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Please save this post: 1- RACA token = 1.000X Easy = 0,20 very Easy. 2- USMLab.bab Metamon, lands, NFTs (BSC) = 10.000X Easy 3- Looki.bab = 1.000.000,00 USD 4- Matrix Plus Box (MPB) 15.000.000,00 USD 5- NODE R = 20k usdt per month 6- NODE SR = 200k usdt...

12,020 görüntüleme • 1 yıl önce •via X (Twitter)

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King_SpawN profil fotoğrafı
King_SpawN1 yıl önce

@RACA_3 @USMverse @LookiAvatar @MPB_USM @DrWatney @KodaRobotDog @bsf_ai 🤝🚀🚀🚀🚀 #raca 10.000x go go go

Travala.com 🏨 ✈️ profil fotoğrafı
Travala.com 🏨 ✈️1 yıl önce

🚨 WIN $500 IN BITCOIN! 🚨 Enter by creating a free Travala account to book travel with crypto. PLUS every entry gets a BONUS US$50 credit to use on their first booking! T&Cs apply

SteveHally profil fotoğrafı
SteveHally1 yıl önce

@RACA_3 @USMverse @LookiAvatar @MPB_USM @DrWatney @KodaRobotDog @bsf_ai 🚀🚀🚀🚀🚀🚀 If what you say comes true. You can declare your prophethood. 😂😂😂 God bless you Rico🙏🙏

Rico.bab profil fotoğrafı
Rico.bab1 yıl önce

@RACA_3 @USMverse @LookiAvatar @MPB_USM @DrWatney @KodaRobotDog @bsf_ai Amen

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Bangla Ventures1 yıl önce

@RACA_3 @USMverse @LookiAvatar @MPB_USM @DrWatney @KodaRobotDog @bsf_ai Mpb holders airdrop? Is this estimate for 2025? Or till 2030?

Rico.bab profil fotoğrafı
Rico.bab1 yıl önce

@RACA_3 @USMverse @LookiAvatar @MPB_USM @DrWatney @KodaRobotDog @bsf_ai At any moment they will press the START button, when they press it you will start to believe me.

Dark_Crypto profil fotoğrafı
Dark_Crypto1 yıl önce

@RACA_3 @USMverse @LookiAvatar @MPB_USM @DrWatney @KodaRobotDog @bsf_ai Your numbers are impressive. But you know it's just a dream.

Rico.bab profil fotoğrafı
Rico.bab1 yıl önce

@RACA_3 @USMverse @LookiAvatar @MPB_USM @DrWatney @KodaRobotDog @bsf_ai Please save this post, we'll talk later if it's a dream or not.

burak demirci profil fotoğrafı
burak demirci1 yıl önce

@RACA_3 @USMverse @LookiAvatar @MPB_USM @DrWatney @KodaRobotDog @bsf_ai #RACA

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Paraminatör1 yıl önce

@RACA_3 @USMverse @LookiAvatar @MPB_USM @DrWatney @KodaRobotDog @bsf_ai When, bro? When I’m in the grave?😂😂😂 I’m waiting for it to happen while we’re still alive

Rico.bab profil fotoğrafı
Rico.bab1 yıl önce

@RACA_3 @USMverse @LookiAvatar @MPB_USM @DrWatney @KodaRobotDog @bsf_ai The time is coming, stop being anxious… 😃😃

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Becoming a multimillionaire at any age is easy. Here are the literal steps: 1) Move to Vietnam. Rent a mansion in a rural province for a $346 a month. 2) Find an online, W2 job to cover your rock-bottom costs of living, while living in absolute luxury, and being legally exempt from taxes on your income. 3) You are allowed to do 4 things: a. Work on your business. b. Read. c. Work out. d. Start a harem 4) Do nothing else till you're making $50,000 a month. 5) Rotate with a new country of your choice every 3 months to void all territorial tax The end. Do this and you'll: a. Have endless time to work on your craft. b. Enjoy it, because your brain will have nothing else to latch onto. This is the most surefire, near-guaranteed way to become successful. Everyone is doing it. Most people turn 20, move to Kansas to live in a run-down, over-priced shoe box. They get $100k in debt for a liberal arts degree, only to graduate with no knowledge of how to optimize US tax law. Address the root causes. Leverage an advantaged tax structure. Live overseas as the sole pathway to reduce expenses to under $1,000 a month, while profiting, tax-free, from a W2 job. Even with just a $50,000 a year salary with $1,000 expenses per month, you save $38,000 a year to investment into your business. Here's one half of the mansion I rented out for exactly $346 per month in rural Vietnam at age 23. It had a wrap-around garden, a literal cave with trees and dead bear skins fermenting in alcohol, three stories, three separate tea rooms, and a terrace balcony. And this is ONE side of the total property for less than $400 a month! You can do this in most any developing nation beyond the USA. I most recommend Vietnam to start, Georgia to bank, and the home nation of whatever woman you eventually marry to invest long-term, America or otherwise.

Rogue | Frontier Philosophy

36,347 görüntüleme • 17 gün önce

Different Airdrops and their Update. If you have been participating in airdrops with me then here is an update for you, 1. Quip Network Quip Network > daily check in for points > deposit some funds for extra points > share content to participate in $100,000 reward > step by step guide on CoinStudy 2. Xeet AI xeet > wait for tournaments, expected to live this week > buy creators' card in order to join their squad > step by step guide on CoinStudy 3. Nesa AI (raised $5 Million USD) Nesa > join beta version > complete social tasks, earn XPs > stake NES faucet tokens daily on DAI > get pro membership for extra faucet > share content for discord role > step by step guide on CoinStudy 4. Legion (raised $6 Million USD) LEGION > join legion, take part in presales > join legion republic for guaranteed allocation > join legion republic through Ethos for extra points > step by step guide on CoinStudy 5. Mercle Mercle > Install mercle app > vouch others and get vouch > earn MERCI points > step by step guide on CoinStudy 6. Arc Network (raised $222 Million USD) Arc > join arc community, earn points daily > join arc discord > build on arc > apply for arc role after 500 points > step by step guide on CoinStudy 7. Edgen Tech (raised $26 Million USD) Edgen > join edgen tech with your X account > earn daily credits and Aura points > complete daily and weekly tasks > invite others and climb leaderboard > step by step guide on CoinStudy 8. Base Network Base > join guild, get discord roles > on chain footprints > install base app, use daily > build on base > step by step guide on CoinStudy 9. Genlayer (raised $8 Million USD) GenLayer > join testnet > join community and contribute > join rally dot fun > participate in rally campaigns > step by step guide on CoinStudy 10. Aro Network (raised $7 Million USD) ARO Network > install chrome extension > run node, get badges > step by step guide on CoinStudy 11. LitVM LitVM > join testnet, get faucet > join LitVM points campaign on Arkada > step by step guide on CoinStudy 12. Kuru Exchange (raised $13 Million USD) Kuru > create account on Kuru exchange > swap daily , generate volume > park some MON tokens > invite others > step by step guide on CoinStudy 13. Checkpoint Exchange Checkpoint > join testnet beta > connect account, check crypto points > trade crypto points > invite others > step by step guide on CoinStudy 14. Arc Nova (raised $15 Million USD) ArcNova > join leaderboard > complete social tasks > watch AI videos > submit AI content > step by step guide on CoinStudy 15. Vibestarter Vibestarter > Join and complete mainnet quests > participate in presales > Invest in VIBES > step by step guide on CoinStudy 16. Nucleus Nucleus > join and check your onchain + social reputation > participate in live campaigns for creators > step by step guide on CoinStudy 17. Sleepagotchi (raised $6 Million USD) Sleepagotchi 💤🦖 > Install app > participate in campaign on Nucleus > step by step guide on CoinStudy 18. Canopy Network (raised $1.2 Million USD) Canopy > join testnet > participate in campaign on Nucleus > allocated $100,000 for 300 content creators > step by step guide on CoinStudy more airdrops with easy step by step guide coming on CoinStudy This is not a paid post.

AInvestor

15,290 görüntüleme • 1 ay önce

Self Attention by hand ✍️ ~ 9 steps walkthrough below Self-attention is what enables LLMs to understand context. How does it work? So I drew and calculated one entirely by hand. Goal: turn four 6D features into four 3D attention weighted features, filling in every cell yourself. = 1. Given = Four feature vectors, six dimensions each, one per position. = 2. Query, key, value = Let us multiply the features by WQ, WK and WV. Queries, keys and values all come out of the same four features, and that is what the word "self" is doing in self-attention. = 3. Prepare for MatMul = We copy the queries across the top and the transposed keys down the side. Lining the two up is half the work. = 4. MatMul = Let us multiply K transpose by Q. Every cell is the dot product of one key with one query, which we use as a matching score. That works because the dot product is the numerator of cosine similarity: it is how alike two vectors are, before anyone divides by their lengths. = 5. Scale = We divide by the square root of dk, the dimension of a key vector, here 3. Without it the scores grow with the dimension and a 64-wide head would swamp the softmax. To keep the page doable in pen, the drawing approximates dividing by root 3 with halving. = 6. e to the power = Let us raise e to the power of each score. This is the first half of softmax, and the drawing uses 3 in place of e, which is close enough to do in your head. = 7. Sum = We add up each column: 16, 6, 7 and 12. = 8. Normalize = Let us divide every cell by its column sum. That gives the attention weight matrix in yellow, and each of its four columns is now a probability distribution over the four positions. The decimals are nudged as they are rounded, so every column still sums to exactly 1. = 9. MatMul = We multiply the value vectors by those weights. Each output is a blend of all four values, mixed in the proportion the attention matrix just decided, and it goes to the position-wise feed forward network in the next layer: the FFN box at the bottom of the page. The outputs: Attention weights (A), by column = [.2, .6, 0, .2], [.2, .4, .2, .2], [.4, .2, 0, .4], [.1, .7, .1, .1] Attention weighted features (Z) = [8, 2, 6], [8, 4, 4], [16, 4, 2], [4, 2, 7] The takeaway: attention is a weighted average, and everything before step 9 exists to decide the weights. Compare every position with every other, turn the scores into one distribution per position, then blend. 💾 Save this post!

Tom Yeh

25,913 görüntüleme • 2 gün önce

An Anthropic safety researcher closed her laptop when she saw my screen at Philz Coffee. I was running my Polymarket bot from the corner table. She was in line. Looked over my shoulder. Stopped moving. That is not a normal trading app. What model is that running on? I told her. Claude Code. Four repos. $25 a month. She sat down without asking. I work on the alignment team. We test Claude for exactly this kind of autonomous behavior. You are letting it find its own trading signals. Not just signals. Wallets. github/warproxxx/poly_data 86 million trades. Every wallet. Every entry. Every exit. You are feeding Claude raw wallet data and letting it identify which traders consistently win. Then cloning their behavior. She said it slowly. Like she was writing an internal report in her head. Claude Code finds the top wallets. Reverse-engineers their timing. Copies their entries. Then exits before they do. Before they do? My bot cuts at 85% of expected move or on a 3x volume spike. Top wallets exit before resolution 91% of the time. They capture 86% of the move. Losers hold to 58%. She put her coffee down. How did you get Claude to learn exit timing on its own? I showed her the second repo. github/Polymarket/polymarket-cli Three commands. 500+ markets. No API key. Claude scores them in 20 minutes. We have 14 people stress-testing Claude's autonomous capabilities. You are just using them. My setup: Claude API: $20 per month VPS: $5 per month poly_data: free polymarket-cli: free 19 days. 4 agents. 74% win rate. She stared at the screen for a long time. This is literally what our red team simulates. Except you actually deployed it. She emailed me two days later. Our policy team found your post. Please take it down. Too late. I built the entire framework: How to connect Claude Code to poly_data wallet analysis How to configure autonomous exit timing at 85% threshold How to deploy polymarket-cli for market scoring How to run 4 parallel agents on a single VPS How to start with $500 and scale on evidence The system runs 24/7. Finds proven wallets. Copies their timing. Exits before the crowd. No prediction. No guessing. Just wallet cloning. You only need Claude + device + 1 hour per day. Giving this free for 24 hours. To get it: 1. Comment the word MoneyBot 2. Like and retweet this 3. Follow me Himanshu Kumar so I can DM you Save this post. Deploy the wallet cloning system this week. Start with $500. Scale on evidence.

