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🦀 Crabwalk for OpenClaw🦞 v1.0.5 + v1.0.6 Release 🦀 Subagent Support and Follow Mode 🤖 Subagent Support — Track your agent as they spawn subagents in real-time. Hierarchical layout shows parent→child relationships, collapsible groups in the sidebar, and exec processes rendered as nodes with status-colored edges. 🎯 Follow Mode... show more

Luciano Castillo

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59,009 次观看 • 7 个月前 •via X (Twitter)

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🦀 Introducing Crabwalk 🦀 Open-source companion monitor for Clawdbot. Watch your Clawdbot agents work in real-time: → Live node graph of sessions & action chains → WhatsApp, Telegram, Discord, Slack... → See thinking states, tool calls, responses as they happen → Filter by platform, search by recipient... → More features to come, I just built it during the snowstorm 🚧❄️. Plus a little crab bastard that chases your nodes around 🫡Follow me Luciano Castillo to stay up to date.

🦀 Introducing Crabwalk 🦀 Open-source companion monitor for Clawdbot. Watch your Clawdbot agents work in real-time: → Live node graph of sessions & action chains → WhatsApp, Telegram, Discord, Slack... → See thinking states, tool calls, responses as they happen → Filter by platform, search by recipient... → More features to come, I just built it during the snowstorm 🚧❄️. Plus a little crab bastard that chases your nodes around 🫡Follow me Luciano Castillo to stay up to date.

Luciano Castillo

457,835 次观看 • 7 个月前

Codex team is back in the kitchen with a really nice quality of life upgrade for subagents. With the advent of custom roles, they have also upgraded the TUI experience in two really meaningful ways. > All agents now get a name for better readability > Additionally, the agent role is declared. > Subagent name, role, and status are now color coded. > Subagent rendering was also optimized for readability > /agents slash command shows all agents, even 2+ layers deep. And here's the biggest and most important change. Subagent injection. Before, sometimes the orchestration agent would continue work and lose track of the work of a subagent. Now, when a subagent is blocked or completed, it injects a message back up the chain to ensure that the parent sees the message. This is a really big improvement overall, and leads to much more reliable inter-agent communication, reliability, and DX. In this example, I used the parent agent to spin up a worker agent, which then spawned two more "Spark" agents a second layer deep. I was able to easily tell them apart, switch between the threads, and see exactly what they were prompted. All of this will be available in update 0.105.0 I don't know who JIF is at OpenAI, but they are truly a legend.

Codex team is back in the kitchen with a really nice quality of life upgrade for subagents. With the advent of custom roles, they have also upgraded the TUI experience in two really meaningful ways. > All agents now get a name for better readability > Additionally, the agent role is declared. > Subagent name, role, and status are now color coded. > Subagent rendering was also optimized for readability > /agents slash command shows all agents, even 2+ layers deep. And here's the biggest and most important change. Subagent injection. Before, sometimes the orchestration agent would continue work and lose track of the work of a subagent. Now, when a subagent is blocked or completed, it injects a message back up the chain to ensure that the parent sees the message. This is a really big improvement overall, and leads to much more reliable inter-agent communication, reliability, and DX. In this example, I used the parent agent to spin up a worker agent, which then spawned two more "Spark" agents a second layer deep. I was able to easily tell them apart, switch between the threads, and see exactly what they were prompted. All of this will be available in update 0.105.0 I don't know who JIF is at OpenAI, but they are truly a legend.

am.will

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BREAKING: OpenAI has officially released Agent Mode, allowing users to spin up a virtual desktop and take action. I got early access to ChatGPT Agent Mode and want to share my thoughts. Agent Mode lets you delegate tasks like searching or browsing to an agent inside a virtual desktop inside ChatGPT. You can spin up multiple little “workers” to fire off tasks and keep tabs as they chug through your to-do list AT THE SAME TIME. If it gets stuck or goes off track, you can take over manually. The UI is friendly and keeps the reasoning transparent, so you’re not left guessing what it’s doing or why. It’s not perfect and doesn’t give you as many artifacts as other players in the space, but a strong platform for “let’s see how much I can hand off and supervise”, and a first step toward managing fleets of AI workers instead of pinging a single chatbot for answers. If you’re on ChatGPT Pro, Plus, or Team, look for Agent Mode in the tools dropdown.

BREAKING: OpenAI has officially released Agent Mode, allowing users to spin up a virtual desktop and take action. I got early access to ChatGPT Agent Mode and want to share my thoughts. Agent Mode lets you delegate tasks like searching or browsing to an agent inside a virtual desktop inside ChatGPT. You can spin up multiple little “workers” to fire off tasks and keep tabs as they chug through your to-do list AT THE SAME TIME. If it gets stuck or goes off track, you can take over manually. The UI is friendly and keeps the reasoning transparent, so you’re not left guessing what it’s doing or why. It’s not perfect and doesn’t give you as many artifacts as other players in the space, but a strong platform for “let’s see how much I can hand off and supervise”, and a first step toward managing fleets of AI workers instead of pinging a single chatbot for answers. If you’re on ChatGPT Pro, Plus, or Team, look for Agent Mode in the tools dropdown.

