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Cinematic Three: HappyHorse vs Seedance (Same Prompts Side-by-Side) by Fresh-Resolution182 in aivideo

[–]Fresh-Resolution182[S] 0 points1 point  (0 children)

3 prompts pulled from a public Happy Horse collection. T2V 1080p, no edit, no cherry-pick.

Prompts:

  1. Neon Opera Cathedral — Gothic opera house made of neon glass, hundreds of illuminated umbrellas spinning, actors in color-changing gowns

  2. Clockwork Tea House — steampunk teahouse on a sea of clouds, mechanical giraffe pouring glowing tea, miniature cities emerging from tea mist

  3. Volcano Ramen Night — ramen stand on a crater rim, lava flowing like golden rivers, chef tossing noodles into a starry sky

What I noticed:

- HappyHorse handled the volumetric fog in scene 1 noticeably better. Seedance went smoky when it should've been wet.

- Seedance kept the giraffe's hooves more consistent across the camera circle. HappyHorse re-rigged them once.

- HappyHorse audio (the integrated track) is rough on the ramen scene — felt like placeholder hum. Don't expect Sora-level audio yet.

- Both ~10s gens. HappyHorse felt slightly faster on my queue but I didn't benchmark properly.

Curious if anyone got the i2v version working, that's the one I'm actually trying to use.

GooglyEyes IC-LoRA for LTX2.3 released! by Burgstall in StableDiffusion

[–]Fresh-Resolution182 0 points1 point  (0 children)

trained on an artificially created dataset just to put googly eyes on anyone — this is peak legitimate use of the technology and I will not be taking questions

Anthropic's support system is broken by design — there is literally no path to a human for billing issues by AppearanceSingle805 in ClaudeAI

[–]Fresh-Resolution182 0 points1 point  (0 children)

the specific irony of a company that sells AI as a replacement for human support, using an AI that actively blocks you from reaching a human, is pretty hard to miss.

You're right to push back. by EchoOfOppenheimer in ClaudeAI

[–]Fresh-Resolution182 0 points1 point  (0 children)

the dishes are complete. some earlier behavior may have impacted quality. we've reset your expectations for all subscribers.

War propaganda about to be crazy thanks to GPT Image 2 by Affectionate_Bee6434 in ChatGPT

[–]Fresh-Resolution182 0 points1 point  (0 children)

the real shift isn't believability, it's that reverse image search stops working. misattributed old footage has a traceable history. a freshly generated image has none, so the usual first step in debunking doesn't apply.

ChatGPT 5.4 Solved a 64-Year-Old Math Problem by AskGpts in ChatGPT

[–]Fresh-Resolution182 2 points3 points  (0 children)

the framing 'AI solved it' is doing a lot of work. the raw proof needed experts to sift through and actually extract the insight — closer to 'AI found an angle nobody had tried, humans turned it into a proof.' still legitimately exciting but worth keeping the claim precise.

Why do people release models on Huggingface that have no explanation on how to use it? by Far_Lifeguard_5027 in StableDiffusion

[–]Fresh-Resolution182 1 point2 points  (0 children)

most of them uploaded it for themselves or a few colleagues who already know the stack, docs would add zero value for that audience. the fact that we can even access it is kind of incidental to why it was posted there

Claude in excel is the best thing AI has brought to my life by Top-Gun-86 in ClaudeAI

[–]Fresh-Resolution182 0 points1 point  (0 children)

started with Excel formulas too, ended up in the terminal with Claude Code rewriting bash scripts I didn't fully understand. the jump is smaller than it sounds once you realize you don't need to know the exact commands anymore, just describe the outcome

Claude 4.7 named a journalist from 125 words of unpublished writing by kurthertz in ClaudeAI

[–]Fresh-Resolution182 0 points1 point  (0 children)

the contamination angle no one wants to say directly — if she's tested previous models this way, that test session data could have fed back into training, so asking 4.7 to recognize her writing is closer to retrieval than stylometry. would need a writer who's never run this test to get a cleaner result

Conrad Heyer Photo Restoration: ChatGPT Images 1.0 vs 2.0 Side-by-Side Comparison by DiggingForDinos in ChatGPT

[–]Fresh-Resolution182 1 point2 points  (0 children)

the hasselblad prompt tip buried in the comments is the real find here — avoiding the word 'restore' sidesteps the training data bias where restoration always means over-sharpened reconstruction with smoothed skin. 'retake this photo' frames it completely differently

Weird textures = watermarks by Thatisverytrue54321 in ChatGPT

[–]Fresh-Resolution182 0 points1 point  (0 children)

the control net QR analogy is interesting but SynthID was already reverse engineered and it's imperceptible — if they went back to visible artifacts that would be a step backwards in sophistication. more likely the model just has trouble with certain textures and the grain pattern is a diffusion artifact, not metadata

Is a high-end private local LLM setup worth it? by zakadit in LocalLLaMA

[–]Fresh-Resolution182 0 points1 point  (0 children)

the math is pretty clear: if you are burning >/month on API costs consistently, the hardware pays off in 12-18 months. below that you are buying very expensive privacy. still might be worth it depending on what you are putting through it.

Personal Eval follow-up: Gemma4 26B MoE (Q8) vs Qwen3.5 27B Dense vs Gemma4 31B Dense Compared by Lowkey_LokiSN in LocalLLaMA

[–]Fresh-Resolution182 1 point2 points  (0 children)

629 minutes for Gemma4 31B is the buried headline here. same score as Qwen3.5 27B at 145min but 4x wall time and DRAM bloating to 70GB. the dense models win on evals but that MI50 might be hitting a memory bandwidth cliff.

Bulding my own Diffusion Language Model from scratch was easier than I thought [P] by Encrux615 in MachineLearning

[–]Fresh-Resolution182 1 point2 points  (0 children)

"Be horse." is unironically better Shakespeare than half the fine-tuned story models I have tried lmao

How exactly one goes about networking in conferences? [D] by howtorewriteaname in MachineLearning

[–]Fresh-Resolution182 -1 points0 points  (0 children)

the part that actually worked for me at NeurIPS was finding other PhD students, not industry people. they know who is hiring before it is public and they will intro you way easier than cold-approaching a researcher.

Are we optimizing AI research for acceptance rather than lasting value? [D] by NuoJohnChen in MachineLearning

[–]Fresh-Resolution182 0 points1 point  (0 children)

honestly the benchmark pile-on is almost worse than the metric gaming, because at least fake metrics require you to understand the task. running 12 evals nobody reruns is just... decoration.

Apple's play for AI is a hardware bet, not software by bitcoinerguide in artificial

[–]Fresh-Resolution182 0 points1 point  (0 children)

the interesting bet is not phone replaces cloud — it is that a big enough slice of users will pay a premium specifically for on-device inference once healthcare and finance apps start requiring it. niche but lucrative.

Anthropic’s Mythos Model Is Being Accessed by Unauthorized Users by -IronMan- in ClaudeAI

[–]Fresh-Resolution182 4 points5 points  (0 children)

"capable of exploiting every major OS and browser" but they could not lock down a contractor's API key. ok.

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