Himanshu Kumar

23,015 görüntüleme • 1 ay önce

Announcing the BOOM DAO GRANT PROGRAM!📢🚨🚀 The BOOM Grant Program is designed to accelerate the expansion of the BOOM ecosystem and enhance the broader Internet Computer ecosystem by empowering game developers to create exceptional video games on the BOOM World Protocol. By offering grants, the program encourages developers to innovate and build engaging gaming experiences that integrate seamlessly with the BOOM Gaming Guild. Game developers who participate in the BOOM Grant Program have the opportunity to integrate quests from the BOOM Gaming Guild into their games. This integration not only enriches the BOOM game platform but also rewards gamers and developers. Additionally, by incorporating BOOM Gaming Guild quests, developers can tap into the extensive Gaming Guild userbase, potentially acquiring thousands of new users. This synergy creates powerful network effects that benefit both the BOOM ecosystem and the Internet Computer ecosystem at large. Grantees can also give back to BOOM DAO through future token launches or NFT launches. The program seeks to make building games on ICP more accessible and appealing by providing the necessary financial, tech, and marketing support to promising teams and individuals. Through this initiative, game developers are equipped with the resources they need to bring their visionary games to life, contributing to interconnected gaming community on the Internet Computer blockchain. Focus Areas for the Grants 👉 Building simple, fun, casual, and visually beautiful 3D minigames using the BOOM Minigame Template, which automatically integrates ICP login and quests in the BOOM Gaming Guild. 👉 Integrating the BOOM Unity Package into your existing Unity game, deploying it on ICP using WebGL, and creating quests in the BOOM Gaming Guild for it. 👉 All games must meet the requirements of having high-quality graphics, easy-to-learn gameplay, built in Unity, optimized for WebGL, and a focus on a crypto-native user base. 👉 Overly complex games (eg. Advanced Strategy games) or visually boring games (eg. 2D or cheap graphics) will be rejected. Grant Application Process A motion proposal must be made by the game development team or individual to the BOOM SNS DAO with a detailed breakdown of their funding tier and the milestones of their grant application. This is subject to the DAO voting for approval. We are currently offering three funding tiers, and ask you to tailor your application and scope of work accordingly: 👉 5,000 USD - Your work should be scoped according to a 1-2 month timeline. 👉 10,000 USD - Your work should be scoped according to a 2-3 month timeline. 👉 25,000 USD - Your work should be scoped according to a 3-4 month timeline. More than 1 game can be built during the process of a grant, in fact BOOM DAO encourages teams to build as many high-quality games as they can during a grant timeline. The more games that can be built during a grant, the more games that are growing the BOOM ecosystem. Each grant will consist of 4 milestones, with funding being distributed in 4 equal increments. Each milestone will be accountable to a motion proposal with a detailed progress update and links to any deliverables available to review. After each milestone has been reached and approved through the motion proposal, a transfer proposal can be made for ICP tokens from the treasury using the USD value on the day of distribution. Let's grow the ICP and BOOM DAO gaming ecosystem! 🎮🌏

BOOM DAO

12,041 görüntüleme • 2 yıl önce

Important reminder Binance CZ 🔶 BNB 🚨 Remember what Binance did to us on 10.10. The big picture here. Here is a summary, an analysis, a reminder, and a warning. Never forget. Whoever has too much power is too dangerous. 🔺 1. What happened on 10.10: On 10 October 2025 the crypto market suffered the largest single liquidation event in its history. More than 19 billion USD in leveraged positions were wiped out within hours, affecting well over 1.6 million traders across all major venues. Bitcoin had just printed an all time high above 122000 USD. Within the 10 to 11 October window it crashed to lows around 104000 to 110000 USD, a drawdown of 10 to 15 percent in less than a day. This day is now referenced across mainstream media, research and exchanges simply as 10/10. The trigger in the headlines was clear: ▶️ Trump announced additional 100 percent tariffs on Chinese imports. US China trade war reignited. But the scale and structure of the crypto damage did not match a normal macro move. They matched a structural failure inside the plumbing of one venue. That venue is Binance. 🔺 2. Binance: Before the crash Binance handled: ▶️ 60 to 70 percent of global USDT altcoin spot volume ▶️ The deepest unified collateral system in crypto ▶️ Cross margin links across spot, futures, options and structured products Independent data providers like Kaiko and CoinGlass consistently identify Binance as the global price discovery engine for altcoins. On 10.10 that centralization became a single point of catastrophic failure. Across research from Kaiko, CoinGlass, Coindesk, Aurpay, Galaxy and independent analysts: ▶️ Binance order book depth collapsed more than any other exchange ▶️ Venue specific collateral assets broke first and hardest on Binance ▶️ Liquidations elsewhere followed Binance with multi minute lag ▶️ On chain and off chain data show certain wallets profited massively from the failure pattern This was a centralized system imploding under stress. 🔺 3. The Binance specific anomalies: Three Binance collateral assets behaved abnormally: ▶️ USDe traded at 0.62 to 0.65 USD on Binance while near 1 USD elsewhere ▶️ wBETH printed 430 USD while ETH traded near 3500 USD on other venues ▶️ BNSOL printed 34.9 USD while far higher elsewhere Insights4vc and Galaxy found ATOM, ENJ and other majors printed near zero only on Binance. Global markets remained far above. When you see: 1 exchange 3 collateral assets 80 to 99 percent divergence Invalid prices Frozen liquidity You are seeing a matching engine and oracle collapse. Binance later called this a “technical ghost”. It behaved like a centralized kill switch. 🔺 4. The liquidation cascade and ADL CoinGlass, Reuters and FT all agree: 10.10 created the largest liquidation cascade in crypto history. More than 19 billion USD were liquidated. But this number is only the visible liquidation counter. It does not include: • ADL reductions on profitable positions • Forced margin reductions not registered as liquidations • Collateral destruction from oracle mispricing • Spot positions force closed • Options and structured product collateral failures • Off book desk unwinds and hidden exposure reductions When analysts reconstruct the full chain, the true economic unwind is well above 40 billion USD. Several market structure estimates place the systemic damage between 60 and 100 billion USD. 19B is what dashboards show. 40B+ is what the market absorbed. Insights4vc documented: ▶️ Thousands of liquidations per second ▶️ Hyperliquid triggered ADL ▶️ Binance triggered its own ADL events Distorted Binance prices fed industry oracles and dragged the global market down. 🔺 5. On chain and off chain fingerprints: Wallet 0xb317..: ▶️ 192 million USD BTC short during crash ▶️ 163 million USD short after ▶️ Perfect timing with Binance anomalies Binance publicly acknowledged peg failures in USDe, wBETH and BNSOL. Zero prints happened only on Binance. The data convicts the structure. 🔺 6. Collapse of Fake Liquidity: Altcoins that went to zero on Binance did not do so elsewhere. Spoof liquidity, wash trading and internalized market making created an illusion of depth that vanished instantly under stress. 🔺 7. Comparison with fair, regulated markets: On NASDAQ: Market makers must quote both sides Liquidity withdrawal requires approval Wash trading is prohibited Exchanges cannot run secret market makers On 10.10 Binance’s order book had a buy side vacuum with no notice and no accountability. 🔺 8. Binance’s regulatory vacuum and conflict of incentives: Longs were liquidated. Shorts were ADL’d. Delta neutral strategies were wiped out. In an unregulated venue generating 70 million USD per day in fees, fairness is not enforced. 🔺 9. Evidence Binance refuses to provide: Mark price logs Oracle inputs Liquidation engine data ADL queues Insurance fund movements Engine parameters Matching neutrality proof None provided. 🔺 10. Why “never forget” matters: A single exchange distorted global prices in minutes. Fake liquidity collapsed. Oracle flaws vaporized billions. Unified margin amplified everything. 🔺 11. The message The data is here. The traces are here. The failures are documented. Remember what Binance did to us on 10.10. Concentrated power in crypto is systemic fragility with better marketing. Power is liquidity. Only users decide who holds it. Thanks for reading. — by $MASTR crypto project

MASTR

17,432 görüntüleme • 5 ay önce

This is where a lot of tech professionals landing 6-figure roles actually get hired from. Not random job boards. Not even the usual “Easy Apply.” Here are 8 platforms that are genuinely high-signal for UX designers and tech professionals looking for fully remote roles. I also broke down what makes each one stand out, and how you should use them properly. 1. Wellfound (AngelList) URL: How to win here: Build a profile like a landing page (2 to 3 outcomes + 1 niche). Filter by salary range + stage. Apply to roles where your portfolio matches the product type. Message founder/recruiter with 2 lines: relevant proof + quick question. You will also need a USD account to receive salary, go to Cleva (YC W24) and open one. Best level: mid to senior (junior can still get something here with strong case studies). 2. Otta URL: How to win here: Set preferences tightly (role, level, industry, remote rules). Treat it like “high quality, low volume”: 3–5 strong apps/week. Tailor your first line of CV to match the job’s problem space. Best level: junior-mid to senior (works for all, but best when your profile is clear). 3. Y Combinator Jobs (Work at a Startup) URL: How to win here: Apply to roles where you can show 0→1 or growth-stage wins. Add a short “Operating style” section in your profile (collaboration, scope). Follow up off-platform (LinkedIn/email) with a 3-sentence note. You may also need a USD account to receive salary, go to Cleva (YC W24) and open one. Best level: mid to senior (but juniors can land roles in smaller teams with strong proof). 4. Himalayas URL: How to win here: Set location/timezone filters correctly. Save searches + alerts for your niche (e.g., B2B SaaS, fintech). Apply within 24 - 48 hours of posting when possible. Best level: all levels. 5. Remotive URL: How to win here: Filter to “worldwide” only if you truly can work globally. Don’t apply without rewriting your top 3 bullets to match role keywords. Pair every application with a short “proof note” (1 case study link + why). Best level: mid-level + seniors, but juniors can win with tailored apps. 6. We Work Remotely URL: How to win here: Apply fast (same day if possible). Use a “1-minute cover letter”: 3 bullets (domain match, proof, link). Only apply when you match 70%+ of requirements. Best level: mid to senior. 7. Remote OK URL: How to win here: Use strict filters (role + seniority + benefits). Ignore anything vague (“rockstar”, no salary, unclear company). Treat it like lead gen: apply + then research and follow up elsewhere. Best level: mid to senior. 8. FlexJobs (paid, but filtered) URL: How to win here: Only pay if you’ll apply consistently for 30 days. Use advanced filters and avoid anything without clear employer info. Cross-check listings on the company’s careers page. Best level: junior to mid (also useful for career switchers). You will need a USD account to receive salary, go to Cleva (YC W24) and open one. If you find breakdowns like this useful, Follow for more, I share more of them here. Don't mention.