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OpSec will support both normal and validator nodes for the U2U network Amigo BNB, allowing end users to stake their U2U holdings. By running validator nodes on cloudVerse users can participate in U2U staking which is the process of actively participating in transaction validation of the Unicorn Ultra Network Consensus. On the Unicorn Ultra network, anyone with a minimum required balance of *1* U2U can validate and earn staking rewards. This video outlines the process of deployment of U2U normal and validator nodes on the CloudVerse platform. OpSec users will be able to easily manage their balances and rewards as well as have full control over the mode their node operates in. This quick overview video shows what happens once a user clicks deploy and includes the installation steps, Docker container download, node start-up, and real-time validation & streaming. - End of post, beware of scams -

OpSec will support both normal and validator nodes for the U2U network Amigo BNB, allowing end users to stake their U2U holdings. By running validator nodes on cloudVerse users can participate in U2U staking which is the process of actively participating in transaction validation of the Unicorn Ultra Network Consensus. On the Unicorn Ultra network, anyone with a minimum required balance of 1 U2U can validate and earn staking rewards. This video outlines the process of deployment of U2U normal and validator nodes on the CloudVerse platform. OpSec users will be able to easily manage their balances and rewards as well as have full control over the mode their node operates in. This quick overview video shows what happens once a user clicks deploy and includes the installation steps, Docker container download, node start-up, and real-time validation & streaming. - End of post, beware of scams -

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Build better RAG by letting a team of agents extract and connect your reference materials into a knowledge graph. Our new short course, “Agentic Knowledge Graph Construction,” taught by Neo4j Innovation Lead Andreas Kollegger, shows you how. Knowledge graphs are an important way to store information accurately but they are a lot of work to build manually. In this course you’ll learn how to build a team of agents that turn data– in this case product reviews and invoices from suppliers–into structured graphs of entities and relationships for RAG. Learn how agents can automatically handle the time-consuming work of building graphs — extracting entities and relationships (e.g., Product "contains" Assembly, Part "supplied_by" Supplier, Customer review "mentions" Product), deduplicating them, fact-checking them, and committing them to a graph database — so your retrieval system can find right information to generate accurate output. For example, you can use agents to help trace customer complaints directly to specific suppliers, manufacturing processes, and product hierarchies, thus turning fragmented information into queryable business intelligence. Skills you’ll gain: - Build, store, and access knowledge graphs using the Neo4j graph database - Build multi-agent systems using Google’s Agent Development Kit (ADK) - Set up a loop of agentic workflows to propose and refine a graph schema through fact-checking - Connect agent-generated graphs of unstructured and structured data into a unified knowledge graph This course gets into the practicum of why knowledge graphs give more accurate information retrieval than vector search alone, especially for high-stakes applications where precision matters more than fuzzy similarity matching. Sign up here:

Build better RAG by letting a team of agents extract and connect your reference materials into a knowledge graph. Our new short course, “Agentic Knowledge Graph Construction,” taught by Neo4j Innovation Lead Andreas Kollegger, shows you how. Knowledge graphs are an important way to store information accurately but they are a lot of work to build manually. In this course you’ll learn how to build a team of agents that turn data– in this case product reviews and invoices from suppliers–into structured graphs of entities and relationships for RAG. Learn how agents can automatically handle the time-consuming work of building graphs — extracting entities and relationships (e.g., Product "contains" Assembly, Part "supplied_by" Supplier, Customer review "mentions" Product), deduplicating them, fact-checking them, and committing them to a graph database — so your retrieval system can find right information to generate accurate output. For example, you can use agents to help trace customer complaints directly to specific suppliers, manufacturing processes, and product hierarchies, thus turning fragmented information into queryable business intelligence. Skills you’ll gain: - Build, store, and access knowledge graphs using the Neo4j graph database - Build multi-agent systems using Google’s Agent Development Kit (ADK) - Set up a loop of agentic workflows to propose and refine a graph schema through fact-checking - Connect agent-generated graphs of unstructured and structured data into a unified knowledge graph This course gets into the practicum of why knowledge graphs give more accurate information retrieval than vector search alone, especially for high-stakes applications where precision matters more than fuzzy similarity matching. Sign up here:

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15,053 次观看 • 1 年前

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As we reach the end of 2024, we reflect on a year full of milestones and achievements. Here at AIT, we've accomplished many of the goals we set for ourselves, but the work doesn't stop here. We’re determined to start 2025 strong, and we’re excited to begin the year with a major announcement: The official release of AIT's customizable service Assistant! Our Assistant is 80% developed and is on track to go live in Q1 2025. Once fully deployed, it will become an essential part of our customers' websites and other digital platforms, tailored specifically to meet their business needs. The Assistant will serve as the first point of contact for visitors, providing answers to their inquiries. Think of it as a live chat agent, equipped with all the necessary knowledge to assist multiple customers simultaneously. This reduces the need for manual support, saving valuable man-hours that can be redirected toward other business priorities. In today's fast-paced world, time is one of the most valuable resources. We’re excited to share more about what’s been in the works at AIT. Happy New Year! Here's to a successful and productive 2025. The AIT Team

