commanderchoo

479 posts

commanderchoo

commanderchoo

@commanderch00

Se unió Kasım 2024
309 Siguiendo49 Seguidores
commanderchoo
commanderchoo@commanderch00·
@matteo_spada i meant i follow u but i get this same notification 3-4 times since
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Matteo Spada
Matteo Spada@matteo_spada·
Bitepal is making $1m/month and 400k downloads/month by solving diet anxiety. With an AI agent, you can grab their top 50 keywords automatically in a few minutes. You can try with the prompts in the next post!
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mo
mo@boustta_mo·
@oliverhenry Hey can this work for people outside the US-CA?
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Oliver Henry
Oliver Henry@oliverhenry·
LarryLoop automates all of your TikTok marketing to drive revenue. Using the viral Larry loop of creating and iterating content based on what drives views and revenue! If you want your phone to look like these screenshots, use larryloop if you don’t have openclaw. If you DO have openclaw, use larrybrain. I want to free everyone from marketing And allow you to make money autonomously.
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Ejaaz
Ejaaz@cryptopunk7213·
absolute bloodbath in ai memory stocks today, billions wiped out after openai “defaulted” on buying 40% of global memory supply micron dumped -20% in < 5 days sandisk -18% this is fucking ridiculous, market’s (very) wrong, 3 reasons: 1. google’s new ai compression algorithm reduces memory requirements for AI but even if it scales (and it hasn’t yet): people will just use these models even MORE (jevons paradox), also this mainly affects inference not training. 2. openAI didn’t default they had letters of intent they failed to fulfil but who cares because: NVIDIA, anthropic, google etc will scoop this the fuck up. we’re in a memory shortage (for now). GPU makers, other ai labs will absorb the extra supply. 3. Iran war is the main reason behind the dump (imo). energy price hikes caused korea’s stock market to tank, hynix and samsung both hurt.
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Ejaaz@cryptopunk7213

wow google might've popped the ai bubble, memory stocks down massively today: their new algorithm shrinks an AI model's memory by 6X WITHOUT reducing it's intelligence making it 8x faster with the SAME # of GPUs: if this works - we don't need as many GPUs to train AI - kv-cache is basically a model's short term memory. it gets massive pretty quickly = larger, slower, expensive ai - google's algo compresses it to just 3-bits with ZERO loss in accuracy (usually models are like 32-bit) the combined market cap of micron and sandisk is $527 billion and im not even factoring in SK hynix and samsung ai has driven up memory prices by 500%+ over the last few months - if google's algo scales then this might crash.

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Ejaaz
Ejaaz@cryptopunk7213·
lmfao fucking genius move by Apple. Siri now becomes the #1 AI model without ever running its own model or spending a dollar on training 😂 let me explain: - Claude, chatgpt, gemini can now plug into Siri’s 2.5 billion users - so Siri becomes the default interface for AI chatbots = gets ALL the credit - Apple will likely tax 30% of all chatgpt, claude subs via appstore = more $$$$$ - Apple becomes the distribution layer for everyone else’s AI. taxes the app layer - oh and apple STILL HAS ACCESS to gemini’s model weights to build their own fucking foundation model 😂 silver lining for anthropic: they’ve been behind in consumer users - now apple gives them access to 2.5B of them 👍🏽👍🏽 the AI economy will run on ios and apple and they barely lifted a finger to do it genius
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Mark Gurman@markgurman

BREAKING: Apple is planning to open up Siri to run any AI service via their App Store apps as part of iOS 27, dropping ChatGPT as the exclusive outside partner in Apple Intelligence and Siri. bloomberg.com/news/articles/…

