The use of GPS scrapers is going to get to "
Zoom | ENHANCE" trope levels:
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"Find me a product family of the same [PRODUCT SPEC/MODEL/TYPE] {such as a web cam} - which is online. Build a model for" <<---- Such an idea, using a feeder-AI to slurp such and then feed it as a module for "Open WebCams of [MNFR],[MODEL],[FIRMWARE]) which is connected to [ISP] (via ipv4 allocations (AS#s))" == CVEs available
(Maybe I have a lib/ability to have a bot continually CVE-MAP (nmap) for those that match my exploit, but be able to do it from a diffuse perspective, as NLP requested - so my CVE can even hit patterns that are not obvious, over a long time....
Lets say I CVE all webcames in [AREA AROUND TARGET] - then let it run with lots of models, and scan for trafficking (humans walking, as well as cars driving) - but now I can tag that:
Show me every time 'that car' has driven near hear in N period.
Give me a list of frequency of license plates, anomolies, move that to plotly - show me who always drives by, and whomever is driving in this area with a different, but consistant frequency over a short period of time"
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This power is finally in the hands of anyone who can connect visual tagged feeds to llms which are currently avail... and a f-ton of folks....
SO....
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This is why we need the ROBOTS.TXT version of AI.txt on INDIVIDUAL LINES OF ANYTHING readable by any AI bot.
Like a singular UNICODE char, at beginning|end of {ELEMENT} to EXCLUDE that from your model training?
a [REDACTED] Function, mayhaps?
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I mean something more /enforeble/ as a gitignore?
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Does this already exist, as a function in all languages - such that you can have this integrated to any repo easily?
(UNDERSTAND our business model based on [WHATEVER])
(REDACT anything from REPO which refers to function X, look at the outcomes for function X and recommend other areas of REDACTION which relate to our business model. (even in schemas/challs/variables that may not be trained on?)
((I am not sure what this level of code "obfuscation from observation by AI" falls into?))
Lets say, we want to identify useful data analysis ARCHETYPE logic - without revealing business logic.
Manufacturer
Country
IP-AS#/ISP
Firmware version
blah blah
you get the idea.
Code crawl security.
Open
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An interesting dataset would be any open DARPA/DOD/[WHATEVER] contract.
Look at the similarities in contracts for accepted archetypes that get funded, and who submitted, budget, success, news stories, lawsuits, congress-folk-and-circle connected...
Yeah - .gov corruption should be afraid of datasets developed by just simple SaaS' corpus available.
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So develop an active scanning GPT-corporate-espionage-bot?
But that easily delves to pico-NSA's (corporate GPTs searching for sensitive [stuff] (AI CyberSecurity is the FUTURE)
However, protect your GPTs, which one may publish on a GPT store: - the logic can be used to reverse engineer your own business logic. It will show what your corp security GhostShell is paying attention to - thus, exactly what your surface area is?
The really crappy secure model is toxic injection. So one must really look REALLY FUCKING HARD to indexing the internet on their models with each result as a hash - AND THEN
Tracking that result hash. For trust.
Look at a publication over time. Alert on edits - but the AI, can check on remote/foreign reposts for a hash...
Even a sentence - so tokenize a sentence, against a URL such that if the sequence in words in a particular body of [electronic text] (body/paragraph whatever - of text] is given an original hash of token for creation?
So you literally type something into and get youre uniqueness which allows for signatures.
Done with stream.