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114,561 次观看 • 1 年前

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Chao Huang

25,232 次观看 • 5 个月前

Multi-agent systems offer incredible potential and unprecedented risks. How do you solve for observability, failure mode analysis, and guardrailing in the era of agents? Today, we’re announcing our Agent Reliability platform to observe, evaluate, guardrail, and improve agents at scale. You can get started with the complete platform for trustworthy agentic AI today for free, and here’s how we’re solving some of the biggest challenges in agent reliability: - Observability redesigned for agents Trace views collapse under complex workflows, so we created the Graph View, Timeline View, and Conversation View to offer rich, intuitive visualizations of agent decisions, tool calls, and conversation flows. This multi-dimensional approach enables teams to pinpoint exactly where and why agents deviate or fail. - Automated Failure Mode Analysis with our new Insights Engine Our Insights Engine ingests your logs, metrics, and agent code to automatically surface nuanced failure modes and their root causes. But knowing the problem is not enough; you need to know how to fix it. Insights Engine delivers actionable fixes and can even apply them automatically. With adaptive learning, your insights become smarter and more relevant as your agents evolve. - Evaluating Agents Across Multiple Dimensions Agentic systems interact across complex pathways, and evaluating their performance requires new metrics that reflect this increasing complexity. To deliver comprehensive agentic measurements, we’ve added more out-of-the-box agent metrics like flow adherence, agent flow, agent efficiency, and more. For specialized domains and unique workflows, custom metrics powered by our new Luna-2 small language models can be rapidly designed and fine-tuned for your specific use case. - Real-Time Guardrails Powered by Luna-2 As AI agents become more autonomous and complex, failures like hallucinations or unsafe actions increase dramatically. Without real-time guardrails, these errors will hurt your user experience and brand reputation. Our Luna-2 family of small language models is purpose-built to provide low-latency, cost-effective guardrails that actively stop agent errors before they happen. With support for out-of-the-box and custom metrics, Luna-2 enables enterprises to enforce safety, compliance, and reliability at scale. Enterprises running hundreds of agents and processing hundreds of millions of queries daily already rely on Galileo’s Agent Reliability platform to protect their users, safeguard brand trust, and accelerate innovation. Agent Reliability is available starting today. Try it for free and experience the new standard in AI reliability. Learn more below 👇

Galileo

1,276,298 次观看 • 1 年前

What does the reputation model look like for agents? (alpha leak below) And how do we associate the proofs that we have about human beings with the agents who represent them? You may have heard of a process called KYC or Know Your Customer. That's very common with traditional financial applications and services. We have introduced a concept that we call KYA or Know Your Agent, which is a structured way to be able to express what model, how data was used in training, who the deployer is, what entities this agent instance is accountable back to, providing not only provenance but identity of the associated organization or entity. That's also another root of trust that we think about a lot: Enterprises and organizations tied back to things like their domains. To share a little bit of an alpha leak here, a product that we're excited to be rolling out in the next few weeks will allow our enterprise partners to more easily verify and prove the traits and capabilities of their teams as well as their counterparties. On the agent front, that makes it really easy to prove that an agent is acting on behalf of a given business or entity. We've already seen lawsuits where the absence of such technology has been a huge risk, such as with airlines that incorporate ChatGPT wrappers in their support pages. And then those AI enabled interactions end up making up plane tickets that don't exist and those airlines have to honor them. As small of an example as that might be, being able to prove agent accountability also unlocks a huge set of opportunities for use in enterprise for those agent to agent interactions. The Deep Trust Framework that our team has put together that we're excited to be bringing into a friendly SDK form in the next few weeks for some of our partners includes those reputation based capabilities, so how you can basically keep track of the interactions an agent has had, associate all of that to the entity to which they're accountable, and then that creates a sustainable reputation model for these agent to agent Interactions. Source: Billions CEO Evin McMullen evin speaking at House of Chimera Spaces Event Dec 3, 2025

What does the reputation model look like for agents? (alpha leak below) And how do we associate the proofs that we have about human beings with the agents who represent them? You may have heard of a process called KYC or Know Your Customer. That's very common with traditional financial applications and services. We have introduced a concept that we call KYA or Know Your Agent, which is a structured way to be able to express what model, how data was used in training, who the deployer is, what entities this agent instance is accountable back to, providing not only provenance but identity of the associated organization or entity. That's also another root of trust that we think about a lot: Enterprises and organizations tied back to things like their domains. To share a little bit of an alpha leak here, a product that we're excited to be rolling out in the next few weeks will allow our enterprise partners to more easily verify and prove the traits and capabilities of their teams as well as their counterparties. On the agent front, that makes it really easy to prove that an agent is acting on behalf of a given business or entity. We've already seen lawsuits where the absence of such technology has been a huge risk, such as with airlines that incorporate ChatGPT wrappers in their support pages. And then those AI enabled interactions end up making up plane tickets that don't exist and those airlines have to honor them. As small of an example as that might be, being able to prove agent accountability also unlocks a huge set of opportunities for use in enterprise for those agent to agent interactions. The Deep Trust Framework that our team has put together that we're excited to be bringing into a friendly SDK form in the next few weeks for some of our partners includes those reputation based capabilities, so how you can basically keep track of the interactions an agent has had, associate all of that to the entity to which they're accountable, and then that creates a sustainable reputation model for these agent to agent Interactions. Source: Billions CEO Evin McMullen evin speaking at House of Chimera Spaces Event Dec 3, 2025

