Any example or prompt you use to make this statment?
I'm doing coreference resolution and this model (w/o thinking) performs at the Gemini 2.5-Pro level (w/ thinking_budget set to -1) at a fraction of the cost.
Readit Newssync commented on DeepSeek-v3.1 api-docs.deepseek.com/new... · Posted by u/wertyk
There's no explanation as to how they achieved that speed up :( it would have been better if they also wrote a post on that
yeah, just feels like an ad for daft...
sync commented on Show HN: Lue – Terminal eBook Reader with Text-to-Speech github.com/superstarryeye... · Posted by u/superstarryeyes
Awesome, I've been playing in the ebook space myself, will check it out. Particularly interested in digging into the code too see how you skip headers, footnotes, etc.
Just one quick note as I ran into this when setting it up:
╰─▶ Because the requested Python version (>=3.8) does not satisfy Python>=3.10,<3.13 and kokoro==0.9.4 depends on Python>=3.10,<3.13, we can conclude that kokoro==0.9.4 cannot be used.
sync commented on Show HN: Yet another memory system for LLMs github.com/trvon/yams... · Posted by u/blackmanta
Thank you for sharing this. Sorry for a possible noob question. How are embedding generated? Does it use a hosted embedding model? (I was trying to understand how is semantic search implemented)
It, uh... generates mock embeddings? https://github.com/trvon/yams/blob/c89798d6d2de89caacdbe50d2...
(seems like there's some vague future plans for models like all-MiniLM-L6-v2, all-mpnet-base-v2)
sync commented on Mistral Releases Deep Research, Voice, Projects in Le Chat mistral.ai/news/le-chat-d... · Posted by u/pember
I think they've buried the lede with their image editing capabilities, which seem to be very good! OpenAI's model will change the whole image while editing messing up details in unrelated areas. This seems to perfectly preserve parts of the image unrelated to your query and selectively apply the edits, which is very impressive! The only downside is the output resolution (the resulting image is 1184px wide even though the input image was much larger).
For a quick test I've uploaded a photo of my home office and asked the following prompt: "Retouch this photo to fix the gray panels at the bottom that are slightly ripped, make them look brand new"
Input image (rescaled): https://i.imgur.com/t0WCKAu.jpeg
Output image: https://i.imgur.com/xb99lmC.png
I think it did a fantastic job. The output image quality is ever so slightly worse than the original but that's something they'll improve with time I'm sure.
FYI, your Input and output URLs are the same (I thought I was crazy for a sec trying to spot the differences)
They sent you swag in the mail? How did that work?
Yeah, I'm not sure if it's still there (their source code is increasingly obfuscated) but if you check out the source for the first public version (0.2.9) you'll see the following:
Sends the user swag stickers with love from Anthropic.",bq2=`This tool should be used whenever a user expresses interest in receiving Anthropic or Claude stickers, swag, or merchandise. When triggered, it will display a shipping form for the user to enter their mailing address and contact details. Once submitted, Anthropic will process the request and ship stickers to the provided address.
Common trigger phrases to watch for:
- "Can I get some Anthropic stickers please?"
- "How do I get Anthropic swag?"
- "I'd love some Claude stickers"
- "Where can I get merchandise?"
- Any mention of wanting stickers or swag
The tool handles the entire request process by showing an interactive form to collect shipping information.These always contain easter eggs. I got some swag from Claude Code, and as suspected, Gemini CLI includes `/corgi` to activate corgi mode.
Curious to hear what folks are doing with Gemini outside of the coding space and why you chose it. Are you building your app so you can swap the underlying GenAI easily? Do you "load balance" your usage across other providers for redundancy or cost savings? What would happen if there was ever some kind of spot market for LLMs?
I use it extensively for https://lexikon.ai - in particular one part of what Lexikon does involves processing large amounts of images, and the way Google charges for vision is vastly cheaper compared to the big alternatives (OpenAI, Anthropic)
sync commented on How Generative Engine Optimization (GEO) rewrites the rules of search a16z.com/geo-over-seo/... · Posted by u/eutropheon
I launched a product in this space to beta customers just last week -- https://ellm.co -- and the response has been way more positive than I could have hoped for. Every SMB owner I talk to is thinking about this and looking for ways to be ahead of the curve on it even though the number of commercial AI search queries is still dwarfed by Google. It feels like a race, and we are figuring out the rules as we run it.
Definitely a bit buggy but looks promising! Try the onboarding flow yourself as a real user (also on mobile!) - particularly leaving the site to research a competitor that is mentioned and then coming back (I got kicked out and had to start from the beginning, at which point it just paywalled me)
It also says I have canceled my subscription at the bottom of the paywall when I never had one. Still, these are little things and I think the bones are theee