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Introducing SciSpace BioMed Agent! Biomedical research keeps getting more complex, and the tools rarely keep up. So we decided to push things forward and build an agent that actually does. Whether you're working in Genomics, Single-Cell, Clinical Genomics, Microbiology, Pharmacology, Molecular Biology, or Multi-Omics, the agent adapts to your...

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SciSpace

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864,631 görüntüleme • 7 ay önce •via X (Twitter)

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Introducing Skills in SciSpace Agent. Specialized modes built for specific research workflows. Describe the task, and the right workflow activates automatically. Yes, the right Skill gets loaded based on what you need. Built to simplify multi-step research work and reduce friction around execution. Skills are now live. Try it inside SciSpace Agent.
0:40

Introducing Skills in SciSpace Agent. Specialized modes built for specific research workflows. Describe the task, and the right workflow activates automatically. Yes, the right Skill gets loaded based on what you need. Built to simplify multi-step research work and reduce friction around execution. Skills are now live. Try it inside SciSpace Agent.

SciSpace

43,422 görüntüleme • 5 ay önce

Introducing "Save to Notebook" Now you can save agent outputs directly into SciSpace Notebook — all content and citations automatically transferred. No more copy-pasting, just seamless research workflows. Collect, refine, and get publish-ready in no time.
0:27

Introducing "Save to Notebook" Now you can save agent outputs directly into SciSpace Notebook — all content and citations automatically transferred. No more copy-pasting, just seamless research workflows. Collect, refine, and get publish-ready in no time.

SciSpace

18,174 görüntüleme • 6 ay önce

Create your presentations with evidence-based data. SciSpace Agent does that. Try it out today!
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Create your presentations with evidence-based data. SciSpace Agent does that. Try it out today!

SciSpace

192,517 görüntüleme • 4 ay önce

Browse. Choose. Run. Agent Gallery gives you ready‑made workflows and tasks you can run instantly to accelerate your research.
1:00

Browse. Choose. Run. Agent Gallery gives you ready‑made workflows and tasks you can run instantly to accelerate your research.

SciSpace

49,157 görüntüleme • 7 ay önce

The depth of your research insights depends entirely on the precision of your prompts. In Episode 5 of Decoding Data Insights, Dr. Lyndon Walker sits down to demonstrate how to find sources, run advanced regressions and mediation analysis, and decode highly transparent, reproducible workflows with SciSpace Agent. Trusted by 9.6M+ researchers worldwide. Sign up for free and see how it works:
3:16

The depth of your research insights depends entirely on the precision of your prompts. In Episode 5 of Decoding Data Insights, Dr. Lyndon Walker sits down to demonstrate how to find sources, run advanced regressions and mediation analysis, and decode highly transparent, reproducible workflows with SciSpace Agent. Trusted by 9.6M+ researchers worldwide. Sign up for free and see how it works:

SciSpace

167,924 görüntüleme • 29 gün önce

Claude Code now supports agent teams (in research preview) Instead of a single agent working through a task sequentially, a lead agent can delegate to multiple teammates that work in parallel to research, debug, and build while coordinating with each other. Try it out today by enabling agent teams in your settings.json!
0:40

Claude Code now supports agent teams (in research preview) Instead of a single agent working through a task sequentially, a lead agent can delegate to multiple teammates that work in parallel to research, debug, and build while coordinating with each other. Try it out today by enabling agent teams in your settings.json!

Lydia Hallie ✨

1,442,364 görüntüleme • 5 ay önce

We’re entering the 10x speed of research publication workflow with AI. SciSpace (SciSpace), the first AI Agent built exclusively for the scientific community, is releasing so many inredibly useful features. 🎯 This is the AI Agent that can use 150+ tools, 59 databases, and 280M+ papers A few weeks back they launched BioMed Agent - It can design entire molecular biology workflows and even create publication-ready illustrations in a single prompt. This is its new domain-specialized AI co-scientist that sits on top of the existing SciSpace Agent and automates full biomedical workflows, from raw data and papers to analysis, decisions, and the final production-grade illustrations. You just need to give it 1 prompt. And today the added the following - Library Search, so it can search and analyze the PDFs already sitting in My Library, letting people ask questions across their own paper pile while keeping it private. - Now connects directly to Zotero, so the Agent can pull and work with the papers you already saved there without manual uploads. - For bigger prompts, it auto-triggers a Report Writing Sub-Agent that turns the chat into a structured research-style report, which is way cleaner for literature reviews and long summaries. - And when you get something worth keeping, Save to Notebook lets you store the output as .md notes with citations in My notebooks, so the work becomes reusable research notes instead of disappearing into chat. Behind the scenes, it indexes the PDF text, pulls a few relevant chunks for the question, then writes an answer grounded on those chunks.
0:22