Billions Network

68,503 次观看 • 8 个月前

✨"Cubism Editor 5.4.00 alpha1" limited release until September 14, 2026✨ We are also releasing Cubism 5 SDK for Unity R7 alpha1, which supports these new features, at the same time. Check out the accompanying digest video to learn about the main new features. 🔥[New Features] ✏️ [Parameter Controller SDK Support] Parameter controllers (IK) are now supported in the SDK. You can configure them directly on the model and export them as runtime files. Additionally, a new "target-only" controller can be defined to allow the controller to follow a path. ✏️ [Model State Set] A new model state set feature has been added. You can register working states in a dedicated palette, enabling you to recall specific states of visibility, lock, and parameter values with a single click. This helps you work more efficiently by allowing you to switch between states tailored to different tasks. ✏️[Expanded Editing Support for External Application Integration API ] The external application integration API has been expanded to include object editing and more. You can now integrate an API to directly add and edit parts, deformers, and parameters on models in the editor. ✏️[Enhanced automatic layout for texture atlases] The automatic layout algorithm for texture atlas editing has been completely redesigned. This enables more efficient packing with less unused space. You can configure the layout settings individually for each texture, allowing for flexible layouts. [How to use Cubism 5.4 alpha] Please see the announcement page for details on downloading and feedback. ⚠Notes on using the alpha version - The alpha version is provided for the purpose of gathering feedback on the usability and performance of new features. - Usage Period: Until September 14, 2026. - Please be sure to create a backup, as there is a possibility of data corruption. - Alpha version data and SDK outputs are not guaranteed to function properly and we do not provide support for it. #Live2D #cubism54_alpha

✨"Cubism Editor 5.4.00 alpha1" limited release until September 14, 2026✨ We are also releasing Cubism 5 SDK for Unity R7 alpha1, which supports these new features, at the same time. Check out the accompanying digest video to learn about the main new features. 🔥[New Features] ✏️ [Parameter Controller SDK Support] Parameter controllers (IK) are now supported in the SDK. You can configure them directly on the model and export them as runtime files. Additionally, a new "target-only" controller can be defined to allow the controller to follow a path. ✏️ [Model State Set] A new model state set feature has been added. You can register working states in a dedicated palette, enabling you to recall specific states of visibility, lock, and parameter values with a single click. This helps you work more efficiently by allowing you to switch between states tailored to different tasks. ✏️[Expanded Editing Support for External Application Integration API ] The external application integration API has been expanded to include object editing and more. You can now integrate an API to directly add and edit parts, deformers, and parameters on models in the editor. ✏️[Enhanced automatic layout for texture atlases] The automatic layout algorithm for texture atlas editing has been completely redesigned. This enables more efficient packing with less unused space. You can configure the layout settings individually for each texture, allowing for flexible layouts. [How to use Cubism 5.4 alpha] Please see the announcement page for details on downloading and feedback. ⚠Notes on using the alpha version - The alpha version is provided for the purpose of gathering feedback on the usability and performance of new features. - Usage Period: Until September 14, 2026. - Please be sure to create a backup, as there is a possibility of data corruption. - Alpha version data and SDK outputs are not guaranteed to function properly and we do not provide support for it. #Live2D #cubism54_alpha

Live2D

100,494 次观看 • 1 个月前

New short course: Practical Multi AI Agents and Advanced Use Cases with crewAI. Learn to build and deploy advanced agent-based systems in real applications in this course, created with CrewAI and taught by its founder, João Moura! (Disclosure: I've made a small seed investment in CrewAI.) In this course, you’ll learn how to create advanced agent-based apps that use external tools, do performance testing, can be trained with human feedback, and perform multiple tasks with different large language models. You will build several practical agentic apps that provide real business value, such as an automated project planning system, lead scoring and engagement pipeline, customer support data analysis, and a robust content creation system. In detail, you will learn how to: - Create these multi-agent systems with the building blocks of tasks, agents, and crews, along with the different things that make them work, such as caching, memory, and guardrails. - Integrate your multi-agent application with internal and external systems. - Connect multiple agents in complex setups, including parallel, sequential, and hybrid configurations, and create flows involving multiple agentic applications working together. - Test your agentic workflow and train it using human feedback to optimize its performance for better and more consistent results. - Work with multiple LLMs in your multi-agent system, using the appropriate model sizes and providers to fit each agent’s specific task. - Start a project from scratch in your environment and prepare it for deployment. You’ll also learn from an interview between João and Jacob Wilson, the Commercial GenAI Principal at PwC , in which they discuss deploying agentic workflows in real industry use cases. By the end of this course, you will be equipped to start building custom multi-agentic systems for your work. Please sign up here!