designwithkingsley

14,721 görüntüleme • 4 ay önce

This is part 2 of a 2 part post (see part 1 here Below is a structured analysis to demonstrate the validity of using buyers of Veritaseum #SmartMetal to buy into and sell compute from globally aggregated cell phone compute pools - directly compeiting with the big guys - Google, Amazon and Microsoft cloud businesses. We discuss estimates, business model propositions, and potential economic outcomes, but first, see my Executive Global Article on Zero Profit Models( and purchase Veritaseum SmartMetal here - Can you really disintermediate the most profitable revnues of t $6.7 trillion worth of technology cloud providers? Well, the fact that it is among, if not the, most profitable of their revenue drivers is a very material clue! Step 1: Estimating the Number of High-End Smartphones Globally As of early 2025, approximately 7.5 billion smartphones are actively used worldwide. Considering that: About 30% of global smartphones are high-end (comparable or superior to an iPhone X; for instance, Samsung Galaxy S22/S23 Ultra, iPhone 16 Pro Max with A18 chips, and Qualcomm Snapdragon 8 Gen 3 or newer). Thus, approximately 2.25 billion high-end smartphones exist today (30% of 7.5B). Step 2: Aggregate Compute Power Estimation (Idle Capacity) Average Computational Capacity per High-End Smartphone: A high-end phone has roughly: CPU: ~1 to 1.5 TFLOPS GPU: ~1.5 to 2 TFLOPS Average Idle Compute per Phone: 1 TFLOPS (CPU) + 1.5 TFLOPS (GPU) = ~2.5 TFLOPS idle. Total Potential Compute Power: 2.25B smartphones × 2.5 TFLOPS each ≈ 5,625,000,000 TFLOPS (5.625 ExaFLOPS) Comparison to Cloud Vendors: Amazon AWS, Microsoft Azure, Google Cloud combined currently deploy approximately ~1 to 2 ExaFLOPS of continuous computing power. Thus, aggregate idle compute power from high-end smartphones (5.625 ExaFLOPS) exceeds the largest cloud vendors combined by at least 2.8x. Step 3: Proposed Business Model ("Zero Margin Trustless Model") Following Middleton’s economic principles, a decentralized marketplace based on his IP (SmartMetal Rounds and patented protocols) would allow individual users to rent their smartphones’ idle compute power. The economics would follow: Revenue Structure: Compute resources provided by phone owners (children, elderly, economically disadvantaged communities) rented to consumers (AI firms, universities, research institutions, enterprises). Offered at 10% above net cost ("as close to free as possible" per the attached article​Executive Global articl…). Revenue Distribution: SmartMetal Owners (phone owners): Receive 20% of net revenue generated. Platform Cost & Overhead: Costs for electricity, network management, and maintenance (approximately 70% of net revenue). Intellectual Property Licensing (Middleton’s IP): A modest licensing fee—around 10% (aligned with Middleton’s zero-margin, IP-licensing-centric model). Step 4: Revenue Estimation Example Assumptions: Average monthly idle compute contribution per phone: 4 hours/day, 30 days = 120 hours/month. Market price for decentralized high-performance computing: approximately $0.10 per TFLOP-hour. Revenue per Smartphone per Month: Compute provided: 2.5 TFLOPS × 120 hrs = 300 TFLOP-hours Revenue at $0.10 per TFLOP-hour: 300 × $0.10 = $30/month per smartphone Aggregate Monthly and Annual Revenue: Monthly revenue (2.25 billion phones): $30 × 2.25B ≈ $67.5 billion Annual revenue potential: $67.5B × 12 months = $810 billion annually Distribution of Annual Revenue: SmartMetal Round Owners (20%): $810B × 20% ≈ $162 billion/year Operational Cost (70%): $810B × 70% ≈ $567 billion/year Middleton IP Licensing (10%): $810B × 10% ≈ $81 billion/year Thus, the total economic benefit is substantial, particularly transformative for economically disadvantaged participants (children, elderly, developing regions). Step 5: Practical Impact & Social Value Impact on Children & Young Adults: Empowerment through earning potential (around $360 annually per child smartphone owner). Practical, intuitive introduction to economics, technology, and entrepreneurship through gamified interfaces and secure, decentralized platforms. Impact on Elderly and Economically Disadvantaged Communities: Significant supplemental income (potentially exceeding many pension plans or assistance programs). Bridging the technology gap, ensuring inclusive participation in global digital economies. Step 6: Strategic Value & Market Positioning Middleton's patented Zero Margin Trustless Model ("ZMTM")​Executive Global articl… creates a highly attractive, low-cost computational offering. Competing directly with incumbent cloud providers: The computational marketplace can massively disrupt cloud computing with lower fees and broader global reach. Leveraging Middleton’s IP and SmartMetal Rounds, it creates defensible competitive barriers and immense value for early adopters. Step 7: Driving Middleton’s Peer-to-Peer Economy As described in Middleton’s vision​Executive Global articl…, this marketplace underpins a global peer-to-peer economy, transforming idle smartphone resources into meaningful economic output. The P2P economy will leverage: AI-driven autonomous economic agents. Secure blockchain-based IP rights enforcement. Economic democratization by redistributing traditional cloud revenues directly to everyday device owners. Summary & Strategic Conclusion Implementing a decentralized compute platform powered by high-end smartphones and Middleton’s patented Zero Margin Trustless Model presents enormous economic potential, far exceeding current major cloud vendors combined. With annual revenues estimated up to $810 billion, and meaningful income distribution to disadvantaged demographics, this innovative model could dramatically reshape the global computational economy, achieve significant social impacts, and provide the backbone for Middleton’s envisioned peer-to-peer decentralized economy.

Reggie Middleton, Disruptor-in-Chief

14,751 görüntüleme • 1 yıl önce

$AMD| The FOMO to buy AMD Chips is NOW 🧵 Not Financial Advice! DYOR! Research Purpose Only! The Inference Queen is the biggest winner in Agentic AI where all other CPUs are struggling to compete with a 2yr old EPYC Turin and EPYC Venice is in mass production phase. AMD stresses deployability today on standard x86 platforms (no proprietary architectures required), full software compatibility, and open standards. This positions Venice + Helios as a practical, high-density alternative to competing solutions while underscoring that agentic AI shifts the balance toward CPU-rich racks alongside GPUs, and most importantly, lowering the cost of token to accelerate adoption and innovation. Context: The Wall Street Journal yesterday came out with an article that OpenAI is condiering drasstically lowering the token prices to win more customers from Anthropic. The narrative "they" are trying to exacerbate the current AI selloff won't last long. This is a fundamental misunderstanding of what is going on, or what I already discussed for months and years. Followers and Subscribers already knew this for years, that this day would come, where token cost will bcome the central discussion among enterprises as there is no such thing as unlimited budget or Tokenmaxxing when they use $NVDA chips or In-house Hyperscalers chips. I will link various threads if you are interested in understanding the full picture from supply chain to recent TSMC Rapid 2nm expansion up to 12 Fabs total by 2027/2028. Hyperscalers and AI natives effectively have no choice but to buy more AMD system for Agentic AI as leadership in economical, power-aware, high-volume internal + agentic use. However, due to supply constraints where Supply is far behind Demand, this makes multi-vendor reality along with in-house chips drive faster industry progress, lower overall costs, and better sustainability. NVIDIA’s Vera Rubin cannot compete with a 2 years old EPYC Turin, but AMD under Dr. Lisa Su has engineered the lowest cost-per-million-tokens, highly competitive energy-efficient solutions, and superior CPU orchestration for agentic AI at scale with Helios. Dr. Su has championed this shift since at least 2023, foreseeing the rise of agentic workflows that demand far more orchestration, parallel agents, and balanced compute well before the industry fully embraced it. Her long-term vision of AI moving from simple prompts to always on, multi-agent systems has driven AMD’s investments in high-core EPYC CPUs and integrated rack-scale solutions, perfectly positioning the company for today’s realities. The OpenAI-AMD 1GW Helios deployment (starting H2 2026) represents a pivotal vertical integration move that directly supercharges the inference economics. This isn't incremental; it's a structural shift toward ownership of massive, optimized rack-scale capacity, enabling the lowest token costs and triggering the enterprise adoption flywheel. We need to be honest, $AMD is the only company that made a big bet on Inference since the day Chatgpt became sensational where $NVDA and others were betting big on Training. At the end of the day, Token bill from Anthropic has to obey economics. Meaning the bills rise, companies have to get more out of it to justify the cost. It cannot be an unlimited inference budget, and it has to show up on efficiency, profitability and operating leverage. 1. Tokenomics After you understand this, you will understand why Citi cited Anthropic is likely to sign a deal with $AMD along with Hyperscalers, AI Labs, Sovereign AI like Softbank 5GW in France and many other countries. However, OpenAI and $META are now wanting faster deployment, and they are AMD shareholders now, they have prioritized allocation. Anthropic and Hyperscalers just cannot compete when Helios Rack lower token cost to$0.0003–$0.0005 per million tokens at GW scale. Cost to build 1GW data center 1GW Helios Rack full build is estimated $30-$35B 1GW Rubin Rack full build is estimated $45-$55B Inference (Cost per Million Tokens) ~$NVDA B200 / HGX: ~$0.02–$0.08 on optimized workloads (FP4/MXFP4, speculative decoding). Significant improvement over Hopper but still premium-priced. GB200 NVL72 rack-scale: $0.05–$0.25+ ~$AMD Helios Racks: $0.0003-$0.0005 per M tokens, dramatically lower than NVIDIA equivalents in owned infra. MI355X node-level: Up to 40% more tokens per dollar vs. competing solutions ( B200), driven by higher memory capacity (up to 288GB+ HBM), strong bandwidth, and lower acquisition costs. Training ~$NVDA Rubin Rack is estimated $0.7-$1.2/M Tokens ~$AMD Helios Rack is estimated $0.65-$1.0/M Tokens Now, OpenAI, META and Hyperscalers can lower Inference cost even further with $AMD EPYC Venice "dense rack" or Agentic AI Rack. AMD published a detailed technical blog emphasizing that the future of agentic AI autonomous, multi-step AI systems requiring heavy orchestration, databases, caching, APIs, and control planes demands massive CPU-dense rack-scale infrastructure, not just GPUs. The catalyst prominently positions their upcoming 6th Gen EPYC "Venice" processors as the key enabler for next-generation dense racks, delivering leadership throughput under real-world power, cooling, and density constraints. ~EPYC Venice (Zen 6 architecture, up to 256 cores / 512 threads per socket) is projected to deliver exceptional rack-level performance. In AMD’s modeled 100 kW rack comparisons, Venice-powered systems are expected to achieve ~3.30x the throughput of NVIDIA’s Vera (88-core Olympus) baseline across a broad mix of agentic-supporting workloads. ~This builds on current-generation 5th Gen EPYC "Turin" (up to 192 cores), which already delivers ~2.37x rack throughput vs. Vera and ~1.6x vs. Intel’s Xeon 6980P (128 cores). ~ Liquid-cooled Turin deployments already support >27,000 CPU cores per rack today. Venice is architected to push this beyond 36,000 cores in the same rack class, dramatically increasing concurrent agent capacity and overall infrastructure efficiency. 2. Ownership vs renting compute from Hyperscalers matter to OpenAI and only owning $AMD chips can meaningfully lower token cost for enterprises. ~Eliminates cloud overhead: No provider margins, utilization buffers, or egress fees. Direct control over power contracts, cooling, scheduling, and orchestration at dedicated facilities. ~Helios optimizations at GW scale: Rack-level density (1.4+ exaFLOPS FP8 per rack), high HBM4 bandwidth, EPYC orchestration for agentic workloads, and superior TCO/TDP. AMD's long-standing focus on tokens per dollar/watt shines here 20-40%+ efficiency edges in inference-heavy scenarios. ~At 1GW+ optimized deployment, inference hits $0.0003–$0.0005 per million tokens (community/analyst models tied to Helios metrics). This is dramatically lower than typical rented/cloud equivalents, especially for high-volume output tokens in agentic flows. High token bills today, enterprises running heavy agentic/coding/analysis workloads can face $50-100M+/month at current API rates (flagship models $5-30+/M output, scaled to massive volumes). Post-Helios compression, same volume will drop to $10-15M/month (or better) via lower underlying costs passed through as pricing flexibility, volume tiers, caching, or batch discounts. ROI thresholds collapse. More companies greenlight pilots → production → massive scaling. Agentic AI (autonomous workflows) multiplies token demand exponentially, but affordability removes the friction. OpenAI gains flexibility, Unlike more cloud-dependent rivals (Anthropic), they can lower effective pricing, offer aggressive enterprise bundles, or absorb volume without margin destruction directly tackling "high token bill" complaints while maintaining profitability as usage explodes. 3. Agentic AI Models shifted CPU:GPU Ratio to 1:1 toward 3-5:1 with Explosively Token-Hungry Workloads Agentic AI (autonomous, multi-step agents with planning, tool use, iteration, and self-correction) is fundamentally more compute and token intensive than conversational or single-turn generative AI. Agentic AI. autonomous, multi-step workflows with orchestration, tool use, parallel agents, data movement, and enterprise integration has dramatically increased the importance of strong host CPUs alongside GPUs. This shifts the CPU-to-GPU ratio higher and makes balanced systems critical toward 1:1 to 5:1 as enterprises testing more than 5-10 agents. AMD EPYC Venice excels ~Leadership core density (up to 256 Zen 6 cores per socket) for running many agents in parallel, orchestration layers, and high-throughput control-plane tasks. ~Superior performance-per-core and power efficiency ( up to 2.1x higher perf/core and 2.26x better SPECpower vs. NVIDIA Grace in benchmarks). ~Tight integration in Helios: One Venice CPU + multiple MI450 GPUs per node, enabling efficient data feeding to GPUs ("zero-copy"), parallel execution, and full rack utilization for complex agentic loops. Hyperscalers (Meta, Microsoft, Amazon, Google, Softbank) and AI natives (OpenAI, Anthropic...) are adopting high-core EPYC at scale specifically for these agentic demands, as CPUs now handle a larger share of non-model work (orchestration, policy enforcement, tool calls). This complements AMD’s lower-cost GPUs for overall TCO wins. ~Agents often generate 10–100x+ more tokens per task due to iterative reasoning chains, multiple tool calls, verification loops, and long-context orchestration. ~Goldman Sachs forecasts token consumption multiplying 24x by 2030 (to 120 quadrillion tokens/month) largely driven by agentic adoption in consumer and enterprise. ~Enterprise data shows agent-pattern workloads growing at 680% annualized rates, projected to surpass conversational AI in token volume by Q3 2026. ~Daily enterprise agent token consumption is already in the billions, with complex workflows (coding, workflows, analysis) amplifying this dramatically. 4. Competitive Edge: Winning Customers from Anthropic Anthropic’s Claude models (especially Opus/Sonnet) excel in complex reasoning and agentic coding, commanding premium positioning. However, their higher underlying costs (heavier reliance on third-party cloud with margins) limit pricing flexibility compared to OpenAI’s owned Helios capacity. Anthropic is on track to generate $10.9 billion in Q2 revenue. The company expects to achieve its first-ever quarterly adjusted operating profit of $559 million. However, sustaining full-year profitability remains challenging due to immense computing and model training costs The truth is, Anthropic has no choice but to buy as much $AMD chips as possible if they want to compete with OpenAI or get investors attention. This 5% adjusted operating profit to revenue ratio is just pathetic. Current pricing dynamics (2026): OpenAI already undercuts on many tiers ( flagship output tokens significantly cheaper than equivalent Claude Opus). Nano/mini models offer 5–10x advantages for volume work. Anthropic holds edges in long-context flat pricing and certain reasoning quality. OpenAI after Helios Rack Ownership, At $0.0003–$0.0005/M effective costs, OpenAI gains massive headroom to: ~Aggressively discount high-volume agentic tiers or bundles. ~Offer “unlimited” enterprise plans or usage-based models that Anthropic struggles to match without margin erosion. ~Target cost-sensitive, high-throughput agent deployments (dev tools, automation platforms) where token bills explode. Enterprises facing $ millions in monthly agentic bills will migrate to the provider delivering better economics at scale. OpenAI’s combination of strong models (o-series reasoning) + lowest TCO positions it to erode Anthropic’s enterprise share, especially as agentic becomes the dominant token consumer. Cheaper tokens expand the total addressable market dramatically. This feeds the data/model improvement loop, justifying further capex. AMD benefits from proven scale pulling in more customers (Meta, Oracle, Microsfot, Amazon, Softbank, TensorWave, LumaAI ... already aligned on Helios). Conclusion: Dr. Lisa Su has been laser focused on inference economics since at least 2022–2023, repeatedly emphasizing that the real battleground for AI scalability would be TCO, power efficiency (TDP), and ultimately tokens per dollar and per watt not just raw training FLOPS. While many viewed inference as a secondary, commoditized workload, Dr. Su architected AMD’s roadmap around rack-scale systems optimized for high-volume, sustained inference that would dominate as models matured and usage exploded. Helios represents the culmination of that multi-year bet: a fully integrated, open platform designed precisely for the economics of massive token throughput. This deep, strategic partnership with OpenAI starting with the 1GW Helios deployment in H2 2026 and scaling to 6GW, is the embodiment of that shared vision. Both companies foresaw a future where agentic AI models evolve to become extraordinarily token-hungry: autonomous agents executing complex, iterative workflows with planning, tool use, verification loops, and long-context reasoning. These workloads can consume 100x+ more tokens per task than traditional chat or single-turn generation, driving exponential demand as capabilities improve and enterprises deploy them at scale. By owning and optimizing this massive Helios capacity at GW scale, OpenAI achieves inference costs as low as $0.0003–$0.0005 per million tokens. This structural cost advantage allows OpenAI to absorb the coming token explosion profitably, dramatically lower effective pricing for enterprises, and win high-volume agentic workloads from higher-cost competitors like Anthropic. What was once a prohibitive monthly token bill becomes an affordable accelerator for productivity and innovation. The OpenAI-AMD alliance validates Dr. Su’s prescient strategy and turns the Agentic flywheel into reality: Collapsing inference costs → explosive token consumption → richer data and better models → accelerate greater demand. This partnership doesn’t just address today’s economics, it positions both leaders at the center of the infrastructure buildout that will power AI’s next decade. By delivering the lowest inference economics at scale, OpenAI not only solves enterprise bill pain but gains a decisive weapon to win share from higher-cost rivals like Anthropic. And that is why OpenAI and $META will deploy EPYC Dense Rack Not Financial Advice! DYOR! Research Purpose Only!

