Me and the problem I’m solving
How best to dig into the capabilities of different AI focused software? This is my journey to slicing, dicing and presenting data using IBM Cloud, python and Dash from plot.ly.
Introductions
You know the scenario. You are in a room full of new people for some reason, and the “creeping death” introductions have started.
“Hi, I’m <name>, I’m a <complicated job title that generally means something only to the person who does it> and I’m attending this <event name> because I want to <wide sweeping aspiration that this event may or may not help with>.”
It’s nicknamed “creeping death” for a good reason.
About me and what keeps me busy
Anyway, I wanted to introduce myself and a problem that I’m working on solving.
Hi, I’m Mandie, I’m the WW Technology Lead in the Power Ecosystems Development….
Hang on. No more creeping death intros! Let’s try again…
I work at IBM in the hardware division (that’s the bit of a cloud / computer you can kick), specifically the part where we make servers with POWER processors. My job is to work with software developers, which incidentally is one of the most fun jobs I’ve had, to find out what really cool thing they are doing with their software (usually AI focused and / or GPU accelerated which is my area of interest) and how they might benefit by pairing their very cool software with our very cool hardware. It’s all about building an ecosystem — which is a bit of a buzz word — but ecosystem is so important. I’m also an ex-astrophysicist, swear too much and don’t thrive in too formal an environment. :)
[side note — there’s a lot in that paragraph that could be expanded and likely will in a later post, but treat it as context and bear with me for now.]
What’s the problem I’m solving?
My problem is this — and it’s a good problem to have — we work with *lots* of companies with *lots* of software. How do I best get a view of the various applications and their capabilities (i.e. specifically what they do)? That’s important for our teams that work with customers for a number of reasons:
- Will software A do what my customer needs?
- If the answer to the above is “not quite”, then could I complement software A with software B and C? Or would software D be more complementary?
- What kind of skill level does software E cater for? Expert data scientist or expert business user?
You get the idea. But the key element is here is that this needs to be facts based. I’m a pedantic scientist at heart and don’t like fluff.
Celebrating the journey
One of the many smart people I work with (a Distinguished Engineer, something else to expand on another day) told me recently about the concept of a growth mindset vs a fixed mindset. A key element to having a growth mindset is to celebrate the achievements on your journey to an end goal. This is in contrast to focusing on only the final achieving (or potentially not) of the goal. There’s a Ted Talk and an HBR article if you want to find out more. I’ve not had a chance to read the book yet (it’s sitting on my virtual bookshelf next to the partly read “Getting things done” book) but I really like the concept.
Hence this series of blog posts celebrating my learnings and progress as I’m working on a solution. Incidentally, I’m not 100% sure how I feel about the word “celebrating” in that context, feels a bit over the top, like party poppers and champagne required, but maybe that’s what I should be doing to fully embrace the concept.
And last but not least, what tools am I using to solve the problem?
Bottom line — I’m working on a web application focused on software capabilities which I’ll go into in subsequent posts. This is based on IBM Cloud, is written in python and uses Dash from plot.ly to slice and data capability data for different applications.
I will be anonymising the data to protect the innocent, but by all means get in touch if you’ve got a specific use case you want to solve. Stay tuned for more!
