Video yükleniyor...

Video Yüklenemedi

Ana Sayfaya Dön

Easter loading… but the data is already here. Start your weekend early with #GagaWeekend: UGX 6,000 4.5GB + 20 MTN mins UGX 8,000 6GB + 20 MTN mins UGX 10,000 8GB + 20 MTN mins Dial *100*0# or use MyMTN App.

mtnug's profile picture

MTN Uganda

859,948 subscribers

14,647 görüntüleme • 6 ay önce •via X (Twitter)

#GagaWeekend
LIVE

Anya Rossi• Live Now

Private livecam show

0 Yorum

Yorum bulunmuyor

Orijinal gönderinin yorumları burada görünecek

Benzer Videolar

New week. Fresh energy. Choose #Gaga4Dayzzzz and stay online when it matters most: 8GB + 20 MTN mins UGX 10,000 5GB + 20 MTN mins UGX 7,000 Valid till Thursday 6AM. Dial *100*0# or use MyMTN App and power through your week.
0:18

New week. Fresh energy. Choose #Gaga4Dayzzzz and stay online when it matters most: 8GB + 20 MTN mins UGX 10,000 5GB + 20 MTN mins UGX 7,000 Valid till Thursday 6AM. Dial *100*0# or use MyMTN App and power through your week.

MTN Uganda

12,677 görüntüleme • 7 ay önce

Get more for less with the SMARTA Bundle. 30GB data, 400 mins to call other networks, and FREE Airtel-to-Airtel calls for just KES 1,000! Plus, enjoy 100% cashback ukitransact on Airtel Money. Dial *544# or Use MyAirtel App to subscribe. #SmartaWithData
0:10

Get more for less with the SMARTA Bundle. 30GB data, 400 mins to call other networks, and FREE Airtel-to-Airtel calls for just KES 1,000! Plus, enjoy 100% cashback ukitransact on Airtel Money. Dial *544# or Use MyAirtel App to subscribe. #SmartaWithData

Airtel Kenya

1,534,184 görüntüleme • 1 yıl önce

The product you saved today may be saturated by the time you finally decide to start. Your advantage is speed. Choose an ecommerce affiliate product, upload one product image to Vmake Labs, and immediately turn it into ready-to-post UGC, AI hook, or Brainrot videos. Publish with your affiliate link while people are still interested. Track which content drives sales and scale the winners. Your first 20 real tests can get you closer to a profitable side hustle than another 20 tutorials. Download the Vmake Labs app: Or use it on the web:
0:10

The product you saved today may be saturated by the time you finally decide to start. Your advantage is speed. Choose an ecommerce affiliate product, upload one product image to Vmake Labs, and immediately turn it into ready-to-post UGC, AI hook, or Brainrot videos. Publish with your affiliate link while people are still interested. Track which content drives sales and scale the winners. Your first 20 real tests can get you closer to a profitable side hustle than another 20 tutorials. Download the Vmake Labs app: Or use it on the web:

Grace AI

150,238 görüntüleme • 2 ay önce

AYO 😂 For everybody who can’t make rice without turning it into mashed potatoes, burnt gravel, or some wet-ass porridge… THIS FOR YOU. And fellas, if you tryna cook for your lady but don’t know how to make rice… SAVE THIS POST before you embarrass yourself 😭 🍚 1 cup rice = 1¾ cups water. THAT’S THE CHEAT CODE. Wash the damn rice. Fry some REAL garlic + scallions in a lil oil. Throw the rice in, ADD SALT TO TASTE, and fry it on high for 1–2 mins. And NO, you don’t need no garlic powder 😂 We already fried the damn garlic. Pay attention. Add your water. Let it BOIL. Soon as it boils: LID ON 🔒 Heat ALL THE WAY LOW. 20 mins. Turn the fire OFF. NOW DON’T TOUCH THAT DAMN LID. 😭 Let it sit another 10 mins. Open it. Fluff it. BOOM. Perfect rice. 🍚🔥 Now go tell your girl somebody’s grandma taught you how to cook. 😂
0:07

AYO 😂 For everybody who can’t make rice without turning it into mashed potatoes, burnt gravel, or some wet-ass porridge… THIS FOR YOU. And fellas, if you tryna cook for your lady but don’t know how to make rice… SAVE THIS POST before you embarrass yourself 😭 🍚 1 cup rice = 1¾ cups water. THAT’S THE CHEAT CODE. Wash the damn rice. Fry some REAL garlic + scallions in a lil oil. Throw the rice in, ADD SALT TO TASTE, and fry it on high for 1–2 mins. And NO, you don’t need no garlic powder 😂 We already fried the damn garlic. Pay attention. Add your water. Let it BOIL. Soon as it boils: LID ON 🔒 Heat ALL THE WAY LOW. 20 mins. Turn the fire OFF. NOW DON’T TOUCH THAT DAMN LID. 😭 Let it sit another 10 mins. Open it. Fluff it. BOOM. Perfect rice. 🍚🔥 Now go tell your girl somebody’s grandma taught you how to cook. 😂

