Please share with the community what you think needs improvement with IBM Watson Machine Learning.
What are its weaknesses? What would you like to see changed in a future version?
They should add more GPU processing power to improve performance, especially when dealing with large amounts of data.
I haven't dealt with the solution as significantly in the last probably two or three years. That said, my last deeper dive into that was around the need for the product within the organization. I'm sure it's gotten better and better as the program has gotten better, however, early on, they relied heavily on building out these massive reference tables. That was a ton of the work that had to be done Honestly, I haven't seen any comparative report that has run the same data through two different artificial intelligence or machine learning capabilities to get something out of it. I would love to see that. The top three industries should go head to head to feed the same data and then get evaluated for accuracy. Something like that would be tremendously interesting. I don't know if something like that exists.
The solution needs to improve on its consumerization. They need to expand on it. Right now, they don't make it very easy. Scaling is limited in some use cases. They need to make it easier to expand in all aspects. Their service is a little bad sometimes.
What do you like most about IBM Watson Machine Learning?
Thanks for sharing your thoughts with the community!