Notes on data, AI, IT
and security
No marketing fog. The way I think about real problems with founders and managers.
GPT-2 and language models: what the signal means for business right now
After GPT-2, the conversation about text generation shifted. I look at what actually changes for companies today and what is still in the lab.
AutoML: what it is and what a manager should not expect from it
How AutoML tools lower the barrier to machine learning - and where they still require expertise and management decisions.
Cloud security after the first wave of containers: more than just the network
Why the perimeter security model does not work in a container environment - and what actually needs protecting instead.
Stream processing is an operations question, not an architecture question
Why the decision to move to streaming should start with understanding operational load, not with choosing a technology.
Cloud egress cost: the hidden budget line that is easy to miss
Why the cost of transferring data out of the cloud often comes as an unpleasant surprise - and how to keep it under control.
Autonomous mobile robots in the warehouse: when it makes sense and when it does not
How to assess warehouse readiness for AMR deployment - without the marketing simplifications that robots will fix everything.
The real cost of an NLP pipeline before you are sold by the demo
What actually requires ongoing support in a production NLP system - from data labelling to quality control in live operation.
Attack through a software vendor: when your perimeter starts elsewhere
Why a compromise of third-party software is a threat to your infrastructure, and how to think about managing this risk.
A data lake without governance is a swamp, not an asset
Why a data lake without access policy and governance turns into unmanageable storage that nobody can get trustworthy data from.
Data ownership matters more than a data platform
Why companies buy expensive data platforms and end up with the same problems - and what needs to be resolved before choosing a tool.
Model drift: why an ML system degrades without visible failures
Machine learning models in production lose accuracy over time - quietly, with no errors and no alerts. What drift is and how to monitor for it.
GDPR: nine months in and the first major fine
In January 2019 Google was fined 50 million euros under GDPR. What it means and why having a privacy policy is not the same as actual compliance.