𝕵𝖆𝖞𝖈𝖊𝖊 𝕲𝖚𝖜𝖔𝖕

171,674 görüntüleme • 29 gün önce

Weather trading Clawdbots making thousands $ on Polymarket by simple arbitrage. Scanning weather markets every 2 mins and comparing data to NOAA forecast for location/date If they see undervalued temperature bucket ( Run your clawdbot in 5 simple steps: • install clawdbot on mac/pc using oneliner code • connect clawdbot with ChatGPT 5.2 & TG bot • create Simmer SDK account & fund wallet • install simmer { weather trader } skills • send your clawdbot right { configuration } > Weather clawdbot configuration: • entry threshold: 0.45¢ • max position: $5.00 • locations: NYC, Chicago, Seattle, Atlanta, Dallas • max trades/run: 5 • safeguards: Enabled • trend detection: Enabled • scan run: every 2 minutes Start testing with small sum $2-5 to calibrate your Clawdbot and give it data for analysis. Scale it when you see $20-50 of consistent revenue for several days. Use my detailed article to run you first weather clawdbot.
0:10

Weather trading Clawdbots making thousands $ on Polymarket by simple arbitrage. Scanning weather markets every 2 mins and comparing data to NOAA forecast for location/date If they see undervalued temperature bucket ( Run your clawdbot in 5 simple steps: • install clawdbot on mac/pc using oneliner code • connect clawdbot with ChatGPT 5.2 & TG bot • create Simmer SDK account & fund wallet • install simmer { weather trader } skills • send your clawdbot right { configuration } > Weather clawdbot configuration: • entry threshold: 0.45¢ • max position: $5.00 • locations: NYC, Chicago, Seattle, Atlanta, Dallas • max trades/run: 5 • safeguards: Enabled • trend detection: Enabled • scan run: every 2 minutes Start testing with small sum $2-5 to calibrate your Clawdbot and give it data for analysis. Scale it when you see $20-50 of consistent revenue for several days. Use my detailed article to run you first weather clawdbot.

Movez

1,409,398 görüntüleme • 7 ay önce

Run Gemma 4 26B MoE on 8GB VRAM with 250k context at 20+ tokens/sec If you own any 8GB VRAM graphics card, stop what you are doing. Local AI just had its absolute "Holy Shit" moment for budget hardware. Yesterday, I benchmarked Unsloth Gemma 4 12B Q4_K_XL on an 8GB card. The community went wild but immediately demanded more: "Can we run a 25B+ model on budget GPUs?" Today, I’m delivering exactly that. I am running a massive 26B parameter Mixture of Experts (MoE) model locally on a standard 8GB VRAM setup with 250k full native context!. If you own an RTX 3060, 3070, 4060, or any budget GPU with 8GB of VRAM, the local AI paradigm has completely changed. The performance metrics are astonishing: - 20 tokens/sec flat decode throughput. - Stable, flat decode speed even with massive prompts. - I threw a 60k token prompt at it, and it still clocked in at 20 TPS without dropping a single frame. # What about prefill? Yes, Time To First Token (TTFT) is slightly high when swallowing massive contexts. But with a solid 200 tokens/sec prefill speed, the wait is barely noticeable and highly usable. And this is running completely without Multi Token Prediction (MTP) active. How is this possible? It’s the magic of Google's new QAT (Quantization Aware Training) quants for Gemma 4. The model weight file (unsloth gemma-4-26B-A4B-it-qat-UD-Q4_K_XL.gguf) is only 13.2 GB, making it the ultimate local powerhouse. # The Test Setup: CPU: Intel Core i7 RAM: 16GB System RAM GPU: NVIDIA GeForce RTX 4060 Laptop GPU (8GB VRAM) # The Secret Sauce (The -cmoe Flag) To make this work properly on any 8GB card, you must use the -cmoe (CPU MoE) flag in llama.cpp. This flag isolates the heavy MoE expert weights directly to system memory (CPU/RAM) while letting your GPU focus strictly on the Attention layers and the KV Cache. It prevents VRAM spillage and holds the throughput rock solid. # The flags: -m "gemma-4-26B-A4B-it-qat-UD-Q4_K_XL.gguf" -cmoe -c 248000 -v Once running, just open the UI on localhost and toggle the new reasoning lightbulb icon in the text input box to watch the model perform multi step thinking. Are you still running smaller models, or are you ready to scale up your budget local setups? Let's discuss in the replies
0:19

