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Solo dev reverse-engineered Google's billion-dollar algorithm in 7 days Google published the paper that crashed memory stocks worldwide. Then shipped zero code. Tom Turney read the math, opened his terminal, and built the whole thing with Claude - then made it faster than Google promised. Day 1-3: Core algorithms,...

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BuBBliK

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1,655,559 次观看 • 2 个月前 •via X (Twitter)

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.[TEST] #25 v AVL - All Actions. Made in with Python, event data from Insight90 by Sahil Gidwani and Mohammad Adnan, and a code assist from Google Gemini/Claude
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.[TEST] #25 v AVL - All Actions. Made in with Python, event data from Insight90 by Sahil Gidwani and Mohammad Adnan, and a code assist from Google Gemini/Claude

📈 #WinstanleyOUT #StewartOUT #ShieldsOUT

28,593 次观看 • 3 个月前

If you can draw, you can code. Sketch out your idea and upload a picture in the Google Gemini with a quick description and go from paper to prototype just like that.
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If you can draw, you can code. Sketch out your idea and upload a picture in the Google Gemini with a quick description and go from paper to prototype just like that.

Google

144,128 次观看 • 9 个月前

Goldman Sachs rejected him for partner, he quit, started with $3 million, and built a fund that made $7 billion in a single year then he bought his former boss's $43.5 million beach house - and demolished it. Built one twice the size in its place Bookmark & Watch it. Then read the post below - a hedge fund manager called a $5 billion company "the best managed pyramid scheme in history" ↓
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Goldman Sachs rejected him for partner, he quit, started with $3 million, and built a fund that made $7 billion in a single year then he bought his former boss's $43.5 million beach house - and demolished it. Built one twice the size in its place Bookmark & Watch it. Then read the post below - a hedge fund manager called a $5 billion company "the best managed pyramid scheme in history" ↓

Сarm1ne

576,676 次观看 • 28 天前

THIS AMERICAN DEVELOPER SPENT WEEKS DEBUGGING TIMEOUT ERRORS IN OLLAMA. THEN HE LOOKED UNDER THE HOOD LM Studio is just llama.cpp Ollama is just llama.cpp so he cloned llama.cpp from source, pulled Qwen 3.6 35B off Hugging Face, set up asymmetric KV quantization and got a local server running on 127.0.0.1:8080 plugged it into VS Code, connected it to OpenClaw, 53 tok/s on an M1 Max with 262K context zero wrappers, zero timeout errors, zero API fees bookmark & like this before your next timeout error hits​​​​​​​​​​​​​​​​ full breakdown of my raw llama.cpp setup ↓
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THIS AMERICAN DEVELOPER SPENT WEEKS DEBUGGING TIMEOUT ERRORS IN OLLAMA. THEN HE LOOKED UNDER THE HOOD LM Studio is just llama.cpp Ollama is just llama.cpp so he cloned llama.cpp from source, pulled Qwen 3.6 35B off Hugging Face, set up asymmetric KV quantization and got a local server running on 127.0.0.1:8080 plugged it into VS Code, connected it to OpenClaw, 53 tok/s on an M1 Max with 262K context zero wrappers, zero timeout errors, zero API fees bookmark & like this before your next timeout error hits​​​​​​​​​​​​​​​​ full breakdown of my raw llama.cpp setup ↓

leopardracer

238,296 次观看 • 21 天前

nvidia's 3B mamba destroyed alibaba's 3B deltanet on the same RTX 3090. only 24 days between releases. same active parameters, same VRAM tier, completely different architectures. nemotron cascade 2: 187 tok/s. flat from 4K to 625K context. zero speed loss. flags: -ngl 99 -np 1. that's it. no context flags, no KV cache tricks. auto-allocates 625K. qwen 3.5 35B-A3B: 112 tok/s. flat from 4K to 262K context. zero speed loss. flags: -ngl 99 -np 1 -c 262144 --cache-type-k q8_0 --cache-type-v q8_0. needed KV cache quantization to fit 262K. both models held a flat line across every context level. both architectures are context-independent. but nvidia's mamba2 is 67% faster at generating tokens on the exact same hardware and needs fewer flags to get there. same node, same GPU, same everything. the only variable is the model. gold medal math olympiad winner running at 187 tokens per second on single RTX 3090 a card from 6 years ago. nvidia cooked.
0:36

