FANS STUNNED: JASON MOMOA’S NEW 12-YEAR-YOUNGER GIRLFRIEND RESEMBLES HIS EX-WIFE

Jason Momoa’s new relationship is making waves in the news after he posted pictures of his girlfriend, who is also well-known.

Fans have been talking about how his new girlfriend looks similar to his ex-wife and even his daughter. Some people think it’s odd that his girlfriend looks like his teenage daughter.

Jason Momoa has confirmed that he’s dating again. With his new girlfriend’s photos spreading online, people are comparing her to his family members. Some say his ex is more beautiful, while others find it uncomfortable that his new girlfriend resembles his child.

Jason Momoa is famous for his role in the 2018 film “Aquaman,” where he starred with Amber Heard. They both returned for the sequel in 2023.

He has also acted with Vin Diesel, Tyrese Gibson, Michelle Rodriguez, and Gal Gadot in the popular movie “Fast X.”

Besides his successful acting career, Jason Momoa’s love life has also attracted a lot of public interest. He has been romantically linked to several well-known women over the years.

Jason Momoa was married to Lisa Bonet, who is famous for her role on “The Cosby Show.” They became a well-known couple. They started dating in 2005 after friends introduced them to each other.

At the time, Lisa Bonet was 12 years older than Jason Momoa and was a single mom raising her teenage daughter, Zoë Kravitz, from her previous marriage to Lenny Kravitz.

Momoa built a close bond with both Zoë and Lenny. He affectionately calls Zoë “Zozo bear,” and she calls him “Papa bear.” Momoa also has a lot of respect for Lenny Kravitz, and the feeling is mutual.

Jason Momoa and Lisa Bonet got married in October 2017. They have two children together: a daughter named Lola and a son named Nakoa-Wolf. Both kids are now teenagers.

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In a 2018 interview, Jason Momoa talked about how much he enjoyed his marriage with Lisa Bonet. He said she was very funny and quirky, which made him laugh a lot. He also praised her for being a great mom and said they were a “perfect fit.”

However, after being together for 16 years and married for four of those years, Momoa and Bonet announced they were separating in January 2022. They explained that they were going through big changes and that their love was evolving.

They said in a joint statement, “We have all felt the squeeze and changes of these transformational times… A revolution is unfolding and our family is no exception… feeling and growing from the seismic shifts occurring.”

The couple’s breakup surprised many fans, and later, it was revealed what led to their separation.

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Jason Momoa and Lisa Bonet’s split happened because they had different priorities. A source revealed that Momoa was very focused on his career and enjoyed the success it brought him. Meanwhile, Bonet wanted to stay in Los Angeles and focus on health and wellness. Their different lifestyles led them to drift apart.

Two years after they announced their separation, Bonet filed for divorce in January 2024. She mentioned “irreconcilable differences” and said they separated in October 2020. The court quickly approved their divorce. They had already agreed on the terms, including joint custody of their children and no child or spousal support.

After the divorce, Momoa briefly dated Mexican singer and actress Eiza Gonzalez. Their relationship ended in June 2022, partly because they were at different stages in their lives.

Since then, Momoa has started a new relationship. At a Comic Con event in May 2024, he confirmed he was dating someone but kept her identity private. He later shared photos from a trip to Japan with some friends, including a woman who might be his new partner.

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Jason Momoa shared his gratitude on social media, thanking everyone who welcomed them into their homes and made new memories together. In the post, he went public with his new relationship with Puerto Rican actress Adria Arjona. Arjona, who is 12 years younger than Momoa, was featured in several photos, including one where she is smiling and sitting on his lap.

Their relationship has caught the attention of many fans, who are excited to follow their love story as they continue to share moments from their lives together.

Synaptic Information Storage Capacity Measured With Information Theory

Ever wondered just how much data your brain can hold? We often compare the brain to a supercomputer, but what if that comparison isn’t just a metaphor—it’s literal? Deep within your brain, at the junctions where neurons meet, lies an extraordinary form of biological storage: the synapse. And thanks to breakthroughs in information theory, we’re beginning to quantify its staggering capacity.

In this article, we’ll dive into how synaptic storage works, how scientists measure it, and why this knowledge could shape the future of data storage—from artificial intelligence to DNA-based memory.

What Are Synapses and Why Are They Important?