Run Gemma 4 26B MoE on 8GB VRAM with 250k context at 20+ tokens/sec If you own any 8GB VRAM graphics card, stop what you are doing. Local AI just had its absolute "Holy Shit" moment for budget hardware. Yesterday, I benchmarked Unsloth Gemma 4 12B Q4_K_XL on an 8GB card. The community went wild but immediately demanded more: "Can we run a 25B+ model on budget GPUs?" Today, I’m delivering exactly that. I am running a massive 26B parameter Mixture of Experts (MoE) model locally on a standard 8GB VRAM setup with 250k full native context!. If you own an RTX 3060, 3070, 4060, or any budget GPU with 8GB of VRAM, the local AI paradigm has completely changed. The performance metrics are astonishing: - 20 tokens/sec flat decode throughput. - Stable, flat decode speed even with massive prompts. - I threw a 60k token prompt at it, and it still clocked in at 20 TPS without dropping a single frame. # What about prefill? Yes, Time To First Token (TTFT) is slightly high when swallowing massive contexts. But with a solid 200 tokens/sec prefill speed, the wait is barely noticeable and highly usable. And this is running completely without Multi Token Prediction (MTP) active. How is this possible? It’s the magic of Google's new QAT (Quantization Aware Training) quants for Gemma 4. The model weight file (unsloth gemma-4-26B-A4B-it-qat-UD-Q4_K_XL.gguf) is only 13.2 GB, making it the ultimate local powerhouse. # The Test Setup: CPU: Intel Core i7 RAM: 16GB System RAM GPU: NVIDIA GeForce RTX 4060 Laptop GPU (8GB VRAM) # The Secret Sauce (The -cmoe Flag) To make this work properly on any 8GB card, you must use the -cmoe (CPU MoE) flag in llama.cpp. This flag isolates the heavy MoE expert weights directly to system memory (CPU/RAM) while letting your GPU focus strictly on the Attention layers and the KV Cache. It prevents VRAM spillage and holds the throughput rock solid. # The flags: -m "gemma-4-26B-A4B-it-qat-UD-Q4_K_XL.gguf" -cmoe -c 248000 -v Once running, just open the UI on localhost and toggle the new reasoning lightbulb icon in the text input box to watch the model perform multi step thinking. Are you still running smaller models, or are you ready to scale up your budget local setups? Let's discuss in the replies

Alok

292,770 görüntüleme • 4 ay önce

Right now, you may not have access to models like GPT‑5.6 Sol, GPT‑4.6 Terra, GPT‑5.6 Luna, Claude Mythos 5, or Claude Fable 5. But you can run something surprisingly powerful today, locally, and completely free. in the next 10 mins on your 8 GB VRAM gaming laptop. Gemma 4 26B A4B QAT (MoE) delivers strong performance on a standard 8 GB VRAM GPU using Ollama, with no API, no usage limits, and no external dependencies. Out of the box, it reaches around 20 tokens per second without any optimizations. Only one command in your terminal: Ollama run gemma4:26b This means: Full offline capability (privacy by default) Zero recurring cost Competitive performance for many real world tasks Fast enough for interactive use on cheap consumer hardware If you're waiting for cutting edge cloud models, you're missing what is already practical today: a capable, local LLM that runs entirely on your own machine.
0:19

Right now, you may not have access to models like GPT‑5.6 Sol, GPT‑4.6 Terra, GPT‑5.6 Luna, Claude Mythos 5, or Claude Fable 5. But you can run something surprisingly powerful today, locally, and completely free. in the next 10 mins on your 8 GB VRAM gaming laptop. Gemma 4 26B A4B QAT (MoE) delivers strong performance on a standard 8 GB VRAM GPU using Ollama, with no API, no usage limits, and no external dependencies. Out of the box, it reaches around 20 tokens per second without any optimizations. Only one command in your terminal: Ollama run gemma4:26b This means: Full offline capability (privacy by default) Zero recurring cost Competitive performance for many real world tasks Fast enough for interactive use on cheap consumer hardware If you're waiting for cutting edge cloud models, you're missing what is already practical today: a capable, local LLM that runs entirely on your own machine.