nvidia's 3B mamba destroyed alibaba's 3B deltanet on the same RTX 3090. only 24 days between releases. same active parameters, same VRAM tier, completely different architectures. nemotron cascade 2: 187 tok/s. flat from 4K to 625K context. zero speed loss. flags: -ngl 99 -np 1. that's it. no context flags, no KV cache tricks. auto-allocates 625K. qwen 3.5 35B-A3B: 112 tok/s. flat from 4K to 262K context. zero speed loss. flags: -ngl 99 -np 1 -c 262144 --cache-type-k q8_0 --cache-type-v q8_0. needed KV cache quantization to fit 262K. both models held a flat line across every context level. both architectures are context-independent. but nvidia's mamba2 is 67% faster at generating tokens on the exact same hardware and needs fewer flags to get there. same node, same GPU, same everything. the only variable is the model. gold medal math olympiad winner running at 187 tokens per second on single RTX 3090 a card from 6 years ago. nvidia cooked.

Sudo su

186,203 次观看 • 2 个月前

Google Maps to find them -> Claude to write them -> Lovable to ship them. $1-2k a day, 5 days a week, no team, no agency, no overhead. Web agencies charge $5,000 and take 3 weeks, he charges $1,000 and ships in 15 minutes. The math is brutal. Find a local business on Google Maps, copy their reviews, use Claude to generate site copy, publish via Lovable, then send the link and get paid. The whole loop fits between two cups of coffee. Real Stripe payouts hitting his Chase account every few days, $793 paid, $1,100 paid, $1,200 paid, while web agencies are still drafting their kickoff PDFs. 5 sales a day is $5,000 -> 10 is $10,000 -> 20 is $20,000. No funnel, no email list, no Twitter audience, no personal brand, no LinkedIn presence, no portfolio, no resume. Just a laptop, a Google Maps tab and 3 AI tools doing the work humans used to charge $5,000 for. Most people watch this method and bookmark it, he turned it into a $10,000 a week income while everyone else was still wondering if it was real. And most people will still hate and say "ugh that's not real"...
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Google Maps to find them -> Claude to write them -> Lovable to ship them. $1-2k a day, 5 days a week, no team, no agency, no overhead. Web agencies charge $5,000 and take 3 weeks, he charges $1,000 and ships in 15 minutes. The math is brutal. Find a local business on Google Maps, copy their reviews, use Claude to generate site copy, publish via Lovable, then send the link and get paid. The whole loop fits between two cups of coffee. Real Stripe payouts hitting his Chase account every few days, $793 paid, $1,100 paid, $1,200 paid, while web agencies are still drafting their kickoff PDFs. 5 sales a day is $5,000 -> 10 is $10,000 -> 20 is $20,000. No funnel, no email list, no Twitter audience, no personal brand, no LinkedIn presence, no portfolio, no resume. Just a laptop, a Google Maps tab and 3 AI tools doing the work humans used to charge $5,000 for. Most people watch this method and bookmark it, he turned it into a $10,000 a week income while everyone else was still wondering if it was real. And most people will still hate and say "ugh that's not real"...

