Fable will NOT help if it thinks your ML research/ML engineering is interesting
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There's a lot of impressive engineering inside Honor's Magic V6, but it's let down by software that desperately needs polish.
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AI-generated code does not remove the need for software engineering. It raises the abstraction layer. As code becomes easier to produce, engineers must define the system around it: topology, contracts, constraints, evaluation, provenance, approved patterns, and accountability.
AI is changing software faster than cloud, Agile, or DevOps by compressing the entire development lifecycle at once.
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QC for electronics goes beyond AQL sampling — component substitution, counterfeit parts, and firmware integrity require engineering-level review. Standard pre-shipment inspection catches scratched housings, incorrect carton labels, and missing accessories. It does not catch the IC swap the fact...
I asked 4 working engineers this exact question on my podcast: a Google Developer Advocate (Stockholm), a Senior Software Engineer/consultant (Paris), an NVIDIA Deep Learning Institute Instructor (Morocco), and an Infrastructure Engineer at IBM (Dublin). Here's what they actually said: - The Sen...
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AI-generated code can work perfectly and still fail as engineering. It passes all functional tests while introducing SaaS cost drift, operational burden, license incompatibility, lifecycle drift, internal-platform drift, optimization drift, and failure-behavior drift. Functional tests are no lo...
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