Think of neurons as the brain’s messengers. But without synapses—the gaps between them where signals are transmitted—those messages would go nowhere. A synapse is where the magic happens: it’s the space where one neuron sends a chemical or electrical signal to another, sparking thoughts, memories, movements, and more.

Now here’s the kicker: each of these tiny junctions doesn’t just pass along data—it stores it.

Your brain has about 86 billion neurons, and each one can form around 1,000 synapses. That’s a total of roughly 125 trillion synapses buzzing away in your brain, constantly sending and receiving signals. These connections form the foundation of your memories, knowledge, and perception.

Measuring Synaptic Storage with Information Theory

To understand how synapses store information, scientists turn to information theory—a branch of mathematics that deals with encoding, decoding, and compressing data. Think of it like analyzing how much a hard drive can hold, but on a biological scale.

Video : 2-Minute Neuroscience: Synaptic Transmission

Each synapse, as it turns out, can store up to 4.7 bits of information. That might not sound like much until you consider the scale:

  • 1 bit is a single piece of binary data (a 0 or 1)
  • 4.7 bits per synapse × 125 trillion synapses = over 500 trillion bits of potential storage

Translated into digital terms, your brain can theoretically store more data than the entire internet—all in a compact, low-energy package powered by biology.

The Brain’s Efficiency: Powering Trillions of Connections

Here’s something even more mind-blowing: while your laptop heats up and guzzles electricity, your brain handles all of this complex storage and processing using roughly 20 watts of power—that’s about the same as a dim light bulb.

This insane efficiency is what’s inspiring researchers to build neural networks and deep learning systems that mimic the brain. If computers could process and store data like synapses do, we’d have faster, smarter, and greener technology.

Artificial Intelligence and Synaptic Models

The field of AI, especially machine learning and deep learning, borrows heavily from how the brain processes and stores information. Artificial neural networks use layers of interconnected nodes (inspired by neurons) to simulate learning.

But here’s where it gets interesting: researchers are now using real data about synaptic information capacity to refine these systems. The goal? To build AI models that are more human-like, not just in intelligence but in efficiency and adaptability.

Imagine a future where your smartphone thinks and stores information with the same elegance as your brain. That future isn’t science fiction—it’s science.

Beyond the Brain: DNA as the Ultimate Storage Device

While the brain remains the pinnacle of biological storage, it’s not the only game in town. Enter DNA, nature’s original information vault.

DNA doesn’t just code for life—it can be used to store digital data. And we’re not talking small files here. A single gram of DNA can hold up to 215 petabytes of data. That’s 215 million gigabytes—enough to store every photo, song, and document you’ve ever owned, plus millions more.

In fact, researchers have already done it. In one groundbreaking study, scientists encoded a 52,000-word book into synthetic DNA. They converted the digital content into binary (0s and 1s), then translated those digits into DNA’s four-letter alphabet: A, T, G, and C. The result? A physical strand of DNA holding a complete, retrievable digital file.

Why DNA Storage Matters for the Future

Traditional storage devices—hard drives, SSDs, even cloud servers—have physical limits. They degrade over time and take up massive amounts of space. DNA, on the other hand, is incredibly compact, durable, and stable for thousands of years if stored properly.

If scaled correctly, DNA storage could revolutionize how we preserve knowledge. Imagine backing up the entire contents of the Library of Congress on something no bigger than a sugar cube. That’s the level we’re talking about.

Video : How Your Brain Remembers: Neurons & Synapses Explained!

Bridging Biology and Technology

What’s exciting is how these two areas—brain synapses and DNA storage—are starting to intersect. Both are nature’s proof that small-scale systems can handle mind-blowing amounts of data. As scientists continue to decode these systems using information theory, they’re finding ways to integrate them into technology.

It’s not about replacing computers with brains or turning DNA into a USB drive. It’s about learning from nature’s most efficient designs to build the next generation of computing and storage systems.

Conclusion: Reimagining Storage in a Biological World

Your brain’s 125 trillion synapses silently store and process more information than entire server farms, all while sipping on 20 watts of energy. Meanwhile, DNA—the code of life—is showing us how to pack massive libraries of data into microscopic strands.

By measuring synaptic storage capacity with information theory, we’re not just understanding the brain better—we’re laying the foundation for a new era of intelligent, efficient technology.

The takeaway? Nature has already solved problems we’re only beginning to understand. And the more we study it, the closer we get to unlocking the true potential of both our minds and our machines.

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