Defileo🔮

42,550 次观看 • 1 个月前

someone at ANTHROPIC just showed CLAUDE finding ZERO DAY vulnerabilities in a live conference demo claude has found zero day in Ghost, 50,000 stars on github, never had a critical security vulnerability in its entire, history... it found the blind SQL injection in 90 minutes, stole the admin api key, then did the exact, same thing to the linux kernel
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someone at ANTHROPIC just showed CLAUDE finding ZERO DAY vulnerabilities in a live conference demo claude has found zero day in Ghost, 50,000 stars on github, never had a critical security vulnerability in its entire, history... it found the blind SQL injection in 90 minutes, stole the admin api key, then did the exact, same thing to the linux kernel

chiefofautism

1,900,053 次观看 • 2 个月前

Google's CEO "any solo developer with Claude can now outcompete a 10-person Google team" he's right but 90% of developers using Claude Code daily are starting from zero every session no stack context. no memory. no behavior rules. $975 wasted per developer every single week Sundar is talking about the future. here's the setup that makes the present actually work:
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Google's CEO "any solo developer with Claude can now outcompete a 10-person Google team" he's right but 90% of developers using Claude Code daily are starting from zero every session no stack context. no memory. no behavior rules. $975 wasted per developer every single week Sundar is talking about the future. here's the setup that makes the present actually work:

Dep

400,320 次观看 • 14 天前

A 16-year-old American student made $7,000 in his first month after publishing his first game on Google Play - and GPT-5.5 built the whole thing for him. He had zero programming knowledge and no $50,000 dev team. He just opened GPT-5.5, described what he wanted to build, and went to play while the AI wrote every line of code for him. GPT-5.5 built a complete 3D game called Hormuz Escape from scratch - obstacle avoidance mechanics, high score system, particle effects, AdMob integration for ads, and a Firebase leaderboard. All from one prompt in a week of work. A Google Play Developer account cost $25 once and forever. 10,000 active players at $0.03 a day through AdMob is already $9,000 a month in passive income. He stopped at $7,000 in the first month and the number keeps growing. 3 billion Android devices in the world and the Play Store is open to anyone with $25 and an idea. AI removed the last barrier - needing to know how to code. $25 to register, One week of work. $7,000 in the first month.
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A 16-year-old American student made $7,000 in his first month after publishing his first game on Google Play - and GPT-5.5 built the whole thing for him. He had zero programming knowledge and no $50,000 dev team. He just opened GPT-5.5, described what he wanted to build, and went to play while the AI wrote every line of code for him. GPT-5.5 built a complete 3D game called Hormuz Escape from scratch - obstacle avoidance mechanics, high score system, particle effects, AdMob integration for ads, and a Firebase leaderboard. All from one prompt in a week of work. A Google Play Developer account cost $25 once and forever. 10,000 active players at $0.03 a day through AdMob is already $9,000 a month in passive income. He stopped at $7,000 in the first month and the number keeps growing. 3 billion Android devices in the world and the Play Store is open to anyone with $25 and an idea. AI removed the last barrier - needing to know how to code. $25 to register, One week of work. $7,000 in the first month.

Sprytix

85,133 次观看 • 1 个月前

I added KV caching and INT8 KV quantization to our transformer inference, improving throughput by 35x. All of this was done from scratch in Rust + CUDA, on top of a homemade ML framework. On a 4-token prompt with 252 generated tokens: - Original: 0.76 tok/s - KV cache fp32: 27.21 tok/s - KV cache int8 (quantized): 27.29 tok/s Try it out yourself here: In practice: - KV caching gave us about a 35x end-to-end speedup - INT8 KV cache kept roughly the same speed as fp32 but cut KV cache memory by 3.78x FP32 cache used 4.5 MB in this run while the INT8 cache used only 1.19 MB This simple change to inference created a huge impact on performance. To learn more about the KV cache and other optimizations like this, check out the blog at
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I added KV caching and INT8 KV quantization to our transformer inference, improving throughput by 35x. All of this was done from scratch in Rust + CUDA, on top of a homemade ML framework. On a 4-token prompt with 252 generated tokens: - Original: 0.76 tok/s - KV cache fp32: 27.21 tok/s - KV cache int8 (quantized): 27.29 tok/s Try it out yourself here: In practice: - KV caching gave us about a 35x end-to-end speedup - INT8 KV cache kept roughly the same speed as fp32 but cut KV cache memory by 3.78x FP32 cache used 4.5 MB in this run while the INT8 cache used only 1.19 MB This simple change to inference created a huge impact on performance. To learn more about the KV cache and other optimizations like this, check out the blog at

