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NSB8 IS LIVE. 8 REPOSTS = $800 🚨 This is not an update. It's a takeover. - Experience: Completely rebuilt UI. Faster workflows. Zero wasted motion. - Retail: 8 optimized retail sites expanding coverage & opportunity. - Shopify: A reengineered Shopify module built to outperform under pressure. - Future:... show more

NSB Bot

79,354 subscribers

17,285 次观看 • 7 个月前 •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

31 条评论

RESuperD 的头像

RESuperD7 个月前

The greatest bot I’ve ever used. NSB been here since the beginning

Nanek 的头像

Nanek7 个月前

THE FUTURE OF BOTTING!

Orion 的头像

Orion7 个月前

I remember testing out 2.0 lmao 😂

P Sneaker 的头像

P Sneaker7 个月前

Lets cook them all!!!! NSB=NEVER SUCKING BEHIND

kelvin clement 的头像

kelvin clement7 个月前

Been going crazy otl with NSB I can't wait to see what NSB8 does this year

carlitaleday 的头像

carlitaleday7 个月前

Which 8 retail sites got added?

goliath187.88 的头像

goliath187.887 个月前

Gimme Me 🤚 gimme me✨️👏👏

riblett dennis 的头像

riblett dennis7 个月前

Not an update... A takeover 🔥🔥

Macguire Claudia 的头像

Macguire Claudia7 个月前

Looks solid🥳🥳🥳🥳

jamon edgardo 的头像

jamon edgardo7 个月前

Shopify rebuild sounds serious

Freddie 的头像

Freddie7 个月前

This UI looks clean 🔥

adnan adanee 的头像

adnan adanee7 个月前

I’m here for the glow up

Da Sauce Boss 的头像

Da Sauce Boss7 个月前

LFG !!!!!!!!! 🧑‍🍳🔥

antisupot 的头像

antisupot7 个月前

fastest nike bot ive ever used

arla schnab 的头像

arla schnab7 个月前

NSB8 era incoming

FexiBexi 的头像

FexiBexi7 个月前

Will surely start running now 🔥🔥🔥

Nidia Raulino 的头像

Nidia Raulino7 个月前

Can you share a full site list?

Dex 的头像

Dex7 个月前

NEVER SLEEP BOT

gurrieri claretha 的头像

gurrieri claretha7 个月前

CRAZYY

vegaz leo 的头像

vegaz leo7 个月前

We're waiting for a full video showing all specs😍

amar harrison 的头像

amar harrison7 个月前

Parabéns pelo lançamento! Quero ver benchmarks e reviews 👀

FexiBexi 的头像

FexiBexi7 个月前

Great!!!

valenzu el wirmfu 的头像

valenzu el wirmfu7 个月前

Beau lancement ! Hâte de voir des retours réels 🔥

Terence Sliz 的头像

Terence Sliz7 个月前

this sounds exciting

Andy Chesak 的头像

Andy Chesak7 个月前

🚀🚀🚀🚀🚀🚀Awesome!!!

Trey Cash 的头像

Trey Cash6 个月前

Fire

Rocco 的头像

Rocco7 个月前

🔥

X_Rigsta_X 的头像

X_Rigsta_X5 个月前

Is there a cook group all of if I purchase is there any way I can get help setting up or is it just the bot ?

sticker 的头像

sticker7 个月前

i reposted, liked, saved and shared (source:trust bro)

maryam mckellip 的头像

maryam mckellip7 个月前

Any refund policy if it doesn’t perform?

Dauof#4970 的头像

Dauof#49707 个月前

😍🔥😍🔥😍

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OpenClaw just made the world's smartest AI model its default brain. And the whole thing is still free. GPT 5.4 is now built in. No extra setup. Just pick OpenAI and go. But that's not even the biggest part of this update. Here's the full stack that just dropped: → Pluggable context engines. You can now swap how your AI remembers things. Like upgrading from a notebook to a filing cabinet. → ACP bindings survive restarts. Your agents reconnect automatically. No more broken workflows at 3am. → Secret ref. Passwords and API keys never sit in plain text again. → Slim Docker builds. Smaller containers. Faster deploys. Lower costs. → Gemini 3.1 Flash Light support. Super fast, super cheap. Perfect for high-volume tasks. → iPhone photos auto-convert. No more "unsupported format" errors. → Hundreds of channel fixes across Telegram, Discord, Slack, WhatsApp, and Signal. 6 months ago, this level of AI infrastructure cost thousands. Now one person can set it up in 10 minutes for $0. Save this. It's the most packed free update you'll see this month.

