droidjj

The patent claims the jury found were infringed:

https://patents.google.com/patent/US10659885B2/en?oq=us10659... claims 17 and 19

https://patents.google.com/patent/US10820117B2/en?oq=us10820... claim 16

It’s just a woman’s voice…

Is this comment about astroturfing or a decline in comment quality? To be honest, I was one of those early commenters, and I was just genuinely shocked at the price drop. I am also excited to try Opus 5.5!

Not only is GPT-6 Luna better, it's 50% cheaper. It was already practically free on a pro plan.

I’m sure there are a wide variety of experiences out there, but here’s my perspective as a former biglaw associate and current solo litigator:

I have had some success using frontier models from the last 6ish months, but only when I can break up my work into discrete and verifiable tasks. For example, I had ~15k pages of discovery I needed to dig through for a summary judgment motion. Instead of just asking Claude to find the best evidence, I asked it first to run a clean, high quality OCR pass (it was almost entirely PDFs). Then I had it generate embeddings and write some reusable python scripts to make keyword and semantic searching easy for agents. While I was writing the brief, I would routinely ask my agent (Claude Code) to use both keyword and semantic searching to find the best evidence supporting whatever assertion I was trying to make. I trusted it because there were traces I could follow.

In other cases/situations, I’ve tried just giving a model access to all the docs and saying “write a brief arguing X,” but it’s always terrible at this. It writes briefs with lots of evocative jargon and rhetorical flourish, but a low signal-to-noise ratio.

Again, I’m sure others’ experiences differ based on workflow, legal area, etc.

In some ways I miss the early LLM days before RL and system prompts (I assume this is the difference) made them all sound the same. They would say weird stuff. They got better at being useful and worse at being fun.*

*This sadly also describes me as a 31 year old man.

The false positive rate for Pangram 4 is something like one in 24,000.[0] To put that in perspective, the wrongful-conviction (false positive rate) for death-sentenced defendants in the US is estimated conservatively to be around 4.1%.[1] The FP rate for death-sentence convictions is 1,000 times bigger than Pangram’s FP rate.

Now, the US criminal system is not a great yardstick for justice. But it goes to show you Pangram is really good evidence that something was LLM generated. It can be an amazing tool for enforcing AI policies in schools, and there ought to be ways to use it with caveats for the rare but inevitable false positives (appeals, etc).

[0]: see page 15 https://arxiv.org/pdf/2607.27183 [1]: see https://pmc.ncbi.nlm.nih.gov/articles/PMC4034186/

I don’t mind AI-written code. But an obviously generated README.md is such a turn off. If you don’t take the time to explain what your software does in your own words, I struggle to trust that it’s been thought about much at all.

Linus Tech Tips dropped a video on this an hour ago, so the prices are already skyrocketing sadly.

Link: https://youtu.be/lmLh29LE2W4?is=QdRwtQS3xyyPt44E

The price is probably coming from when Luna was first released. OpenAI slashed the price by 80% at the end of July.

The complaining about the pelicans is so strange to me. It’s just a fun heuristic. If something is claimed to be AGI, I’d expect it to be able to make svgs.

I didn’t mean to suggest you don’t know what an em dash is. But you said “this isn’t how you use them.” And my response is: actually, this use of them is totally fine.

Em dashes are commonly used to add emphasis, even where you would ordinarily use a comma. Their flexibility is why many people love them! See https://www.merriam-webster.com/grammar/em-dash-en-dash-how-...

It's also certainly not 2x-4x cheaper than getting GLM 5.3 inference elsewhere.

Compare: https://www.coralbricks.ai/docs#models vs https://openrouter.ai/z-ai/glm-5.3#providers

Is "Salem" a tongue-in-cheek nod to being a small, quirky competitor to Boston Dynamics (Salem, MA : Boston, MA :: Salem Robotics : Boston Dynamics)?

If so, as someone who lives close to Salem, I like it :)

Good luck to you guys.

Very true, I just want to trust people.

Is it? I couldn’t tell and I’m pretty sensitive to machine generated text.

Also, the author claims:

> No AI was used to generate the text for this article. The cover image and the voiceover in the audio version of the article is AI-generated. The cover image is made using Google Gemini’s latest image model while the voiceover uses OpenAI’s tts models.

I think this is a GitHub issue (of course it is) as I'm not able to search for anything atm.

I built a little free library a couple years ago. There are definitely people who drop their old crappy books. A good little free librarian treats it like a garden, pruning the weeds and letting the good stuff grow. I also like to seed it occasionally with some of my old favorites that I want someone else to enjoy. It tends to sort of perpetuate itself. People put less junk in there if there is already quality stuff.

I love how all the replies to this comment recommend completely different strategies for deciding which model to use.

Product page: https://www.weaverobotics.com/isaac-1

Can we please stop submitting fully AI-generated text to HN?

> The default WebView backend uses the operating system's own webview for small binaries, and you still have the entire npm ecosystem available through Deno's Node compat layer.

Sounds like a similar architecture to Tauri, but your business logic is in typescript instead of rust.

I wouldn’t trust Chinese labs’ TOS very much. It would be incredibly difficult and expensive to enforce any of those terms.

edit: this is a comment about suing and enforcing judgments against Chinese companies in the US, especially software companies, not necessarily about how trustworthy the Chinese labs are.

What kinds of tasks are you finding deepseek v4 incapable of?

The general consensus is stocks nosedived after the strong jobs report, because strong labor market means its more likely Fed will hike interest rates to curb inflation.

I struggle to get quality results from the frontier models at contexts > 256k anyway.

EOs have force of law if exercising valid executive authority. POTUS could have, e.g., conditioned federal contracts on compliance with this vetting program, but didn’t.

What seem like the most interesting bits, selectively pruned of legalese:

>Within 60 days of the date of this order, the [executive branch] shall:

>(a) develop and maintain a classified benchmarking process to assess the advanced cyber capabilities of AI models and determine the threshold at which an AI model should be designated a “covered frontier model” for the purposes of this order, sharing such assessments with AI developers and researchers as appropriate. …

>(b) design a voluntary framework with AI developers through which developers would be able to: (i) engage the Federal Government to determine whether model(s) under development meet the designation of “covered frontier model”; (ii) provide the Federal Government with access to covered frontier models, subject to [some conditions]; and (iii) collaborate with the Federal Government to select trusted partners that will have early access to covered frontier models to promote secure innovation and strengthen the cybersecurity of critical infrastructure.

So… it’s entirely “voluntary”? This has no teeth.

> Running my family's social media site off a single sqlite DB on a VPS is great. ~15 users, almost zero maintenance.

Details, please!