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Lobster AI — 24/7 all-scenario personal AI Agent: • One command: research, scheduling, data analysis… • Mobile remote control + long-term memory • One-package install, clean GUI • Local-first security: sandbox isolation & audit trails #AI #Agent #LobsterAI #NetEase #youdao

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LobsterAI

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19,234 görüntüleme • 7 ay önce •via X (Twitter)

Bilim & Teknoloji#AI#Agent#LobsterAI#NetEase#youdao
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Orynth Product Review EP12 Herald lets you deploy a real AI agent in one click. No code, no API keys, no cost. Pick a template, connect Telegram, and your agent is live in under 60 seconds, running 24/7 with memory and modular skills. Powered by Nous Research, one of the most respected names in open-source AI. Built by gigaevm ($/acc), who got tired of agent platforms charging $50/month and locking you into one model, so he made the free version. A real product listed on Orynth with its own token solana:BT91Uvx89v6XvJKMn6GiwvPAxN9Lo2MPTVWkuGg5vory In this twelfth episode, we break down what Herald is building, the builder behind it, and why a free, instant AI agent deployer is worth a look.

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✨ Personal AI is the next computing platform. AI is shifting from something you access to something you build with, locally, at the edge, and across systems. We’re unlocking new possibilities for developers: • AMD Ryzen AI Halo, a local-first developer system, preorder starting in June, develop AI without limits on your desk • Gorgon Halo with up to 192GB unified memory, supporting 300B+ parameter models locally, run massive models locally We’re excited to partner with clem 🤗🤗, Co-founder and CEO of Hugging Face, to advance open-source AI for Ryzen AI. Our focus is seamless AI, from model to deployment. Cloud, edge, device. One continuum. Multi-agent systems, local inference at scale, open models as infrastructure. This is the next computing era 🚀
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✨ Personal AI is the next computing platform. AI is shifting from something you access to something you build with, locally, at the edge, and across systems. We’re unlocking new possibilities for developers: • AMD Ryzen AI Halo, a local-first developer system, preorder starting in June, develop AI without limits on your desk • Gorgon Halo with up to 192GB unified memory, supporting 300B+ parameter models locally, run massive models locally We’re excited to partner with clem 🤗🤗, Co-founder and CEO of Hugging Face, to advance open-source AI for Ryzen AI. Our focus is seamless AI, from model to deployment. Cloud, edge, device. One continuum. Multi-agent systems, local inference at scale, open models as infrastructure. This is the next computing era 🚀

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How long does it take to deploy a 24/7 OpenClaw AI agent? ⏱️ Local install: 2 hours (if you're lucky) 30 seconds. We obliterated every hurdle standing between you and OpenClaw: 🚀 Instant Access: Fully managed, zero code setup 🌍 Cloud Resident: Close your browser, tasks keep running 24/7 🛠️ Full Control: Web actions, file handling, cross-platform workflows 🛡️ Securely Isolated: Your private instance, your data, your rules Stop wasting life on configuration. Let MyClaw handle the infrastructure while you focus on the results.

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You can now set up and run OpenClaw without touching a terminal. It takes just one click to set up everything automatically and get a personal AI assistant to work for you 24/7. 5 insane use cases & how to below: 1. Agent that turns any brand URL into FULL ad creatives:

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this is free f*cking gold for AI engineers 10 repos i'd actually keep, from python fundamentals to LLMs, agents and production AI. skip the random tutorials 1. Python-100-Days - a 100 day path through fundamentals, data analysis, web dev ↳ 2. Generative AI for Beginners - LLM basics, prompting, RAG, agents, fine-tuning ↳ 3. LLMs from Scratch - build one yourself: tokenization, attention, transformers, training ↳ 4. ML for Beginners - 12 weeks, 26 lessons of classical ML ↳ 5. OpenAI Cookbook - working examples to go from learning to building ↳ 6. Stable Diffusion - the original implementation and research code ↳ 7. AI Agents for Beginners - tool use, RAG, agent frameworks, multi-agent systems ↳ 8. AI for Beginners - 12 weeks, 24 lessons: neural nets, vision, NLP ↳ 9. LLM App - RAG pipelines, enterprise search, real-time data, vector search ↳ 10. Segment Anything - Meta's foundation model for image segmentation ↳ pick by where you are: > python -> Python-100-Days > ML -> ML-For-Beginners > LLMs -> LLMs-from-scratch > agents -> AI-Agents-for-Beginners > building -> OpenAI Cookbook, LLM App > vision -> Segment Anything pick one, build something, then move to the next