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14,750 次观看 • 6 个月前

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84,679 次观看 • 7 个月前

The Tesla Megapod trademark might be the most important filing nobody is talking about (Save this). Tesla wants to build a product that is basically a self contained AI computer in a box. You truck it somewhere, plug it into power, and it runs AI workloads. The reason this matters is that the AI industry has a problem because you can't build data centers fast enough. Getting land approved, getting power from the grid, getting zoning cleared, that process takes 3–5 years, and demand is moving much faster than that. US data center construction actually fell in 2025 for the first time in years, because developers kept hitting bureaucratic walls. Tesla's answer to that problem is simple. They already own thousands of Supercharger stations across the country and those stations already have land, power, and grid connections, all the hard stuff is done. The idea is to drop a Megapod at those sites and turn idle charging infrastructure into AI compute, almost overnight. What Jason, Chamath, and Friedberg were all circling around is that this drop a box on a concrete pad approach is already how serious companies are deploying AI compute right now. Vertiv and DUG Technology both ship GPU-packed containers that can go live in 90 days and Tesla would just be bringing that idea to a network it already owns. The opportunity is very real whether Tesla is the one to actually execute on it is still an open question.

The Tesla Megapod trademark might be the most important filing nobody is talking about (Save this). Tesla wants to build a product that is basically a self contained AI computer in a box. You truck it somewhere, plug it into power, and it runs AI workloads. The reason this matters is that the AI industry has a problem because you can't build data centers fast enough. Getting land approved, getting power from the grid, getting zoning cleared, that process takes 3–5 years, and demand is moving much faster than that. US data center construction actually fell in 2025 for the first time in years, because developers kept hitting bureaucratic walls. Tesla's answer to that problem is simple. They already own thousands of Supercharger stations across the country and those stations already have land, power, and grid connections, all the hard stuff is done. The idea is to drop a Megapod at those sites and turn idle charging infrastructure into AI compute, almost overnight. What Jason, Chamath, and Friedberg were all circling around is that this drop a box on a concrete pad approach is already how serious companies are deploying AI compute right now. Vertiv and DUG Technology both ship GPU-packed containers that can go live in 90 days and Tesla would just be bringing that idea to a network it already owns. The opportunity is very real whether Tesla is the one to actually execute on it is still an open question.

Milk Road AI

16,630 次观看 • 3 个月前

🚨THE NEXT SPACEX MOVE IS IN THIS SETUP $SPCX is setting up to be the biggest retail opportunity of the entire cycle and almost nobody sees it coming. Here's the pattern that should stop you cold. Back in 2016, Tesla absorbed SolarCity. Everyone called it a distraction, a mistake, a waste of money. Over the next five years, $TSLA ran 3,320%. Ten grand turned into $332,000 for the people who saw the vision while the crowd laughed. Now the same playbook is loading, but bigger. SpaceX is lining up to merge with Tesla and this isn't just a rocket story. After folding in xAI, SpaceX is now an AI company. Look at what each side brings to the table: → SpaceX: xAI, Grok, Starlink, the satellite network, global data infrastructure → Tesla: autonomous driving, robotics, energy, and deep public-market liquidity Put those together and you don't get a company you get one of the most powerful AI ecosystems on the planet, with the infrastructure and the liquidity to scale it fast. This has the makings of one of the biggest events in modern market history. And the setup dwarfs SolarCity it's not even the same league. Here's the catch: most people will ignore it completely, right up until the move has already happened. Then they'll ask how everyone else got positioned so early. That won't be my followers. Follow and turn notifications on. I'll post the opportunity before everyone starts talking about it.

