GenAi, Deep Learning and Computer Vision

"Agents are not enough." New Microsoft research explores that for the latest wave of agents, differentiated by GenAI, to succeed, they need to work together with Sims and Assistants (see diagram on page 3):

Agents are nothing new, evolving from early agents (1950s) to expert systems (1980s), reactive agents (1990s), and more recently multi-agent systems and cognitive architectures.

While frameworks like AutoGen help modern agents tackle complex tasks in narrow domains, challenges like generalization, scalability, and coordination persist.

To help tackle challenges and improve standardization, privacy, personalization, and trust, the research advocates for an ecosystem centered on Agents, Sims, and Assistants.

1\ Agents:

→ Narrow and purpose-driven modules that are trained to do a specific task. Each agent can be autonomous, but with an ability to interface with other agents.

2\ Sims:

→ Representations of the user, built from their profile, preferences, and behaviors, capturing key aspects of who the user is.
→ Sims can act on the user’s behalf, interacting with agents to accomplish tasks, guided by the user’s Assistant.

3\ Assistants:

→ Programs that interact directly with users, deeply understand them, and can call Sims or Agents to handle tasks reactively or proactively.
→ Assistants act as private agents, accessing personal information and fine-tuned to the user, enabling them to perform tasks on the user's behalf.

Interaction

→ Agents, Sims, and Assistants work together with high degree of synergy.
→ The Assistant, deeply understanding the user, co-creates and manages Sims with user input, reflecting different facets of the user’s life.
→ Sims engage specialized Agents to complete tasks effectively, ensuring precision and personalization, which enhances user satisfaction.

P.S. Paper attached with link dives deeper: https://www.arxiv.org/pdf/2412.16241

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www.tgoop.com/awesomedeeplearning/245

4.07K viewsArtificial Intelligence, Dec 26, 2024 at 12:24

"Agents are not enough." New Microsoft research explores that for the latest wave of agents, differentiated by GenAI, to succeed, they need to work together with Sims and Assistants (see diagram on page 3):

Agents are nothing new, evolving from early agents (1950s) to expert systems (1980s), reactive agents (1990s), and more recently multi-agent systems and cognitive architectures.

While frameworks like AutoGen help modern agents tackle complex tasks in narrow domains, challenges like generalization, scalability, and coordination persist.

To help tackle challenges and improve standardization, privacy, personalization, and trust, the research advocates for an ecosystem centered on Agents, Sims, and Assistants.

1\ Agents:

→ Narrow and purpose-driven modules that are trained to do a specific task. Each agent can be autonomous, but with an ability to interface with other agents.

2\ Sims:

→ Representations of the user, built from their profile, preferences, and behaviors, capturing key aspects of who the user is.
→ Sims can act on the user’s behalf, interacting with agents to accomplish tasks, guided by the user’s Assistant.

3\ Assistants:

→ Programs that interact directly with users, deeply understand them, and can call Sims or Agents to handle tasks reactively or proactively.
→ Assistants act as private agents, accessing personal information and fine-tuned to the user, enabling them to perform tasks on the user's behalf.

Interaction

→ Agents, Sims, and Assistants work together with high degree of synergy.
→ The Assistant, deeply understanding the user, co-creates and manages Sims with user input, reflecting different facets of the user’s life.
→ Sims engage specialized Agents to complete tasks effectively, ensuring precision and personalization, which enhances user satisfaction.

P.S. Paper attached with link dives deeper: https://www.arxiv.org/pdf/2412.16241

BY GenAi, Deep Learning and Computer Vision