w
4K image generation in 10 seconds! ⚡
Meet MiniMax H3-Image.
16 million pixel resolution. Stunning realism. Precise prompt following & editing. Up to 16 reference images. All in 10 seconds.
And it's open-weight. 🚀
Available now via our API, MiniMax Code, and Hailuo AI — with 50% off 16MP+ generations during launch week!
Can't wait to see what you create. 🔥
Hugging Face: huggingface.co/MiniMaxAI/Min…
API: platform.minimax.io/docs/gui…
MiniMax Code: code.minimax.io/about
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what findings and open methods????about what????
Replying to @MyDaebakCafe
> The entire beauty of open weights is that anyone can fine-tune whatever worldview they want into their local metal
Yes, that’s what’s interesting about the research and you can replicate it using our findings and open methods towards whichever belief system you want
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Thank you, Congresswoman. I am a local resident here. If the data center is built, we will not be able to afford our household electricity bills. Thank you for thinking about the local residents.
I’m fighting to block a proposed 400-megawatt data center from being built on federal land at NAVWAR, here in San Diego. If built, this would be the largest data center in the state. Our community has been clear: we don’t want this!
sandiegouniontribune.com/202…
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我们早就准备好了
NU7 is live on zcash: faster blocks, stronger shielded protection, and a network built for the long run
we rebuilt every sapling service for NU7 weeks early, ran our own NU7 zcash node and tested it all end to end. at block 3,543,405 sapling kept running with zero downtime
launch, trade and cash out from your zcash wallet, ready for the new era
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deepseek,1分😂
We’ve released AA-Omniscience v1.1, updating our knowledge and reasoning benchmark with a refreshed public set, removal of saturated questions, and ambiguity fixes
AA-Omniscience is our proprietary benchmark measuring model knowledge and hallucinations, including whether models admit when they don’t know an answer. Our primary metric, Net Score, rewards correct answers, penalizes incorrect answers, and treats abstentions neutrally.
AA-Omniscience was updated to v1.1 as part of the Artificial Analysis Intelligence Index v5 release.
Key changes in AA-Omniscience v1.1:
➤ Updated 3,000-question dataset: Down from 6,000 questions, with previously public and saturated questions removed, errors and ambiguities corrected, and new questions added
➤ Newly calibrated 300-question public set: AA-Omniscience v1.1 has a new public set on @huggingface calibrated to match the difficulty of the private set. At release, public and private scores have a 0.99 Pearson correlation and 0.99 Spearman rank correlation for AA-Omniscience Net Score, with a median difference of 0.0 points. Accuracy and hallucination rate also have 0.99 correlations, with median differences of -0.07 and -0.29 percentage points, respectively
➤ Slightly updated domain distribution: Questions span the same 6 domains and 42 topics as version 1, with a revised distribution: Science, Engineering and Mathematics (600), Software Engineering (600), Finance (450), Health (450), Humanities and Social Sciences (450), and Law (450)
Key results for AA-Omniscience v1.1:
➤ Rank order largely preserved: AA-Omniscience v1.1 has a 0.98 Spearman rank correlation with v1. The recently released Gemini 4 Carbon (high) leads with a Net Score of 54, followed by Claude Opus 5.5 (48, max with fallback) and Claude Fable 5.1 (46, max with fallback). Muse Spark Open (xhigh) is the leading open weights model, 28 points behind Gemini 4 Carbon
➤ Scores average ~2 points lower on the refreshed set: Models score 1.9 points lower on Net Score on average compared to v1, with a median decrease of 0.6 points. Some models see much larger declines, particularly MiniMax M3.1 Flash, down 22 points (16 to -6), and MiMo V2.6 Pro, down 13 points (8 to -5)
➤ Slightly lower accuracy: AA-Omniscience Accuracy measures the percentage of questions the model answers correctly. Models answer a median of 1.5 percentage points fewer questions correctly on average compared to v1. Claude Fable 5.1 (max with fallback) has the highest accuracy at 68%, followed by Claude Opus 5.5 (max with fallback) at 66%
➤ Hallucination rates decrease: AA-Hallucination measures how often models choose to answer when they do not know the answer. The median Hallucination Rate falls 1.4 percentage points, with Gemini 4 Argon (high) recording the lowest hallucination rate at 4%
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傻逼给我气消了,融资到账笑嘻嘻,北京不偷你的数据了? @Alibaba_Qwen 法务部不出来走走?
We're proud to announce the initial close of our Series E, targeting up to CAD $7 billion at a CAD $35.7 billion valuation; marking the largest private financing round in Canadian startup history.
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那谁来监督你们呢?各种遥测信息收集?
We’ve trained Claude to flag potential misuse in conversations, a technique we call self-assessment. Right after it responds, Claude gives a preliminary safety assessment of the conversation.
Since we began using self-assessment in June, it has surfaced misuse that our other safeguards weren’t designed to catch.
Because Claude has already read the conversation, self-assessment is very efficient. And unlike classifiers, which target a discrete set of harms, it draws on Claude’s own judgment, so it gets more accurate as our models improve.
Read more on our new Safeguards blog:
safeguards.anthropic.com/202…
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zillion!
zm, an update about sapling:
we're moving sapling launches off @Pumpfun
so we're migrating to @Raydium LaunchLab. more flexible, more control, and room to build sapling the way it should be built
we're also building a better flywheel that supports the top coins in the sapling ecosystem alongside solana:BZFYNPeQAEW3HWQ4DNsTVahC1n4ZjTgn6jB2nnBbB96W
and many more big updates coming soon
zillions!
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