🚨THE NEXT SPACEX MOVE IS IN THIS SETUP $SPCX is setting up to be the biggest retail opportunity of the entire cycle and almost nobody sees it coming. Here's the pattern that should stop you cold. Back in 2016, Tesla absorbed SolarCity. Everyone called it a distraction, a mistake, a waste of money. Over the next five years, $TSLA ran 3,320%. Ten grand turned into $332,000 for the people who saw the vision while the crowd laughed. Now the same playbook is loading, but bigger. SpaceX is lining up to merge with Tesla and this isn't just a rocket story. After folding in xAI, SpaceX is now an AI company. Look at what each side brings to the table: → SpaceX: xAI, Grok, Starlink, the satellite network, global data infrastructure → Tesla: autonomous driving, robotics, energy, and deep public-market liquidity Put those together and you don't get a company you get one of the most powerful AI ecosystems on the planet, with the infrastructure and the liquidity to scale it fast. This has the makings of one of the biggest events in modern market history. And the setup dwarfs SolarCity it's not even the same league. Here's the catch: most people will ignore it completely, right up until the move has already happened. Then they'll ask how everyone else got positioned so early. That won't be my followers. Follow and turn notifications on. I'll post the opportunity before everyone starts talking about it.

Shelpid.WI3M

30,075 次观看 • 2 个月前

🇨🇳 China’s AI+ economy isn’t chasing AGI fantasies, it’s rebuilding the foundations of a real economy. Watch this WEF panel and one thing becomes obvious: Western commentators keep asking, “Has China caught up?” China is asking, “How do we deploy AI across an entire nation?” Two completely different civilizational contexts. China’s strategy isn’t AGI worship, it’s diffusion, cost reduction, and industrial embedding. AI isn’t a demo or a press release. It’s flowing into manufacturing, logistics, finance, autonomous driving, energy, into the places where real value is created. Core points from the panel: 1. AI Action Plan — China is not obsessed with AGI timelines, but with making AI cheap, scalable, and ubiquitous. 2. Adoption Targets — 70% AI device penetration by 2027, 90% by 2030. 3. Extreme Efficiency — top labs are producing competitive models with 1% of the resources used by Western labs. 4. Market-first ecosystem — 85% approval for autonomous driving; China is the world’s largest real-world sandbox for AI-native services like RoboTaxi. 5. Infrastructure advantage — energy strategy + green data centers = long-term compute stability. 6. Full industrial chain integration — AI is lowering costs in retail design, marketing, drug R&D, and more — turning AI into a return-on-investment engine, not a bubble. 7. Education reform — AI literacy is being embedded from elementary school; the challenge isn’t “AI taking jobs” but raising students who can think deeper than AI’s instant answers. 8. DeepSeek moment — the benchmark shock isn’t a one-off; China’s iteration speed is accelerating. Meanwhile, Western CEOs keep saying the quiet part out loud: “We can’t pause AI because China won’t.” Exactly. Because China’s AI isn’t built for headlines, it’s built for industry, productivity, and national-scale deployment. China is no longer playing the same game, it already moved to the next board. The West debates safety memos, China deploys AI to 1.4 billion people. This is what an AI+ economy actually looks like.

🇨🇳 China’s AI+ economy isn’t chasing AGI fantasies, it’s rebuilding the foundations of a real economy. Watch this WEF panel and one thing becomes obvious: Western commentators keep asking, “Has China caught up?” China is asking, “How do we deploy AI across an entire nation?” Two completely different civilizational contexts. China’s strategy isn’t AGI worship, it’s diffusion, cost reduction, and industrial embedding. AI isn’t a demo or a press release. It’s flowing into manufacturing, logistics, finance, autonomous driving, energy, into the places where real value is created. Core points from the panel: 1. AI Action Plan — China is not obsessed with AGI timelines, but with making AI cheap, scalable, and ubiquitous. 2. Adoption Targets — 70% AI device penetration by 2027, 90% by 2030. 3. Extreme Efficiency — top labs are producing competitive models with 1% of the resources used by Western labs. 4. Market-first ecosystem — 85% approval for autonomous driving; China is the world’s largest real-world sandbox for AI-native services like RoboTaxi. 5. Infrastructure advantage — energy strategy + green data centers = long-term compute stability. 6. Full industrial chain integration — AI is lowering costs in retail design, marketing, drug R&D, and more — turning AI into a return-on-investment engine, not a bubble. 7. Education reform — AI literacy is being embedded from elementary school; the challenge isn’t “AI taking jobs” but raising students who can think deeper than AI’s instant answers. 8. DeepSeek moment — the benchmark shock isn’t a one-off; China’s iteration speed is accelerating. Meanwhile, Western CEOs keep saying the quiet part out loud: “We can’t pause AI because China won’t.” Exactly. Because China’s AI isn’t built for headlines, it’s built for industry, productivity, and national-scale deployment. China is no longer playing the same game, it already moved to the next board. The West debates safety memos, China deploys AI to 1.4 billion people. This is what an AI+ economy actually looks like.