Mike

84,951 görüntüleme • 1 ay önce

CANCEL Your Weekend Plans and Learn Vibe Coding Today, Start Making $10,000/Month Building Apps for People. $0 in Coding Experience. I made 5 AI Trading Bots & Apps Built in 6 Hours. Each One Worth $3,000-$15,000 to Clients. You Spent $500 on a Bootcamp and Still Can't Deploy a Landing Page. That's not the bootcamp's fault. That's you. People with zero coding skills are building full apps with payments, databases, and authentication using AI. Charging clients $5,000-$10,000 per project. Finishing in one afternoon. You're still Googling "should I learn Python or JavaScript first." This attached video is a goldmine. 6 hours. 5 real apps. From complete beginner to deploying revenue-generating products. One video. Free. Save it. Watch it this weekend. Not next weekend. Today. Now let me break down exactly what's inside and why you can't afford to ignore this. Save this post. You'll hate yourself if you lose it. ↓ Let's talk about why you still can't code... You bought the Udemy course. $12.99. Watched 3 lectures. Got confused. Told yourself you'd continue tomorrow. That was 8 months ago. You bought another course. $49.99. This one had better reviews. Watched the intro. Bookmarked the rest. Never opened it again. You signed up for a bootcamp. $5,000. Dropped out at week 4 because "life got busy." Life didn't get busy. You got scared. Three years. Hundreds of dollars. Multiple courses. Zero apps built. Zero projects deployed. Zero revenue generated. And now someone with zero coding experience is building full apps in hours using AI tools you haven't even tried. You're not falling behind slowly. You're falling behind at full speed. Save this post right now. This is the course that makes every other coding course you bought irrelevant. Follow Himanshu Kumar so you don't miss the breakdown. ↓ What is vibe coding and why should you care? Traditional coding: Learn syntax for 6 months. Build a to-do app. Feel proud. Realize nobody will pay for a to-do app. Give up. Vibe coding: Describe what you want to build. AI builds it. You guide, adjust, deploy. People pay for it. You're not writing code line by line. You're directing an AI agent that writes code for you. Think of it like this: Traditional coding = you're the construction worker. Vibe coding = you're the architect. The architect makes more money. The architect doesn't carry bricks. The architect doesn't need to know how to pour concrete. The architect needs to know what to build and why. That's vibe coding. And while you've been debating whether to learn Python or JavaScript first, people are skipping both and building apps that generate revenue. With zero coding knowledge. This isn't the future. This is right now. Save this post and follow Himanshu Kumar for more vibe coding breakdowns that actually make you money. ↓ What this 6-hour course covers. This isn't some 20-minute tutorial that shows you how to make a button change color. This is 6 hours. 5 complete apps. Real software engineering. Real deployment. Real money-making potential. Here's what you'll build: > Portfolio website - deployed live on Netlify > Full-stack client dashboard - with database and auth > Lead generation app - with API integrations > Thumbnail generator - with payment integration via Stripe > Splinter - a full SaaS product with pricing and marketing Not toy projects. Not "follow along and never use again." Actual apps that people pay for. Built with Gemini 3.1 Pro, Antigravity, Supabase, Next.js, Vite, and more. You know how many people charge $5,000+ to build a single one of these apps for a client? You'll be able to build all 5 by the end of this weekend. You can't afford to scroll past this. Bookmark this post. Follow Himanshu Kumar because I'm breaking down every tool in this stack separately. ↓ The tools you'll master. Gemini 3.1 Pro: Google's most powerful AI model. You'll use it to generate entire codebases. Not snippets. Entire apps. Antigravity: The AI coding environment that makes vibe coding actually work. Agent chat. MCP servers. Voice dictation. It's not VS Code with a chatbot bolted on. It's built from the ground up for AI-first development. Supabase: Your backend. Database. Authentication. All set up in minutes. Not weeks of configuration. Next.js + Vite: Modern frameworks that make your apps fast, scalable, and professional. Stripe: Payment integration. So your apps can actually charge people money. You know, the whole point. Claude Code: Yes, Claude Code is covered too. Because the best developers in 2026 don't use one AI tool. They use all of them. While you're still trying to decide which AI tool is "the best one," smart people are using all of them together and making money from every angle. Stop debating tools. Start using them. Save this post and follow Himanshu Kumar for deep dives into each of these tools. ↓ What you'll actually learn beyond just "building apps." This course doesn't just teach you to copy and paste prompts. You'll learn real software engineering: > Hosting and deployment > Modern software design patterns > Languages and frameworks > Version control and GitHub > Programming with AI agents and agent teams > Database design (SQL vs NoSQL) > Security audits > API integration > Payment processing This is everything a $15,000 bootcamp teaches. In 6 hours. For free. On YouTube. Your friend who spent $15K on a bootcamp is going to be really upset when you build better apps than them after watching one YouTube video this weekend. Don't tell them about this course. Or do. Their reaction will be priceless. This is a $15,000 education for $0. Save this post before it gets buried. Follow Himanshu Kumar for more free resources that make paid courses look like scams. ↓ The guy teaching this actually makes money. Not "makes money selling courses about making money." Actually makes money. Nick built automated businesses with Make . Most notably 1SecondCopy, a content company that hit 7 figures. Seven figures. From automation. He's not teaching theory. He's showing you what real systems that generate real revenue look like. 90% of coding teachers on YouTube have never shipped a product that made $1. They teach coding. They don't use coding to make money. This guy does both. That's why this course is different. You've been learning from people who teach for a living. Start learning from people who build for a living. Save this post. Follow Himanshu Kumar for more content from builders, not lecturers. ↓ Let me tell you what's really happening while you "think about learning to code." Every week that passes, AI coding tools get better. Every week that passes, more people learn vibe coding. Every week that passes, the market gets more competitive. Right now, vibe coding is still early. Not many people know how to do it well. Clients are desperate for someone who can build apps fast. $3,000 for a landing page with payments. $5,000 for a SaaS MVP. $10,000 for a full client dashboard. These are real prices people are charging for apps they built in a single day using the exact tools in this course. But this window won't last forever. In 6 months, everyone will know how to vibe code. In 12 months, it'll be a basic requirement. In 24 months, not knowing this will be like not knowing how to use email in 2010. You're either early or you're irrelevant. Right now you can still be early. But not if you spend this weekend on Netflix. The window is closing. Every weekend you waste is a weekend someone else uses to get ahead of you. Save this post. Follow Himanshu Kumar before this opportunity becomes obvious to everyone. ↓ The 5 apps you'll build and what they're actually worth. App 1: Portfolio Website. What clients pay for this: $500-$2,000. Time to build with vibe coding: 30 minutes. App 2: Client Dashboard. What clients pay for this: $5,000-$15,000. Time to build with vibe coding: 2-3 hours. App 3: Lead Generation Tool. What clients pay for this: $3,000-$8,000. Time to build with vibe coding: 1-2 hours. App 4: Thumbnail Generator with Payments. What clients pay for this: $2,000-$5,000. Or sell it as a SaaS for recurring revenue. Time to build: 1-2 hours. App 5: Splinter (Full SaaS Product). What clients pay for this: $10,000-$25,000. Or launch it yourself for monthly recurring revenue. Time to build: 2-3 hours. Total value of apps you can build after this course: $20,000-$55,000. Total cost of this course: $0. Total time investment: one weekend. You spend more than one weekend deciding which Netflix show to start next. At least this weekend would pay you back. Read those numbers again. Save this post. Follow Himanshu Kumar because I'll be breaking down how to sell each of these apps as a service. ↓ Here's the business model nobody's talking about. Learn vibe coding this weekend. Build 5 apps. Pick the one you're best at. Offer it as a service. "I build professional SaaS dashboards for businesses using AI. Faster than agencies. Fraction of the cost. $5,000 per project." 2 projects per month = $10,000/month. Working maybe 20 hours total. While you're applying for jobs that pay $4,000/month and require 5 years of experience you don't have, someone who watched this course last weekend just landed their second $5,000 client. No degree. No portfolio. No 5 years of experience. Just the ability to build what people need faster than anyone else. That's the entire business model. Learn fast. Build fast. Charge accordingly. Stop applying for jobs. Start creating them. Save this post. Follow Himanshu Kumar for the exact outreach scripts to land your first vibe coding client. ↓ Why you won't watch this course. Because it's 6 hours. "6 hours?? That's too long." You binged an entire season of a show last weekend in 8 hours. You scrolled Twitter for 4 hours yesterday. You spent 3 hours watching YouTube shorts that you don't even remember. But 6 hours to learn a skill that could make you $10,000/month? "I don't have time for that." You have time. You just don't have discipline. And that's the actual reason you're broke. Not the economy. Not the market. Not your circumstances. Your inability to sit down for 6 hours and learn something that changes your life. Everything else is a story you tell yourself to feel better about doing nothing. That's the uncomfortable truth. Save this post so it stares at you every time you open your bookmarks. Follow Himanshu Kumar because I'll keep reminding you until you actually do something. ↓ What happens this weekend determines your next year. Path A: Watch the course Saturday. Build your first app Sunday. Start offering services Monday. Land first client within 2 weeks. $5,000-$10,000/month within 60 days. Path B: Sleep in Saturday. Brunch Sunday. Netflix Sunday night. Monday morning alarm goes off. Back to the same job. Same salary. Same frustration. Same "I'll start next weekend." 52 weekends in a year. How many have you already wasted? Path A costs you one weekend. Path B costs you your entire future. Same video. Same information. Same 6 hours. Two completely different lives. ↓ Full 6-hour course attached. 5 real apps. Real deployment. Real revenue potential. From the guy who built a 7-figure automated business. Not theory. Not motivation. Actual hands-on building. The course is free. The tools are free. The knowledge is right here. The only thing that costs money is your decision to do nothing. And that cost compounds every single day. Follow Himanshu Kumar for more breakdowns that turn free YouTube videos into $10,000/month skill sets. Save this post. Watch the video. Build something this weekend that your Monday self will thank you for. Or don't. And wonder next year why nothing changed.