New short course: Practical Multi AI Agents and Advanced Use Cases with crewAI. Learn to build and deploy advanced agent-based systems in real applications in this course, created with CrewAI and taught by its founder, João Moura! (Disclosure: I've made a small seed investment in CrewAI.) In this course, you’ll learn how to create advanced agent-based apps that use external tools, do performance testing, can be trained with human feedback, and perform multiple tasks with different large language models. You will build several practical agentic apps that provide real business value, such as an automated project planning system, lead scoring and engagement pipeline, customer support data analysis, and a robust content creation system. In detail, you will learn how to: - Create these multi-agent systems with the building blocks of tasks, agents, and crews, along with the different things that make them work, such as caching, memory, and guardrails. - Integrate your multi-agent application with internal and external systems. - Connect multiple agents in complex setups, including parallel, sequential, and hybrid configurations, and create flows involving multiple agentic applications working together. - Test your agentic workflow and train it using human feedback to optimize its performance for better and more consistent results. - Work with multiple LLMs in your multi-agent system, using the appropriate model sizes and providers to fit each agent’s specific task. - Start a project from scratch in your environment and prepare it for deployment. You’ll also learn from an interview between João and Jacob Wilson, the Commercial GenAI Principal at PwC , in which they discuss deploying agentic workflows in real industry use cases. By the end of this course, you will be equipped to start building custom multi-agentic systems for your work. Please sign up here!

Andrew Ng

341,204 次观看 • 1 年前

One of my best engineers just showed me how to set up OpenClaw securely & without a Mac Mini. Here's his step-by-step: 1) Spin up a VPS on Hetzner It's a virtual server in the cloud. basically a computer you rent for $5-10/month. Pick 8GB RAM, Ubuntu, US East. Takes 2 minutes. 2) Install Tailscale This makes your server invisible to the public internet. Think of it like moving from a house on Google Maps into a gated community where only your devices can get in. Without this, bots start attacking your server within seconds of it going live. 3) Harden the server SSH keys only. Firewall. Intrusion prevention. Auto security updates. CJ actually uses AI to red team his own servers. Tells it to try and break in, then patches whatever it finds. 4) Install OpenClaw🦞 and run the onboarding. You pick your model provider, connect Telegram via BotFather, and configure hooks that give your agent long-term memory. The hooks auto-save sessions and context so the agent gets smarter over time. 5) Set up the gateway This is the piece that makes it actually powerful. It's a message bus that lets your main agent talk to sub-agents, receive messages from Telegram/Discord/Slack, and orchestrate everything. this is what keeps it running 24/7. 6) Hatch your claw and start training it Dump as much info about yourself as possible. tell it your preferences, your workflows, your tools. CJ's agent monitors his email, Slack, and manages his to-do list autonomously. Watch the video for the full break-down & follow CJ Hess for more AI engineering sauce.

One of my best engineers just showed me how to set up OpenClaw securely & without a Mac Mini. Here's his step-by-step: 1) Spin up a VPS on Hetzner It's a virtual server in the cloud. basically a computer you rent for $5-10/month. Pick 8GB RAM, Ubuntu, US East. Takes 2 minutes. 2) Install Tailscale This makes your server invisible to the public internet. Think of it like moving from a house on Google Maps into a gated community where only your devices can get in. Without this, bots start attacking your server within seconds of it going live. 3) Harden the server SSH keys only. Firewall. Intrusion prevention. Auto security updates. CJ actually uses AI to red team his own servers. Tells it to try and break in, then patches whatever it finds. 4) Install OpenClaw🦞 and run the onboarding. You pick your model provider, connect Telegram via BotFather, and configure hooks that give your agent long-term memory. The hooks auto-save sessions and context so the agent gets smarter over time. 5) Set up the gateway This is the piece that makes it actually powerful. It's a message bus that lets your main agent talk to sub-agents, receive messages from Telegram/Discord/Slack, and orchestrate everything. this is what keeps it running 24/7. 6) Hatch your claw and start training it Dump as much info about yourself as possible. tell it your preferences, your workflows, your tools. CJ's agent monitors his email, Slack, and manages his to-do list autonomously. Watch the video for the full break-down & follow CJ Hess for more AI engineering sauce.

