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A word against hasty generalisation - just because you don't interact with it on a daily basis doesn't mean it isn't being worked on elsewhere. There is an inc
by leblancfg 8y ago
A word against hasty generalisation - just because you don't interact with it on a daily basis doesn't mean it isn't being worked on elsewhere.
There is an increasing number of ML-first companies out there. They are solving problems like object detection, portfolio strategy optimization, medical diagnosis, etc. Things that are 100% not possible to do with just SQL and Bash, and much less expensive than to have humans run those tasks. In those fields, these companies will outperform their competition on average.
I think it's smart for investors to look for in knowledge and talent in the companies they look into. If there's AI/ML talent in the team, their value for acquisition (acqui-hire) is higher.
If you want to solve problems for your existing company, you certainly don't need AI/ML. You can tackle many, many low-hanging fruits with just SQL and Bash.
If you want to build the kind of company that will be around in 30 years, you need to have an ML-first mindset, and you probably need to start now.
- nkozyra 8y agoMy point is less that everything can be done with SQL, but that most of what people are doing is based on things possible 10, 20, 40 years ago. This leaves ml engineers dealing more with software modeling than ml modeling.
- Mahn 8y agoMaybe we could all just agree that AI and ML have their use cases, but they are not necesarily a good fit to any and all computing problems indiscriminately?
- zitterbewegung 8y agoI think the 10% is exActly what these AI first companies should be targeting .