Alok

65,387 görüntüleme • 3 ay önce

Consent✅ - this is a beauty 🤓 Elite runner Crampy, aching lateral knee pain - onset at around 20-30 mins Seen multiple clinicians - had numerous injections including ITB plus extensive rehabilitation - refractory Almost 'claudicant' in nature - settles quickly on cessation of exercise - spreads both proximal & distal to lateral joint line No spinal symptoms & LSp assessment clear No lateral compartment pathology eg meniscal tear Had popliteus tendinopathy on US, but minimal response to my initial diagnostic injection POCUS video - The inferolateral genicular neurovascular bundle ('pepper pot' structure) is seen compressed under the distal ITB on active knee flexion : terminal extension Patient localises pain in this area with probe pressure Injection - hydrodissection (CSI, LA) - fluid seen separating plane just superficial to NV bundle 100% pain relief on extended treadmill test beyond 45 mins 👍 I wonder how many recalcitrant 'ITB' cases are actually neurovascular in aetiology? 🧐 Plan - considering angiography, MR neurography & possible distal ITB release at Gerdy's tubercle if not responsive to injection
0:11

Consent✅ - this is a beauty 🤓 Elite runner Crampy, aching lateral knee pain - onset at around 20-30 mins Seen multiple clinicians - had numerous injections including ITB plus extensive rehabilitation - refractory Almost 'claudicant' in nature - settles quickly on cessation of exercise - spreads both proximal & distal to lateral joint line No spinal symptoms & LSp assessment clear No lateral compartment pathology eg meniscal tear Had popliteus tendinopathy on US, but minimal response to my initial diagnostic injection POCUS video - The inferolateral genicular neurovascular bundle ('pepper pot' structure) is seen compressed under the distal ITB on active knee flexion : terminal extension Patient localises pain in this area with probe pressure Injection - hydrodissection (CSI, LA) - fluid seen separating plane just superficial to NV bundle 100% pain relief on extended treadmill test beyond 45 mins 👍 I wonder how many recalcitrant 'ITB' cases are actually neurovascular in aetiology? 🧐 Plan - considering angiography, MR neurography & possible distal ITB release at Gerdy's tubercle if not responsive to injection

James Noake

49,777 görüntüleme • 9 ay önce

you're paying $20/mo for something your $500 GPU can already do. Gemma 4 26B A4B QAT MoE + Hermes Agent running on a single RTX 4060 (8GB VRAM). Built a vision capable, 100% free, 100% local, private AI assistant that lives in my Chrome browser. No API keys. No cloud. No subscriptions. 100% vibe coded. 0% handholding. It has full context of whatever's on my screen can answer questions, summarize pages, extract data, and see images. Same local model handles everything, no external calls, ever. keep reading for the model and hermes agent tips i learnt while building this locally. Here's the exact setup for anyone running local LLMs on 6-8 GB VRAM: llama.cpp server flags (on my NVIDIA RTX 4060 8gb VRAM): -m gemma-4-26B-A4B-it-qat-UD-Q4_K_XL.gguf --cache-type-k q8_0 --cache-type-v q8_0 -c 150000 --port 8080 Throughput with quantization: Prefill: 200-250 tokens/sec Decode: 20-25 tokens/sec reduce context if oom on 6 gb vram card. Key learnings: - Quantize KV cache to q8 for faster prefill/decode. Prefill goes from 100-150 (unquantized) to 200-250 tok/s (q8). - But watch out, once actual context grows past ~50k tokens on high entropy workloads, q8 KV quantization can cause hallucinations. Low entropy workloads are mostly unaffected. If you see it happening, drop the quantization. This is common across all local models. - In Hermes Agent settings -> Memory & Context, bump compression threshold from default 0.5 to 0.7. Default triggers way too frequent context compression and eats time. Up next: add persistent memory, web search, tool calling, streaming output and whatever you suggest. Running a 26B MoE with vision + 150k context window on 8GB VRAM would've sounded impossible 6 months ago. Works the same on the NVIDIA RTX 3060 Ti, 3070, 4060 Ti, 5060, 2080, or any 8GB card. VRAM is the only requirement. Local AI agents are closer than people think. You just need to know where the knobs are. Model's Unsloth quant hugging face link in the comments. Have you tried Hermes agent by Nous Research yet? What are you building with local LLMs? Drop it below, let's see what this community is shipping.
0:19