Alex Lieberman

64,999 次观看 • 6 个月前

This little device lets your agents do what they do best, whilst making sure you approve every important action. This is a Ledger Nano Gen5, a hardware signer that keeps your accounts secure. You can install a CLI and a set of skills in your projects. These will enable your agents to send their plan to the signer, so you can approve it. This is awesome: 1. You can have an automated agentic workflow 2. Your agents can't make costly mistakes Check the video I recorded to see how this works. You can run all of this in two commands: 1. Install the CLI 2. Install the skills for your agent From here, the agent can query my Ethereum accounts, check balances, and even initiate transactions as long as my Ledger Nano Gen5 is plugged into the computer. My keys are never stored in my computer and never shared with the agent. This is huge! Also, while the agent can set up transactions, it can't execute them unless a human approves them using the device. Pretty awesome! Thanks to the Ledger team for partnering with me on this post.

This little device lets your agents do what they do best, whilst making sure you approve every important action. This is a Ledger Nano Gen5, a hardware signer that keeps your accounts secure. You can install a CLI and a set of skills in your projects. These will enable your agents to send their plan to the signer, so you can approve it. This is awesome: 1. You can have an automated agentic workflow 2. Your agents can't make costly mistakes Check the video I recorded to see how this works. You can run all of this in two commands: 1. Install the CLI 2. Install the skills for your agent From here, the agent can query my Ethereum accounts, check balances, and even initiate transactions as long as my Ledger Nano Gen5 is plugged into the computer. My keys are never stored in my computer and never shared with the agent. This is huge! Also, while the agent can set up transactions, it can't execute them unless a human approves them using the device. Pretty awesome! Thanks to the Ledger team for partnering with me on this post.

Santiago

44,296 次观看 • 2 个月前

Ferris State HC Tony Annese - Cardinal Rules to Successful Coaching 1. Serve the heart of your players, not their talents 2. Find the good in every player and enthusiastically celebrate whatever strength that individual displays 3. Show compassion and empathy for our players and provide the love and support they need to flourish 4. Love your position group and take care of them like they are your own children 5. Master your relationships with the Jimmy's and Joe's before you focus on the X's and O's 6. Be a Life Coach - Provide spiritual, emotional, and social awareness and support for the players - Understand how vulnerable young people are at this stage and provide the support they need to navigate through the challenges they face 7. Be a Doer! -Spend time with the Head Coach and determine what you can do to help him and the team 8. Be passionate about your role as a coach - Realize that you will impact more people in one year than most people do in a lifetime 9. Make the coaching staff your best friends - You are blessed to have the opportunity to connect with people who are working toward a common goal. 10. Be loyal to the University, Athletic Department, Coaching Staff, Head Coach, and the Players you serve.

Ferris State HC Tony Annese - Cardinal Rules to Successful Coaching 1. Serve the heart of your players, not their talents 2. Find the good in every player and enthusiastically celebrate whatever strength that individual displays 3. Show compassion and empathy for our players and provide the love and support they need to flourish 4. Love your position group and take care of them like they are your own children 5. Master your relationships with the Jimmy's and Joe's before you focus on the X's and O's 6. Be a Life Coach - Provide spiritual, emotional, and social awareness and support for the players - Understand how vulnerable young people are at this stage and provide the support they need to navigate through the challenges they face 7. Be a Doer! -Spend time with the Head Coach and determine what you can do to help him and the team 8. Be passionate about your role as a coach - Realize that you will impact more people in one year than most people do in a lifetime 9. Make the coaching staff your best friends - You are blessed to have the opportunity to connect with people who are working toward a common goal. 10. Be loyal to the University, Athletic Department, Coaching Staff, Head Coach, and the Players you serve.

James Light

104,247 次观看 • 8 个月前

long time no posting, here's some of the stuff we released in helium recently: - customizable keyboard shortcuts on all platforms - automatic updates on windows - frameless mode (previously zen mode), with floating sidebar, is now out of beta and included in settings by default - improved fingerprint noising: fixed the canvas noising algorithm and added protections against analysis attacks (thank you Cynthia 🐈 for your report, research, and assistance) - tab URL copying, one or multiple, formatted as a list with line breaks - manual tab hibernation, with an option to hibernate all tabs except for selected/active ones - an option to close tabs to the left (or above, in vertical layout) - redesigned toast notifications, now anchored to the active web page, and no longer blinding in dark mode - toast notification about newly opened background tabs in frameless mode (can be disabled in settings) - redesigned the infobar, it no longer looks out of place - improved QR code generation, now it's actually useful - downloads bubble is now shown instead of the full page whenever applicable - kagi search now supports reverse image search from image context menu - frameless mode animations are now smoother - better color contrast in light and dark modes - a lot of bug fixes and other minor improvements all of these changes are present in the latest version of helium. if you're using helium on windows, please update to the latest version, so your browser can be updated automatically from now on!

long time no posting, here's some of the stuff we released in helium recently: - customizable keyboard shortcuts on all platforms - automatic updates on windows - frameless mode (previously zen mode), with floating sidebar, is now out of beta and included in settings by default - improved fingerprint noising: fixed the canvas noising algorithm and added protections against analysis attacks (thank you Cynthia 🐈 for your report, research, and assistance) - tab URL copying, one or multiple, formatted as a list with line breaks - manual tab hibernation, with an option to hibernate all tabs except for selected/active ones - an option to close tabs to the left (or above, in vertical layout) - redesigned toast notifications, now anchored to the active web page, and no longer blinding in dark mode - toast notification about newly opened background tabs in frameless mode (can be disabled in settings) - redesigned the infobar, it no longer looks out of place - improved QR code generation, now it's actually useful - downloads bubble is now shown instead of the full page whenever applicable - kagi search now supports reverse image search from image context menu - frameless mode animations are now smoother - better color contrast in light and dark modes - a lot of bug fixes and other minor improvements all of these changes are present in the latest version of helium. if you're using helium on windows, please update to the latest version, so your browser can be updated automatically from now on!