Reese Chong

51,192 次观看 • 1 个月前

“A Google engineer took all the IP of how Google designed their AI chips, moved to China, and then started a company. DeepSeek came out of nowhere. Everyone was so surprised at how capable their model was—or they managed to have a high-end espionage operation to steal all of our trade secrets from the United States and then re-implement them back in China… The way he stole the data out of Google's corporate cloud was so stupid. He just copy-pasted all the code into Apple Notes, exported it to PDF, printed it, and then just walked out with it. That’s it.” Alexandr Wang
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“A Google engineer took all the IP of how Google designed their AI chips, moved to China, and then started a company. DeepSeek came out of nowhere. Everyone was so surprised at how capable their model was—or they managed to have a high-end espionage operation to steal all of our trade secrets from the United States and then re-implement them back in China… The way he stole the data out of Google's corporate cloud was so stupid. He just copy-pasted all the code into Apple Notes, exported it to PDF, printed it, and then just walked out with it. That’s it.” Alexandr Wang

Shawn Ryan

558,315 次观看 • 11 个月前

🚨 Breaking: Google will soon launch Gemini CLI, a powerful open-source AI agent built for the terminal. - Built on Gemini 2.5 Pro - 1 million token context window - Free tier with 60 requests per minute and 1,000 per day - Google Search grounding for real-time context - Script and plugin support - Non-interactive mode for automation - Support for Model Context Protocol (MCP) - Integrated with Gemini Code Assist in VS Code - Fully open-source under Apache 2.0
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🚨 Breaking: Google will soon launch Gemini CLI, a powerful open-source AI agent built for the terminal. - Built on Gemini 2.5 Pro - 1 million token context window - Free tier with 60 requests per minute and 1,000 per day - Google Search grounding for real-time context - Script and plugin support - Non-interactive mode for automation - Support for Model Context Protocol (MCP) - Integrated with Gemini Code Assist in VS Code - Fully open-source under Apache 2.0

AshutoshShrivastava

217,397 次观看 • 11 个月前

A programmer got fired on a Tuesday He opened Claude and just asked: "What do I do now?" Claude walked him through prediction markets. Told him the crowd is predictably wrong, smart money leaves patterns, and nobody's built a proper system to track it. "You could build that." 3 days. No sleep. Him + Claude tearing through 10,847 wallets. Found 7 traders with actual edge. Built an agent to copy them in real time - news feeds, mispricing detection, Kelly sizing. Fully autonomous. Deployed it at 11:47pm. Went to sleep. Day 1: +$8,400 Day 2: +$11,200 Day 3: +$9,800 Day 4: +$12,100 Day 5: +$6,300 Day 6: +$4,876 $52,676 in 6 days. His old salary: $48k/year. 786 trades. 68.4% win rate. He never touched it once. check here: Wall Street pays $2M/year for a person who does this. He paid $20/month for Claude. Getting fired was the best thing that ever happened to him. His boss just doesn't know it yet.
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A programmer got fired on a Tuesday He opened Claude and just asked: "What do I do now?" Claude walked him through prediction markets. Told him the crowd is predictably wrong, smart money leaves patterns, and nobody's built a proper system to track it. "You could build that." 3 days. No sleep. Him + Claude tearing through 10,847 wallets. Found 7 traders with actual edge. Built an agent to copy them in real time - news feeds, mispricing detection, Kelly sizing. Fully autonomous. Deployed it at 11:47pm. Went to sleep. Day 1: +$8,400 Day 2: +$11,200 Day 3: +$9,800 Day 4: +$12,100 Day 5: +$6,300 Day 6: +$4,876 $52,676 in 6 days. His old salary: $48k/year. 786 trades. 68.4% win rate. He never touched it once. check here: Wall Street pays $2M/year for a person who does this. He paid $20/month for Claude. Getting fired was the best thing that ever happened to him. His boss just doesn't know it yet.

