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Research Focus: AI agents leaking enterprise data, a smarter OS for cloud deployment, and new research on how to actually structure AI use at work.

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Microsoft Research

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15,340 просмотров • 3 месяцев назад •via X (Twitter)

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Today, Box announced new AI Agents to work with enterprise content, powering Deep Research, Search, and enhanced Data Extraction. There’s a tremendous amount of value that’s trapped in unstructured data, from contracts to research data, that we can finally unlock with AI.
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Today, Box announced new AI Agents to work with enterprise content, powering Deep Research, Search, and enhanced Data Extraction. There’s a tremendous amount of value that’s trapped in unstructured data, from contracts to research data, that we can finally unlock with AI.

Aaron Levie

60,262 просмотров • 1 год назад

Today, Box is announcing major new AI agent capabilities to let customers tap into the full value of their unstructured data. First, we’re announcing all new updates to the Box AI Studio to make it even easier to build AI agents that tap into your enterprise content for any job function, business process, or industry specific use case. We are also expanding our set of foundational agents that customers will be able to use to work with their enterprise content, including new features like search and research on unstructured data. Next, we’re announcing Box Extract to enable customers to use AI agents seamlessly for complex data extraction from any type of document or content. This makes it easier than ever to pull out data from contracts, invoices, research data, marketing assets, medical charts, and more. Finally, we’re introducing Box Automate, a new workflow automation solution within Box that lets you deploy AI agents across enterprise content-centric workflows. With Box Automate, you can design your business process in a simple drag and drop builder and then drop in AI agents at any step in the process. This ensures agents execute tasks at the right steps in a workflow every time. Best of all, our AI agents and workflow tools are designed to work across any system our customers work within, whether it’s leveraging pre-built integrations, Box APIs, or the new Box MCP Server. Ultimately, all of these capabilities come together to transform how companies can work with their enterprise content. Software has historically only been good at automating work that deals with structured data, which is why ERP, CRM, and HR systems have been mainstays of enterprise software for so long. The data in these systems fits neatly into a database, and the workflows are very ripe for automation. But it turns out most of the work in the world deals with unstructured data. It’s ideating through research documents, working with a client on contracts, reviewing details for a new product launch, looking at a patient’s healthcare record to make a diagnosis, working through due diligence documents for an M&A deal, and so on. For the first time ever, we can begin to bring all new insights and automation to this work with AI agents. At Box, we’re incredibly excited to be on this journey to help customers transform how they work with their most important data.
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Today, Box is announcing major new AI agent capabilities to let customers tap into the full value of their unstructured data. First, we’re announcing all new updates to the Box AI Studio to make it even easier to build AI agents that tap into your enterprise content for any job function, business process, or industry specific use case. We are also expanding our set of foundational agents that customers will be able to use to work with their enterprise content, including new features like search and research on unstructured data. Next, we’re announcing Box Extract to enable customers to use AI agents seamlessly for complex data extraction from any type of document or content. This makes it easier than ever to pull out data from contracts, invoices, research data, marketing assets, medical charts, and more. Finally, we’re introducing Box Automate, a new workflow automation solution within Box that lets you deploy AI agents across enterprise content-centric workflows. With Box Automate, you can design your business process in a simple drag and drop builder and then drop in AI agents at any step in the process. This ensures agents execute tasks at the right steps in a workflow every time. Best of all, our AI agents and workflow tools are designed to work across any system our customers work within, whether it’s leveraging pre-built integrations, Box APIs, or the new Box MCP Server. Ultimately, all of these capabilities come together to transform how companies can work with their enterprise content. Software has historically only been good at automating work that deals with structured data, which is why ERP, CRM, and HR systems have been mainstays of enterprise software for so long. The data in these systems fits neatly into a database, and the workflows are very ripe for automation. But it turns out most of the work in the world deals with unstructured data. It’s ideating through research documents, working with a client on contracts, reviewing details for a new product launch, looking at a patient’s healthcare record to make a diagnosis, working through due diligence documents for an M&A deal, and so on. For the first time ever, we can begin to bring all new insights and automation to this work with AI agents. At Box, we’re incredibly excited to be on this journey to help customers transform how they work with their most important data.

Aaron Levie

91,863 просмотров • 11 месяцев назад

It’s wild watching AI Agents work with software. Here’s ChatGPT connected to Box running a deep research task on market analysis documents. The future is just giving AI Agents the data and systems to comb through and having them work for you in the background.
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It’s wild watching AI Agents work with software. Here’s ChatGPT connected to Box running a deep research task on market analysis documents. The future is just giving AI Agents the data and systems to comb through and having them work for you in the background.

Aaron Levie

235,980 просмотров • 1 год назад

Introducing Zams: The UI layer for enterprise AI agents. As AI agents get smarter, the real skill isn’t doing the work—it’s knowing how to orchestrate them. We built Zams to solve 3 problems holding AI agents back.
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Introducing Zams: The UI layer for enterprise AI agents. As AI agents get smarter, the real skill isn’t doing the work—it’s knowing how to orchestrate them. We built Zams to solve 3 problems holding AI agents back.