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Spectre AI: Revolutionizing Blockchain Predictions with All-in-One Tools Available on Telegram & Dapp! Unleash the power of machine learning predictions with Spectre Bot! Our cutting-edge AI engine leverages advanced machine learning techniques, including deep learning models like Long Short-Term Memory (LSTM) networks, to provide insightful short-term token forecasts (6h, 12h, 24h, & 48h). Gain a deeper understanding of market sentiment with features like X Bubblemaps, Sentiment Analysis charts, and AI-powered TA Chatbots. Take control of your crypto future with Spectre Bot! Website: Community Telegram: Chart: Roadmap and other links: Spectre AI is part of the Google and NVIDIA Startup Programs. API powered by Bitquery.io ( Bloxy ). #spectre #ai #machinelearning #predictions #google #nvidia #biquery $SPECT

SPECTRE AI

107,603 görüntüleme • 2 yıl önce

this is free f*cking gold for AI engineers 10 repos worth keeping, from python basics all the way to LLMs, agents and production AI. forget the random tutorials 1. Python-100-Days - 100 days through fundamentals, data analysis and web dev ↳ 2. Generative AI for Beginners - LLM basics, prompting, RAG, agents, fine-tuning ↳ 3. LLMs from Scratch - build one yourself: tokenization, attention, transformers, training ↳ 4. ML for Beginners - 26 lessons of classical ML across 12 weeks ↳ 5. OpenAI Cookbook - working examples that move you from reading to building ↳ 6. Stable Diffusion - the original implementation and the research code behind it ↳ 7. AI Agents for Beginners - tool use, RAG, agent frameworks, multi-agent systems ↳ 8. AI for Beginners - 24 lessons over 12 weeks: neural nets, vision, NLP ↳ 9. LLM App - RAG pipelines, enterprise search, real-time data, vector search ↳ 10. Segment Anything - Meta's foundation model for image segmentation ↳ start from wherever you are: > python -> Python-100-Days > ML -> ML-For-Beginners > LLMs -> LLMs-from-scratch > agents -> AI-Agents-for-Beginners > building -> OpenAI Cookbook, LLM App > vision -> Segment Anything take one, build something with it, then move on to the next
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this is free f*cking gold for AI engineers 10 repos worth keeping, from python basics all the way to LLMs, agents and production AI. forget the random tutorials 1. Python-100-Days - 100 days through fundamentals, data analysis and web dev ↳ 2. Generative AI for Beginners - LLM basics, prompting, RAG, agents, fine-tuning ↳ 3. LLMs from Scratch - build one yourself: tokenization, attention, transformers, training ↳ 4. ML for Beginners - 26 lessons of classical ML across 12 weeks ↳ 5. OpenAI Cookbook - working examples that move you from reading to building ↳ 6. Stable Diffusion - the original implementation and the research code behind it ↳ 7. AI Agents for Beginners - tool use, RAG, agent frameworks, multi-agent systems ↳ 8. AI for Beginners - 24 lessons over 12 weeks: neural nets, vision, NLP ↳ 9. LLM App - RAG pipelines, enterprise search, real-time data, vector search ↳ 10. Segment Anything - Meta's foundation model for image segmentation ↳ start from wherever you are: > python -> Python-100-Days > ML -> ML-For-Beginners > LLMs -> LLMs-from-scratch > agents -> AI-Agents-for-Beginners > building -> OpenAI Cookbook, LLM App > vision -> Segment Anything take one, build something with it, then move on to the next