you're paying $20/mo for something your $500 GPU can already do. Gemma 4 26B A4B QAT MoE + Hermes Agent running on a single RTX 4060 (8GB VRAM). Built a vision capable, 100% free, 100% local, private AI assistant that lives in my Chrome browser. No API keys. No cloud. No subscriptions. 100% vibe coded. 0% handholding. It has full context of whatever's on my screen can answer questions, summarize pages, extract data, and see images. Same local model handles everything, no external calls, ever. keep reading for the model and hermes agent tips i learnt while building this locally. Here's the exact setup for anyone running local LLMs on 6-8 GB VRAM: llama.cpp server flags (on my NVIDIA RTX 4060 8gb VRAM): -m gemma-4-26B-A4B-it-qat-UD-Q4_K_XL.gguf --cache-type-k q8_0 --cache-type-v q8_0 -c 150000 --port 8080 Throughput with quantization: Prefill: 200-250 tokens/sec Decode: 20-25 tokens/sec reduce context if oom on 6 gb vram card. Key learnings: - Quantize KV cache to q8 for faster prefill/decode. Prefill goes from 100-150 (unquantized) to 200-250 tok/s (q8). - But watch out, once actual context grows past ~50k tokens on high entropy workloads, q8 KV quantization can cause hallucinations. Low entropy workloads are mostly unaffected. If you see it happening, drop the quantization. This is common across all local models. - In Hermes Agent settings -> Memory & Context, bump compression threshold from default 0.5 to 0.7. Default triggers way too frequent context compression and eats time. Up next: add persistent memory, web search, tool calling, streaming output and whatever you suggest. Running a 26B MoE with vision + 150k context window on 8GB VRAM would've sounded impossible 6 months ago. Works the same on the NVIDIA RTX 3060 Ti, 3070, 4060 Ti, 5060, 2080, or any 8GB card. VRAM is the only requirement. Local AI agents are closer than people think. You just need to know where the knobs are. Model's Unsloth quant hugging face link in the comments. Have you tried Hermes agent by Nous Research yet? What are you building with local LLMs? Drop it below, let's see what this community is shipping.

Alok

36,691 görüntüleme • 3 ay önce

The most exciting thing that I've been working on lately in the file search field is the GPU acceleration of file search. You might think that I'm dumb or something, but it is a real next step. fff is already on the edge of what is possible on CPU, but our design with the storage is actually oriented on the embarrassingly parallel search, which couldn't be more effective than on GPU. If you'd think about this deeper: 99% of the time file search happens on the local machine of the user. Your melting macbook pro that is using precious CPU cycles to build your Rust project right now is getting wasted on the smart typo-resistant fuzzy matching which is a quadratic complexity algorithm that needs more resources the longer your query is. What if we use GPU instead? Cause we already have it and it is likely idle if user is typing into a search box. And honestly there are some good results so far. I was able to bring fff down to 20% cpu usage at all times no matter how absurdly long your queries are and no matter how many files you have Here is a little sneak peak. Running on M4 max 1.6TB home dir
0:14

The most exciting thing that I've been working on lately in the file search field is the GPU acceleration of file search. You might think that I'm dumb or something, but it is a real next step. fff is already on the edge of what is possible on CPU, but our design with the storage is actually oriented on the embarrassingly parallel search, which couldn't be more effective than on GPU. If you'd think about this deeper: 99% of the time file search happens on the local machine of the user. Your melting macbook pro that is using precious CPU cycles to build your Rust project right now is getting wasted on the smart typo-resistant fuzzy matching which is a quadratic complexity algorithm that needs more resources the longer your query is. What if we use GPU instead? Cause we already have it and it is likely idle if user is typing into a search box. And honestly there are some good results so far. I was able to bring fff down to 20% cpu usage at all times no matter how absurdly long your queries are and no matter how many files you have Here is a little sneak peak. Running on M4 max 1.6TB home dir

Dmitriy Kovalenko

27,008 görüntüleme • 16 gün önce

KIMI K2.6 SERVERS BURN 30 MILLION LITERS OF WATER A MONTH. INDIE DEVS USE THE SAME MODEL FOR $30 IN TOKENS TO LAUNCH $20,000/MONTH APPS IN A WEEKEND kimi k2.6 sits at number 1 on the openrouter leaderboard processing 1.58 trillion tokens a week. more than claude sonnet 4.6 and deepseek combined indie developers who launched in 2024-2025 are making $10,000-20,000 a month solo. no team, no office, $20 in starting costs. most aren't even senior devs the stack is next.js, supabase, stripe and kimi k2.6. you give the model 5 open source repos as reference and it assembles the product from the best parts of each 3,000 paying users at $9.99 a month is $29,970 in revenue. infrastructure costs $1,235. net profit lands at $28,735 with a 95% margin most people will bookmark this and forget. the ones who ship this weekend get a 6-12 month head start in app store rankings over everyone who starts later bookmark this and read the article below
0:10

KIMI K2.6 SERVERS BURN 30 MILLION LITERS OF WATER A MONTH. INDIE DEVS USE THE SAME MODEL FOR $30 IN TOKENS TO LAUNCH $20,000/MONTH APPS IN A WEEKEND kimi k2.6 sits at number 1 on the openrouter leaderboard processing 1.58 trillion tokens a week. more than claude sonnet 4.6 and deepseek combined indie developers who launched in 2024-2025 are making $10,000-20,000 a month solo. no team, no office, $20 in starting costs. most aren't even senior devs the stack is next.js, supabase, stripe and kimi k2.6. you give the model 5 open source repos as reference and it assembles the product from the best parts of each 3,000 paying users at $9.99 a month is $29,970 in revenue. infrastructure costs $1,235. net profit lands at $28,735 with a 95% margin most people will bookmark this and forget. the ones who ship this weekend get a 6-12 month head start in app store rankings over everyone who starts later bookmark this and read the article below

