Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

Claude Opus 4.6

anthropic.com

Post reply on HN
Print view View original

891–900 of 1001 posts

Re: Claude Opus 4.6

#891

Post by grey-area »

zaphirplane wrote: post #885
grey-area wrote: post #818

Earlier quoted context omitted.

Surely the corpus Opus 4.6 ingested would include whatever reference you used to check the spells were there. I mean, there are probably dozens of pages on the internet like this: https://www.wizardemporium.com/blog/complete-list-of-harry-p... Why is this impressive? Do you think it's actually ingesting the books and only using those as a reference? Is that how LLMs work at all? It seems more likely it's predicting t…

Why doesn’t you ask it and find out ;)

Because the model doesn't know but will happily tell a convincing lie about how it works.

Re: Claude Opus 4.6

#892

Post by faxmeyourcode »

legitster wrote: post #72

I'm still not sure I understand Anthropic's general strategy right now. They are doing these broad marketing programs trying to take on ChatGPT for "normies". And yet their bread and butter is still clearly coding. Meanwhile, Claude's general use cases are... fine. For generic research topics, I find that ChatGPT and Gemini run circles around it: in the depth of research, the type of tasks it can handle, and the qual…

Everybody is different, I simply cannot stand the sight of chatgpt styled writing. Give me paragraphs.

Re: Claude Opus 4.6

#893

Post by SebastianSosa »

ck_one wrote: post #482

Just tested the new Opus 4.6 (1M context) on a fun needle-in-a-haystack challenge: finding every spell in all Harry Potter books. All 7 books come to ~1.75M tokens, so they don't quite fit yet. (At this rate of progress, mid-April should do it ) For now you can fit the first 4 books (~733K tokens). Results: Opus 4.6 found 49 out of 50 officially documented spells across those 4 books. The only miss was "Slugulus Eruc…

now thx to this post (and the infra provider inclination to appeal to hacker news) we will never know if the model actually discovered the 50 spells or memorized it. Since it will be trained on this. :( But what can you do, this is interesting

Re: Claude Opus 4.6

#894

Post by [deleted] »

neuronexmachina wrote: post #81
pjot wrote: post #62

Claude Code release notes: > Version 2.1.32: • Claude Opus 4.6 is now available! • Added research preview agent teams feature for multi-agent collaboration (token-intensive feature, requires setting CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1) • Claude now automatically records and recalls memories as it works • Added "Summarize from here" to the message selector, allowing partial conversation summarization. • Skills defi…

> Claude now automatically records and recalls memories as it works Neat: https://code.claude.com/docs/en/memory I guess it's kind of like Google Antigravity's "Knowledge" artifacts?

[deleted]

Re: Claude Opus 4.6

#895

Post by setgree »

I asked

> Can you find an academic article that _looks_ legitimate -- looks like a real journal, by researchers with what look like real academic affiliations, has been cited hundreds or thousands of times -- but is obviously nonsense, e.g. has glaring typos in the abstract, is clearly garbled or nonsensical?

It pointed me to a bunch of hoaxes. I clarified:

> no, I'm not looking for a hoax, or a deliberate comment on the situation. I'm looking for something that drives home the point that a lot of academic papers that look legit are actually meaningless but, as far as we can tell, are sincere

It provided https://www.sciencedirect.com/science/article/pii/S246802302....

Close, but that's been retracted. So I asked for "something that looks like it's been translated from another language to english very badly and has no actual content? And don't forget the cited many times criteria. " And finally it told me that the thing I'm looking for probably doesn't exist.

For my tastes telling me "no" instead of hallucinating an answer is a real breakthrough.

Re: Claude Opus 4.6

#897

Post by cherrycherry98 »

LeanderK wrote: post #846
lpcvoid wrote: post #835

Earlier quoted context omitted.

It sounds like it's lying and making stuff up, something everybody seems to be okay with when using LLMs.

I am not sure why...you want the LLM to solve problems not come up with answers itself. It's allowed to use tools, precisely because it tends to make stuff up. In general, only if you're benchmarking LLMs you care about whether the LLM itself provided the answer or it used a tool. If you ask it to convert the notation of sheet music it might use a tool, and it's probably the right decision.

The shortcut is fine if it's a bog standard canonical arrangement of the piece. If it's a custom jazz rendition you composed with an odd key changes and and shifting time signatures, taking that shortcut is not going to yield the intended result. It's choosing the wrong tool to help which makes it unreliable for this task.

Re: Claude Opus 4.6

#898

Post by majora2007 »

endymion-light wrote: post #833
bobbylarrybobby wrote: post #729

Earlier quoted context omitted.

I really like that Claude feels transactional. It answers my question quickly and concisely and then shuts up. I don't need the LLM I use to act like my best friend.

I love doing a personal side project code review with claude code, because it doesn't beat around the bush for criticism. I recently compared a class that I wrote for a side project that had quite horrible temporal coupling for a data processor class. Gemini - ends up rating it a 7/10, some small bits of feedback etc Claude - Brutal dismemberment of how awful the naming convention, structure, coupling etc, provides e…

This is exactly what got me to actually pay. I had a side project with an architecture I thought was good. Fed it into Claude and ChatGPT. ChatGPT made small suggestions but overall thought it was good. Claude shit all over it and after validating it's suggestions, I realized Claude was what I needed.

I haven't looked back. I just use Claude at home and ChatGPT at work (no Claude). ChatGPT at work is much worse than Claude in my experience.

Re: Claude Opus 4.6

#899

Post by breuleux »

esafak wrote: post #643
breuleux wrote: post #437

Earlier quoted context omitted.

The point is that "predicting the next token" is such a general mechanism as to be meaningless. We say that LLMs are "just" predicting the next token, as if this somehow explained all there was to them. It doesn't, not any more than "the brain is made out of atoms" explains the brain, or "it's a list of lists" explains a Lisp program. It's a platitude.

It's not meaningless, it's a prediction task, and prediction is commonly held to be closely related if not synonymous with intelligence.

In the case of LLMs, "prediction" is overselling it somewhat. They are token sequence generators. Calling these sequences "predictions" vaguely corresponds to our own intent with respect to training these machines, because we use the value of the next token as a signal to either reinforce or get away from the current behavior. But there's nothing intrinsic in the inference math that says they are predictors, and we typically run inference with a high enough temperature that we don't actually generate the max likelihood tokens anyway.

The whole terminology around these things is hopelessly confused.

Re: Claude Opus 4.6

#900

Post by nopinsight »

Some of Opus 4.6's standout results for me:

* GDPVal Elo: 1606 vs. GPT-5.2's 1462. OpenAI reported that GPT-5.2 has a 70.9% win-or-tie rate against human professionals. (https://openai.com/index/gdpval/) Based on Elo math, we can estimate Opus 4.6's win-or-tie rate against human pros at 85–88%.

* OSWorld: 72.7%, matching human performance at ~72.4% (https://os-world.github.io/). Since the human subjects were CS students and professionals, they were likely at least as competent as the average knowledge worker. The original OSWorld benchmark is somewhat noisy, but even if the model remains somewhat inferior to humans, it is only a matter of time before it catches up or surpasses them.

* BrowseComp: At 84%, it is approaching human intersubject agreement of ~86% (https://openai.com/index/browsecomp/).

Taken together, this suggests that digital knowledge work will be transformed quite soon, possibly drastically if agent reliability improves beyond a certain threshold.

Post reply on HN