English Amiga Board


Go Back   English Amiga Board > Support > support.Hardware

 
 
Thread Tools
Old 04 June 2020, 16:47   #1
PurpleMelbourne
Registered User
 
PurpleMelbourne's Avatar
 
Join Date: Dec 2018
Location: Australia
Age: 51
Posts: 99
Reverse engineering chips from die photos

Looking over some almost 4k res photos of Motorola chips, i first noticed the pictures are kind of blury, but also very regular...

So i was thinking it'd be a great avenue to train an AI on 6800 series before 68000 series as the similarities would be very beneficial for the AI to make good guesses.

If there were preceding compone ts to learn from then even better.

Personally I've never dealt with AI's, but this sounds like a perfect job for them. The 060 is no where near high enough resolution to do more than admire its orderly beauty. But an AI which has learnt all the patterns might recognise 80% of the circuit, making it easier to develop TG68 going forward.

Afterwards we might have a lego library of structures which can be manipulated a lot faster than with HDL alone.
PurpleMelbourne is offline  
 


Currently Active Users Viewing This Thread: 1 (0 members and 1 guests)
 
Thread Tools

Similar Threads
Thread Thread Starter Forum Replies Last Post
Gods reverse engineering Kroah Retrogaming General Discussion 127 27 February 2023 14:46
Megatraveller 1 reverse engineering TreacleWench Coders. General 12 18 May 2020 12:46
Reverse engineering from an executable bloodline Coders. General 13 20 August 2017 08:50
Captive 2 reverse engineering copse Coders. General 2 19 August 2015 21:08
Cadaver reverse engineering Kroah Retrogaming General Discussion 8 11 November 2011 09:35

Posting Rules
You may not post new threads
You may not post replies
You may not post attachments
You may not edit your posts

BB code is On
Smilies are On
[IMG] code is On
HTML code is Off

Forum Jump


All times are GMT +2. The time now is 19:13.

Top

Powered by vBulletin® Version 3.8.11
Copyright ©2000 - 2024, vBulletin Solutions Inc.
Page generated in 0.06438 seconds with 15 queries