Emergence Launch: AI Agents and the future enterprise

Talk transcript

1. 0:00

   [on-hold music] I'm here to tell you a little bit about what we're doing at Emergence in the field of AI agents.

2. 0:17

   But first, I wanna tell, tell you guys a few things about who we are. So we are an R&D-led AI company advancing the science and development of agents. And, uh, we come from some of the world's, uh, top AI labs, uh, founding team out of IBM Research, uh, and then we attracted, uh, talent from places like Google

3. 0:35

   Brain, Alexa, DALL-E Institute of AI, Meta, Microsoft, et cetera. But even more importantly, we have built and deployed some of the most scaled AI deployments on the planet, from the IBM Watson platform, to Alexa, to the backend recommendation engines behind Amazon Prime, Amazon Video, Twitter, Eventbrite, et cetera.

4. 0:55

   So we really think of ourselves as a distributed systems meets AI R&D team. Uh, and our goal is to work on AI agents and to enable all of you to build agents to transform the world.

5. 1:09

   So we're all here today because we are excited about what's actually coming out in AI. So the long promise of AI over this last several decades has always been that AI will perform actions for us.

6. 1:20

   Uh, this is what science fiction authors have told us since the nineteen forties and fifties, and I think the time is finally here. And in particular, what we're very excited about is AI that will operate things like, uh, you know, web browsers and, uh, various other enterprise systems and software, and in the process, uh, drive great productivity

7. 1:39

   benefits for everybody, both in consumer and especially in enterprise, which is our focus. So we're interested in enterprise because the most interesting workflows are actually in enterprise, and this will really stress and push the limits of what AI can do, in particular, what autonomous AI can do.

8. 1:57

   And, uh, so what we're building to enable that future to come to pass, uh, with, uh, with the help of all of you, uh, are two very infrastructural platforms, the first of which will be GA'd in August.

9. 2:08

   Uh, early access al- is already, uh, live right now, so you can go sign up for it. This is, uh, called an orchestrator agent. So first of all, it's an agent and, uh, in the sense that it acts, it plans, it basically also verifies.

10. 2:23

    So it, it finishes that agentic loop between planning, acting, and verifying. It remembers and improves over time. But what does it do? It actually allows you to orchestrate across multiple agents and stitch them together in complex workflows.

11. 2:37

    Uh, a simple version of it is you could simply orchestrate across multiple LLMs, generalist and open source LLMs, but more complex versions of it will basically enable you to solve very complex enterprise workflows like claims processing, et cetera.

12. 2:51

    Now, an orchestrator is only as good as the agents it will orchestrate to. So one of the exciting things that we're doing here is integrating the orchestrator with a project that is currently being developed in the open source called Agent-E.

13. 3:06

    Um, Agent-E is a project that, uh, uh, my, my colleague Tamer had a session on earlier this afternoon. It's a web agent. It's basically meant to control the web like a human would.

14. 3:18

    And currently, it's the best web agent on the planet. It's topping the WebVoyager benchmark, and, uh, it's designed to basically, uh, be used to build multiple enterprise workflows and work seamlessly with agent-- with the, with the orchestrator agent.

15. 3:33

    So I'm gonna play a short video that will show you a little bit more about both these agents, and then I'll, uh, wrap, wrap the talk up.

16. 3:44

    Okay, we don't have sound, so maybe I'll talk over it. So our first product is the Orchestrator-

17. 3:47

    With generalist and task-specific LLMs and agents, all using appropriate guardrails. The developer dashboard helps analyze prompts, optimize cost and latency, create new models with your data, and enhance existing ones.

18. 4:05

    Build with confidence, knowing your solution is future-proof and can migrate to the latest LLMs on demand. The Orchestrator is an intelligent agent that improves with use, connecting to agents like Agent-E, our web automation agent in development in our R&D labs.

19. 4:22

    Agent-E is an open source agent designed to learn how to autonomously operate the web and automate complex workflows. For example, get us a reservation for fifteen people near the office around six PM.

20. 4:34

    We like Asian, Mediterranean, and Mexican. Send the details to Levi, please. At Emergence, our mission is to advance the science of AI agents by tackling core AI problems like planning and self-improvement to enable the full transformation of AI and benefit the world.

21. 4:52

    Okay, so just in conclusion, uh, in our R&D labs, our area of focus is around self-improvement agents. This is our core focus. And in the process, we will advance things like AI planning and reasoning, and also solve things like, uh, you know, how agents should be stitched together in really interesting ways through something called agent-oriented programming.

22. 5:12

    And we're doing all of this in the context of enterprise workflows like RPA and, uh, document processing access, et cetera. So that's my time. Thank you so much. See us at our booth. [outro jingle]