In recent days, social media has been flooded with rumors claiming that Israeli Prime Minister Benjamin Netanyahu has died. As the rumors spread rapidly across different platforms, a video soon appeared showing Netanyahu seemingly alive and speaking.
Supporters quickly shared the video as proof that the rumors were false. However, others began questioning whether the video itself was authentic. Some users suggested that the footage might have been generated or manipulated using artificial intelligence.
This sparked a heated debate across social media. The question was no longer simply whether Netanyahu was alive or not. Instead, the discussion shifted to a deeper and more important question:
Can we still trust what we see when AI can generate highly realistic images and videos?
The Rise of AI That Generates Reality
Modern generative AI systems are incredibly powerful. They can produce realistic images, convincing voices, and even entire videos of people who appear to be speaking or acting in ways that never actually happened.
These systems work using a process called inference. AI models are trained on massive datasets and learn patterns in language, images, and video. When asked to generate content, the AI does not retrieve a factual event from reality. Instead, it predicts what should come next based on those patterns.
In other words, the AI produces something that looks believable, but it does not guarantee that it is true.
This is why technologies like deepfakes have become increasingly sophisticated. A convincing video can now be produced without a real camera recording the event.
The Key Problem: Believable Does Not Mean True
The challenge we now face is that humans are naturally inclined to trust visual evidence. For decades, photos and videos were considered reliable proof of reality.
But in the era of generative AI, visual evidence can be manufactured.
A video can be perfectly realistic while still being completely artificial. A speech can be generated without the speaker ever saying those words.
This creates a new type of information risk: synthetic reality.
A Different Kind of AI: AI That Works on Real Data
Not all AI systems operate in the same way.
While generative AI focuses on producing content based on learned patterns, another category of AI focuses on analyzing real, verifiable data.
Instead of inventing answers, this type of AI connects directly to existing data sources such as:
- company databases
- financial reports
- transaction records
- inventory systems
- operational business data
The AI then analyzes that real data to generate insights and support decision making.
This is the approach used by BizCopilot, an AI platform developed by PT Ide Brilian Digital. Instead of generating answers purely from language patterns, BizCopilot analyzes real business data directly from company systems to provide insights for business owners and executives.
In this model, AI is not “imagining” the answer. It is interpreting real operational data such as sales, financial performance, and operational metrics.
Two Very Different Types of AI
Many people today talk about AI as if it were a single technology. In reality, there are two fundamentally different approaches:
- Generative AI (Inference-Based)
Creates text, images, or videos by predicting patterns. It can look convincing but is not guaranteed to be factual. - Data-Driven AI
Analyzes real-world data to produce insights and decisions based on verifiable information.
Both types of AI are powerful, but they serve very different purposes.
Generative AI is excellent for creativity, content generation, and simulations. Data-driven AI, on the other hand, is designed to help organizations understand real conditions using real data.
The Future: A World Where Reality Can Be Simulated
The debate around the Netanyahu video illustrates something bigger than a single political rumor.
We are entering an era where artificial intelligence can simulate reality with astonishing accuracy. Images, voices, and videos can all be generated with minimal effort.
This means the traditional signals of truth are becoming less reliable.
Seeing is no longer believing.
The Role of Responsible AI
The technology itself is not inherently dangerous. AI can be used to spread misinformation, but it can also be used to improve transparency, analyze complex data, and help people make better decisions.
Platforms like BizCopilot demonstrate how AI can be applied in a responsible and practical way — helping organizations understand their real data rather than generating synthetic narratives.
Conclusion
The controversy surrounding Netanyahu may eventually fade from public attention. But the lesson it leaves behind is significant.
In a world where AI can generate highly convincing content, we must become more careful about how we evaluate information.
The future will not only depend on how advanced AI becomes.
It will depend on whether we build AI systems that help us create more noise — or help us discover the truth hidden within real data.