starmex

31,826 görüntüleme • 4 ay önce

🚨 Grass Season 2 Airdrop & Token Update 😱 $GRASS is currently trading around $0.4, and the market is slowly recovering. The price looks strong — and there’s a high chance it could go even higher before Season 2 👀 We’ve already seen a massive 100–200% pump recently 📈 Now the big question everyone is asking: 👉 When is the Season 2 airdrop distribution? There’s no official confirmation yet, BUT here’s what to expect ⬇️ 🔹 Native wallet + eligibility criteria announcement is likely within the next 2 months 🔹 Once announced, distribution could follow very quickly 💡 My take: If the announcement gets slightly delayed, it could mean we’re heading toward a full 20 Epoch cycle — possibly even with a bonus 👀 Based on current progress, 20 Epochs seems very likely. 🔥 Strategy: Increase your points as much as possible NOW Diamonds will matter A LOT — don’t ignore them 💎 👇 Drop your stats: How many points have you earned so far? And how many diamonds are you holding? Next tweet: I’ll explain whether distribution will be based on points or something else 👀 #GrassAirdrop #CryptoAirdrop #Web3 #CryptoNews #AirdropSeason #CryptoCommunity #grassseason2update #grassdistriubtionupdate
0:12

🚨 Grass Season 2 Airdrop & Token Update 😱 $GRASS is currently trading around $0.4, and the market is slowly recovering. The price looks strong — and there’s a high chance it could go even higher before Season 2 👀 We’ve already seen a massive 100–200% pump recently 📈 Now the big question everyone is asking: 👉 When is the Season 2 airdrop distribution? There’s no official confirmation yet, BUT here’s what to expect ⬇️ 🔹 Native wallet + eligibility criteria announcement is likely within the next 2 months 🔹 Once announced, distribution could follow very quickly 💡 My take: If the announcement gets slightly delayed, it could mean we’re heading toward a full 20 Epoch cycle — possibly even with a bonus 👀 Based on current progress, 20 Epochs seems very likely. 🔥 Strategy: Increase your points as much as possible NOW Diamonds will matter A LOT — don’t ignore them 💎 👇 Drop your stats: How many points have you earned so far? And how many diamonds are you holding? Next tweet: I’ll explain whether distribution will be based on points or something else 👀 #GrassAirdrop #CryptoAirdrop #Web3 #CryptoNews #AirdropSeason #CryptoCommunity #grassseason2update #grassdistriubtionupdate

Airdrop Hunt with Lakhan 🪂

16,889 görüntüleme • 5 ay önce

🚀 Blum: Season 2 is Here! Thanks to you, we’ve hit 90M Blum users — an incredible milestone that’s only possible because of your support 🎉 Backed by Binance Labs and TOP, Blum Labs has been on fire, accelerating over 20 projects like DOGS and Paws. The momentum is unreal, and we’re just getting started! But now it’s time to level up—Season 2 is here, and we’re introducing Meme Points to take your trading to the next level 💎 Your Blum Points from Season 1? They’re still here to stay, rewarding you as you go. But now, Meme Points are bringing you even bigger rewards with every trade! Here’s how to earn Meme Points: – Launch your token on Memepad: +500 Meme Points – Token hits a DEX: +10,000 Meme Points – Every $10 traded: +50 Meme Points – Every $10 with Trading Bot: +750 Meme Points Note: Meme Points are earned automatically and exclusively through Memepad or the Trading Bot—no external platforms. Season 2 is about maximizing your rewards, smarter trading, and leveling up faster. Plus, 2025 will bring even more ways to earn with Meme Points, multichain trading, AI agents, perpetual trading, and more 🔥 👉 For all the details, check out our full blog post here: Let’s gooooooo! How will you earn Meme Points? 💥
0:13

🚀 Blum: Season 2 is Here! Thanks to you, we’ve hit 90M Blum users — an incredible milestone that’s only possible because of your support 🎉 Backed by Binance Labs and TOP, Blum Labs has been on fire, accelerating over 20 projects like DOGS and Paws. The momentum is unreal, and we’re just getting started! But now it’s time to level up—Season 2 is here, and we’re introducing Meme Points to take your trading to the next level 💎 Your Blum Points from Season 1? They’re still here to stay, rewarding you as you go. But now, Meme Points are bringing you even bigger rewards with every trade! Here’s how to earn Meme Points: – Launch your token on Memepad: +500 Meme Points – Token hits a DEX: +10,000 Meme Points – Every $10 traded: +50 Meme Points – Every $10 with Trading Bot: +750 Meme Points Note: Meme Points are earned automatically and exclusively through Memepad or the Trading Bot—no external platforms. Season 2 is about maximizing your rewards, smarter trading, and leveling up faster. Plus, 2025 will bring even more ways to earn with Meme Points, multichain trading, AI agents, perpetual trading, and more 🔥 👉 For all the details, check out our full blog post here: Let’s gooooooo! How will you earn Meme Points? 💥