Himanshu Kumar

39,379 görüntüleme • 3 ay önce

Made $313 → $2,382,780 in 4 Days Using a Claude AI Bot on Polymarket. 26,738 trades. 98% win rate. Full blockchain proof. Every single trade verifiable on-chain. I've made the exact step-by-step guide to build this Claude Polymarket bot from scratch. You've been trading for 3 years. Still red. He gave Claude $313. Woke up rich. Free for 24 hours. To get this Setup guide: 1. Comment "Money" 2. Like and Retweet 3. Follow me Himanshu Kumar (so i can DM you) Full 2-hour video tutorial attached. Every single click and command explained. Beginner to running bot. Now let me break down exactly how this works. Save this post. This is the most important trading breakdown you'll ever read. ↓ Let's start with the number that should make you sick. $313. That's what this wallet started with. Not $50,000. Not $10,000. Not even $1,000. $313. Less than your monthly Netflix + Uber Eats + Spotify combined. 4 months later: $2,382,780.80. That's a 7,942x return. While you spent those same 4 months staring at charts, drawing trendlines, panic selling, revenge trading, and ending the month exactly where you started. Minus the $200 you lost on that "sure thing." Same 4 months. Same market. Same opportunities. He had a bot. You had feelings. Guess who won. Save this post right now. What I'm about to explain is the exact mechanism behind every dollar of that $2.38M. Follow Himanshu Kumar so you don't miss the rest. ↓ How Polymarket actually works and why bots print money on it. Polymarket is a prediction market. Will BTC be higher in 15 minutes? Yes or No. Will the Fed raise rates? Yes or No. You buy shares between $0 and $1. If you're right, your share settles at $1. If you're wrong, it settles at $0. Simple. Now here's where it gets interesting. Polymarket updates its prices SLOWER than the real market moves. When BTC drops 0.6% on Binance, Polymarket still shows old odds for about 2.7 seconds. 2.7 seconds. In those 2.7 seconds, the bot already knows the outcome. It's not predicting. It's not guessing. It's reading information that already exists and trading before Polymarket catches up. That's not trading. That's collecting free money with a 2.7 second head start. And you're over there using a 15-indicator TradingView setup trying to "predict" where BTC goes next. The bot doesn't predict anything. It just reads faster than you. That's the entire edge. Save this post because if you understand this one concept you understand how millionaires are being made on Polymarket right now. Follow Himanshu Kumar for more breakdowns like this. ↓ Let me walk you through one single trade. A new 15-minute BTC contract opens on Polymarket. Odds are 50/50. Fair price. 10 minutes in, BTC drops 0.6% on Binance. Hard, fast move. The real probability of BTC being lower at expiry is now about 78%. Polymarket still shows 54/46. The bot sees this instantly. Binance WebSocket feed. Under 50ms latency. The edge is 24 percentage points. On a binary contract, that's basically free money. Bot calculates position size using Kelly Criterion. Executes via Polymarket's API. Done. Within 2-3 seconds, other participants update the odds. 54/46 moves toward 78/22. Bot either exits for immediate profit or holds to resolution. Either way, the trade was entered with near-certainty of a positive outcome. Now repeat this 200-500 times per day. $313 → $2,382,780 in 4 months. Not magic. Not prediction. Not luck. Industrial-scale exploitation of a market inefficiency that still exists today. And you're still placing one manual trade per day and calling yourself a "trader." This is the mechanism behind every single dollar. Bookmark this post so you can study it again. Follow Himanshu Kumar because I'm breaking down each strategy separately. ↓ There are 4 strategies. Not all Claude bots do the same thing. Strategy 1: Latency Arbitrage. Win rate: 85-98%. What 0x8dxd used. Monitor Binance price feeds. When Polymarket odds lag behind reality by 3-5%, buy the correct side before the market corrects. No forecasting. No model. No sentiment analysis. Pure speed. You're not guessing. You're reading an outcome that has already happened. Strategy 2: Oracle Arbitrage. Win rate: 78-85%. Chainlink oracle price feeds occasionally diverge from Polymarket's implied prices. When they do, the settlement direction is known. Fewer opportunities. Higher certainty when they appear. Strategy 3: News-Driven Trading. Win rate: 60-75%. Claude ingests real-time news. Government filings. Central bank statements. On-chain data. Assesses probability impact before retail traders even finish reading the headline. Lower win rate because interpretation introduces uncertainty. But works on ANY market category, not just crypto. Strategy 4: Market Making. Return: 2-5% per month. Place buy and sell orders on both sides. Capture the spread. No prediction required. Most consistent. Hardest to blow up. Compounds aggressively over time. You didn't even know there were 4 strategies. You thought "trading bot" meant one thing. That's how far behind you are. 4 strategies. 4 different risk profiles. 4 ways to make money while you sleep. Save this post. Follow Himanshu Kumar for the deep dive into each one. ↓ The timeline that should haunt you. December 2025: Bot launches with $313. Nobody notices. January 6, 2026: Wallet hits ~$438,000. 140x in 30 days. 6,615 predictions. 98% win rate. Finbold reports it. Crypto Twitter explodes. March 10, 2026: Head-to-head test. Claude bot: $1,000 → $14,216 in 48 hours. +1,322%. OpenClaw bot: fully liquidated. Same market. Same timeframe. Claude won because of better risk management. OpenClaw died because it overleveraged. March 16, 2026: Someone trains a swarm model on 3 years of NBA data. Result: +$1.49M on Polymarket. April 2026: 0x8dxd final verified balance: $2,382,780.80. 26,738 trades. 4 months. This all happened while you were "waiting for the right time to start." The right time was December 2025. The second best time is right now. But you'll probably wait until it's too late. That's what you always do. Every date on this timeline is a day you could have started but didn't. Save this post. Follow Himanshu Kumar so you at least start today. ↓ Why Claude and not ChatGPT? This isn't opinion. It's data. March 2026 head-to-head: Claude bot: +1,322%. OpenClaw (GPT-based): liquidated. Same prompt. Same market. Same conditions. Researchers found Claude's code included: > More defensive edge cases > More conservative default parameters > Better error handling > More legible code for debugging > Proper Kelly Criterion position sizing > Hard drawdown kill switches ChatGPT's code overleveraged into a losing sequence and couldn't recover. Claude's code sized positions conservatively, stopped trading when drawdown thresholds hit, and survived to compound another day. The difference between +1,322% and liquidation wasn't the strategy. It was the risk management. And Claude writes better risk management than ChatGPT. That's not a debate. That's a $15,216 difference in 48 hours. But sure, keep using ChatGPT because "everyone uses it." Everyone's broke too. Coincidence? Stop using the popular tool. Start using the profitable one. Save this post. Follow Himanshu Kumar for more Claude vs ChatGPT comparisons with real data. ↓ Why humans lose to bots. Every single time. Same strategy. Same market. Same period. Bots: ~$206,000 profit. Humans: ~$100,000 profit. 2x gap. Same strategy. Here's why: 1. Late entries. By the time you identify the lag, verify your reasoning, and click buy, the 2.7 second window is gone. The bot executes in under 100ms. You execute in 30 seconds. The opportunity doesn't exist for 30 seconds. 2. Emotional sizing. You oversize when "confident." Undersize when scared. Exact opposite of Kelly math. The bot sizes based on edge. Every time. No feelings. 3. Fatigue. You make worse decisions at hour 6 than at hour 1. The bot makes the same decision at hour 72 that it made at hour 1. 4. Drawdown psychology. After 3 losses you either panic quit or double down trying to recover. Both destroy capital. The bot has a kill switch. It stops. It doesn't feel anything. You're not competing with other humans anymore. You're competing with machines that don't sleep, don't feel, don't flinch. And you're losing. The data doesn't lie. Humans lose to bots 2x on the same strategy. Save this post. Follow Himanshu Kumar for the complete bot setup that removes you from the equation. ↓ What can go wrong. Because I'm not going to lie to you. Most people who build this bot will NOT 7,942x their money. Some will lose their initial capital. Here's what can kill you: Edge compression. The arbitrage window was 12 seconds in 2024. It's 2.7 seconds now. It's shrinking. At some point it hits zero for retail operators. This is a time-limited opportunity. Not a permanent income stream. Rule changes. Polymarket can change contract mechanics, settlement rules, or API terms overnight. What worked yesterday can lose money tomorrow. Risk management bugs. A 98% win rate strategy with broken position sizing will blow up your account on the one losing trade. The March 2026 experiment proved this. Claude survived. OpenClaw got liquidated. Same strategy. Different risk management. That's why the 2-hour video tutorial walks through every single risk parameter. Because the strategy doesn't kill you. Bad risk management kills you. This is the section most "gurus" delete. I'm keeping it because I'd rather you make money safely than blow up and blame me. Save this post. Follow Himanshu Kumar for honest breakdowns, not hype. ↓ The step-by-step to build your own. Step 1: Set up a Polymarket wallet. Fund with USDC via Polygon network. Start with $100-$300 for testing. Step 2: Generate API credentials. CLOB API key from docs.polymarket .com. Store private key in environment variable. Never hardcode it. Never share it. Step 3: Prompt Claude to build the bot. Use Claude Code for best results. It reads your filesystem, executes code, and iterates on errors autonomously. Step 4: Paper trade for at least one week. Minimum 200 completed trades. Win rate must be above 70% before going live. This step is NOT optional. Step 5: Configure risk management. Max single position: 8% of portfolio. Daily loss limit: -20% with auto halt. Kill switch at -40% drawdown. Telegram alerts on every threshold. Step 6: Go live small. $1-5 per trade. Watch every trade for first week. Compare to paper results. Scale only on evidence. Skip steps 4 and 5 and you will lose your money. That's not a warning. That's a guarantee. This is your complete build guide. Save this post. Follow Himanshu Kumar because I'll be posting the exact Claude prompts for each strategy. ↓ The edge exists right now. Not next month. Not "when you're ready." Right now. The arbitrage window is 2.7 seconds. It was 12 seconds in 2024. It's shrinking every week. Every day you wait, more bots enter the space. The window gets smaller. Your potential returns get smaller. The bots already running have a compounding advantage. They're making money today that they'll use to make more money tomorrow. You're reading about it and telling yourself "I'll look into this next weekend." That's what you said last weekend. And the weekend before that. The best time to start was 6 months ago. The second best time is today. But you already know you're going to bookmark this and never open it again. Prove me wrong. ↓ Full 2-hour video tutorial attached. Every single click. Every command. Every parameter. From zero to running bot. Beginner friendly. Nothing skipped. A similar bot has already earned $2,382,780. Full blockchain proof in the article below. The video is free. The tools are free. The edge still exists. The only thing that costs money is another month of doing nothing while bots eat every opportunity you're too slow to catch. Follow Himanshu Kumar for the complete series covering every automated income stream using Claude. Prediction markets are just the beginning. Save this post. Bookmark it. Screenshot it. Whatever you need to do so you actually watch the video and build the bot instead of just reading about people who did. You Must Follow me Himanshu Kumar, so i can send you DM.

