Although the development of technology is exponential, the organizational change happens at a logarithmic rate, as organizations struggles to take the most of the technology developments.
Look at this curve of adoption, how amazing it is:
There has been a steep growth in data training
There is a HUGE investment in training LLMs
According to him, the LLMs are achiveing levels of intelligence that are amazing, when comparing IQ tests.
*This is naive... IQ tests are not really reliable intelligence tests...
AI Inference Costs have rapidly declined due to innovation (40 times reduction/year).
Azure AI is offering more than 11.000 frontier and open odels, including DeepSeek R1 and Gork. The idea is to make these models available to the wide public so they can be adopted and used in organizations. You may avoid trusting issues by running the models in private services.
Companies are experimenting with multiple models. Most companies are using 3 (highest frequency), 4 or 5 different LLMs.
These models can solve complex problems in Chemestry, Life sciences, Physics and other fields. Microsoft has something called Agentic Enterprise Platform
The next setp: multi-task,multi-domain and (intelligence) multi-modality
GenAI Applications:
His favorite application fields are Education and Health due to the impact technologies can have in such relevant human areas. He showed an example of Immersive AI Communication.
Other applications:
With Co-pilot, you can easily create music and lyrics, for instance
He showed different videos, capturing shadows in landscape, human skin (which is very difficult to reproduce)
A growing precision has been achieved and current videos are amazing!
Also the ideas generated for a future can be developed by AI (he showed a video of a future envisioned by a Chinese system).
Agentic AI
Evolution:
Emergence of reasoning-centric models
Proliferation of agentic AI
Expansion of open-seurce model ecosystems
multimodal intelligence becoems mainstream
Rise of small, efficient models
He showed a video of two agents communicaqting, very interesting, because at some point, they realize they are both AI, and then they decide to switch languages for a more efficient AI language.
Copilot is the Microsoft agent (like a personal assistant). It may also be considered a standard User Interface for AI. Behind the scene, you may have multiple agents from different organizations, all using Copilot to communicate to the user
Definitions
He believes we are only the beginning of the "Act" part. There is much more agents will do on our behalf in the near future. We must think about all guard rails we must have in this context. The ability to iterate and have the human-in-the-loop has also evolved with time and can be determinant here.
Recommendation to companies: There is a spectrum of Agents. You should start with simple agents, move slowly to task-based agents, and finally arrive at autonomous agents. Otherwise the project may be unsuccessful
Examples of built in Microsoft agents (these are already working):- Reearcher
- Analyst
- Skills agents
- Facilitator
- Sales Agent
- Project Manager
Recently, there were advertisements in the street of San Francisco, suggesting organizations not to hire human salesmen anymore, but actually use digital sales agents that are more productive
On the agents front, evolution goes from personal agents to organizational agents, moving into business process agents and finally reaching cross-organization agents.
AI as a new dimension
A new metric: The human-agent ratio
What is the optimal balance in this regard?
He showed an experiment with robots being trainned to look sad, angry, happy, shy etc. Only with the movement of other people, the robot is able to learn how to emulate emotions.
Gardner Report 2025 (from hype to technology maturity):
82% of business leaders say employees will need new skills ot prepare for AI.
Finishing remark: The difference between science fiction and nonfiction is often just a matter of time.
Giancarlo: Is Microsoft betting in other AI technologies other than LLMs?
He says that there is a big part that is knowledge (such as in Knowledge Graphs). But for sure Microsoft is making a big bet on LLMs and they are currently dependent on OpenAI. Although they have an open source LLM that is good, it is not as good as GPTs.
They are also beting a lot on user experience. The bet in the long run is to provide the platform and not really the services since businesses should provide the services. They work on protocols and base infrastructure that can be applied.
They are also betting a lot on GitHub (bought 5 years ago) as the biggest developers community. He says many things will change in Software Development.
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