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#SoftwareDeveloper working on 2 Projects at same time 🤪 Google Microsoft Infosys Tata Consultancy Services CA Technologies Jain Software®

267,738 Aufrufe • vor 3 Jahren •via X (Twitter)

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elvis

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I just ran Gemma 4 31B on @CerebrasSystems at 1,800+ tokens/sec and it's multimodal. For context: that's 35x faster than a typical GPU endpoint, and the first token (reasoning included) lands in 1.5 seconds. This isn't a benchmark slide, I recorded the inference live. Prompt I used: "Create a simulation of an iPhone. Include at least one working dummy note taking app, a functional notification pulldown, high quality graphics, single HTML file, any libs via CDN." - Generation time: 3 seconds. - Notes app worked. - Notification panel worked. - Rendered first try. This is what wafer-scale inference unlocks, not just "faster," but a different category of product. When generation is this fast, you stop waiting and start iterating in real time. Why this matters: Gemma 4 31B is Google DeepMind's flagship open weight model, Apache 2.0 licensed, dense (not MoE), and built for efficiency over raw parameter count. It scores close to Claude Haiku 4.5 on the Artificial Analysis Intelligence Index (30 vs 29) but runs ~18x faster on Cerebras. It's also the first multimodal model on Cerebras's platform, meaning you can now feed it screenshots, documents, charts, and UI states at wafer scale speed. # Applications I'm most excited about: - Screenshot → Insight: Drop in a dashboard or document screenshot, get structured findings back instantly. no waiting, no batching. - Live UI generation: Full interactive interfaces (like my iPhone sim) generated and rendered in under 2 seconds. - Screenshot -> Patch: Feed it a broken UI + console error, get a minimal code fix and verification steps back. - Computer use & agentic loops: See -> reason -> act - verify, fast enough to keep a human in the loop instead of waiting on the model. - Long context summarization: Full research reports condensed into decision ready summaries you can read and requery in one sitting. The bigger unlock isn't the speed number itself, it's that agentic and multimodal loops (see -> reason -> output -> tool call -> verify -> retry) finally run in real time instead of feeling sluggish. As Logan Kilpatrick (Logan Kilpatrick) put it: "If every model was doing 2,000 tokens per second, you wouldn't build the same product and just have it be faster, you'd build different products." Gemma 4 31B is live now on Cerebras Inference Cloud in public preview. If you're building multimodal, agentic, or real time apps, this is worth testing today. What would you build with such insane inference throughput?

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This trader gave Claude $44 and one question. Not “what should I build.” Not “how do bots work.” He asked: what’s the easiest way to consistently extract money from short-term mispricing. No lecture. No disclaimer. No theory. It said: find small windows where the market is off by a few percent. Quietly. Repeatedly. At scale. Then it dropped a wallet. stargate5 $165,618 profit 16,279 trades Joined November 2025 He almost skipped it. Then he opened the activity. No predictions. No narratives. Just micro trades on 5–15 minute windows. Over and over and over. Tiny edges. Constant flow. The entire strategy: scan for mispricing above ~6% enter instantly redeem at $1 repeat. He asked Claude how this keeps working. It said: you don’t need big wins. You need a small edge executed thousands of times at near-even conditions. Volume handles the rest. He asked: what kind of capital this started with. Claude: based on sizing — probably under $1,000. Compounding did the rest. He went through the trades manually. Same pattern every time: short window mispriced odds fast execution instant settlement No randomness. No luck. The same edge, repeated 16,279 times until it turned into $165K. He asked Claude one last thing. What do you call this strategy? It said: capturing the gap between panic pricing and actual probability on repeat. At scale, that gap becomes income. Still running. You only need Claude + laptop + 1 hour/day. Giving This Free for 24 hours. To get it: Just: 1. Comment the word ‘CLAUDE’ 2. Like and Retweet this post 3. Follow me Marry Evan (so that I can message you)

Marry Evan

63,191 Aufrufe • vor 5 Monaten

This trader gave Claude $44 and one question. Not “what should I build.” Not “how do bots work.” He asked: what’s the easiest way to consistently extract money from short-term mispricing. No lecture. No disclaimer. No theory. It said: find small windows where the market is off by a few percent. Quietly. Repeatedly. At scale. Then it dropped a wallet. stargate5 $165,618 profit 16,279 trades Joined November 2025 He almost skipped it. Then he opened the activity. No predictions. No narratives. Just micro trades on 5–15 minute windows. Over and over and over. Tiny edges. Constant flow. The entire strategy: scan for mispricing above ~6% enter instantly redeem at $1 repeat. He asked Claude how this keeps working. It said: you don’t need big wins. You need a small edge executed thousands of times at near-even conditions. Volume handles the rest. He asked: what kind of capital this started with. Claude: based on sizing — probably under $1,000. Compounding did the rest. He went through the trades manually. Same pattern every time: short window mispriced odds fast execution instant settlement No randomness. No luck. The same edge, repeated 16,279 times until it turned into $165K. He asked Claude one last thing. What do you call this strategy? It said: capturing the gap between panic pricing and actual probability on repeat. At scale, that gap becomes income. Still running. You only need Claude + laptop + 1 hour/day. Giving This Free for 24 hours. To get it: Just: 1. Comment the word ‘CLAUDE’ 2. Like and Retweet this post 3. Follow me ZAYVEN KNOX (so that I can message you)

ZAYVEN KNOX

10,809 Aufrufe • vor 5 Monaten