We’re entering the 10x speed of research publication workflow with AI. SciSpace (SciSpace), the first AI Agent built exclusively for the scientific community, is releasing so many inredibly useful features. 🎯 This is the AI Agent that can use 150+ tools, 59 databases, and 280M+ papers A few weeks back they launched BioMed Agent - It can design entire molecular biology workflows and even create publication-ready illustrations in a single prompt. This is its new domain-specialized AI co-scientist that sits on top of the existing SciSpace Agent and automates full biomedical workflows, from raw data and papers to analysis, decisions, and the final production-grade illustrations. You just need to give it 1 prompt. And today the added the following - Library Search, so it can search and analyze the PDFs already sitting in My Library, letting people ask questions across their own paper pile while keeping it private. - Now connects directly to Zotero, so the Agent can pull and work with the papers you already saved there without manual uploads. - For bigger prompts, it auto-triggers a Report Writing Sub-Agent that turns the chat into a structured research-style report, which is way cleaner for literature reviews and long summaries. - And when you get something worth keeping, Save to Notebook lets you store the output as .md notes with citations in My notebooks, so the work becomes reusable research notes instead of disappearing into chat. Behind the scenes, it indexes the PDF text, pulls a few relevant chunks for the question, then writes an answer grounded on those chunks.

Rohan Paul

11,574 görüntüleme • 6 ay önce

Here is how simple it is to build a UI front-end for an AI agent (assuming you are using . The video here is 90 seconds and will show you everything you need to connect an agent to a web app: 1. Set up CopilotKit🪁 in your app 1. Copy the agent's localhost URL from LangGraph Studio 2. Paste that URL into a CopilotKit🪁 remote endpoint That's all you need to get a front-end to interact with the agent! The secret sauce here is CoAgents, an open-source library. You can use CoAgents to integrate any agent with your web application. Here is what you get: • Human-in-the-loop to steer and correct the agent • Stream intermediate agent state • Real-time state sharing between the agent and the application • Agentic generative UI to build trust that the agent is on the right path Watch the attached demo so you see it in action.
1:32

Here is how simple it is to build a UI front-end for an AI agent (assuming you are using . The video here is 90 seconds and will show you everything you need to connect an agent to a web app: 1. Set up CopilotKit🪁 in your app 1. Copy the agent's localhost URL from LangGraph Studio 2. Paste that URL into a CopilotKit🪁 remote endpoint That's all you need to get a front-end to interact with the agent! The secret sauce here is CoAgents, an open-source library. You can use CoAgents to integrate any agent with your web application. Here is what you get: • Human-in-the-loop to steer and correct the agent • Stream intermediate agent state • Real-time state sharing between the agent and the application • Agentic generative UI to build trust that the agent is on the right path Watch the attached demo so you see it in action.

Santiago

46,109 görüntüleme • 1 yıl önce

✨ 🤝 Introducing SciSpace for Teams The Smarter Way to Collaborate on Research 🔬 A powerful new feature designed to make research teamwork effortless. With SciSpace for Teams, you can: 📁 Create Shared Libraries ✍️ Co-write in real time 🔍 Discover, save, and organize papers together 🔗 See how it works and try it out today:
1:06

✨ 🤝 Introducing SciSpace for Teams The Smarter Way to Collaborate on Research 🔬 A powerful new feature designed to make research teamwork effortless. With SciSpace for Teams, you can: 📁 Create Shared Libraries ✍️ Co-write in real time 🔍 Discover, save, and organize papers together 🔗 See how it works and try it out today:

SciSpace

820,900 görüntüleme • 1 yıl önce

Introducing the Legora Agent: the execution engine at the core of the Legora aOS™. Most legal AI responds to prompts. The Agent executes objectives. You give it a goal and it builds a plan, presents it for approval, then carries the work out end-to-end — selecting the right tools as it goes, whether that's research, drafting, or review. It keeps working while you review, instead of waiting for the next prompt — while you're with clients, with family, or even while you sleep. It isn’t a tool you use. It's a super-associate you supervise. The Legora Agent is live today. Read the announcement here:
1:27

Introducing the Legora Agent: the execution engine at the core of the Legora aOS™. Most legal AI responds to prompts. The Agent executes objectives. You give it a goal and it builds a plan, presents it for approval, then carries the work out end-to-end — selecting the right tools as it goes, whether that's research, drafting, or review. It keeps working while you review, instead of waiting for the next prompt — while you're with clients, with family, or even while you sleep. It isn’t a tool you use. It's a super-associate you supervise. The Legora Agent is live today. Read the announcement here:

Legora

36,858 görüntüleme • 1 ay önce

PantheonOS allows any biologist to perform complex data analyses of emerging single cell, multi-omics and spatial transcriptomics datasets end to end through AI agent and human collaboration. We are releasing six replays of use cases trajectories. Each "trajectory" is a complete end-to-end run, from prompt to analysis, to figures, and finally to report, and in fully inspectable and reproducible manner. See the six user cases in our PantheonOS Gallery: 1. 3D mouse embryo analysis: Tangram deconvolution and PyVista-based 3D visualization of E6 mouse embryo spatial transcriptomics data 2. 3D human fetal heart analysis: Spatial mapping of heart disease gene patterns using MERFISH data 3. Multi-omics spatial integration: Single cell multi-omics-to-spatial mapping with MOSCOT optimal transport 4. Gene panel design: 1000-plex immune-oncology MERFISH gene panel optimization 5. Cell segmentation benchmarking: Comparative evaluation of Cellpose-SAM, InstanSeg, StarDist, and other tools 6. Spatial disease biology: Ligand–receptor analysis of disease-associated tissue microenvironments We would love to hear how you can use PantheonOS for your research! Got an interesting agent run of your own and want to share? In the Pantheon UI, click Export Bundle (top-right of any chat) to package the full trajectory — chat history, code, figures, report — then submit it here:
0:58

PantheonOS allows any biologist to perform complex data analyses of emerging single cell, multi-omics and spatial transcriptomics datasets end to end through AI agent and human collaboration. We are releasing six replays of use cases trajectories. Each "trajectory" is a complete end-to-end run, from prompt to analysis, to figures, and finally to report, and in fully inspectable and reproducible manner. See the six user cases in our PantheonOS Gallery: 1. 3D mouse embryo analysis: Tangram deconvolution and PyVista-based 3D visualization of E6 mouse embryo spatial transcriptomics data 2. 3D human fetal heart analysis: Spatial mapping of heart disease gene patterns using MERFISH data 3. Multi-omics spatial integration: Single cell multi-omics-to-spatial mapping with MOSCOT optimal transport 4. Gene panel design: 1000-plex immune-oncology MERFISH gene panel optimization 5. Cell segmentation benchmarking: Comparative evaluation of Cellpose-SAM, InstanSeg, StarDist, and other tools 6. Spatial disease biology: Ligand–receptor analysis of disease-associated tissue microenvironments We would love to hear how you can use PantheonOS for your research! Got an interesting agent run of your own and want to share? In the Pantheon UI, click Export Bundle (top-right of any chat) to package the full trajectory — chat history, code, figures, report — then submit it here:

evo-devo

13,339 görüntüleme • 2 ay önce

Anyone can build an agent. But to build a trustworthy agent at enterprise scale that is durable, long-running, optimized, contextually aware, and autonomous, the right infrastructure is required. At DevCon 6 we introduced the Agent Stack, the culmination of learnings gathered over years of agentic implementations. Orchestrator, Agent Engine, Agent SDK, Agent Builder, Agent Manager, AIP Evolve, SuperRepo, and so much more. All built on the Ontology, to power agents that actually work in production.
4:07

Anyone can build an agent. But to build a trustworthy agent at enterprise scale that is durable, long-running, optimized, contextually aware, and autonomous, the right infrastructure is required. At DevCon 6 we introduced the Agent Stack, the culmination of learnings gathered over years of agentic implementations. Orchestrator, Agent Engine, Agent SDK, Agent Builder, Agent Manager, AIP Evolve, SuperRepo, and so much more. All built on the Ontology, to power agents that actually work in production.