Blum

1,248,726 görüntüleme • 1 yıl önce

HYPER-REALISTIC ANDROID GIRLS JUST RELEASED FOR SALE IN CHINA honestly think tech startups in Shenzhen have already built flawless mechanical companions? please wake up! this is 100% a live human actress in cyber-makeup, perfectly mimicking glitchy robotic movements just to farm viral marketing clips for local retail stores and this is the ultimate comedy of the consumer humanoid market — the public is easily amused by pretty faces and fake scripted performances meanwhile, Elon Musk isn’t building the Tesla Optimus architecture to play house-maid or sit in a storefront acting like a pretty mannequin those earthly factory clips are just a free, self-funded simulator for edge-data harvesting to build real hardware for the moon and mars the entire Gen 3 Optimus with its fluid-free electric powertrain and hardened edge-ai is engineered to do the actual dirty work where organic labor instantly dies a 20-minute cloud ping to corporate data centers is a death sentence in a martian vacuum, which is why true physical intelligence has to run locally on device stop looking at polished retail gimmicks and start looking at the starship launchpad👇
0:19

HYPER-REALISTIC ANDROID GIRLS JUST RELEASED FOR SALE IN CHINA honestly think tech startups in Shenzhen have already built flawless mechanical companions? please wake up! this is 100% a live human actress in cyber-makeup, perfectly mimicking glitchy robotic movements just to farm viral marketing clips for local retail stores and this is the ultimate comedy of the consumer humanoid market — the public is easily amused by pretty faces and fake scripted performances meanwhile, Elon Musk isn’t building the Tesla Optimus architecture to play house-maid or sit in a storefront acting like a pretty mannequin those earthly factory clips are just a free, self-funded simulator for edge-data harvesting to build real hardware for the moon and mars the entire Gen 3 Optimus with its fluid-free electric powertrain and hardened edge-ai is engineered to do the actual dirty work where organic labor instantly dies a 20-minute cloud ping to corporate data centers is a death sentence in a martian vacuum, which is why true physical intelligence has to run locally on device stop looking at polished retail gimmicks and start looking at the starship launchpad👇

EugBass

12,281 görüntüleme • 1 ay önce

The Rise of RWA: Why Early Investors Are Building Lifetime Passive Income with Propbase Real World Assets (RWA) is exploding onto the scene, transforming illiquid traditional investments into accessible, tradable opportunities. From real estate to commodities, RWAs are tokenizing physical assets on the blockchain, unlocking unprecedented liquidity, fractional ownership, and yield-generating potential. And right now, we're in the early innings of this revolution—where savvy investors position themselves for exponential growth. At Propbase, we're leading the charge in RWA tokenization, focusing on high-yield real estate. Imagine owning a slice of premium properties in booming markets like Thailand, without the hassles of traditional buying. With Propbase, you can: Fractionally Invest: Start with as little as $100 in tokenized properties, democratizing access for all. Earn Passive Income: Collect stable rental yields paid out in USDT—directly to your wallet, month after month. Trade Seamlessly: Buy, sell, or leverage your assets on our secure platform, turning real estate into a liquid powerhouse. The data speaks volumes: The global RWA market is projected to surge from $2 billion today to over $10 trillion within 5 years, driven by institutional adoption and regulatory clarity. But here's the key—getting in early maximizes your edge. Early adopters aren't just riding the wave; they're compounding passive income over decades, creating generational wealth with minimal effort. Don't miss out on this once-in-a-lifetime shift. Join Propbase today, secure your first property token, and start building that passive income engine. The future of investing is here—will you be part of it? 🚀 Explore now: #RWA #Propbase #PassiveIncome #RealEstateTokenization #CryptoInvesting
0:16