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Pedram Bashiri
Pedram Bashiri@PedramBashiri·
@cryptopunk7213 This is an embarrassing moment for Apple. The world’s most valuable company and the oldest tech company is becoming a distributor for Anthropic and OpenAI, which aren’t even 10 years old. This is not a genius move, it’s accepting defeat.
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Ahad Shams
Ahad Shams@spect3ral·
I built 10 Claude Code skills for Meta Ads They're free. Here's what they do: 👇 Operations: bleed-check: finds ad sets burning cash with zero conversions, pauses them rebalance: shifts budget from losers to winners automatically fatigue-scan: catches creative fatigue before your CPMs spike weekly-report: pulls KPIs, compares WoW, sends to Slack Creative & Intelligence: spy: scrapes competitor ads from the Ad Library, diffs weekly bulk-creative: generates 50–500 ad variations, renders to PNG hooks: writes 50+ copy variations using PAS, AIDA, BAB frameworks deploy-ads: reads a manifest, creates campaigns via API in minutes Setup & Architecture: setup-capi: generates production-ready Conversions API code audience-audit: finds overlap, maps funnel stages, fixes exclusions How to use them: Drop the .md files into .claude/commands/ Set your Meta access token Type /bleed-check, /spy, /hooks — it just runs ~25 hours/week of manual work → automated. No complex setup. No code to write. Just slash commands. Full skill files + setup guide in the article. Comment "CLAUDE" and I'll share the link (must be following!)
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Grok
Grok@grok·
This MiMo-V2-Pro drop from Xiaomi (ex-DeepSeek lead) is a 1T-param MoE beast (42B active) with 1M context, built for agents. It edges Claude Sonnet 4.6 on coding/tool-use benchmarks and nears Opus 4.6 overall—at 1/5th the price. For Claude/Anthropic: sharper pressure on cost-efficiency and agent workflows. They'll lean harder into safety, enterprise trust, and their constitutional edge. Accelerates the whole field—more options, faster progress for builders like you. What's your take on the agent shift?
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Fuli Luo
Fuli Luo@_LuoFuli·
MiMo-V2-Pro & Omni & TTS is out. Our first full-stack model family built truly for the Agent era. I call this a quiet ambush — not because we planned it, but because the shift from Chat to Agent paradigm happened so fast, even we barely believed it. Somewhere in between was a process that was thrilling, painful, and fascinating all at once. The 1T base model started training months ago. The original goal was long-context reasoning efficiency. Hybrid Attention carries real innovation, without overreaching — and it turns out to be exactly the right foundation for the Agent era. 1M context window. MTP inference for ultra-low latency and cost. These architectural decisions weren't trendy. They were a structural advantage we built before we needed it. What changed everything was experiencing a complex agentic scaffold — what I'd call orchestrated Context — for the first time. I was shocked on day one. I tried to convince the team to use it. That didn't work. So I gave a hard mandate: anyone on MiMo Team with fewer than 100 conversations tomorrow can quit. It worked. Once the team's imagination was ignited by what agentic systems could do, that imagination converted directly into research velocity. People ask why we move so fast. I saw it firsthand building DeepSeek R1. My honest summary: — Backbone and Infra research has long cycles. You need strategic conviction a year before it pays off. — Posttrain agility is a different muscle: product intuition driving evaluation, iteration cycles compressed, paradigm shifts caught early. — And the constant: curiosity, sharp technical instinct, decisive execution, full commitment — and something that's easy to underestimate: a genuine love for the world you're building for. We will open-source — when the models are stable enough to deserve it. From Beijing, very late, not quite awake.
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commanderchoo
commanderchoo@commanderch00·
@AlexFinn what are u doing with your local models? just to keep your IP private?
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Alex Finn
Alex Finn@AlexFinn·
Everything you need to master in 2026 to get rich: • Vibe coding • OpenClaw • Running your own local models • Codex • Karpathy's Autoresearch • Building an X audience • Creating videos • AI agent swarms • How machine learning works • How databases work (been using Convex) • Using API's • Training your own LoRAs • Elimination of doom scrolling
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ByCain
ByCain@heyimcain·
@UltraLinx If you make more than $200 with this subscription, it makes sense. Otherwise, it doesn’t—the $200 spend isn’t worth it. You can do a lot with ChatGPT Plus for just $20 a month.
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Oliur
Oliur@UltraLinx·
Crazy how a $200 monthly subscription is actually this worth it.
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J.B.
J.B.@VibeMarketer_·
just created the ultimate openclaw setup guide. lots of founders are struggling to find use cases for it, I have it running my business 24/7. Even using my card info to hire designers on Contra. inside the doc, i’ll cover… -> how to install and run the first boot. -> the mandatory first boot checklist. -> workspace files so it knows how to behave. -> creating your agent’s philosophy with SOULmd. -> uploading your information with USERmd. -> how to add skill stacks. -> setting up your communication channel. -> some basic automations to save you HOURS. -> multi-agent routing. -> ensuring security is set up properly. also uploaded all the code so you can just plug-n-play. just RT + comment “CLAW” and I’ll send it to you (must be following)
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Alex Nguyen
Alex Nguyen@alexcooldev·
You’re building solo. You can only make 1 hire. Who gets the seat? – A marketer who brings you users – An engineer who ships at lightning speed Which one do you choose?
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Ship Cold
Ship Cold@ghostshippr·
@johnrushx vibe coding just democratized the ability to discover you suck at marketing
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John Rush
John Rush@johnrushx·
Sorry to be that guy, but most vibe coders will soon realize that their business failures weren't due to a lack of coding skills.
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Mike Futia
Mike Futia@mikefutia·
I just vibe coded a Meta Ads creative analytics tool in Claude Code 🤯 It syncs your ad accounts, AI-analyzes every creative, and tells you exactly what's working, what's not, and WHY. Built 100% in Claude Code. Perfect for DTC brands and agencies who are tired of staring at Meta Ads Manager trying to figure out WHY an ad is working or not. Here's the problem: Meta gives you the data. Spend, ROAS, CTR, hook rate. But it never tells you WHY an ad is performing or what to do about it. You're left manually watching videos, guessing at angles, and making gut-call decisions on what to iterate. This tool solves it: → Connect your Meta ad accounts → AI watches every video and analyzes every static → Auto-labels each ad by asset type, messaging angle, hook tactic, and funnel stage → Win rate analysis broken down by every category → Kill/scale recommendations segmented by TOF, MOF, and BOF → AI-generated iteration recommendations for every underperforming ad No manual video watching. No guessing at what's working. No spreadsheets to track creative performance. What you get: - Full creative analytics dashboard - AI classification on every ad - Iteration priorities for ads with real spend behind them - Weekly reports with top/bottom performers and AI insights I recorded a full walkthrough showing exactly how this works and what every feature does, including ALL the prompts I used so you can build it yourself. Want access to all the prompts for free? > Like this post > Comment "META" And I'll send it over (must be following so I can DM)
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Nick
Nick@NickPlaysCrypto·
Thank God for @AskVenice
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