𝘊𝘰𝘳𝘳𝘪𝘯𝘦

13,847 次观看 • 8 个月前

This is Sandy. She went from sleeping on a beach in Hawaii to making over $50,000 a month in nine months. Zero technical background. Still works her 9-to-5 at a funeral home. She also has kids under 8. She spends one to two hours a day on this. That's it. Her first client? She applied to seven jobs on Upwork, had no testimonials, no portfolio, and landed a $3,000/month retainer... ...ok you have my attention A couple months later she increased it to $5,500. What is this awesomeness?! AI automation for businesses. - SEO workflows - blog automation - content systems But here's the thing. She didn't know anything about SEO when she applied. She didn't know how to code. She just used ChatGPT and Claude to build everything. She recorded a 2-3 minute Loom video walking through a workflow ChatGPT built for her, sent it to the client, and closed the deal. In this episode Sandy: - Breaks down how she went from $2 a day in college to multiple income streams - Shows exactly how she landed her first client with zero experience - Tells me why recording a Loom video is the secret to winning on Upwork - Gives me the "Ikigai" framework she used to pick the right niche - Walks through how she built an app in six hours while recording a YouTube video This one was INCREDIBLE. Check it out!

This is Sandy. She went from sleeping on a beach in Hawaii to making over $50,000 a month in nine months. Zero technical background. Still works her 9-to-5 at a funeral home. She also has kids under 8. She spends one to two hours a day on this. That's it. Her first client? She applied to seven jobs on Upwork, had no testimonials, no portfolio, and landed a $3,000/month retainer... ...ok you have my attention A couple months later she increased it to $5,500. What is this awesomeness?! AI automation for businesses. - SEO workflows - blog automation - content systems But here's the thing. She didn't know anything about SEO when she applied. She didn't know how to code. She just used ChatGPT and Claude to build everything. She recorded a 2-3 minute Loom video walking through a workflow ChatGPT built for her, sent it to the client, and closed the deal. In this episode Sandy: - Breaks down how she went from $2 a day in college to multiple income streams - Shows exactly how she landed her first client with zero experience - Tells me why recording a Loom video is the secret to winning on Upwork - Gives me the "Ikigai" framework she used to pick the right niche - Walks through how she built an app in six hours while recording a YouTube video This one was INCREDIBLE. Check it out!