The Rise of RWA: Why Early Investors Are Building Lifetime Passive Income with Propbase Real World Assets (RWA) is exploding onto the scene, transforming illiquid traditional investments into accessible, tradable opportunities. From real estate to commodities, RWAs are tokenizing physical assets on the blockchain, unlocking unprecedented liquidity, fractional ownership, and yield-generating potential. And right now, we're in the early innings of this revolution—where savvy investors position themselves for exponential growth. At Propbase, we're leading the charge in RWA tokenization, focusing on high-yield real estate. Imagine owning a slice of premium properties in booming markets like Thailand, without the hassles of traditional buying. With Propbase, you can: Fractionally Invest: Start with as little as $100 in tokenized properties, democratizing access for all. Earn Passive Income: Collect stable rental yields paid out in USDT—directly to your wallet, month after month. Trade Seamlessly: Buy, sell, or leverage your assets on our secure platform, turning real estate into a liquid powerhouse. The data speaks volumes: The global RWA market is projected to surge from $2 billion today to over $10 trillion within 5 years, driven by institutional adoption and regulatory clarity. But here's the key—getting in early maximizes your edge. Early adopters aren't just riding the wave; they're compounding passive income over decades, creating generational wealth with minimal effort. Don't miss out on this once-in-a-lifetime shift. Join Propbase today, secure your first property token, and start building that passive income engine. The future of investing is here—will you be part of it? 🚀 Explore now: #RWA #Propbase #PassiveIncome #RealEstateTokenization #CryptoInvesting

Propbase

35,646 görüntüleme • 1 yıl önce

chat even without wi-fi and mobile data it's called protestchat it never asks for a network (repo in replies) e.g. Delhi rolled portable jammers into a protest on july 20 and cut mobile data with it so this dev built a fix 2.4 ghz stays wide open the entire time every other messenger dies the second the internet does BUT this one no > phones hand msgs to each other over bluetooth le > zero routing, every phone carries every unexpired envelope and offers it to whoever it meets > the recipient is just whoever can decrypt it > walk out of the jammed zone and your phone delivers the queue for people still stuck inside > 6 hour expiry, panic wipe, fresh key per message > 72 tests on the crypto and mesh layer > MIT and no account anywhere so if u dont have an internet or gov jammed it just use this repo to text someone how it works:
0:14

chat even without wi-fi and mobile data it's called protestchat it never asks for a network (repo in replies) e.g. Delhi rolled portable jammers into a protest on july 20 and cut mobile data with it so this dev built a fix 2.4 ghz stays wide open the entire time every other messenger dies the second the internet does BUT this one no > phones hand msgs to each other over bluetooth le > zero routing, every phone carries every unexpired envelope and offers it to whoever it meets > the recipient is just whoever can decrypt it > walk out of the jammed zone and your phone delivers the queue for people still stuck inside > 6 hour expiry, panic wipe, fresh key per message > 72 tests on the crypto and mesh layer > MIT and no account anywhere so if u dont have an internet or gov jammed it just use this repo to text someone how it works:

savip

32,690 görüntüleme • 2 ay önce

Are you an Insurance Advisor/Mutual Fund Distributor or advise clients on financial products? To make life easier for financial advisors, we have now integrated the ProtectMeWell API into a Google Sheet This means that you can work on a Google Sheet and generate reports (👇) like these for your prospective customers in real-time. 🚀Would you want to be an early adopter of "ProtectMeWell on Google Sheets"? Here is the deal 1⃣ I am seeking the help of 20 passionate advisors for closed user group testing. On a first come, first serve basis. DM me, if you are interested 2⃣ I will extend access to the Google Sheets for two weeks for ₹999. 100% refundable when you provide me with at least 5 actionable areas of improvement from a usability perspective of Google Sheets. 3⃣ When it is launched for the wider audience (late August 2023) you get to use it for free until 31 March 2024 (subject to 10,000 API calls) PS: To clarify, it is not the testing exercise of API (or algorithm), which is robust and has been used by over 100K people. The focus is on the usability of Google Sheets so that a wider audience finds it easy to navigate Sounds interesting? DM me Please amplify for good karma 🙏
0:15

Are you an Insurance Advisor/Mutual Fund Distributor or advise clients on financial products? To make life easier for financial advisors, we have now integrated the ProtectMeWell API into a Google Sheet This means that you can work on a Google Sheet and generate reports (👇) like these for your prospective customers in real-time. 🚀Would you want to be an early adopter of "ProtectMeWell on Google Sheets"? Here is the deal 1⃣ I am seeking the help of 20 passionate advisors for closed user group testing. On a first come, first serve basis. DM me, if you are interested 2⃣ I will extend access to the Google Sheets for two weeks for ₹999. 100% refundable when you provide me with at least 5 actionable areas of improvement from a usability perspective of Google Sheets. 3⃣ When it is launched for the wider audience (late August 2023) you get to use it for free until 31 March 2024 (subject to 10,000 API calls) PS: To clarify, it is not the testing exercise of API (or algorithm), which is robust and has been used by over 100K people. The focus is on the usability of Google Sheets so that a wider audience finds it easy to navigate Sounds interesting? DM me Please amplify for good karma 🙏

Sumit Ramani

42,240 görüntüleme • 3 yıl önce