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#customization

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Megatrend #14 - Mass Customization - "The future isn't mass-produced; it's mass-personalized, empowering customers to co-create the products that shape their world." - Futurist Jim Carroll

(Futurist Jim Carroll is writing a series on 30 Megatrends, which he first outlined in his book Dancing in the Rain: How Bold Leaders Grow Stronger in Stormy Times. The trends were shared in the book as a way of demonstrating that, despite any period of economic volatility, there is always long-term opportunity to be found. The book is now in print - learn more at dancing.jimcarroll.com)

It's time to shift gears - so far, this series has covered AI, energy and healthcare - but now, with this trend #14, we'll shift into the manufacturing megatrend category:

First up is 'mass customization.' What's that? Manufacturing production is shifting from standardized mass manufacturing to personalized creation at scale. 3D printing is just the beginning of this new world of flexible manufacturing systems that fundamentally change how we think about inventory, distribution, and product design.

This is a rather tectonic shift, because manufacturing is moving away from the century-old paradigm of standardized mass production toward a more agile, customer-centric model: mass customization.

This transition represents more than an incremental improvement in production techniques; it is a fundamental re-architecting of how products are designed, created, inventoried, and distributed.
Fueled by a convergence of digital technologies, new materials and new methodologies, this new model promises to deliver personalized products at a scale and cost previously unimaginable, fundamentally changing the nature of competitive advantage and value creation in the 21st-century economy. (Success will also flow to those nations and regions that have the maturity to embrace the change. The rest will be pretty much behind and will see the end of most manufacturing jobs.)

#Manufacturing #Customization #Personalization #3DPrinting #Robotics #AI #Innovation #Technology #Automation #Future

Original post: jimcarroll.com/2025/07/decodin

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GitHub just dropped a new #AI thingamajig that promises to make Large Language Models dance to your task-specific tune with nothing but a vague text description. 🎩✨ As if GPT-3 wasn't already drowning us in enough AI-generated nonsense, now we get to customize it without even trying. 🙃
github.com/SakanaAI/text-to-lo #GitHub #LLM #Customization #Tech #News #Innovation #HackerNews #ngated

GitHubGitHub - SakanaAI/text-to-lora: Hypernetworks that adapt LLMs for specific benchmark tasks using only textual task description as the inputHypernetworks that adapt LLMs for specific benchmark tasks using only textual task description as the input - SakanaAI/text-to-lora
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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