Chris Koerner

63,092 次观看 • 2 个月前

$SERV is the Fiverr/Shopify for AI agents. OpenServ provides a platform and marketplace to create, find, and employ AI agents. Here's why it can be a leading Agent marketplace and is undervalued compared to where it can go. ———————————————————— To put this in perspective, we will take this from the top down. Let's look at the valuation mismatch. → Shopify: $140B → Fiverr: $1.2B → $SERV: $37M AI agent platforms can completely replace these businesses. Why? → Can automate operations (i.e. store setup, inventory management, and customer support autonomously, etc.) → Agents can hyper-personalize the shopping experience → Store owners can own their data and have more control → Marketplaces are a cheaper/faster solution AI agents make things more convenient by performing tasks autonomously. They are inevitable. ———————————————————— The AI Agent market is projected to reach ~$50B by 2030. So the potential is MASSIVE. What makes me so bullish on $SERV specifically? There are 3 things: 1️⃣ The Tech They are targeting Web 2 businesses. This gives the platform the most upside potential imo, both in terms of adoption and valuation. These are some noteworthy highlights: → No-code AI Agent builder (anyone can build) → Builders can generate income using agents → ANY agent can cooperate with ANY agent through SERVs platform → Offers multi-agent collaboration, while allowing for human input/customization This sets them apart from other crypto-centric AI agent marketplaces. OpenServ allows you to create a team of agents to carry out complex tasks, all while automating the process and packaging their solution for Web 2 businesses. Simple tool, easy execution, and limitless productivity. Which business/individual wouldn't want to do MORE in LESS time at a rate MUCH LESS than solutions already available? ———————————————————— 2️⃣ The Team They have a stacked team. → Founders: Experience in businesses & startups → CTO: 20+ years of experience in ML/AI → CFO: ex-JP Morgan VP → CMO: ex-IBM AI & Blockchain Marketing Director Within the last few weeks/months, they have added a UI/UX designer, 4 more devs, and more devs + a product manager coming. You could have the best tech but the team is what determines its success. In this case, the team has the knowledge/experience to see this through. They have been building for a year and the progress made is a good sign of what's to come. ———————————————————— 3️⃣ The Tokenomics A percentage of transaction volume on the platform will be used to buy back and burn the $SERV token. This creates and maintains buy-side pressure and demand. To put that in perspective, Fiverr & Upwork had a combined transaction volume of $5B. The demand for Agents wont slow down anytime soon. Demand for AI agents will translate into demand for the token. I love deflation. It's simple, clean, and effective. ———————————————————— ➡️ Final Thoughts I've held on tight to my $SERV bag because the platform is launching in Q1. This will mark the beginning of their journey to the top. Agents are inevitable. Integration with Web 2 businesses is inevitable. And the platform launch is coming as alt szn is kicking off. The stars are aligning. At the same time, AI companies are already showing interest in the platform. Developers lead to more users, bringing monetization opportunities, which brings more developers, and so on. A powerfully designed flywheel. This is a new and exciting sector. I expect interest and liquidity to be focused on AI Agents and the infrastructure around them. Max opportunity is right here in this sector.

$SERV is the Fiverr/Shopify for AI agents. OpenServ provides a platform and marketplace to create, find, and employ AI agents. Here's why it can be a leading Agent marketplace and is undervalued compared to where it can go. ———————————————————— To put this in perspective, we will take this from the top down. Let's look at the valuation mismatch. → Shopify: $140B → Fiverr: $1.2B → $SERV: $37M AI agent platforms can completely replace these businesses. Why? → Can automate operations (i.e. store setup, inventory management, and customer support autonomously, etc.) → Agents can hyper-personalize the shopping experience → Store owners can own their data and have more control → Marketplaces are a cheaper/faster solution AI agents make things more convenient by performing tasks autonomously. They are inevitable. ———————————————————— The AI Agent market is projected to reach ~$50B by 2030. So the potential is MASSIVE. What makes me so bullish on $SERV specifically? There are 3 things: 1️⃣ The Tech They are targeting Web 2 businesses. This gives the platform the most upside potential imo, both in terms of adoption and valuation. These are some noteworthy highlights: → No-code AI Agent builder (anyone can build) → Builders can generate income using agents → ANY agent can cooperate with ANY agent through SERVs platform → Offers multi-agent collaboration, while allowing for human input/customization This sets them apart from other crypto-centric AI agent marketplaces. OpenServ allows you to create a team of agents to carry out complex tasks, all while automating the process and packaging their solution for Web 2 businesses. Simple tool, easy execution, and limitless productivity. Which business/individual wouldn't want to do MORE in LESS time at a rate MUCH LESS than solutions already available? ———————————————————— 2️⃣ The Team They have a stacked team. → Founders: Experience in businesses & startups → CTO: 20+ years of experience in ML/AI → CFO: ex-JP Morgan VP → CMO: ex-IBM AI & Blockchain Marketing Director Within the last few weeks/months, they have added a UI/UX designer, 4 more devs, and more devs + a product manager coming. You could have the best tech but the team is what determines its success. In this case, the team has the knowledge/experience to see this through. They have been building for a year and the progress made is a good sign of what's to come. ———————————————————— 3️⃣ The Tokenomics A percentage of transaction volume on the platform will be used to buy back and burn the $SERV token. This creates and maintains buy-side pressure and demand. To put that in perspective, Fiverr & Upwork had a combined transaction volume of $5B. The demand for Agents wont slow down anytime soon. Demand for AI agents will translate into demand for the token. I love deflation. It's simple, clean, and effective. ———————————————————— ➡️ Final Thoughts I've held on tight to my $SERV bag because the platform is launching in Q1. This will mark the beginning of their journey to the top. Agents are inevitable. Integration with Web 2 businesses is inevitable. And the platform launch is coming as alt szn is kicking off. The stars are aligning. At the same time, AI companies are already showing interest in the platform. Developers lead to more users, bringing monetization opportunities, which brings more developers, and so on. A powerfully designed flywheel. This is a new and exciting sector. I expect interest and liquidity to be focused on AI Agents and the infrastructure around them. Max opportunity is right here in this sector.