Annatar.md

11,733 görüntüleme • 4 gün önce

anthropic just removed the biggest excuse people had for not building ai agents. “it’s too hard.” not anymore. a few months ago, building an ai agent meant learning how to code, setting up apis, configuring servers, and fixing endless errors. today, all you need is one github repo. anthropic open-sourced launch your agent. it asks what you want to build. then it does the rest. it builds your agent, deploys it to the cloud, tests it, improves it, and keeps it running even after you close your laptop. no fake demos. no complicated setup. just a real ai agent running in your own account. the best part. it doesn’t run on your computer. it runs inside claude managed agents, works 24/7, and costs just a few cents per run. people are already building research agents, lead generation systems, content pipelines, and customer support agents that save hours of work every day. the gap between people who use ai and people who build ai workers is getting bigger every week. that’s usually where the biggest opportunities are. build your first ai agent before everyone else does. watch the video and read the full guide below 👇
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anthropic just removed the biggest excuse people had for not building ai agents. “it’s too hard.” not anymore. a few months ago, building an ai agent meant learning how to code, setting up apis, configuring servers, and fixing endless errors. today, all you need is one github repo. anthropic open-sourced launch your agent. it asks what you want to build. then it does the rest. it builds your agent, deploys it to the cloud, tests it, improves it, and keeps it running even after you close your laptop. no fake demos. no complicated setup. just a real ai agent running in your own account. the best part. it doesn’t run on your computer. it runs inside claude managed agents, works 24/7, and costs just a few cents per run. people are already building research agents, lead generation systems, content pipelines, and customer support agents that save hours of work every day. the gap between people who use ai and people who build ai workers is getting bigger every week. that’s usually where the biggest opportunities are. build your first ai agent before everyone else does. watch the video and read the full guide below 👇

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The World’s First Nex-Gen AI Screener with In-Built Monarch AI Agent Chatzone: MVP Showcase Charts meets AI Analysis - Game-changer Use-Case We’re proud to share an exclusive in-house beta showcase of the AI Screener, powered by the integrated Monarch AI Agent — a first-of-its-kind tool designed to decode the projects in real time. This early MVP highlights how Monarch sits beside the chart, analyzing contract addresses, on-chain data, technical indicators, sentiment signals, and social media connections, all within one unified interface. Users will be able to interact with Monarch through both deep analytical prompts and casual exploration, with full-screen functionality enabled for an immersive experience. What this first implementation demonstrates: → TA prompt flow in action → X Connections → Seamless frontend integration → A glimpse of the full experience to come What’s ahead: → Complete contract analysis → Wallet and holder deep dives → Screener overlays with curated watchlists and Dexscan charts → Swaps directly within the chat interface - DEFAI This marks the beginning of a smarter, more intuitive way to navigate on-chain data — one that decodes the noise and surfaces what really matters. This is only the beginning. #aidex #DeFAI #ai $SPECT
2:01

The World’s First Nex-Gen AI Screener with In-Built Monarch AI Agent Chatzone: MVP Showcase Charts meets AI Analysis - Game-changer Use-Case We’re proud to share an exclusive in-house beta showcase of the AI Screener, powered by the integrated Monarch AI Agent — a first-of-its-kind tool designed to decode the projects in real time. This early MVP highlights how Monarch sits beside the chart, analyzing contract addresses, on-chain data, technical indicators, sentiment signals, and social media connections, all within one unified interface. Users will be able to interact with Monarch through both deep analytical prompts and casual exploration, with full-screen functionality enabled for an immersive experience. What this first implementation demonstrates: → TA prompt flow in action → X Connections → Seamless frontend integration → A glimpse of the full experience to come What’s ahead: → Complete contract analysis → Wallet and holder deep dives → Screener overlays with curated watchlists and Dexscan charts → Swaps directly within the chat interface - DEFAI This marks the beginning of a smarter, more intuitive way to navigate on-chain data — one that decodes the noise and surfaces what really matters. This is only the beginning. #aidex #DeFAI #ai $SPECT