Helium

154,633 次观看 • 2 个月前

Maple is preparing for the release of a co-working agent. You install it locally and it works with your files, whether it's office work or building websites and apps. It's a turnkey solution, as easy as Claude Code, that keeps your data secure and private, no data sharing with closed AI labs. This is THE sovereign AI app for individuals and businesses who want powerful AI while retaining ownership of their information. Why build an agent into the Maple app when other agents already exist? Easy, we want to give you control over your work. We don't have a business plan that incorporates making money off our users' data. In the age of AI, your information, whether it's personal or company trade secrets, is the single thing that differentiates you from everyone else. We all have access to AI that can build a professional website for selling shoes. But your strategy and network for how you sell shoes should not be shared with your competitors. Sovereignty is the path to protecting what makes you, you. Maple sits at the intersection of Usability and Sovereignty. Maple gives you the best tools that are both easy to use and maintain your data sovereignty. Sovereign for one, sovereign for all. It has been a journey to get here. We brought to market the very first personal chatbot with end-to-end encryption using TEEs in late 2024. Prior to that there were proofs of concept but no full product offerings. Every other AI chat product on the market handled your data in plain text, either selling you a service to get your data or asking you to trust that they won't snoop on you. Quickly people found Maple and latched onto its open-source code and verifiable encryption. We didn't stop there. You may remember earlier this year we teased a product called "Maple Agent" and opened up a waiting list. That product is a mobile app that acts as your AI "friend", maintaining one long continuous chat, and getting to know you over time. I dislike using the word "friend" there, but it's the best way to convey the UX in a few words. AI is a tool, always has been, always will be. Any kind of friendly personality on top is just synthetic. In our testing, the UX of Maple Agent is really powerful for what it does. Think about the many short AI chats you have in your favorite app, whether it's looking up a historical fact or asking advice about a topic. With Maple Agent, those all go away in favor of the long-running chat with the friendly agent. It's like you have your own personal assistant who knows you so well and can look up anything for you. When I ask AI certain questions, I want to ask an expert who already understands my situation so I'm not repeating myself for the 100th time. That's the amazing value the personal agent brings to the table. We still see great utility for a personal agent like the "Maple Agent". Thousands of people on the waiting list, hoping to get their hands on it, agree that the concept is worth exploring and trying out. We were constrained in launching it due to a few circumstances, one of them being access to the scale of compute needed to power it. We have a clear path laid out for how to get there, but today is not the day to execute on that. It will be in the near future. Instead we have a different agent ready to go that we think is also incredible. We now have an agentic harness inside of the Maple Research app. This thing is a powerhouse. It even builds and publishes its own software releases. The agent in Maple Research works with your local filesystem, speaks to the largest open models running in TEEs, utilizes local models for certain tasks, is compatible with MCP tools, has an API for connecting to anything you need, and also supports the ACP protocol, which means it can be extended in the future to speak to other tools like Claude Code, Codex, and local models running on your own hardware. A big unlock for us was the Goose Development Kit, which powers the core of our agent harness. More on that to come as we publish articles and documentation later about the agent. The agent inside Maple Research doesn't have a name. At least not yet, not sure if it ever will. For now we call it "Chat Mode" and "Agent Mode". Think of this as the workhorse, the truck, the heavy lifter. Our other "Agent", the phone app, is your sidekick in your pocket, ready to help with quick things and ongoing conversations about life. I am incredibly excited about the Maple Research Agent. While I'm already seeing great results using it for internal work items, I'm especially thrilled about the personal health and wellness work it's doing for me. I know there are plenty of apps out there for compiling wellness data, but I'm having it build a tool tailored specifically for what I need, without the extra fluff. And none of my health data is being donated to the closed AI labs or sent to advertisers. I know that the AI logic is not being silently adjusted to fit the whims of a large corporation that has paid for product placement. It's me, state of the art AI, and my data. That's how I want it. Maple's new agent makes that possible. We can't wait for you to try it out. If you want early access, comment here, email us, reach out in some way. To those on the other agent waitlist, you're already in the queue. Thanks for reading this lengthy update. :)