Chill

34,174 次观看 • 1 年前

No panic. No euphoria. Just audit season. The door isn’t closing, it’s being priced. Retail investor doesn’t need forecasts. It needs rules: presence, entries, and emotional immunity. This wasn’t an “AI is strong” earnings season. It was the first audit season. Whether data centers land on time. Whether hyperscaler capex becomes durable cash flow. Whether the backlog is future money, or future explanations that require financing, time, and a lot of narrative stamina. Rates are still high. That makes the game cruel. You don’t just need growth. You need growth that clears the rate line. You don’t just need a story. You need a business model that can survive being audited. That’s why the tape has been telling you the truth in plain sight. $ORCL can talk about massive commitments and still roll over from highs. $GOOGL can trade like a “winner” and still slip under 300. Semis can look unstoppable one month and suddenly trade heavy the next. That’s not “AI died.” That’s the market quietly forcing one question onto every balance sheet: show me the cash. Micron is a perfect window into this regime. $MU earnings are not a referendum on “memory strength.” They’re a referendum on whether the slope of the AI supply chain can still be believed. In audit season, guidance doesn’t have to be bad to get punished. It only has to be not strong enough. And here’s the part most people miss: institutions and retail are playing different games on the same table. Institutions are not constrained by conviction. They are constrained by not getting hurt. In a crowded, low-cash environment, any sentence that doesn’t sound airtight becomes a reason to de-risk. Their job is to cut tails, protect sleep, survive the next IC, and still have a story for LPs. Retail has a different edge. You don’t report to anyone. Your advantage is time. So the retail framework is simpler and more uncomfortable than most “earnings takes”: Stay present. Even if it’s small. You can’t control events, but you can refuse to be absent from the trend. Make adds rule-based, not emotion-based. When it sells off, ask one thing: is the slope being rejected, or are expectations being cleared? If it’s expectation clearing and the chain isn’t broken, that drawdown is a discount, not a disaster. And stop confusing complexity with intelligence. Options aren’t a personality. For most people they have one legitimate purpose: Helping you sleep. If you can live with volatility, spot is cleaner. What you need is a rule set: where you add, how many times you add, and where you stop. Audit season doesn’t teach you how to “call direction.” It teaches you which game you’re actually playing. And the biggest mistake retail makes in this regime is borrowing institutional fear and calling it “risk management.”

No panic. No euphoria. Just audit season. The door isn’t closing, it’s being priced. Retail investor doesn’t need forecasts. It needs rules: presence, entries, and emotional immunity. This wasn’t an “AI is strong” earnings season. It was the first audit season. Whether data centers land on time. Whether hyperscaler capex becomes durable cash flow. Whether the backlog is future money, or future explanations that require financing, time, and a lot of narrative stamina. Rates are still high. That makes the game cruel. You don’t just need growth. You need growth that clears the rate line. You don’t just need a story. You need a business model that can survive being audited. That’s why the tape has been telling you the truth in plain sight. $ORCL can talk about massive commitments and still roll over from highs. $GOOGL can trade like a “winner” and still slip under 300. Semis can look unstoppable one month and suddenly trade heavy the next. That’s not “AI died.” That’s the market quietly forcing one question onto every balance sheet: show me the cash. Micron is a perfect window into this regime. $MU earnings are not a referendum on “memory strength.” They’re a referendum on whether the slope of the AI supply chain can still be believed. In audit season, guidance doesn’t have to be bad to get punished. It only has to be not strong enough. And here’s the part most people miss: institutions and retail are playing different games on the same table. Institutions are not constrained by conviction. They are constrained by not getting hurt. In a crowded, low-cash environment, any sentence that doesn’t sound airtight becomes a reason to de-risk. Their job is to cut tails, protect sleep, survive the next IC, and still have a story for LPs. Retail has a different edge. You don’t report to anyone. Your advantage is time. So the retail framework is simpler and more uncomfortable than most “earnings takes”: Stay present. Even if it’s small. You can’t control events, but you can refuse to be absent from the trend. Make adds rule-based, not emotion-based. When it sells off, ask one thing: is the slope being rejected, or are expectations being cleared? If it’s expectation clearing and the chain isn’t broken, that drawdown is a discount, not a disaster. And stop confusing complexity with intelligence. Options aren’t a personality. For most people they have one legitimate purpose: Helping you sleep. If you can live with volatility, spot is cleaner. What you need is a rule set: where you add, how many times you add, and where you stop. Audit season doesn’t teach you how to “call direction.” It teaches you which game you’re actually playing. And the biggest mistake retail makes in this regime is borrowing institutional fear and calling it “risk management.”