Palantir

80,948 görüntüleme • 17 gün önce

Whenever you're stuck reading an article, just highlight the text to extract explanations and summaries. Or ask questions and get real-time answers. Introducing SciSpace Copilot Chrome Extension. Download today #AItools #AcademicTwitter #Research
0:20

Whenever you're stuck reading an article, just highlight the text to extract explanations and summaries. Or ask questions and get real-time answers. Introducing SciSpace Copilot Chrome Extension. Download today #AItools #AcademicTwitter #Research

SciSpace

8,137,080 görüntüleme • 3 yıl önce

New Course: ACP: Agent Communication Protocol Learn to build agents that communicate and collaborate across different frameworks using ACP in this short course built with IBM Research's BeeAI, and taught by Sandi Besen, AI Research Engineer & Ecosystem Lead at IBM, and Nicholas Renotte, Head of AI Developer Advocacy at IBM. Building a multi-agent system with agents built or used by different teams and organizations can become challenging. You may need to write custom integrations each time a team updates their agent design or changes their choice of agentic orchestration framework. The Agent Communication Protocol (ACP) is an open protocol that addresses this challenge by standardizing how agents communicate, using a unified RESTful interface that works across frameworks. In this protocol, you host an agent inside an ACP server, which handles requests from an ACP client and passes them to the appropriate agent. Using a standardized client-server interface allows multiple teams to reuse agents across projects. It also makes it easier to switch between frameworks, replace an agent with a new version, or update a multi-agent system without refactoring the entire system. In this course, you’ll learn to connect agents through ACP. You’ll understand the lifecycle of an ACP Agent and how it compares to other protocols, such as MCP (Model Context Protocol) and A2A (Agent-to-Agent). You’ll build ACP-compliant agents and implement both sequential and hierarchical workflows of multiple agents collaborating using ACP. Through hands-on exercises, you’ll build: - A RAG agent with CrewAI and wrap it inside an ACP server. - An ACP Client to make calls to the ACP server you created. - A sequential workflow that chains an ACP server, created with Smolagents, to the RAG agent. - A hierarchical workflow using a router agent that transforms user queries into tasks, delegated to agents available through ACP servers. - An agent that uses MCP to access tools and ACP to communicate with other agents. You’ll finish up by importing your ACP agents into the BeeAI platform, an open-source registry for discovering and sharing agents. ACP enables collaboration between agents across teams and organizations. By the end of this course, you’ll be able to build ACP agents and workflows that communicate and collaborate regardless of framework. Please sign up here:
2:49

New Course: ACP: Agent Communication Protocol Learn to build agents that communicate and collaborate across different frameworks using ACP in this short course built with IBM Research's BeeAI, and taught by Sandi Besen, AI Research Engineer & Ecosystem Lead at IBM, and Nicholas Renotte, Head of AI Developer Advocacy at IBM. Building a multi-agent system with agents built or used by different teams and organizations can become challenging. You may need to write custom integrations each time a team updates their agent design or changes their choice of agentic orchestration framework. The Agent Communication Protocol (ACP) is an open protocol that addresses this challenge by standardizing how agents communicate, using a unified RESTful interface that works across frameworks. In this protocol, you host an agent inside an ACP server, which handles requests from an ACP client and passes them to the appropriate agent. Using a standardized client-server interface allows multiple teams to reuse agents across projects. It also makes it easier to switch between frameworks, replace an agent with a new version, or update a multi-agent system without refactoring the entire system. In this course, you’ll learn to connect agents through ACP. You’ll understand the lifecycle of an ACP Agent and how it compares to other protocols, such as MCP (Model Context Protocol) and A2A (Agent-to-Agent). You’ll build ACP-compliant agents and implement both sequential and hierarchical workflows of multiple agents collaborating using ACP. Through hands-on exercises, you’ll build: - A RAG agent with CrewAI and wrap it inside an ACP server. - An ACP Client to make calls to the ACP server you created. - A sequential workflow that chains an ACP server, created with Smolagents, to the RAG agent. - A hierarchical workflow using a router agent that transforms user queries into tasks, delegated to agents available through ACP servers. - An agent that uses MCP to access tools and ACP to communicate with other agents. You’ll finish up by importing your ACP agents into the BeeAI platform, an open-source registry for discovering and sharing agents. ACP enables collaboration between agents across teams and organizations. By the end of this course, you’ll be able to build ACP agents and workflows that communicate and collaborate regardless of framework. Please sign up here:

Andrew Ng

105,343 görüntüleme • 1 yıl önce

Today, we're launching a new Laracasts series that will show you the essentials building an AI agent from scratch. We start with a basic chat response and gradually introduce new concepts, such as the agent loop, custom tools, and more. 😀 "So You Want To Build An Agent"
9:08

Today, we're launching a new Laracasts series that will show you the essentials building an AI agent from scratch. We start with a basic chat response and gradually introduce new concepts, such as the agent loop, custom tools, and more. 😀 "So You Want To Build An Agent"

Laracasts

16,427 görüntüleme • 3 ay önce

Introducing the new Aomni - an AI agent that builds other agents for you. Now you can go from idea -> fully working agent with 1 prompt. We provide all the tools and contact datasets to build agents that excel at revenue gen activities. Here are some cool use cases 🧵
7:48

Introducing the new Aomni - an AI agent that builds other agents for you. Now you can go from idea -> fully working agent with 1 prompt. We provide all the tools and contact datasets to build agents that excel at revenue gen activities. Here are some cool use cases 🧵

David

71,729 görüntüleme • 1 yıl önce

Over the past couple of years, you’ve heard us reference “agents” and “agentic capabilities,” nebulous concepts that are designed to help you with coding, booking trips, and other complex multi-step tasks. But, what actually IS an agent? We think of AI agents as systems that combine the intelligence of advanced AI models with access to tools so they can take actions on your behalf, under your control. Whether it’s a coding agent or our recently unveiled experimental tool Gemini Agent in the Google Gemini, these are systems that will meet you where you are, in the products that you love, to help take the tedious tasks you want off your plate.
0:57

Over the past couple of years, you’ve heard us reference “agents” and “agentic capabilities,” nebulous concepts that are designed to help you with coding, booking trips, and other complex multi-step tasks. But, what actually IS an agent? We think of AI agents as systems that combine the intelligence of advanced AI models with access to tools so they can take actions on your behalf, under your control. Whether it’s a coding agent or our recently unveiled experimental tool Gemini Agent in the Google Gemini, these are systems that will meet you where you are, in the products that you love, to help take the tedious tasks you want off your plate.

Google AI

120,813 görüntüleme • 8 ay önce

Coming Soon: The All-In-One Research Agent Built to simplify complex academic tasks. Full-spectrum assistance. One powerful AI. 🔬 Stay tuned. Launching soon at
0:40

Coming Soon: The All-In-One Research Agent Built to simplify complex academic tasks. Full-spectrum assistance. One powerful AI. 🔬 Stay tuned. Launching soon at

SciSpace

368,715 görüntüleme • 1 yıl önce

I vibe coded Gumloop over the weekend!! Presenting Agent Flow - an open-source alternative to Gumloop! We built a free no-code AI Agent builder with @composiohq and LangChain's Langgraph that lets you automate workflows and complex agentic patterns with drag-and-drop nodes. Try it out: Here's the code: Looking forward to open-sourcing more YC startups over the coming weekends. Comment below which one you would like to use.
1:10

I vibe coded Gumloop over the weekend!! Presenting Agent Flow - an open-source alternative to Gumloop! We built a free no-code AI Agent builder with @composiohq and LangChain's Langgraph that lets you automate workflows and complex agentic patterns with drag-and-drop nodes. Try it out: Here's the code: Looking forward to open-sourcing more YC startups over the coming weekends. Comment below which one you would like to use.

Karan Vaidya

46,666 görüntüleme • 1 yıl önce