Zams

40,421 просмотров • 1 год назад

New certification. 200k+ salary? AWS Generative AI Developer – Professional Validates real skills for enterprise AI: • scalable RAG pipelines • vector DBs • AI agents • production deployment This might become the highest paying cloud certification.
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New certification. 200k+ salary? AWS Generative AI Developer – Professional Validates real skills for enterprise AI: • scalable RAG pipelines • vector DBs • AI agents • production deployment This might become the highest paying cloud certification.

Xinoyaps

73,132 просмотров • 5 месяцев назад

AI isn’t replacing lawyers — it’s helping them work smarter. From drafting documents to legal research, AI is cutting down hours of rote work, allowing lawyers to focus on higher-value strategy and better serve their clients. But as with all enterprise customers handling sensitive data and complex workflows, selling to the legal profession means taking great care to build a great UX, prioritize security, and understand the field inside and out. For more, listen to Aatish Nayak, head of product at Harvey and a16z’s Kimberly Tan on the AI + a16z podcast:
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AI isn’t replacing lawyers — it’s helping them work smarter. From drafting documents to legal research, AI is cutting down hours of rote work, allowing lawyers to focus on higher-value strategy and better serve their clients. But as with all enterprise customers handling sensitive data and complex workflows, selling to the legal profession means taking great care to build a great UX, prioritize security, and understand the field inside and out. For more, listen to Aatish Nayak, head of product at Harvey and a16z’s Kimberly Tan on the AI + a16z podcast:

a16z

31,065 просмотров • 1 год назад

How to fully automate keyword research with AI agents:
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How to fully automate keyword research with AI agents:

The Boring Marketer

30,302 просмотров • 1 год назад

We release a new urban simulator, MetaUrban, to support research on AI agents for micromobility. The work will be presented at #ICLR2025, and the demo code can run on any laptop. Webpage: Code: Paper:
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We release a new urban simulator, MetaUrban, to support research on AI agents for micromobility. The work will be presented at #ICLR2025, and the demo code can run on any laptop. Webpage: Code: Paper:

Bolei Zhou

30,344 просмотров • 1 год назад

Super excited to share 🧠MLGym 🦾 – the first Gym environment for AI Research Agents 🤖🔬 We introduce MLGym and MLGym-Bench, a new framework and benchmark for evaluating and developing LLM agents on AI research tasks. The key contributions of our work are: 🕹️ Enables the exploration of different training algorithms for AI Research Agents such as RL 🛠️ Provides a flexible evaluation framework that can accommodate different artifacts such as models, algorithms, or predictions 🤖 Allows researchers to evaluate any model without the need to develop a custom agentic harness 🎯 Introduces 13 diverse open-ended AI Research tasks for evaluating AI Research Agents on a wide range of domains such as computer vision, natural language processing, reinforcement learning, game theory, and logical reasoning. 📈 Proposes a new evaluation metric for AI Research Agents MLGym makes it easy to: 1) Add new tasks 2) Evaluate new models 3) Integrate new agents Check out a video of the MLGym Agent to see how it performs the full pipeline of idea generation💡, implementation 👩‍💻, experimentation 👩‍🔬, and iteration 🔄 to improve on ML tasks. Huge thanks to the exceptionally talented Deepak Nathani who led this work and to all the other amazing collaborators who made this possible 🙏🫶🚀
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Super excited to share 🧠MLGym 🦾 – the first Gym environment for AI Research Agents 🤖🔬 We introduce MLGym and MLGym-Bench, a new framework and benchmark for evaluating and developing LLM agents on AI research tasks. The key contributions of our work are: 🕹️ Enables the exploration of different training algorithms for AI Research Agents such as RL 🛠️ Provides a flexible evaluation framework that can accommodate different artifacts such as models, algorithms, or predictions 🤖 Allows researchers to evaluate any model without the need to develop a custom agentic harness 🎯 Introduces 13 diverse open-ended AI Research tasks for evaluating AI Research Agents on a wide range of domains such as computer vision, natural language processing, reinforcement learning, game theory, and logical reasoning. 📈 Proposes a new evaluation metric for AI Research Agents MLGym makes it easy to: 1) Add new tasks 2) Evaluate new models 3) Integrate new agents Check out a video of the MLGym Agent to see how it performs the full pipeline of idea generation💡, implementation 👩‍💻, experimentation 👩‍🔬, and iteration 🔄 to improve on ML tasks. Huge thanks to the exceptionally talented Deepak Nathani who led this work and to all the other amazing collaborators who made this possible 🙏🫶🚀

Roberta Raileanu

105,052 просмотров • 1 год назад

💡 Acronym of the day: EGI [Enterprise General Intelligence] Salesforce AI Research coined it to define how well AI agents deliver consistent, capable performance across business tasks. 🔎 Dig deeper into our new framework for excellence in AI systems for business:
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💡 Acronym of the day: EGI [Enterprise General Intelligence] Salesforce AI Research coined it to define how well AI agents deliver consistent, capable performance across business tasks. 🔎 Dig deeper into our new framework for excellence in AI systems for business:

Salesforce

30,804 просмотров • 1 год назад

"AI agents are using the XRP Ledger x402 facilitator to produce better research by paying for proprietary data" That's most of the +1M AI agent transactions currently on XRP. You ask a research question, the AI agent can access data behind a paywall by paying for it via the XRPL x402 facilitator.
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"AI agents are using the XRP Ledger x402 facilitator to produce better research by paying for proprietary data" That's most of the +1M AI agent transactions currently on XRP. You ask a research question, the AI agent can access data behind a paywall by paying for it via the XRPL x402 facilitator.

