticking with them and am consistently impressed. Cost is so good and kind of keeps you honest.

definitely could use less thinking time and lower token usage, which is what this bump is focused on

> improve on what's already there for any task I know of

What about "good governance"?

Does it have zero hallucinations? Does it reflect thoroughly on every single idea it uses, verifying its solidity?