Maple is preparing for the release of a co-working agent. You install it locally and it works with your files, whether it's office work or building websites and apps. It's a turnkey solution, as easy as Claude Code, that keeps your data secure and private, no data sharing with closed AI labs. This is THE sovereign AI app for individuals and businesses who want powerful AI while retaining ownership of their information. Why build an agent into the Maple app when other agents already exist? Easy, we want to give you control over your work. We don't have a business plan that incorporates making money off our users' data. In the age of AI, your information, whether it's personal or company trade secrets, is the single thing that differentiates you from everyone else. We all have access to AI that can build a professional website for selling shoes. But your strategy and network for how you sell shoes should not be shared with your competitors. Sovereignty is the path to protecting what makes you, you. Maple sits at the intersection of Usability and Sovereignty. Maple gives you the best tools that are both easy to use and maintain your data sovereignty. Sovereign for one, sovereign for all. It has been a journey to get here. We brought to market the very first personal chatbot with end-to-end encryption using TEEs in late 2024. Prior to that there were proofs of concept but no full product offerings. Every other AI chat product on the market handled your data in plain text, either selling you a service to get your data or asking you to trust that they won't snoop on you. Quickly people found Maple and latched onto its open-source code and verifiable encryption. We didn't stop there. You may remember earlier this year we teased a product called "Maple Agent" and opened up a waiting list. That product is a mobile app that acts as your AI "friend", maintaining one long continuous chat, and getting to know you over time. I dislike using the word "friend" there, but it's the best way to convey the UX in a few words. AI is a tool, always has been, always will be. Any kind of friendly personality on top is just synthetic. In our testing, the UX of Maple Agent is really powerful for what it does. Think about the many short AI chats you have in your favorite app, whether it's looking up a historical fact or asking advice about a topic. With Maple Agent, those all go away in favor of the long-running chat with the friendly agent. It's like you have your own personal assistant who knows you so well and can look up anything for you. When I ask AI certain questions, I want to ask an expert who already understands my situation so I'm not repeating myself for the 100th time. That's the amazing value the personal agent brings to the table. We still see great utility for a personal agent like the "Maple Agent". Thousands of people on the waiting list, hoping to get their hands on it, agree that the concept is worth exploring and trying out. We were constrained in launching it due to a few circumstances, one of them being access to the scale of compute needed to power it. We have a clear path laid out for how to get there, but today is not the day to execute on that. It will be in the near future. Instead we have a different agent ready to go that we think is also incredible. We now have an agentic harness inside of the Maple Research app. This thing is a powerhouse. It even builds and publishes its own software releases. The agent in Maple Research works with your local filesystem, speaks to the largest open models running in TEEs, utilizes local models for certain tasks, is compatible with MCP tools, has an API for connecting to anything you need, and also supports the ACP protocol, which means it can be extended in the future to speak to other tools like Claude Code, Codex, and local models running on your own hardware. A big unlock for us was the Goose Development Kit, which powers the core of our agent harness. More on that to come as we publish articles and documentation later about the agent. The agent inside Maple Research doesn't have a name. At least not yet, not sure if it ever will. For now we call it "Chat Mode" and "Agent Mode". Think of this as the workhorse, the truck, the heavy lifter. Our other "Agent", the phone app, is your sidekick in your pocket, ready to help with quick things and ongoing conversations about life. I am incredibly excited about the Maple Research Agent. While I'm already seeing great results using it for internal work items, I'm especially thrilled about the personal health and wellness work it's doing for me. I know there are plenty of apps out there for compiling wellness data, but I'm having it build a tool tailored specifically for what I need, without the extra fluff. And none of my health data is being donated to the closed AI labs or sent to advertisers. I know that the AI logic is not being silently adjusted to fit the whims of a large corporation that has paid for product placement. It's me, state of the art AI, and my data. That's how I want it. Maple's new agent makes that possible. We can't wait for you to try it out. If you want early access, comment here, email us, reach out in some way. To those on the other agent waitlist, you're already in the queue. Thanks for reading this lengthy update. :)

Mark

44,707 次观看 • 1 个月前

Triton Poker Series is back, and this time, we're taking you to the exotic island of Jeju for a showdown like never before! Mark your calendars for March 2024, as Triton Poker takes over Jeju with high-stakes action and unforgettable action. Tune in to us live from Jeju and witness legends being made, fortunes being won, and the poker world coming alive! Catch all the action live at the tables! Triton Poker SHRS Jeju is a tournament you won't want to miss! Set those reminders ⏰ and follow the link in our bio for more info! 📌 Landing Casino, Shinhwa World 🗓️ 5th - 21st March, 2024

Triton Poker Series is back, and this time, we're taking you to the exotic island of Jeju for a showdown like never before! Mark your calendars for March 2024, as Triton Poker takes over Jeju with high-stakes action and unforgettable action. Tune in to us live from Jeju and witness legends being made, fortunes being won, and the poker world coming alive! Catch all the action live at the tables! Triton Poker SHRS Jeju is a tournament you won't want to miss! Set those reminders ⏰ and follow the link in our bio for more info! 📌 Landing Casino, Shinhwa World 🗓️ 5th - 21st March, 2024

Triton Poker

209,685 次观看 • 2 年前