For the longest time, Mozilla was synonymous with the Firefox browser, but for the last few years, Mozilla has started to look beyond Firefox, especially
one passage of note:
Where does all of this leave the Firefox browser. Surman argued that the organization is very judicious about rolling AI into the browser — but he also believes that AI will become part of everything Mozilla does. “We want to implement AI in a way that’s trustworthy and benefits people,” he said. Fakespot is one example of this, but the overall vision is larger. “I think that’s what you’ll see from us, over the course of the next year, is how do you use the browser as the thing that represents you and how do you build AI into the browser that’s basically on your side as you move through the internet?” He noted that an Edge-like chatbot in a sidebar could be one way of doing this, but he seems to be thinking more in terms of an assistant that helps you summarize articles and maybe notify you proactively. “I think you’ll see the browser evolve. In our case, that’s to be more protective of you and more helpful to you. I think it’s more that you use the predictive and synthesizing capabilities of those tools to make it easier and safer to move through the internet.”
Neuromorphic hardware seems to be best suited as an extension of RAM storage. It doesn’t need to use the DAC/ADC approach of Mythic AI, some versions are compatible with a CMOS process, and could be either integrated directly into the processor, maybe as an extension of the cache or a dedicated neural processing module, or into RAM modules.
It’s pretty clear that current NN processing solutions, by repurposing existing hardware, are bound to get replaced by dedicated hardware with a fraction of the power requirements and orders of magnitude larger processing capabilities.
Once some popular use cases for large NNs have been successfully proven, we can expect future hardware to come with support for them, so it also makes sense to make plans for software that can use them. And yes, local AI… and possibly trainable locally.
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Neuromorphic hardware seems to be best suited as an extension of RAM storage. It doesn’t need to use the DAC/ADC approach of Mythic AI, some versions are compatible with a CMOS process, and could be either integrated directly into the processor, maybe as an extension of the cache or a dedicated neural processing module, or into RAM modules.
It’s pretty clear that current NN processing solutions, by repurposing existing hardware, are bound to get replaced by dedicated hardware with a fraction of the power requirements and orders of magnitude larger processing capabilities.
Once some popular use cases for large NNs have been successfully proven, we can expect future hardware to come with support for them, so it also makes sense to make plans for software that can use them. And yes, local AI… and possibly trainable locally.
Oh yeah Intel’s version of that was looking promising too.