Himanshu Kumar

52,890 görüntüleme • 3 ay önce

Our goal has always been to offer you car care solutions that are both effective and affordable. For KSh 10,000 per year, you can join our membership package, which includes the following services: 1. AFTER GARAGE INSPECTIONS This involves inspecting your car after it has been worked on by a garage to ensure quality work was done and that the reported issues were properly resolved. We also carry out a detailed follow-up to confirm that the parts claimed to have been replaced were indeed changed. Data is collected before and after repairs to ensure accurate and factual findings. 2. DETAILED INSPECTION EVERY FOUR MONTHS Every four months, we conduct a comprehensive inspection of your vehicle, focusing on the engine, transmission, auto-electrical systems, suspension, tyre wear patterns, and more. Early diagnosis helps you take preventive action by addressing issues before they fully develop and become costly repairs. 3. AFTER SERVICE COMPUTERISED DIAGNOSIS Every time you take your car for an oil service, we carry out a computerized diagnostic scan focusing on the engine and gearbox. Some dishonest garages exaggerate fault reports to justify unnecessary repairs and sell parts. At 4Real, our reports are completely independent, as we are not in the business of repairing cars, but rather providing unbiased car care through professional inspections. 4. FREE PRE-PURCHASE INSPECTIONS If you are a member and intend to buy a car, you are entitled to 1 FREE pre-purchase inspection. We also offer additional services such as Pre-Purchase Inspections where we inspect the car you intend to buy and give you a very detailed yet easy to understand report on the car. It helps you decide on whether to buy the car or not. We are very independent on our reports. Other than that we also offer car consultancy. If you are unsure which car to buy, we provide a detailed comparison between your shortlisted options, helping you choose the car that will serve you best. Our comparison report is based on: 1. Initial buying price 2. Cost of maintenance 3. Fuel consumption 4. Safety, performance & comfort 5. Practicality 6. Reliability 7. Resale value over time Car consultancy services costs KSh 1,000, but it is FREE for those under our membership packages. To access our services, contact us on 0729 686 646.

4Real

14,965 görüntüleme • 6 ay önce

What is an Automated Market Maker (AMM)? ************* Notes: The video is attached. Links to the shorts on other platforms are in the second Tweet. Voting on fees using your LP tokens is limited to the 8 biggest LP holders. For auctions, the discount gets you close to 0% but not effectively 0%. The math example couldn’t exist in reality based on G3M. It is just an example to explain the process. ************* Imagine a robot (AMM) that's always ready to help you trade your money (assets) with others on a special online platform (the XRP Ledger's decentralised exchange). This robot doesn’t need to find someone else to take the other side of your trade; it just makes the trade happen using a big pot of money (pool) it manages. How Does it Work? Trading: You can swap one type of money (asset) for another anytime you want, using the robot’s pot of money. The robot uses a special formula to decide the swap rate. Creating a Pool: Anyone can create a new pot of money for two different types of assets if it doesn’t exist yet, or add to an existing one. Rewards for Pool Creators: People who add money to the pot (liquidity providers) get special tokens (LP Tokens) as a thank-you. These tokens can be used to: • Get a share of the money in the pot back, along with some extra (fees collected). • Have a say in changing the robot’s settings, like trading fees. • Bid to get a temporary discount on trading fees. Risks and Rewards: If many people are swapping money and the pot stays balanced, the people who added money to the pot earn some passive income from the fees. But, if the value of the assets changes a lot, they might lose some money. More Technical Bits: Exchange Rate: The robot adjusts the swap rate based on how much each asset has in its pot. If it has a lot of one asset, that asset becomes cheaper to swap. Trading Fees: The robot charges a small fee for each swap, which goes to the people who added money to the pot. Voting on Fees: People with LP Tokens can vote to change the trading fee; the more tokens you have, the more your vote counts. Auction Slot: There’s a special feature where you can bid to get a discount on trading fees for a day. You bid with LP Tokens, and if you win, you (and up to 4 friends) pay no trading fees for 24 hours. LP Tokens: These are special tokens you get for adding money to the pot. They can be traded, used to vote on fees, or redeemed to pull your money out of the pot. Deleting an AMM: If all the money gets pulled out of the pot, the robot (AMM) gets deleted. But, it can be recreated by adding money to the pot again. In a Nutshell: An AMM is like a robot banker that helps people easily swap different types of money using a big shared pot. People who add money to the pot get special tokens and can earn fees from the swaps, but there are some risks if the market changes a lot. They can also vote on settings and bid for fee discounts. If the pot empties, the robot goes away but can be brought back by refilling the pot. Let’s look at an Example: Step 1: Creating a Money Pot with the AMM Robot Alice creates a new money pot (AMM) using the robot. She chooses two types of money: US Dollars (USD) and XRP. She puts in: 1000 USD 10 XRP In this example, we assume an exchange rate of $1 per XRP for easy math. Alice gets special tokens (LP Tokens) from the robot as a thank-you for adding money to the pot. These tokens prove she added money and can be used later to get her money back, plus some extra if the robot earns fees. Step 2: Bob Makes a Swap Bob wants to swap his 100 USD for XRP. He doesn’t have to wait for someone to take his offer; the robot does it instantly using the money in the pot. The robot uses a formula to decide how much XRP Bob gets for his 100 USD, ensuring it's a fair rate based on how much USD and XRP are in the pot. Step 3: Earning Fees The robot charges Bob a small fee, let’s say 1%, for convenience. So, Bob pays 1 USD as a fee, which stays in the pot. Now, the pot has more money than it started with, which is good for Alice because she can earn that extra when she uses her LP Tokens. Step 4: Alice Withdraws Her Money After some time, Alice decides to take her money out of the pot. Thanks to the fees the robot earned from Bob and others, the pot has grown to: 1101 USD 9 XRP Alice uses her LP Tokens to claim her share of the money in the pot. If she puts in 100% of the original money, she gets 100% of what’s in the pot now, including the extra earned from fees. Step 5: Voting and Discounts Alice can also use her LP Tokens to vote on things, like changing the robot’s fee. And, if she wants a discount on fees, she can bid for a special 24-hour discount slot using her LP Tokens. Conclusion In this example, the AMM robot helped Alice earn extra money by providing a convenient way for Bob to swap his USD for XRP. Alice took on some risk by putting her money into the pot, but she earned fees from Bob’s and others’ trades as a reward. Bob enjoyed the convenience of instant, hassle-free trading. And the AMM robot managed it all automatically!

Daniel "CEO of the XRPL" Keller

238,435 görüntüleme • 2 yıl önce

Multiple Indian companies are saying it's really easy to get work in New Zealand Now that I've started looking for these promotional videos by Indian companies, I've found way too many, which is really concerning. Why has National, Labour, and ACT "sold us out" by signing the India-NZ FTA that will make it even easier? It's already way too easy. With the example below, you'll see that nearly anyone can get in. Here's a quick example: "If your age is between 18 and 55 then you can work here" "The cost of this visa is between 18,000 to 20,000 which is $325 New Zealand Dollars" "You can earn from 2 to 3.5 lakh rupees per month [$6,571 NZD p/m]" This will be the last example I post. It was posted yesterday and specifically targets low-skilled jobs that were typically taken by our Pacific neighbors, students, those who can't find full-time employment, etc. Here's the translation to about two thirds of the way through - the rest was repetitive so I didn't include it: TRANSLATION: "So guys New Zealand's seasonal visa has started. If you want to work on New Zealand's seasonal visa for a year, in this video i will guide you step by step how you can get New Zealand's seasonal visa. What are the requirements of the documents? How much is the cost of the visa? What is the process time and what is the age limit? You will get all the details in this video so keep watching the video till the end. So basically, you can do apple picking on seasonal visa in which you can earn from 2 to 3.5 lakh rupees per month [$6,571 NZD p/m] and you can also do your fruit picking job as a Cherry Picker, Grab Picker, Pack House Worker, Orchard Worker, Pruning Worker, Farm Worker, Meat Processing, etc. If your age is between 18 and 55 then you can work here. You can work as warehouse worker, housekeeper, cleaner and farm worker. You can apply even if your education is in 8th or 10th or 12th grade [NZ NCEA Level 1 - NCEA Level 3]. Both male and female candidates can apply for this visa. To apply for New Zealand seasonal visa, first you have to do a job application. Job application is shown on the screen. You can go inside and do job application. If you don't know how to do job application, you can contact me. I will give you all the numbers. We will apply for you and also make a professional CV and cover letter of New Zealand format. This is the first step: - First you have to do job application - After that CV is selected - After that company gives you sponsorship letter - After that you can apply for this visa The cost of this visa is between 18,000 to 20,000 which is $325 New Zealand Dollars and after processing time you can get one or two weeks visa. And friends Indian, Pakistan, Nepali and Bangladesh also can apply for this visa So i am showing you how you can apply for this visa so guys if you want to work on New Zealand's seasonal visa many people are confused about which country they can go to and which country they can't go to I am going to clear that too. This visa is a fixed length of stay, you can stay here for maximum 11 months and in some cases if your employer sponsor you for 1 year, then you can stay here for 1 year.... The processing time of required seasonal visa is 80% in 4 days and sometime in 1 or 2 weeks. Tis is the total process time if your age is between 18 years and 55 years. If you are physically fit and can lift maximum weight from 25 to 30 kgs, you can apply for this visa but you should have an offer letter from New Zealand. Through this letter you can apply for this visa and you will get the visa for only 20,000 rupees. You cannot bring your family with you for this visa you can only apply as an individual and you can work here. So one important thing here is that you can't change your employer or company. You have to work where you get a sponsorship...." Translated using Whisper AI Original Source: Copyright Authority: Fair Dealing

