AI in 2025
4-6 min read
Dec 25, 2024
AI
Agents
GraphRAG
Responsible AI
AI in 2025 will reshape industries by mixing different data types (multimodal systems), using multi-agent systems, and applying smart reasoning methods. Breakthroughs like GraphRAG, Reports over RAG, and fine-tuned open-source models will make data easier to use. With bigger memory and Responsible AI, future applications will be safer, smarter, and more ethical.
Multimodality
Ability to process and understand multiple types of data or "modalities" such as text, images,
audio, and video. It expands the capabilities of LLMs beyond just text-based tasks, enabling
them to integrate and analyze information from various sources in a unified way.
Multi-agent systems
Allows building of complex and scalable AI agent-based solutions:
- – Each agent is specialized in a specific task
- – LLM and custom logic manage coordination between agents (depending on the architecture): reason, plan, and take action.
- – Agents communicate with each other
Models with Reasoning
Advanced AI systems designed to perform tasks requiring
logical reasoning, structured decision-making, and contextual understanding.
These models are built to work in scenarios where analytical thinking,
problem-solving, or inference is essential.
Example models: o1, o1-mini, o3
Reports over RAG
RAG started with questions, but recommendations are next step. Report generation system automates recurring reports (e.g., monthly sales
reports or operational metrics), ensuring consistency and saving time.
GraphRAG
GraphRAG can turn raw, scattered company documents into a well-structured
knowledge graph that helps teams find and connect crucial insights faster
and more reliably than standard RAG.
| Baseline RAG | GraphRAG | ||||||
| The text does not provide specific information on what Novorossiya has done. | Novorossiya, a political movement in Ukraine, has been involved in a series of destructive activities, particularly targeting various entities in Ukraine [Entities (6494, 912)]. The movement has been linked to plans to destroy properties of several Ukrainian entities, including Rosen, the Odessa Canning Factory, the Odessa Regional Radio Television Transmission Center, and the National Television Company of Ukraine [Relationships (15207, 15208, 15209, 15210)]. In addition to these, Novorossiya has also been associated with plans to destroy properties of Roshen, the Odessa Conservatory Factory, the Odesa Regional Radio Television Transmission Center, and the National Telecommunications Company of Ukraine [Relationships (8329, 8330, 8331, 8332)]. Furthermore, Novorossiya has been implicated in plans to blow up ATMs of PrivatBank, the largest state bank in Ukraine [Relationships (8335, 8335)]. The Office of the General Prosecutor in Ukraine has reported on the creation of Novorossiya, indicating the government’s awareness and potential concern over the activities of this movement [Relationships (8264, 8264)]. The destructive activities of Novorossiya have had significant impacts on the targeted entities and have likely contributed to the ongoing tensions and conflicts in the region. In summary, Novorossiya has been involved in a series of destructive activities targeting various entities in Ukraine. These activities have had significant impacts on the targeted entities and have likely contributed to the ongoing tensions and conflicts in the region. The Ukrainian government, through the Office of the General Prosecutor, has acknowledged the existence and activities of Novorossiya, indicating a level of concern over the movement’s actions. | ||||||
Model Context Protocol
The Model Context Protocol is an open standard that enables developers to
build secure, two-way connections between their data sources and AI-powered tools.
The architecture is straightforward: developers can either expose their data through
MCP servers or build AI applications (MCP clients) that connect to these servers.
Open-source LLMs & Small Models
For specific scenarios, open-source models like Llama 3.3 may provide similar
quality to SaaS-managed models (OpenAI, etc.), but with lower costs.
Small Models are cheap to run and can be effective for specific tasks and domains.
Fine-tuning
Allowing “tuning” models for a specific domain or style.
Large Memory
New models have larger and larger memory (context window).
Near-infinite memory probably comes soon.
Responsible AI
Ensure that LLM-generated answers are valid, stable, and grounded.
The LLM-generated workflow can be tracked step by step from question to answer.