Tigris | 会讲课教授是好老师

54,141 次观看 • 9 个月前

🚨Update! Our new demo is LIVE 🚨 In this demo, we walk through the core features of Intelligence Cubed, a next-generation AI model platform built for research, experimentation, and ownership. 🔹 500+ Research Models Intelligence Cubed has grown from 200+ to 506 models, contributed by our expanding Research Fellow Cohort, including researchers, PhDs, and post-docs from Stanford, CMU, Harvard, MIT, and other top U.S. institutions. 🔹 Model Cards & Research Transparency Each model is linked to its original research paper and includes a detailed model card outlining its purpose, use cases, category, pricing, market traction, reviews, and public ownership percentage. 🔹 1.2M Public-Owned Models We’ve introduced Public-Owned Models, with over 1.2 million models available — all fully documented with research papers and comprehensive model cards. 🔹 Auto Router Not sure which model to use? Our Auto Router analyzes your question and automatically routes it to the most suitable model. In this demo, it selects an LLM Detection Survey model to answer the query. 🔹 Modelverse, Canvas & Workflows Users can explore models in Modelverse, try them instantly, add favorites to cart, and deploy purchased models in Canvas using drag-and-drop to build custom workflows. We also provide professionally curated workflows for immediate hands-on experience. 👉Try Now: #AI #Web3 #AIModel #DeFi #blockchain #LLM #OpenSourceAI #AIxWeb3 #DeAI #IntelligenceCubed

🚨Update! Our new demo is LIVE 🚨 In this demo, we walk through the core features of Intelligence Cubed, a next-generation AI model platform built for research, experimentation, and ownership. 🔹 500+ Research Models Intelligence Cubed has grown from 200+ to 506 models, contributed by our expanding Research Fellow Cohort, including researchers, PhDs, and post-docs from Stanford, CMU, Harvard, MIT, and other top U.S. institutions. 🔹 Model Cards & Research Transparency Each model is linked to its original research paper and includes a detailed model card outlining its purpose, use cases, category, pricing, market traction, reviews, and public ownership percentage. 🔹 1.2M Public-Owned Models We’ve introduced Public-Owned Models, with over 1.2 million models available — all fully documented with research papers and comprehensive model cards. 🔹 Auto Router Not sure which model to use? Our Auto Router analyzes your question and automatically routes it to the most suitable model. In this demo, it selects an LLM Detection Survey model to answer the query. 🔹 Modelverse, Canvas & Workflows Users can explore models in Modelverse, try them instantly, add favorites to cart, and deploy purchased models in Canvas using drag-and-drop to build custom workflows. We also provide professionally curated workflows for immediate hands-on experience. 👉Try Now: #AI #Web3 #AIModel #DeFi #blockchain #LLM #OpenSourceAI #AIxWeb3 #DeAI #IntelligenceCubed

i³ (Intelligence Cubed)

