6 ms·

Annnnd Martha still doesn't have a ml-solvable business problem identified with a large enough curated dataset to actually create a useful model.

baron_harkonnen 7y ago
That's not a problem at all! In the fortune 500 there are plenty of companies with "problems" that used to be solved with boring things like "averages" and "business logic", but now you can replace those things with LSTMs and Deep NLP models and get half the performance with several orders of magnitude more complexity! The best part is the people building these systems have none of that annoying "engineering background" baggage that will mean they don't worry about stupid stuff like support and maintenance, or even basic debugging: if the model breaks you just build a brand new one!
- jorblumesea 7y ago
  As an added bonus, people with these skills cost x3 as much as a standard engineer. HR will love it!
- paulddraper 7y ago
  Who needs a mean when you can train a model to calculate means....
egypturnash 7y ago
Maybe by the end of part 3.
humble_engineer 7y ago
I just had a flashback and blacked out for 15 minutes in a spat of PTSD from your comment, please sir use your words more carefully they are powerful and over the target.
evrydayhustling 7y ago
This made me lol. The comic is seriously a great intro learning resource; it didn't occur to me the subtext might be "don't attempt ML if you're not at Google".
- otabdeveloper2 7y ago
  > The comic is seriously a great intro learning resource No, it isn't. It's horrible. It read like advertising copy to sway dumb investors into pouring their life savings into Google stock.
- khawkins 7y ago
  The message should be, whether intended or not, for Martha to send this comic to her boss and begin scheduling brainstorming meetings. With the vast plethora of introductory resources for ML today, there's no good excuse for both supervisors and engineers to understand what tools it might provide. The phrase "we need to add AI to everything" should be met with as much consternation as "we need to promote synergy". Precision is important. It's the difference between spending 6 months developing an deploying trained neural nets and 60 minutes for linear regression.
  - jacquesm 7y ago
    You'd be surprised how many investment proposals still contain 'AI' just to sex them up. Even if it isn't applicable. Even if the application suggested is way beyond what current AI capabilities are. Case in point: received just such a proposal last week.
jacquesm 7y ago
Well she was warned not to open that door.
ska 7y ago
... so that puts her about par in the industry, no?
happy-go-lucky 7y ago
Managed healthcare companies have huge data and they have begun to use ML to classify their documents as medical and non-medical, as quality of care and quality of service etc., based on the text they extract from their members' health insurance claims. Generally the extracted text needs a lot of preprocessing.

baron_harkonnen 7y ago

That's not a problem at all! In the fortune 500 there are plenty of companies with "problems" that used to be solved with boring things like "averages" and "business logic", but now you can replace those things with LSTMs and Deep NLP models and get half the performance with several orders of magnitude more complexity! The best part is the people building these systems have none of that annoying "engineering background" baggage that will mean they don't worry about stupid stuff like support and maintenance, or even basic debugging: if the model breaks you just build a brand new one!

jorblumesea 7y ago
As an added bonus, people with these skills cost x3 as much as a standard engineer. HR will love it!
paulddraper 7y ago
Who needs a mean when you can train a model to calculate means....

egypturnash 7y ago

Maybe by the end of part 3.

humble_engineer 7y ago

I just had a flashback and blacked out for 15 minutes in a spat of PTSD from your comment, please sir use your words more carefully they are powerful and over the target.

evrydayhustling 7y ago

This made me lol. The comic is seriously a great intro learning resource; it didn't occur to me the subtext might be "don't attempt ML if you're not at Google".

otabdeveloper2 7y ago
> The comic is seriously a great intro learning resource No, it isn't. It's horrible. It read like advertising copy to sway dumb investors into pouring their life savings into Google stock.
khawkins 7y ago
The message should be, whether intended or not, for Martha to send this comic to her boss and begin scheduling brainstorming meetings. With the vast plethora of introductory resources for ML today, there's no good excuse for both supervisors and engineers to understand what tools it might provide. The phrase "we need to add AI to everything" should be met with as much consternation as "we need to promote synergy". Precision is important. It's the difference between spending 6 months developing an deploying trained neural nets and 60 minutes for linear regression.
- jacquesm 7y ago
  You'd be surprised how many investment proposals still contain 'AI' just to sex them up. Even if it isn't applicable. Even if the application suggested is way beyond what current AI capabilities are. Case in point: received just such a proposal last week.

jacquesm 7y ago

Well she was warned not to open that door.

ska 7y ago

... so that puts her about par in the industry, no?

happy-go-lucky 7y ago

Managed healthcare companies have huge data and they have begun to use ML to classify their documents as medical and non-medical, as quality of care and quality of service etc., based on the text they extract from their members' health insurance claims. Generally the extracted text needs a lot of preprocessing.