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I was going to agree with you, but then my last name is Watson :-) Seriously, I used IBM Watson on a consulting project a little over two years ago and I was d

I was going to agree with you, but then my last name is Watson :-) Seriously, I used IBM Watson on a consulting project a little over two years ago and I was disappointed. To be fair I should take another look. IBM has bought some good companies whose work is exposed in BlueBiz and other web services and the permanent free tier levels they give away rival the free tier levels from GCP. I think AutoML and auto data science web hosted offerings will be a huge market with right now Google, Amazon, and Microsoft leading the way. If I worked at IBM in a position of power, I would work hard to create a great developer experience for simplifying the use of machine learning, NLP, etc.

jacquesm 8y ago
IBM bit off more than they could chew with the AI/NLP project and their brand suffered as a consequence. Some problems are simply hard in the general case, though there are some spin-outs and spin-offs of that project for more limited domains that are successful.
- Retric 8y ago
  Comparing the amount their brand suffered vs profits they may have come out ahead. AI got some real products from this hype cycle, but expectations where high enough that a crash was inevitable.
- mindslight 8y ago
  Isn't arbitraging off developed brands just a common contemporary playbook?
xiphias2 8y ago
The big difference with Google and AutoML is that Google was already doing lots of machine learning in the past, just not deep learning. With deep learning it took the transition seriously internally as well: there's a huge push to get all models to use Tensorflow - even if the transition itself is painful - and this helps the infrastructure providers as well to gather feedback. With IBM it all started as a very successful research project, but instead of working more on the Watson system, it decided to rename dumber projects to be under the Watson umbrella as well thereby giving the impression that it's the same system that won in Jeopardy.
Spooky23 8y ago
I used some Watson stuff that came with another project as well. It wasn’t bad at all, we didn’t cure cancer but it provided a not so awful way to do some basic ML workloads. The other problem is that IBM pitches Watson to anyone, and many of the customers lack the clue to utilize it.

jacquesm 8y ago

IBM bit off more than they could chew with the AI/NLP project and their brand suffered as a consequence. Some problems are simply hard in the general case, though there are some spin-outs and spin-offs of that project for more limited domains that are successful.

Retric 8y ago
Comparing the amount their brand suffered vs profits they may have come out ahead. AI got some real products from this hype cycle, but expectations where high enough that a crash was inevitable.
mindslight 8y ago
Isn't arbitraging off developed brands just a common contemporary playbook?

xiphias2 8y ago

The big difference with Google and AutoML is that Google was already doing lots of machine learning in the past, just not deep learning. With deep learning it took the transition seriously internally as well: there's a huge push to get all models to use Tensorflow - even if the transition itself is painful - and this helps the infrastructure providers as well to gather feedback. With IBM it all started as a very successful research project, but instead of working more on the Watson system, it decided to rename dumber projects to be under the Watson umbrella as well thereby giving the impression that it's the same system that won in Jeopardy.

Spooky23 8y ago

I used some Watson stuff that came with another project as well. It wasn’t bad at all, we didn’t cure cancer but it provided a not so awful way to do some basic ML workloads. The other problem is that IBM pitches Watson to anyone, and many of the customers lack the clue to utilize it.