The pros and cons of outsourcing machine learning projects and products to run the business. The presentation covered both the advantages and disadvantages of machine learning outsourcing.

1. outsource or not outsource
MACHINE LEARNING
Martyn Sukys, 2017

2. Source: https://www.boldare.com/blog/machine-learning-digital-product-costs/
The Need for ML and AI Specialists

3. Source: https://www.boldare.com/blog/machine-learning-digital-product-costs/
and … Salaries

4. and … Skills

5. Machine Learning Solution Project

6. Source: https://docs.microsoft.com/en-us/azure/architecture/data-guide/big-data/
Big Data Architecture

7. The Negatives of Machine Learning
Outsourcing
❏ No Competitive Advantage
If there is no development there is no
competitive advantage.
❏ Specific Problems are Not Covered
Some data is too specific and there is no SaaS
for it.
❏ Data Sharing
Some companies operate with critical data,
valuable data or personal data. ML SaaS
companies must have to access the user data.
“For companies like Uber, Airbnb, and Pinterest ML
is the core technology and budgets are enormous,
their ML development is a must-have. For other
companies, there is a more important mission than
replication of ML features.”