NZ Media World - by Brynn Neilson

21,092 görüntüleme • 27 gün önce

This guy made $260K off one AI agent workflow. The whole thing runs on a virtual focus group of 13 AI personas trained to be his customers. He pastes any ad or sales page in, they critique it, the system rewrites it, and a prediction engine picks the winner before he spends a dollar on traffic. Justin Brooke ❤️‍🔥 came on the pod to walk us through it. Here's what I learned: 1) He built a virtual focus group. 13 AI personas critique your ad in parallel, a copywriter agent rewrites it three ways, a prediction engine picks the winner. 13 cents per run. 2) The accuracy is academically validated. Harvard, Stanford, and the NYT have published studies on this. NYT clocked it at 92% accuracy versus human focus groups. 3) Multiple personas beat one ICP. Every copy book preaches one persona. The math says otherwise. Same room of buyers has men, women, young, old, local, software. The mix is the point. 4) The personas are not prompts. They're 1,400 word dossiers with demographics, pain points, empathy maps, and decision making process. Skip the dossier work and you get garbage. 5) Wash everything before it ships. Every ad, sales page, LinkedIn post, tweet. A top 1% copywriter charges $500 an ad. This is 13 cents. 6) "Embody" beats "pretend" as a prompt verb. Machines hear "pretend" as fake-be-this-thing. They hear "embody" as become it. 7) The copywriter agent formats output like an internal team email. Quoted feedback, brief insights, three rewrites. Way more useful than the default AI report format. 8) Each persona votes yes or no on buying. His Black Friday offer scored 7 yeses out of 13. Did $36,000 in revenue. The nos were the wrong-fit personas anyway. 9) It doubles as a copywriting school. The rewrites sometimes contain bullets better than yours and you just steal them. Justin has 20 years in direct response and openly admits the AI catches him slipping. 10) Where to start: build the personas first. Take a weekend, use Claude deep research, write 5 to 13 real dossiers with empathy maps. The prompt is the easy part. His 2 key takeaways: 1) Prediction before deployment is the next layer of marketing. Just like we all added tracking to our ads, virtual testing before spend will be the new default. 2) The ROI is instant. SEO and content agents pay back in months. This one tells you tomorrow if your ad got better. Justin is doing this at a level most marketers are not. Go follow Justin Brooke ❤️‍🔥. Full video below. (Also available on the Build With AI podcast wherever you get your pods)

Corey Ganim

83,916 görüntüleme • 2 ay önce

1 year ago today, I launched my design agency (Finite Supply) with just a tweet. I had nothing lined up, and it was the first time I’d ever fully worked for myself. I want to start by thanking all my clients who have been such a joy to work with. I specifically want to thank: Fedi, OCEAN, Satoshi Nakamoto Institute, HRF, Opennode, and Bull Bitcoin for taking a chance on me as I was just starting out. Here’s a recap of our first year: - We had 22 clients (all bitcoiners). Wallets, exchanges, mining companies, foundations, an institute, multiple saas companies, a merch company, a bitcoin treasury company, a think tank, a financial institution, and an AI company. - Project types: 15 branding, 10 product design, 7 web design, 3 merch, 4 graphic design, and 2 presentations - 11 clients paid in BTC, 11 clients paid in USD, and 2 companies paid in equity. - I greatly exceeded my 20k/month income goal for all 12 months. - The FiniteSupply .co shop shipped out over 200 hats and dialed in production & shipping operations. Upon reflection, we really excelled at: - Creative Direction (being a seasoned “design mind” for founders and teams with little design expertise) - Branding (creating foundational brand identities and guides for new companies/organizations) - Web design (designing and developing websites) - Fractional product design (partnering with teams to design mobile / web apps) Early on I struggled with: - Saying YES to too much work out of fear of the unknown. - Not delegating enough work out. - Not posting enough work on social media. Some things that have worked for the business: - Posting thoughts on the intersection of design and bitcoin - Posting existing work always leads to more work - Fractional design services have been easy and effective for businesses to accept - Accepting and holding bitcoin has fortified the business bigly Some goals for this year (hold me to these!): - Post more to showcase more work, share design knowledge, and connect with potential clients. - Create even cooler hats & products for the Finite Supply shop. - Increase the percentage of bitcoin payments. - Build a product that leverages ai to boost efficiency for American workers who build real things. Thank you for reading, I hope you’ve enjoyed my annual report. The last year was incredibly blessed and I’m so grateful. I'm so proud of all the work we accomplished. If you’re thinking about starting your own thing, quit your job and do it. If you need design, send me a DM. Let’s connect. Last but not least, Happy Bitcoin Pizza Day! – Skyler

Skyler Designer

44,268 görüntüleme • 1 yıl önce

$AMD $5 Trillion MC Is Inevitable Long Term👑 This thread will focus more on Inference! 2026 EPYC "Venice" $TSM 2nm to save Large GW Scale Inference by 40% more than Prior Turin gen. Context: EPYC Turin achieves ~$0.001 per million tokens for batch inference vs $0.02-$0.12/ million tokens as I wrote the thread below. Venice is going to lower cost down to $0.0005-$0.0006/Million Tokens. OpenAI spent roughly $20B on Inference and Training, where 80-90% of that was for Inference per Analysts. AKA Renting Compute is Expensive AF! In this thread, I want to focus on why most analysts and investors are underestimating the role EPYC "Venice" and future Gen on overall Data center revenue. And $TSM ramping up 2nm supply early is a confirmation that AMD will be a major buyer long term. I will also link the thread the Gap between AMD Analysts & Reality and 2nm Ramp Thread so you have more comprehensive view of what I'm writing here. Before I go into detail this is my 2026 Projection: AI GPUs: $35-$50B EPYC Data Center: $15B-$17B Client Segment: $12-$13B Gaming: $6B Embedded: $4B-$5B Total Revenue $70-$100B Non-GAAP net income $18B-$25B Non-GAAP EPS $10.97-$15.40 Foward P/E 55x-70x= $603-$1,078 AMD's Analysts are projecting $0 Revenue for MI450 and sluggish EPYC Growth. Meaning, all analysts are either full of 💩 or Sexist, you decide! Analysts are also projecting 0% growth on AMD "Secret Weapon" Chip as $MSFT said we are at significant Windows refresh and upgrade cycle. Do you think TSMC would allocate more 2nm supply to $AMD at $0 MI450 revenue and sluggish EPYC? 1. EPYC is going to be the leader in lowest Inference! Current Turin cost saving is 95% vs $NVDA or 98-99% on Inference cost when you factor in renting Inference compute from Amazon Web Services, Microsoft Azure, or $NVDA Neocloud pets. TSMC claimed: 10-15% higher performance at iso-power, 25-30% lower power at iso-speed, and ~15% higher transistor density compared to 3nm. This reduces operational expenses (energy, cooling) while increasing throughput per chip. EPYC Turin achieves ~$0.001 per million tokens for batch inference (via vLLM on models like Llama 3 70B), driven by high core counts and low hardware costs. EPYC Venice offers ~1.7x overall performance and up to 70% more compute capability per core, with up to 256 cores (512 threads). Enhanced vector/AI instructions and open-source firmware (openSIL) optimize for inference workloads. AMD Incorporates AI Engines (now part of AMD's XDNA) for on-chip acceleration, improving efficiency for low-latency and edge inference. This reduces reliance on discrete GPUs, lowering system complexity and TCO. Venice SKUs are projected at $3,000-$15,000 ($5,000 for 256-core flagship), far below NVIDIA Rubin ($50,000-$90,000) or AMD's own MI450 GPUs ($40,000-$50,000). High memory bandwidth (up to 1.6 TB/s) supports efficient batch inference. Venice is designed exactly for Large customers that want to lower Inference Cost and MI450 Helios is for Customers that want Training at lowest TCO, TDP as well as lower Upfront 1GW scale(Full build $35-$40B vs $NVDA $55B-$80B). 2. Real World Example: OpenAI's 2025 inference spend reached ~$20B, escalating to even higher total compute rental (mostly inference) amid token volume growth(from video generating). By 2026, with usage doubling (consistent with industry trends: token demand grows 2-5x YoY), assume OpenAI processes ~1,800 billion million-tokens annually $NVDA Blackwell at $0.02-$0.12 is $36B(most optimized) Rubin is projected to be at $0.01/million tokens or $18B annual Inference Cost vs $AMD Venice $0.0005/million tokens or $0.9B annual Inference Cost => Massive saving for OpenAI or anyone that are paying 80-90% Annual Bill for Inference compute. In short, it is unsustainable to pay this much rent vs owning for all current AI players for the medium to long term. Rubin excels in low-latency decode (if Groq integration from $20B deal in 2027-2028), but Venice dominates batch (80% of inference by 2030). Actual savings depend on deployment scale (OpenAI's 6GW AMD plans), electricity rates, and software maturity. If Rubin only hits $0.03, savings swell to $53.1B vs. $17.1B. 3. Will running Inference on Venice and future Gen slow down response generation in 2026 and beyond? Human perception of "fast enough" for chat, agents, search augmentation, summarization, coding assistance is roughly Meaning, EPYC may generate $100B a year on data center revenue, Hence $MSFT $AMZN $META $GOOGL OpenAI xAI and 42+ Countries are leaning AMD for Inference, because the cost saving is MASSIVE! 4. Regular users (you, me, people using ChatGPT, Claude, Gemini, Grok, Perplexity...) are extremely unlikely to notice any slowdown and in many cases might even experience slightly faster or more consistent response times if the industry heavily shifts toward AMD EPYC for inference. What actually happens when companies save massively on inference? When OpenAI , Anthropic , Gemini , Grok Meta .... save billions on the batch/enterprise/RAG layer using EPYC Venice, they typically do one or more of these things with the savings, none of which make your chat slower but enhancing their bottom line(Profit) ~Keep prices the same → make more profit ~Lower subscription prices / increase free tier limits ~Train bigger & better models more frequently ~Offer longer context windows ~Add more reasoning steps / tool calls / agents per query ~Improve multimodal capabilities ~Build more data centers / reduce throttling during peaks In practice the consumer experience usually gets better, not worse, when inference becomes dramatically cheaper. Prime example is $META leaning AMD heavily or currently AMD largest customer. or Grok 2 to Grok 3 heavily used AMD for Inference saving. And most Grok Users reported Groke responses snappier, not slower. 5. What does this mean for potential Revenue? Noted that TSMC is massively ramping 2nm supply for $AMD both MI450 and EPYC. EPYC Conservative projection: FY2025: $10.5B(best Est) FY2026: $16B FY2027: $29B FY2028: $49B FY2029: $75B FY2030: $100B Large customers: $META OpenAI $MSFT $AMZN $GOOGL xAI (Apple?) Smaller customer: $DELL $HPE $SMCI and 42+ other countries. The roadmap to $5 Trillion is very much inevitable as Inference Cost from Renting or owning $NVDA are too high, but $NVDA will still dominate Training market share, where MI families are likely to take 15-20% market share, but the TAM is also expanding Rapidly. Most Institutions are projecting $2-$3Trillion TAM by 2030. $NVDA said $4 Trillion. Dr. Lisa Su said $1 Trillion+ by 2030. So you decide on how much TAM. If you enjoy this kind of analysis, Slap the Like/Repost and Bookmark to please the X Algo as it is Free.99! If you want to support my work further, consider subscribe to see more in-depth analysis! Alright, that is it. Not Financial Advice!

