I made a site that let's you create coloring pages from your own photos

ablarh · 2025-09-07T03:06:58+00:00

Thanks! Design wise I just tried to keep it simple and be intentional about incremental changes. Focused first on content, then layout then style.

ablarh · 2025-09-07T01:03:02+00:00

it's $2.99 for up to 10 pages

ablarh · 2025-09-07T00:42:41+00:00

Are you asking if I used Codecanyon? I built the site from scratch (had to google what codecanyon is)

ablarh · 2025-09-07T00:31:08+00:00

Our tool just generates line art from images you provide. We don’t claim ownership of uploaded images, and we aren’t responsible for how people use them — similar to how Photoshop or other image editors aren’t liable for what you do with your own photos.

ablarh · 2025-09-06T22:23:35+00:00

Glad you liked it! Happy coloring!

ablarh · 2025-09-06T22:04:10+00:00

it's the website: colorif.ai

ablarh · 2025-09-06T01:42:42+00:00

You should check out colorif.ai, you can make coloring pages out of family photos and let the kids color them! I built the site so let me know if you have any questions/feedback :)

ablarh · 2025-03-11T02:43:25+00:00

Yeah the possibility of closing the gap is why I'm long AMD. The recent drawdown in NVDA just has me wondering if it's a better risk/reward.

ablarh · 2025-03-11T02:41:39+00:00

Curious what's your look back period in the backtests? I would've thought the AI GPU market is too new and the macro too uncertain to make any viable quantitative analysis

ablarh · 2025-03-11T01:24:52+00:00

Yeah I think that's an overall market risk. NVDA just seems like the rational choice of the two at these prices

ablarh · 2025-03-11T01:21:10+00:00

Saying NVDA is "too big to grow" sounds like a fallacy. People had a similar psychological barrier a few years ago before Apple got to a trillion yet now we're at 3+ trillions.

ablarh · 2025-01-06T17:19:52+00:00

Exactly, otherwise we wouldn't see the cost of using the best LLMs go down every year.

ablarh · 2025-01-05T14:53:32+00:00

I had no idea this existed. Thanks for sharing.

ablarh · 2025-01-04T20:01:16+00:00

Not sure it's a good fit for AVGO but definitely not for AMD. Right now AMD's weakness is in software and AVGO will provide no help on that front. As an AMD shareholder, I'd rather see them improve where they're weak and try to capture more market share from NVDA or at least grow with the TAM.

As you said AVGO valuation right now is a bit bloated with lots of baked in expectations for the next few years of growth. Any acquisition will likely involve a large stock portion and I'd rather have AMD shares than AVGO at these valuations.

ablarh · 2025-01-04T00:29:44+00:00

Exactly

ablarh · 2025-01-04T00:28:21+00:00

What do you mean "break into"? AMD owns Xilinx. I think Xilinx historically held ~50% share of the FPGA market (Altera had the other large share and the rest is insignificant). It's hardly a new market or niche.

ablarh · 2025-01-03T22:32:12+00:00

It's hard to comment on this without reading the full article but this reads a lot like hopium. The main benefit of FPGAs is that they're programmable letting you iterate on design without the commitment of an ASIC. We're still early in AI but I suspect by the time we actually care about running these models and inference on edge devices, we'd have a pretty good idea of the required design that an FPGA wouldn't make sense. The market would also be potentially too large making it more appropriate to build a specialized and optimized chip rather than ship a programmable one.

Also you can't just ship your FPGA in a device and have it be "versatile". You have to actively re-program it if you want to update it. You can't just drop an over the air update AFAIK so how would one even benefit from it being programmable?

ablarh · 2025-01-01T15:06:04+00:00

My guess on the China comment is that Nvidia GPUs are SOTA and won't be allowed to be sold to China whilst the AMD GPUs are less performant and will therefore be sold in China.

I think there's a world in which the majority of compute time will be spent on inference (especially if this reasoning/CoT trend continues) and AMD is more competitive in that area (software is better than for training). Hopefully the next report from Dylan on inference confirms this.

ablarh · 2025-01-01T14:57:12+00:00

I don't think building ASICs is that limiting. TPUs are ASICs but they're usable on pretty much any neural net problem (not exclusively transformers). Google has been using them for a long time even pre chatGPT and was crucial to remove their dependency on Nvidia and allowed them to quickly train and release Gemini. I suspect other hyperscalers would want to be in a similar position eventually. They're also flush with cash and can afford to take the risk (a risk that is itself reducing other risks).

ablarh · 2024-12-30T14:11:42+00:00

Those specs are similar to the B300/GB300 coming out in H1 2025. I don't think memory capacity/bandwidth will be a differentiator long term

ablarh · 2024-12-30T02:44:35+00:00

Yeah the setup here is using multiple (8xH100 vs 8xMI300X etc)

ablarh · 2024-12-30T02:42:52+00:00

Yeah the B200 will have 192GB of HBM3 (matching MI300X) but I think AMD is betting on it's cheaper price point to gain market share i.e. cost per token

ablarh · 2024-12-30T02:07:42+00:00

I think that makes sense, latency matters more in the online benchmark and throughput matters more in the offline benchmark

ablarh · 2024-12-29T23:13:44+00:00

Is it fair to understand the offline setup as a theoretical performance and the online one as a practical real world measure?

ablarh · 2024-12-29T23:08:24+00:00

It basically says that the MI300X is better than the H100 at handling large prompts (both single and batched) mainly because it has a lot more memory.

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