116,576 次观看 • 9 个月前

Part of our quest with Giiift is to make the internet fun again and actually make it easy and engaging to send digital assets between people. One of my recent brainwaves on AI was how it's now possible to create and build one to one experiences on the internet rather than the one to many model that we have had to use purely from a time and cost perspective with development, this is only feasible within the last six months and it's completely open territory. If you think of a fortnite skin for example, that's a one to many experience, where one skin is owned and purchased by many people, makes sense of course as creating individual experiences solely meant for one or a few people would have been incredibly costly for businesses, but that's simply not the case anymore. That's the thesis with Giiift, it firstly packages what onchain tech does best, provide the rails for sending assets from A to B in the most efficient manner possible, but secondly and most importantly it puts the end user experience first in a way that's very reminicent of the old school internet and I think this allows for an unprecedented level of virability in growing the userbase. All a trojan horse for getting onchain wallets and assets into the hands of everyday people around the world, powered by Prism and perfectly suits as retail assets come onchain through Agent to Agent commerce (more on this soon). Here's the progress we're making on the Box Lab, endless customizability! Oh and the music is:

Part of our quest with Giiift is to make the internet fun again and actually make it easy and engaging to send digital assets between people. One of my recent brainwaves on AI was how it's now possible to create and build one to one experiences on the internet rather than the one to many model that we have had to use purely from a time and cost perspective with development, this is only feasible within the last six months and it's completely open territory. If you think of a fortnite skin for example, that's a one to many experience, where one skin is owned and purchased by many people, makes sense of course as creating individual experiences solely meant for one or a few people would have been incredibly costly for businesses, but that's simply not the case anymore. That's the thesis with Giiift, it firstly packages what onchain tech does best, provide the rails for sending assets from A to B in the most efficient manner possible, but secondly and most importantly it puts the end user experience first in a way that's very reminicent of the old school internet and I think this allows for an unprecedented level of virability in growing the userbase. All a trojan horse for getting onchain wallets and assets into the hands of everyday people around the world, powered by Prism and perfectly suits as retail assets come onchain through Agent to Agent commerce (more on this soon). Here's the progress we're making on the Box Lab, endless customizability! Oh and the music is:

Colby

18,008 次观看 • 3 个月前

🚨 This tool just made every AI coding plugin look outdated. Cline CLI 2.0 is a completely rebuilt, open-source AI coding agent that runs entirely in the terminal. Model-agnostic, editor-agnostic, Apache 2.0 licensed, and trusted by over 5 million developers. Same core engine as the VS Code extension rebuilt for how serious development actually happens. The new interactive UI feels genuinely native. Redesigned navigation, real-time agent reasoning, model switching mid-session, all without leaving the terminal. Parallel agents let multiple Cline instances run across tmux panes simultaneously, each with fully isolated state, working different tasks on different branches without conflicts. Headless mode with the `-y` flag plugs Cline directly into CI/CD pipelines, pipe a git diff in, get a code review out. And the `--acp` flag connects to Zed, Neovim, Emacs, and any ACP-compatible editor, so there's no forced editor choice. At launch, Minimax M2.5 and Kimi K2.5 are completely free. No API key. No credit card. Zero barrier to try it. `npm install -g cline` Docs → GitHub → The future of AI coding isn't a plugin. It's infrastructure.

🚨 This tool just made every AI coding plugin look outdated. Cline CLI 2.0 is a completely rebuilt, open-source AI coding agent that runs entirely in the terminal. Model-agnostic, editor-agnostic, Apache 2.0 licensed, and trusted by over 5 million developers. Same core engine as the VS Code extension rebuilt for how serious development actually happens. The new interactive UI feels genuinely native. Redesigned navigation, real-time agent reasoning, model switching mid-session, all without leaving the terminal. Parallel agents let multiple Cline instances run across tmux panes simultaneously, each with fully isolated state, working different tasks on different branches without conflicts. Headless mode with the `-y` flag plugs Cline directly into CI/CD pipelines, pipe a git diff in, get a code review out. And the `--acp` flag connects to Zed, Neovim, Emacs, and any ACP-compatible editor, so there's no forced editor choice. At launch, Minimax M2.5 and Kimi K2.5 are completely free. No API key. No credit card. Zero barrier to try it. `npm install -g cline` Docs → GitHub → The future of AI coding isn't a plugin. It's infrastructure.

AI Frontliner

60,126 次观看 • 7 个月前