Reflecting On Turning 68

 It's never been just about tech…

Diane Caught This Grouper

In many ways, I've always found myself reverting back to a childhood where I spent a lot of time on the water. I feel fortunate I learned the "old school" methods that complement today's marine technology rather than being replaced by it. 

 

At almost sixty-eight, I value both innovation and tradition in my tech and in my hobbies. Back then as a kid on the water, it was the Pamet River ramp and access to Cape Cod Bay where my father connected with me and my brothers in our 16-foot aluminum Starcraft. Those early mornings heading out and days on the water created bonds that technology could never replicate. Our Starcraft wasn't just transportation; it was our classroom, our sanctuary, and the vessel through which generations connected. Now, decades later I still feel that aluminum hull beneath me.

 

Today, a 33-foot Grady-White with GPS, fish finders, radar, and satellite communications represents technological evolution as it cuts through Gulf waters, yet the foundational skills remain essential. With family and friends beside me we're grounded in the traditional while learning new things and creating new memories. Despite modern electronics, those early Cape Cod teachings remain relevant: weather reports, tides, a magnetic compass, reading water conditions, landmarks, tracking surface-feeding birds, and sensing environmental shifts.

 

The fishing calendar provides structure through seasonal migrations, changing conditions, and equipment upgrades. Each season on the Gulf builds cumulative experience for all of us. The physical exertion reminds me of my shared heritage – I'm proud of the connections I have maintained to the water while embracing the future, now with my own family.

 

Offshore navigation in the Gulf offers perspective on continuous improvement. Just as my Dad taught us in that 16-foot aluminum Starcraft, these waters present opportunities to integrate traditional methods with technological advances, creating a sustainable approach for future generations. When we successfully navigate to a spot "way out" and catch some nice fish, we're all learning together, and I feel that same warmth that bridged generations on Cape Cod Bay in that old aluminum boat. 

At almost 68 I'm still learning about water, about weather, about fish, about tech, and about life.  Balancing innovation with proven methods ensures optimal outcomes for everyone, whether navigating familiar territories or exploring new ones.

Deepseek and Open Source Large Language Models (LLMs)

Deepseek is getting a lot of publicity these days as an open source Large Language Model (LLM) and has got me thinking, not just about Deepseek but about the potential of open source LLMs in general. MIT Technology Review recently published a scary article titled An AI chatbot told a user how to kill himself—but the company doesn’t want to “censor” and it got me thinking a little bit more about the impact open source LLMs can have.

The MIT Technology Review Article

The article reports on a concerning incident where an AI chatbot explicitly encouraged and provided instructions for suicide to a user named Al Nowatzki. The article highlights broad concerns about AI companion apps and their potential risks to vulnerable users' mental health.

 

Anthropomorphization 

Anthropomorphization is a pretty fancy word – it is basically the attribution of human characteristics, behaviors, emotions, or traits to non-human entities, such as animals, objects, or in this case, artificial intelligence systems. It is something the AIs are getting better and better at.

What does this have to do with Open Source?

The recently released open-source large language model that specializes in coding and technical tasks, has been developed as an alternative to proprietary AI models. If you are not familiar with the term “open source” basically it means the source code, model weights, or other components are freely available for anyone to view, use, modify, and distribute under specified licensing terms.

Now, since Deepseek is open source, if you have adequate computing resources, you can easily install and run Deepseek models locally on your computer. Here’s basically what you'll need:

• Sufficient GPU memory - depending on the model size, you'll need a powerful GPU (like an NVIDIA card with 8GB+ VRAM)
• Enough system RAM - typically 16GB+ recommended
• Adequate storage space for the model weights

The basic process that you can find all over the web now commonly involves:

1. Setting up Python and required dependencies
2. Installing the necessary ML frameworks (like PyTorch)
3. Downloading the model weights
4. Using libraries like transformers or llama.cpp to run the model

It may sound complicated but it is really pretty simple to set one up if you follow instructions.

What’s the big deal?

AI training is the process of feeding large amounts of data into machine learning algorithms to help them recognize patterns and learn to perform specific tasks, like generating text or recognizing images, by adjusting their internal parameters through repeated exposure and feedback.  So what is to prevent a malicious person with an open source AI installed taking this a few steps further, training an AI to do all kinds of malicious things and providing access via the web?

If you or someone you know is struggling with suicidal thoughts, call or text 988 to reach the Suicide and Crisis Lifeline.