BuBBliK

227,853 次观看 • 2 个月前

In 2014 a quant at Two Sigma quit his job, waited two months, then hacked back into their network and walked out with the trading algorithms that had made the fund billions. He planned to start his own hedge fund with them. Two Sigma manages $52 billion and was founded by the math PhD who sat next to Jeff Bezos at D.E. Shaw. They almost lost the formula to a former employee with a laptop. The full story is on a YouTube channel almost no one in finance reads. Bookmark it tonight. Then read the article below.
12:17

In 2014 a quant at Two Sigma quit his job, waited two months, then hacked back into their network and walked out with the trading algorithms that had made the fund billions. He planned to start his own hedge fund with them. Two Sigma manages $52 billion and was founded by the math PhD who sat next to Jeff Bezos at D.E. Shaw. They almost lost the formula to a former employee with a laptop. The full story is on a YouTube channel almost no one in finance reads. Bookmark it tonight. Then read the article below.

zostaff

54,215 次观看 • 18 天前

Claude Code is $200/month. GitHub Copilot is $19/month. Jack Dorsey's company just open-sourced a free alternative with 35,000 GitHub stars. It's called Goose. - Works with any LLM — Claude, GPT, Gemini, Llama, DeepSeek - Reads and edits your entire codebase - Runs shell commands and installs dependencies - Executes and debugs code automatically - Desktop, CLI, and web interface - Written in Rust. No bloat. Block is a $40 billion company. They built it for their own engineers then gave it to everyone.
1:49

Claude Code is $200/month. GitHub Copilot is $19/month. Jack Dorsey's company just open-sourced a free alternative with 35,000 GitHub stars. It's called Goose. - Works with any LLM — Claude, GPT, Gemini, Llama, DeepSeek - Reads and edits your entire codebase - Runs shell commands and installs dependencies - Executes and debugs code automatically - Desktop, CLI, and web interface - Written in Rust. No bloat. Block is a $40 billion company. They built it for their own engineers then gave it to everyone.

0xMarioNawfal

179,477 次观看 • 2 个月前

2M scientific papers are published each year. That’s 5,500 per day! If you worked a 10 hour day with no breaks, you’d have to read 1 paper every 7 seconds just to keep up. So we built the Paperscraper to help us programmatically stay on top of the latest scientific research. 1/
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2M scientific papers are published each year. That’s 5,500 per day! If you worked a 10 hour day with no breaks, you’d have to read 1 paper every 7 seconds just to keep up. So we built the Paperscraper to help us programmatically stay on top of the latest scientific research. 1/

Seth Bannon

73,640 次观看 • 3 年前

What does it actually take to run A/B testing at nearly a billion-user scale? Prudhvi Vatala, Head of Engineering Platforms at Snap Inc., explains how his team migrated 10+ petabytes of daily data processing to GPU-accelerated pipelines on Google Cloud — cutting job costs by 76% and memory footprint by 80%, with zero code changes.
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What does it actually take to run A/B testing at nearly a billion-user scale? Prudhvi Vatala, Head of Engineering Platforms at Snap Inc., explains how his team migrated 10+ petabytes of daily data processing to GPU-accelerated pipelines on Google Cloud — cutting job costs by 76% and memory footprint by 80%, with zero code changes.

NVIDIA

49,991 次观看 • 23 天前

Google Flow and Google Veo 3 works with diagrams. Create a still image and annotate it with arrows and text to prompt movement. Google Flow then does the rest for you, here's some examples.
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Google Flow and Google Veo 3 works with diagrams. Create a still image and annotate it with arrows and text to prompt movement. Google Flow then does the rest for you, here's some examples.

