Roy 🎱🦄

1.8K posts

Roy 🎱🦄

Roy 🎱🦄

@hyder13

2018 台灣早期 BNB 投資者 | Web3 深度研究 | Now is Openclaw believer

Private city Katılım Mart 2009
698 Takip Edilen756 Takipçiler
Roy 🎱🦄
Roy 🎱🦄@hyder13·
很多人覺得幣圈已經熊到不能熊了,但對於經歷過 ETH 跌到 80幾的,感覺現在各個主流幣的估值,還是挺高的 ..
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爱丽丝呀!
爱丽丝呀!@BTCqzy1·
大神卡帕西(Karpathy)又开源了一个项目,这次他想让 AI “卷死”所有的 AI 研究员。 GitHub 瞬间炸场:autoresearch。 不到一周狂揽 4.4w+ 星,全网都在疯传这个只有 630 行 的 Python 脚本。 一句话总结:这根本不是一个简单的工具,这是 AI 的“自我进化实验室”。 当大家还在手动调参、熬夜盯 Loss 曲线、改一行代码跑一次实验时,卡帕西已经写了个“分身”去干活了。这个项目最狠的地方在于,它把 AI 关进了一个闭环里:AI 自己写 PyTorch,自己跑实验,自己看结果,自己再改代码。 这就是传说中的“无人值守”科研。 你只需要告诉它:“帮我把模型跑得更稳一点”,然后你就可以去睡觉、去健身、去蒸桑拿。等你回来,AI 已经帮你跑了几百轮实验,还顺手把最优的模型架构和训练参数直接递到了你手里。 为什么这个项目能让全网高潮? 1.极简即暴力:630 行代码,单张 GPU 就能跑,卡帕西再次用实力证明:真正的核弹,不需要成千上万行的垃圾代码。 2.智商碾压:它不是在瞎撞,而是像个老练的工程师一样在做逻辑推演。有人用它一夜之间跑出的 0.8B 小模型,效果直接反超了人类精心微调的 1.6B。 3.科研范式地震:以前是人类研究 AI,现在是 AI 研究 AI。卡帕西说:“我写完代码去蒸了个桑拿,回来 AI 已经把实验跑完了。” 今天的程序员在写代码,明天的程序员在“指挥”AI 写代码。如果你还在手动调参,那你可能真的要被卡帕西的这个“小脚本”给卷没了。 #AI编程 #AndrejKarpathy #GitHub 传送门:github.com/karpathy/autor…
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Roy 🎱🦄
Roy 🎱🦄@hyder13·
我有預感 足球幣 $ATM $ASR 兩兄弟準備要動了
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Roy 🎱🦄
Roy 🎱🦄@hyder13·
我覺得比特幣現在應該就是底部
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Roy 🎱🦄
Roy 🎱🦄@hyder13·
最近的 agent 世界越來越有趣,更多的代理機器人上線,未來是服務 agent 的時代
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Roy 🎱🦄
Roy 🎱🦄@hyder13·
我的刀盾打開了sol中文時代 #sol人生 應該會超過刀盾,成为龍頭,然後正式上幣安開啟sol的中文時代 不要錯過 GWcAPiF2cBf5de8E1eSERcnVdH411NqT2peG7zDJpump
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Roy 🎱🦄 retweetledi
North@CreaoAI
North@CreaoAI@anorth_chen·
今年一定会出现新的职业:skill工程师。 负责跟各种领域的人类专家合作,将他们的领域专业技能结构化、显性化的构建成skill,教给Agent。 人类组织在今年将会出现全新的协作形式,第一批skill工程师可以短时间内获得大量的跨领域专家技能点,这是今年AI最大的红利。
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Roy 🎱🦄
Roy 🎱🦄@hyder13·
中西合併的威力 SOL + 人生,搞不好真起飛呢?@toly
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Brian Roemmele
Brian Roemmele@BrianRoemmele·
BOOM! Apple’s Neural Engine Was Just Cracked Open, The Future of AI Training Just Change And Zero-Human Company Is Already Testing It! In a jaw-dropping open-source breakthrough, a lone developer has done what Apple said was impossible: full neural network training– including backpropagation – directly on the Apple Neural Engine (ANE). No CoreML, no Metal, no GPU. Pure, blazing ANE silicon. The project (github.com/maderix/ANE) delivers a single transformer layer (dim=768, seq=512) in just 9.3 ms per step at 1.78 TFLOPS sustained with only 11.2% ANE utilization on an M4 chip. That’s the same idle chip sitting in millions of Mac minis, MacBooks, and iMacs right now. Translation? Your desktop just became a hyper-efficient AI supercomputer. The numbers are insane: M4 ANE hits roughly 6.6 TFLOPS per watt – 80 times more efficient than an NVIDIA A100. Real-world throughput crushes Apple’s own “38 TOPS” marketing claims. And because it sips power like a phone, you can train 24/7 without melting your electricity bill or the planet. At The Zero-Human Company, we’re not waiting. We are testing this right now on real ZHC workloads. This is the missing piece we’ve been chasing for our Zero Human Company vision: reviving archived data into fully autonomous AI systems with zero human overhead. This is world-changing. For the first time, anyone with a Mac can fine-tune, train, or iterate massive models locally, privately, and at a fraction of the cost of cloud GPUs. No more renting $40,000 A100 clusters. No more waiting in queues. No more massive carbon footprints. Training costs that used to run into the tens or hundreds of thousands of dollars? Plummeting toward pennies on the dollar – mostly just the electricity your Mac was already using while it sat idle. The AI revolution just moved from billion-dollar data centers to your desk. WE WILL HAVE A NEW ZERO-HUMAN COMPANY @ HOME wage for equipped Macs that will be up to 100x more income for the owner! We’re only at the beginning (single-layer today, full models tomorrow), but the door is wide open. Ultra-cheap, on-device training is here. The future isn’t coming. It’s already running on your Mac. Welcome to the Zero-Human Company era.
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Skibidi Toilet
Skibidi Toilet@skibiditoileet9·
I am not a fucking unicorn Im a horse
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Roy 🎱🦄 retweetledi
tuBBy
tuBBy@tubbykin·
$Pippkin is coded
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Roy 🎱🦄
Roy 🎱🦄@hyder13·
今年華人的節日是馬年 馬在古代是負責帶兵打仗的最強助手,並且每個帶兵打仗的,都對馬有格外的情感 感謝大家一起努力,帶著這匹馬 PIPPKIN 衝向天際
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Roy 🎱🦄
Roy 🎱🦄@hyder13·
比特幣在宏觀波動中展現韌性,機構資金注入信心。減半效應顯現,供給緊縮支撐價格。關注監管與通膨,理性規劃,長線佈局為上策。
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