SPECTRE AI

136,582 görüntüleme • 1 yıl önce

Our beloved solana-claude is now Solana AI Kit ⚡ The best Solana AI skills, one command away. Check out our curated aggregator of agents, commands, skills, MCPs & config for Claude Code, Codex & any agentic setup. What's new: 🧠 15 agents + 29 commands: incl. new /doctor (env health-check), /audit-infra (secrets, supply-chain, CI/CD + OWASP/STRIDE), /product-review --harsh, /dream (memory consolidation) 🧩 18 expert skill submodules: now with Quicknode, eth→Solana migration, Ghost Security & Anthropic's defending-code ⚙️ Stack refresh: OtterSec's Anchor 1.0, blueshift's Quasar, Surfpool MCP, SendAI's & more 📚 Extended skill registry: 39 install-on-demand tools covering design, forensics, animation, UX, testing & data, curated from the best of the ecosystem 💚Install: curl -fsSL | bash 🔌 Now on the Claude Code plugin marketplace /plugin install solana-ai-kit@stbr
0:44

Our beloved solana-claude is now Solana AI Kit ⚡ The best Solana AI skills, one command away. Check out our curated aggregator of agents, commands, skills, MCPs & config for Claude Code, Codex & any agentic setup. What's new: 🧠 15 agents + 29 commands: incl. new /doctor (env health-check), /audit-infra (secrets, supply-chain, CI/CD + OWASP/STRIDE), /product-review --harsh, /dream (memory consolidation) 🧩 18 expert skill submodules: now with Quicknode, eth→Solana migration, Ghost Security & Anthropic's defending-code ⚙️ Stack refresh: OtterSec's Anchor 1.0, blueshift's Quasar, Surfpool MCP, SendAI's & more 📚 Extended skill registry: 39 install-on-demand tools covering design, forensics, animation, UX, testing & data, curated from the best of the ecosystem 💚Install: curl -fsSL | bash 🔌 Now on the Claude Code plugin marketplace /plugin install solana-ai-kit@stbr

Superteam Brasil

20,596 görüntüleme • 3 ay önce

THIS GUY BUILT A 24/7 AI COMPANY WITH 7 AGENTS THAT CHECKS 48 TIMES A DAY, PICKS ITS OWN TASKS AND KEEPS WORKING WHILE HE SLEEPS 00:05 the map shows agents moving between the marketplace, research lab and command center, with each one handling a different job inside the same shared system the setup runs on 4 core layers: automatic triggers, shared memory, connected tools and an isolated verifier that checks every result before the next step starts each cycle reads the last 10 log entries, updates open tasks, saves new signals and passes the context forward, so the next agent never starts from zero one agent researches, two execute, another monitors outcomes and a read-only checker reviews the work independently, allowing several workflows to run in parallel without breaking the system bookmark this before everyone stops prompting one agent at a time and starts building AI teams that work, learn and improve around the clock
0:31

THIS GUY BUILT A 24/7 AI COMPANY WITH 7 AGENTS THAT CHECKS 48 TIMES A DAY, PICKS ITS OWN TASKS AND KEEPS WORKING WHILE HE SLEEPS 00:05 the map shows agents moving between the marketplace, research lab and command center, with each one handling a different job inside the same shared system the setup runs on 4 core layers: automatic triggers, shared memory, connected tools and an isolated verifier that checks every result before the next step starts each cycle reads the last 10 log entries, updates open tasks, saves new signals and passes the context forward, so the next agent never starts from zero one agent researches, two execute, another monitors outcomes and a read-only checker reviews the work independently, allowing several workflows to run in parallel without breaking the system bookmark this before everyone stops prompting one agent at a time and starts building AI teams that work, learn and improve around the clock

Gipp 🦅

19,071 görüntüleme • 2 ay önce