Mike

102,223 görüntüleme • 6 ay önce

CANCEL Your Weekend Plans, and Learn Claude Code Today. $5,000/month. $10,000/month. $20,000/month. People are building entire apps and charging clients thousands using Claude Code. You're still Googling 'how to center a div.' While you're binge-watching a show you won't remember next week, a 19 year old with zero coding experience just built a $5,000 SaaS product in one afternoon using the tool I'm about to break down. Same laptop. Same internet. Same 24 hours. He has Claude Code. You have Netflix. That's the only difference. This YouTube video is a goldmine. Full Claude Code tutorial. Beginner to pro. Every feature. Every setup step. Every best practice. Zero prior knowledge needed. Save it. Watch it tonight. Not tomorrow. Tonight. Save this post. This is your complete Claude Code roadmap. Lose it and you lose the next 12 months of income. Follow Himanshu Kumar so you don't miss the breakdowns for each feature. ↓ 1. Understand What Claude Code Actually Is. You think Claude Code is just another chatbot. It's not. And that misunderstanding is why you're broke. ChatGPT gives you text. Claude Code gives you software. It runs in your terminal. It reads your entire codebase. It writes files directly to your project. It runs commands on your machine. It debugs errors autonomously. It builds features end to end. You're not chatting. You're deploying a developer. One that works 24/7. Never asks for a raise. Never calls in sick. Never pushes broken code at 5 PM on a Friday. People are charging clients $5,000-$10,000 for apps they built with Claude Code in 3 hours. And you didn't even know this tool existed because you're still asking ChatGPT to write you a to-do list. The gap between you and people making money with AI isn't intelligence. It's awareness. Now you're aware. Save this post. Follow Himanshu Kumar for the complete breakdown of every Claude Code feature. ↓ 2. Set Up Claude Code Properly. Most people quit here. "It's too complicated." "I don't know terminal." "I'll set it up later." Later never comes. And "complicated" means "I watched for 30 seconds and gave up." The setup takes 10 minutes. Install Node.js. Install Claude Code via npm. Authenticate your account. Open your terminal. Done. 10 minutes. You spent longer this morning deciding what to have for breakfast. The video walks through every single click. Every command. Every screen. Assuming you know absolutely nothing. If you can download an app on your phone, you can set up Claude Code. It's the same level of difficulty. But you'll still tell yourself it's "too technical" because that excuse is more comfortable than admitting you're just scared to try something new. This is the setup that everything else builds on. Skip it and nothing works. ↓ 3. Use the Desktop App. You don't even need to live in the terminal if you don't want to. Claude Code has a desktop app. Clean interface. Visual feedback. Everything you need without touching command line. But here's the thing most people don't know: The desktop app isn't just a pretty wrapper. It lets you manage projects visually. See file changes in real time. Switch between projects instantly. The people making money with Claude Code use the desktop app for client projects because it's faster to manage multiple builds simultaneously. You're still opening 14 browser tabs to organize one project. They open one app and everything's there. Efficiency isn't a personality trait. It's a tool choice. Save this post. Follow Himanshu Kumar for the desktop app workflow that handles 5 client projects at once. ↓ 4. Install the Right Dependencies. This is where beginners silently fail and blame the tool. Claude Code needs certain dependencies installed to work properly. Miss one and everything breaks. Then you go on Twitter and say "Claude Code doesn't work." It works fine. You just didn't read the setup guide. The video covers every dependency you need. What to install. How to install it. How to verify it's working. No guessing. No Stack Overflow rabbit holes at midnight. No "why isn't this working" for 3 hours. Watch the dependency section once. Follow every step. Never deal with setup issues again. You spent more time last week troubleshooting a printer than this takes. ↓ 5. Work Inside Your Code Editor. Claude Code integrates directly with your code editor. VS Code. Cursor. Whatever you use. It's not a separate window you alt-tab between. It's right there. In your workflow. You type a request. Claude writes the code. The code appears in your editor. You review it. Accept it. Done. No copy pasting between windows. No reformatting code that got mangled in transit. No "which version was the right one." It's like pair programming with someone who never gets distracted, never argues about naming conventions, and actually writes code that works on the first try. Your current coding process is: Google the problem, read 5 answers on Stack Overflow, copy the wrong one, debug for an hour, find the right one, paste it in, break something else, repeat. Claude Code's process is: describe what you want, get working code, move on with your life. Same hour. One method produces working software. The other produces frustration and a browser history full of Stack Overflow tabs. Stop coding the hard way. Save this post. Follow Himanshu Kumar for code editor setup guides and integration tips. ↓ 6. Master Basic Usage. Most people learn 5% of a tool and say they "know" it. You "know" Photoshop because you can crop an image. You "know" Excel because you can sum a column. You "know" Claude Code because you asked it one question. Basic usage means: How to give Claude Code context about your project. How to ask for changes to existing code. How to generate new files and features. How to review what Claude produces. How to iterate when the output isn't perfect. These basics are the foundation of everything. Skip them and every advanced feature feels confusing. Master them and every advanced feature feels obvious. The video breaks down each one with real examples. Not theory. Actual usage on actual projects. You've been using AI tools at 5% capacity and wondering why your results are 5% of what others get. Save this post. Follow Himanshu Kumar for daily Claude Code usage tips. ↓ 7. Learn Every Command. Claude Code has commands that most users never discover. Because most users type one message and expect magic. That's not how professionals use it. Professionals use specific commands that tell Claude Code exactly what to do, how to do it, and what constraints to follow. The difference between a beginner and someone making $10K/month with Claude Code is knowing which command to use and when. The video walks through every single one. Not just what they do. But when to use each one. And why one command is better than another for specific situations. You've been using Claude Code like a hammer. These commands turn it into a full toolbox. Stop treating a power tool like a blunt instrument. Save this post. Follow Himanshu Kumar for the command cheat sheet I use daily. ↓ 8. Understand Modes and Shortcuts. Speed matters. The person who builds an app in 2 hours charges $5,000. The person who builds the same app in 2 days charges $2,000. Same app. Same quality. Different speed. Different income. Claude Code has modes that change how it operates. And shortcuts that cut your workflow time in half. Most people don't know either exists. They use Claude Code in default mode for everything. Like driving a car in first gear on the highway. Technically it works. But everyone is passing you. The video shows you every mode. Every shortcut. Every time-saving trick that separates the people charging $2,000 per project from the people charging $10,000. Speed is money. Literally. Save this post. Follow Himanshu Kumar for the shortcuts that cut my build time by 60%. ↓ 9. Write a Proper Planning Prompt. This is the section that separates amateurs from professionals. And it's the section most people skip. A planning prompt tells Claude Code what you're building before you start building it. Architecture. File structure. Technologies. Features. Constraints. Edge cases. Without a planning prompt, Claude Code guesses. And guessing produces garbage. With a planning prompt, Claude Code executes a clear plan. And clear plans produce working software. The video shows you exactly how to write a planning prompt that makes Claude Code produce professional-grade output on the first try. "But I just want to start coding." That's why your code breaks every time. That's why you restart projects 4 times. That's why nothing you build ever gets finished. Because you refuse to plan. A 5-minute planning prompt saves you 5 hours of debugging. But you'd rather skip the 5 minutes and suffer through the 5 hours because patience isn't your thing. And that's exactly why you're not making money. Planning is the most underpaid skill in coding. And the most overpaid when you master it. Save this post. Follow Himanshu Kumar for the planning prompt templates I use for every client project. ↓ 10. Choose the Right Model. Claude Code lets you select different AI models. Not all models are the same. Not all tasks need the same model. Using the most powerful model for a simple task wastes credits. Using a basic model for a complex task wastes time. The video explains: Which model to use for quick fixes. Which model to use for complex architecture. Which model to use for debugging. Which model to use for code generation. Most people pick one model and use it for everything. That's like using a sledgehammer to hang a picture frame. Model selection is strategy. And strategy is money. The people making $10K/month with Claude Code are strategic about every credit they spend. You're burning through credits because you use the most expensive model to write a hello world. ↓ 11. Use Git and Version Control. If you're not using version control, you're one mistake away from losing everything. Claude Code integrates with Git. Every change tracked. Every version saved. Every mistake reversible. Without Git: Claude makes a change. It breaks something. You can't undo it. You start over. 3 hours wasted. With Git: Claude makes a change. It breaks something. You roll back in 5 seconds. Keep working. Version control isn't optional. It's insurance. And the people not using it are the same people who say "I lost my entire project" like it's something that just happens. It doesn't just happen. It happens because you didn't set up Git. The video walks through the entire Git integration. Save this post. Follow Himanshu Kumar for the Git workflow that's saved every project I've ever built. ↓ 12. Set Up Claude.MD and Memory. This is the feature that makes Claude Code feel like a real team member instead of a stranger you explain everything to every time. ClaudeMD is a memory file. You tell Claude Code about your project once. It remembers forever. Coding style preferences. Project architecture decisions. Technology stack. File naming conventions. Business logic rules. Without ClaudeMD: Every new conversation starts from zero. You explain the same things repeatedly. Output is inconsistent. With ClaudeMD: Claude knows your project. Claude follows your rules. Claude produces consistent, professional code. The difference between a sloppy freelancer and a reliable agency is consistency. Claude. MD gives you consistency without the agency overhead. Most people don't set this up and wonder why Claude Code gives different answers every time. ↓ 13. Automate with Tasks. This is where Claude Code stops being a tool and starts being an employee. Tasks let you define repeating workflows. "Every time I push code, run tests." "Every time I create a new file, add boilerplate." "Every time I start a session, check for errors." Automated. Hands-free. Consistent. You're doing these things manually every single day. The same checks. The same steps. The same routine. Tasks do them automatically. So you can focus on the work that actually makes money. Every manual task you automate is time you get back. And time is the only thing you can never make more of. Save this post. Follow Himanshu Kumar for the task automation templates that run my entire workflow. ↓ 14. Explore Features Most People Never Touch. The video covers features that 95% of Claude Code users don't know exist. Because they watched a 3-minute TikTok about Claude Code and think they're experts now. They're not. They're using 5% of a tool that can do everything. The full tutorial goes deep into features that most tutorials skip because they're "too advanced." They're not too advanced. They're too valuable for lazy creators to bother explaining. This video explains all of them. Clearly. For beginners. The 5% of features you don't know about are the 5% that make people rich. ↓ Let's zoom out. I just broke down 14 sections of Claude Code. Setup and installation. Desktop app. Dependencies. Code editor integration. Basic usage. Commands. Modes and shortcuts. Planning prompts. Model selection. Git and version control. Memory and Claude. MD. Tasks and automation. Advanced features. All in one video. All free. All beginner friendly. The person who masters even half of these in the next 2 weeks will be in the top 1% of Claude Code users. The top 1% of Claude Code users are the ones charging $5,000-$10,000 per project and building them in a single afternoon. Everyone else is asking ChatGPT to fix their resume. Same tools. Same access. Completely different outcomes. Because one person treats AI like a toy. And the other treats it like a business. ↓ Here's the hard truth nobody wants to hear. You don't have a talent problem. You don't have an intelligence problem. You don't have a resources problem. You have an action problem. Everything I just listed has a free tutorial right here in the attached video. 33 minutes. That's it. 33 minutes to learn the tool that people are using to build $5,000-$20,000/month businesses. You spent more time today scrolling Twitter than it takes to watch this video. You spent more time this week watching Netflix than it takes to master Claude Code basics. You spent more time this month doing nothing than it would take to completely change your income. The information is free. The tool is accessible. The opportunity is here. The only thing missing is you caring enough to start. ↓ CANCEL your plans this week. This isn't optional anymore. The people learning Claude Code right now will be building apps for the people who didn't learn it. That's not a prediction. That's already happening. Companies are replacing $150/hour developers with one person and Claude Code. If you code: learn Claude Code or become half as valuable by next year. If you don't code: learn Claude Code or miss the biggest opportunity to start earning from tech without a CS degree. There's no path forward that doesn't include AI coding tools. None. You have one window. Right now. This week. ↓ Here's your action plan for the next 7 days: Day 1: Watch the full video. Install Claude Code. Set up dependencies. Day 2: Learn basic usage. Try 5 different commands. Day 3: Write your first planning prompt. Build a small project. Day 4: Set up Claude. MD. Configure your memory file. Day 5: Master modes and shortcuts. Build a second project faster. Day 6: Set up Git integration. Automate with tasks. Day 7: Build something real. A tool, an app, a website. Ship it. 7 days. One tool. One completely different skill set. One completely different income potential. Or 7 more days of scrolling Twitter watching other people build things while you "plan to start." Your call. ↓ This is the most important video you'll watch this year. 33 minutes. Complete Claude Code mastery. From zero to building real projects. Save this post. Come back to it every single day this week. Check off each section as you complete it. Follow Himanshu Kumar for daily Claude Code breakdowns, advanced tutorials, and the exact workflows that are turning beginners into $10K/month builders. The only thing between you and $10K/month with Claude Code is this video and 7 days. Don't waste them. You Must Follow me Himanshu Kumar, so i can send you DM.

Himanshu Kumar

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