Jerrod Lew

196,207 次观看 • 10 个月前

🚨 Claude Code costs $200/month. GitHub Copilot costs $19/month. Jack Dorsey's company built a free alternative. 35,000 GitHub stars. It's called Goose. An open source AI agent built by Block that goes beyond code suggestions. It installs, executes, edits, and tests. With any LLM you choose. Not autocomplete. Not suggestions. A full autonomous agent that takes actions on your computer. No vendor lock-in. No monthly subscription. Bring your own model. Here's what Goose does: → Works with ANY LLM. Claude, GPT, Gemini, Llama, DeepSeek, Ollama. Your choice. → Reads and understands your entire codebase → Writes, edits, and refactors code across multiple files → Runs shell commands and installs dependencies → Executes and debugs your code automatically → Extensible through MCP. Connect it to any external tool. → Desktop app, CLI, and web interface. Pick your workflow. → Written in Rust. Fast. Lightweight. No bloat. Here's the wildest part: Block is a $40 billion company. They built Cash App, Square, and TIDAL. They use Goose internally. Then they open sourced the entire thing. This isn't a side project from a random developer. This is production-grade tooling from a company that processes billions in payments. Built for their own engineers. Given to everyone. Claude Code: $200/month. Locked to Claude. GitHub Copilot: $19/month. Locked to GitHub. Cursor: $20/month. Locked to their editor. Goose: Free. Any LLM. Any editor. Any workflow. Forever. 35.3K GitHub stars. 3.3K forks. 4,078 commits. Built by Block. 100% Open Source. Apache 2.0 License.
1:49

🚨 Claude Code costs $200/month. GitHub Copilot costs $19/month. Jack Dorsey's company built a free alternative. 35,000 GitHub stars. It's called Goose. An open source AI agent built by Block that goes beyond code suggestions. It installs, executes, edits, and tests. With any LLM you choose. Not autocomplete. Not suggestions. A full autonomous agent that takes actions on your computer. No vendor lock-in. No monthly subscription. Bring your own model. Here's what Goose does: → Works with ANY LLM. Claude, GPT, Gemini, Llama, DeepSeek, Ollama. Your choice. → Reads and understands your entire codebase → Writes, edits, and refactors code across multiple files → Runs shell commands and installs dependencies → Executes and debugs your code automatically → Extensible through MCP. Connect it to any external tool. → Desktop app, CLI, and web interface. Pick your workflow. → Written in Rust. Fast. Lightweight. No bloat. Here's the wildest part: Block is a $40 billion company. They built Cash App, Square, and TIDAL. They use Goose internally. Then they open sourced the entire thing. This isn't a side project from a random developer. This is production-grade tooling from a company that processes billions in payments. Built for their own engineers. Given to everyone. Claude Code: $200/month. Locked to Claude. GitHub Copilot: $19/month. Locked to GitHub. Cursor: $20/month. Locked to their editor. Goose: Free. Any LLM. Any editor. Any workflow. Forever. 35.3K GitHub stars. 3.3K forks. 4,078 commits. Built by Block. 100% Open Source. Apache 2.0 License.

Nav Toor

389,929 次观看 • 2 个月前

A 14-year-old from China built three separate AI brains connected to Claude Code - and each one grows every day on its own. One brain for code, one for projects, one for everything else in his life. 600+ conversations on one topic in a single node - everything linked, everything accessible in one request without copying between tabs. But the main thing isn't storage. If Claude Code made a mistake and he corrected it once - the system remembered. That same mistake never happened again. No re-explaining context, no starting from zero - Claude already knows how he thinks. Instead of one giant messy file- a stack of smaller brains passing context to each other. Brain to brain to brain - just stacking intelligence while his classmates do homework by hand.
1:13

A 14-year-old from China built three separate AI brains connected to Claude Code - and each one grows every day on its own. One brain for code, one for projects, one for everything else in his life. 600+ conversations on one topic in a single node - everything linked, everything accessible in one request without copying between tabs. But the main thing isn't storage. If Claude Code made a mistake and he corrected it once - the system remembered. That same mistake never happened again. No re-explaining context, no starting from zero - Claude already knows how he thinks. Instead of one giant messy file- a stack of smaller brains passing context to each other. Brain to brain to brain - just stacking intelligence while his classmates do homework by hand.

Noisy

22,597 次观看 • 1 个月前