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AI, Google Coral: anyone?

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DiTBho:
To tell it with humor:

* everyday, I wake up, and i know i need to find some new exploit to prevent spammers from delivering their spam messages to my letterbox
* everyday, spammers wake up, and know they have to find new exploits to delivery their spam messages into my letterbox
So, every day, no matter if you are a sysadmin or a spammer, what really matters is who thinks better to win the game play :D

... thinking about it differently ...


short version. In order to improve my "anti-spam" mechanism, I am really tempted to buy a PCIe device that enables easy integration of two Edge TPUs into existing systems.

I am currently *somehow* involved in a large project with four EdisonNX A.I. engines; unfortunately I am not involved in anything related to the A.I. programs my colleagues are developing with that beautiful but expensive piece of hardware. I am only the dude with the "sys-admin" hat over his head (D'oh).

Google Coral seems one of the new brand name to look at, and there interesting products(1) available for the purchase. Testing boards, developing boards etc. Not so expensive, and they also seem extremely powerful.

I see supported host OS are Debian Linux and Windows10 (I have both installed on my laptop), while the supported framework is exactly the one I mentioned above, just in a "lite" version: "TensorFlow Lite"


So, what do you think?  :D


edit:
(1) Google AI Coral products

SiliconWizard:
What for?

DiTBho:

--- Quote from: SiliconWizard on June 06, 2021, 07:33:13 pm ---What for?

--- End quote ---

Better spam detection using modern machine learning.
Message classification { nasty/spam, good } by using modern machine learning.

Currently the symbolic manipulator used by my two A.I. bouncers strictly implements a subset of the English grammar, coupled with rules to classify a message as "nasty/spam" based on certain words/idiomatic expressions.

So the two A.I. bouncers don't actually understand the meaning of the message. They simply behave as henchmen, and they are not able to learn anything. When a spammer finds a new message-pattern that somehow passes the spam-filter I have to manually add a new rule to cover it.

I want to go from "symbolic manipulation" to "tensor flow", as written above, for me machine learning means I wouldn't no more have to manually write rules and rules set - how I do for years - but rather only train the A.I. to automatically understand what is "bad / spam" and what is "good" in a human contend called "natural language speaking" (NLP) so full of exceptions and more subjected to false positives and false negatives unless you spend a lot of effort with more detailed and complex rule-sets.

DiTBho:
Anyway, this topic is specific for AI, Google Coral products: anyone has experience with them?

tocsa120ls:
Not yet but I have the 4G dev board up and running - not using the features yet, I just got it working from their somewhat vague description.

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