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#localai

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@Catvalente

Or just use you AI locally 🦾 💻 🧠

I completely understand the concerns about relying too heavily on AI, especially cloud-based, centralized models like ChatGPT. The issues of privacy, energy consumption, and the potential for misuse are very real and valid. However, I believe there's a middle ground that allows us to benefit from the advantages of AI without compromising our values or autonomy.

Instead of rejecting AI outright, we can opt for open-source models that run on local hardware. I've been using local language models (LLMs) on my own hardware. This approach offers several benefits:

- Privacy - By running models locally, we can ensure that our data stays within our control and isn't sent to third-party servers.

- Transparency - Open-source models allow us to understand how the AI works, making it easier to identify and correct biases or errors.

- Customization - Local models can be tailored to our specific needs, whether it's for accessibility, learning, or creative projects.

- Energy Efficiency - Local processing can be more energy-efficient than relying on large, centralized data centers.

- Empowerment - Using AI as a tool to augment our own abilities, rather than replacing them, can help us learn and grow. It's about leveraging technology to enhance our human potential, not diminish it.

For example, I use local LLMs for tasks like proofreading, transcribing audio, and even generating image descriptions. Instead of ChatGPT and Grok, I utilize Jan.ai with Mistral, Llama, OpenCoder, Qwen3, R1, WhisperAI, and Piper. These tools help me be more productive and creative, but they don't replace my own thinking or decision-making.

It's also crucial to advocate for policies and practices that ensure AI is used ethically and responsibly. This includes pushing back against government overreach and corporate misuse, as well as supporting initiatives that promote open-source and accessible technologies.

In conclusion, while it's important to be critical of AI and its potential downsides, I believe that a balanced, thoughtful approach can allow us to harness its benefits without sacrificing our values. Let's choose to be informed, engaged, and proactive in shaping the future of AI.

CC: @Catvalente @audubonballroon
@calsnoboarder @craigduncan

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@system76
I love #LLM, or as they're often called, #AI, especially when used locally. Local models are incredibly effective for enhancing daily tasks like proofreading, checking emails for spelling and grammatical errors, quickly creating image descriptions, transcribing audio to text, or even finding that one quote buried in tons of files that answers a recurring question.

However, if I wanted to be fully transparent to #bigtech, I would use Windows and Android with all the "big brotherly goodness" baked into them. That's why I hope these tools don't connect to third-party servers.

So, my question to you is: Do you propose a privacy-oriented and locally/self-hosted first LLM?

I'm not opposed to the general notion of using AI, and if done locally and open-source, I really think it could enhance the desktop experience. Even the terminal could use some AI integration, especially for spell-checking and syntax-checking those convoluted and long commands. I would love a self-hosted integration of some AI features. 🌟💻
#OpenSource #Privacy #AI #LocalModels #SelfHosted #LinuxAI #LocalLLM #LocalAI

My first real attempt at local AI video creation using Stable Video Diffusion.

I made the candle in SDXL, then used SVD to make a video. Then I fed it through a SD Video upscaler and frame interpolation, to get this result. The flame dance is a little bit wonky due to interpolation.

Not bad for local run open source AI.

The B-17 Bomber was amazing and helped win WWII. I flew on one in 2002 as a tourist - I have family members that were ball turret gunners - bad place to be.

This video was shot on Hi-8, and thankfully I digitized it (at 720x480) way back in that day. Now, I've up-scaled it with local AI (1408x954) and the improvement is astounding.

Sadly, this actual B17 crashed in 2019: en.wikipedia.org/wiki/2019_Boe

#localai
#stablediffusion
#rocm
#amd
#b17
#flyingfortress

Balancing Privacy and Assistive Technology: The Case for Large Language Models

In today’s digital world, the tension between privacy and technology is more pronounced than ever. I’m deeply concerned about the implications of surveillance capitalism—especially the spyware embedded in our devices, cars, and even our bodies. This pervasive technology can lead to a loss of autonomy and a feeling of being constantly monitored. Yet, amidst these concerns, assistive technology plays a critical role, particularly for those of us with neurological impairments.

I recently read a thought-provoking post by @serge that highlighted the importance of sharing perspectives on this issue.

<iframe src="babka.social/@serge/1137542699" width="400" allowfullscreen="allowfullscreen" sandbox="allow-scripts allow-same-origin allow-popups allow-popups-to-escape-sandbox allow-forms"></iframe>

With the rise of large language models (LLMs) like ChatGPT, we’re seeing a shift toward more accessible and user-friendly technology. Local LLMs offer a viable alternative to big tech solutions, often running on specially laptops or even compact devices like Raspberry Pi. For many, including myself, LLMs are invaluable tools that enhance communication, summarize information, transcribe voice, facilitate learning, and help manage tasks that might otherwise feel overwhelming. They can help strike the right emotional tone in our writing and assist in understanding complex data—capabilities that are especially crucial for those of us facing neurological challenges.

While the goal of eliminating surveillance capitalism is commendable, banning technology outright isn’t the answer. We must recognize the significance of LLMs for individuals with disabilities. Calls to remove these technologies can overlook their profound impact on our lives. For many, LLMs are not just tools; they are lifelines that enable us to engage with the world more fully. Removing access to these resources would only isolate individuals who already face significant barriers. Instead, we should focus on utilizing local LLMs and other privacy-focused alternatives.

This situation underscores the need for a nuanced approach to the intersection of privacy and assistive technology. Open-source LLMs, like Piper, exemplify how we can create locally run voice models that are accessible to everyone, even on low-cost devices. Advocating for privacy must go hand in hand with considering the implications for those who rely on these technologies for daily functioning. Striking a balance between protecting individual privacy and ensuring access to vital assistive tools is not just necessary; it’s imperative.

In conclusion, LLMs represent a promising avenue for assisting individuals with neurological impairments. By embracing local and open-source solutions, we can protect our privacy while ensuring that everyone has access to the tools they need to thrive. The conversation around privacy and technology must continue, focusing on inclusivity and empowerment for all.

I use SpeechNotes installed locally all the time, and I’d love to hear how you use LLMs as assistive technology! Do you run your LLM locally? Share your experiences!

Ever tried to set up and use AI Models directly on your laptop or computer? It can get overwhelming very quickly! 😩 Msty is here to change that! 🚀

My newest video walks you through how Msty makes it incredibly easy to tap into the power of AI, both locally (no internet needed) and in the cloud. No more complex setups or slow performance! ⚡

Want to boost your productivity and creativity with AI? ✨ Check out the video and let me know what you think! 👇

🎥 youtu.be/TVcsnof55Kk

#AI#Msty#LocalAI