Vet

12,002 просмотров • 20 дней назад

Clarm (Clarm) builds AI deep research agents that never hallucinate. Clarm connects across your enterprise data to give users precise answers they can trust for critical decisions. Congrats on the launch, Marcus Storm-Mollard and Alex!
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Clarm (Clarm) builds AI deep research agents that never hallucinate. Clarm connects across your enterprise data to give users precise answers they can trust for critical decisions. Congrats on the launch, Marcus Storm-Mollard and Alex!

Y Combinator

26,569 просмотров • 1 год назад

Lindy AI just announced the first AI employee. You can now create custom AI agents with just a prompt and get them to work natively in your browser for limitless use cases. Sales outreach, personalized emails, automated research…anything! Here’s how to set up your AI agent:
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Lindy AI just announced the first AI employee. You can now create custom AI agents with just a prompt and get them to work natively in your browser for limitless use cases. Sales outreach, personalized emails, automated research…anything! Here’s how to set up your AI agent:

Alvaro Cintas

26,763 просмотров • 1 год назад

What if your cloud were built AI‑native from day one? Meet Qwen Cloud — Alibaba Cloud’s new AI‑native platform designed to streamline model access and deployment, offering a unified stack for building, deploying, and scaling AI applications and agents.
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What if your cloud were built AI‑native from day one? Meet Qwen Cloud — Alibaba Cloud’s new AI‑native platform designed to streamline model access and deployment, offering a unified stack for building, deploying, and scaling AI applications and agents.

Alibaba Group

1,956,687 просмотров • 1 месяц назад

Bharat’s Focus: AI for Real Impact ✅ AI for solving real world problems ✅ AI for improving enterprise productivity ✅ AI for population-scale problems: healthcare, agriculture, climate change 📍Research Symposium on “AI & its Impact”
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Bharat’s Focus: AI for Real Impact ✅ AI for solving real world problems ✅ AI for improving enterprise productivity ✅ AI for population-scale problems: healthcare, agriculture, climate change 📍Research Symposium on “AI & its Impact”

Ashwini Vaishnaw

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Elixir Research Lab: 2⃣ AI Agents. Yes! We've been working on agentic infrastructure to power the next-gen of gaming companionship, and helpful agents for players. Conversation with Victor Merino from AI squad at Elixir Games: - 01:18 How Agents in Elixir Games work? - 02:44 Basic Setup for Agents, datasets and more - 04:20 UX for AI devs
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Elixir Research Lab: 2⃣ AI Agents. Yes! We've been working on agentic infrastructure to power the next-gen of gaming companionship, and helpful agents for players. Conversation with Victor Merino from AI squad at Elixir Games: - 01:18 How Agents in Elixir Games work? - 02:44 Basic Setup for Agents, datasets and more - 04:20 UX for AI devs

Elixir Games

46,762 просмотров • 1 год назад

Agentic AI is exposing the limits of traditional LLM benchmarks—and forcing a rethink of how enterprise AI value is actually measured. Analysts Ryan Shrout & Mitch Lewis join Kamiwaza AI Platform Engineer JV Roig to unpack new research from Signal65 and Kamiwaza that demonstrates why legacy benchmarks miss real-world agentic work, and how the Kamiwaza Agentic Merit Index (KAMI) delivers a more meaningful way to evaluate enterprise-ready agentic AI.
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Agentic AI is exposing the limits of traditional LLM benchmarks—and forcing a rethink of how enterprise AI value is actually measured. Analysts Ryan Shrout & Mitch Lewis join Kamiwaza AI Platform Engineer JV Roig to unpack new research from Signal65 and Kamiwaza that demonstrates why legacy benchmarks miss real-world agentic work, and how the Kamiwaza Agentic Merit Index (KAMI) delivers a more meaningful way to evaluate enterprise-ready agentic AI.

Six Five Media

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Introducing Deep Research for legal in Harvey. Built on OpenAI's Deep Research API and Harvey's legal reasoning systems, Deep Research will enable a new class of legal agents for the world's top law firms and enterprise teams.
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Introducing Deep Research for legal in Harvey. Built on OpenAI's Deep Research API and Harvey's legal reasoning systems, Deep Research will enable a new class of legal agents for the world's top law firms and enterprise teams.

Harvey

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Motives (Motives) is a team of AI agents that runs qualitative research projects for consumer brands, replacing slow and expensive focus groups.
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Motives (Motives) is a team of AI agents that runs qualitative research projects for consumer brands, replacing slow and expensive focus groups.

Y Combinator

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