Hey there, The Leading Edge enthusiasts!
Welcome to the second edition of our exciting journey together! 🚀
Your overwhelming interest and support for the first edition have been incredible, and it's awesome to have you here for another week of engaging discussions and insights. This week, we had some of the biggest announcements in recent times for Geenrative AI, and we will definiately spend some time on it.
So, buckle up and get ready for another insightful ride! And don't forget, I'm eager to hear your thoughts and experiences. Let's start a conversation and keep pushing the boundaries of innovation.
The Hottest Job Title in Corporate America - But Does It Really Matter?
The New York Times calls "The Executive in Charge of AI" the hottest job in corporate America.
This brings me back to 2012. Back then, Harvard Business Review called data scientists the sexiest job of the 21st century. The role has grown dramatically since then.
The allure of 'Data Scientist' reflected an emerging realization: data is king.
But is chief AI officer just another C-level title? One more to the ever increasing CXO titles?
Far from it.
The essence of AI's power lies not in abstract technology, but in two concrete elements: data, and the ability to transform that data into unparalleled business value that can outpace your competition.
In the past decade, roles like the CDO, CAO, or CDAO combined responsibilities for data and AI. But many firms treated these roles as purely technical, sidelining them from executive decision-making. This is a critical misstep, akin to self-sabotage.
Even worse, when these roles are subsumed under CIOs or CTOs, it diminishes their potential to drive business-centric results.
Creating a new title will not solve these problems. The fundamental approach needs to change.
The growing FOMO around AI's potential makes it clear: this role is indispensable and should be at the forefront of corporate strategy. And yet, the question lingers – are companies merely adding a title, or are they truly empowering these leaders to reshape their future?
Uneasy indeed lies the head that wears the crown. In the race to harness AI, it's not just about assigning a title; it's about rewriting the rules of corporate leadership and innovation.
OpenAI Announces Sora
Sora is out and it's mindblowing. The quality is leaps and bounds of anything we have seen so far from Text to Video generators.
But don't believe me, see it for yourself.
Now the reactions have been from excited to worried. People are parimarily worried that this is going to give rise to more misinformation and deepfakes.
I have to say i am more excited than worried. I don't think unrealistic to expect full fledged advertisements created just out of Generative AI in a year from now. You could be a one man startup -creating your own marketing material, doing your own SEO and writing your own code with a little help from your AI friends.
What about deepfakes then? Well, i don't believe any videos i see in the internet anymore anyways. And don't forget to fact check what i write here. 😂
When OpenAI stole Google’s 1Mn Token Thunder…
Google made some pretty impressive announcements this week with the Gemini 1.5 Pro.
On the same day, OpenAI released Sora, a massive language model that captured everyone's imagination. Their strategic timing stole Google's thunder.
But it is a no less impressive product.
For starters, it can handle 1 Million token context. It can query a 44-minute movie in a truly multi-modal way, understanding both text and visuals.
What more could it do?
How about sifting through 100,000 lines of code.
Or deep-diving into a 402-page manuscript.
The bad news? It's just a demo for now. We'll have to wait to get our hands on this revolutionary AI.
Can't wait.
Measuring Wrong Things..
My review of Radical Product Thinking talks about the challenge of measuring wrong KPIs.
Your vision sets the destination, but you need milestones to know if you're on course. That's where KPIs (Key Performance Indicators) come in.
Unfortunately, we tend to grab whatever flashy metrics are popular, not what actually aligns with their vision. This gets them obsessed with the wrong data – the book calls it "Hypermetricemia" : an obsession with metrics irrespective of whether they are the right one to measure.
Here’s an example: A common engagement metrics for websites is how much time people spend on your website (or engagement). But what if your vision is to have customers solve their business problems easily and effectively using your website? Maybe what you really need to track is task completion rates or average resolution time.
Have you ever felt your company or product have been measuring wrong KPIs? How would you fix it? Would be interested in your feedback.
Until next week...
And that's a wrap for this week's edition of The Leading Edge! 🌟
This newsletter is way more fun with all of you onboard! Huge thanks for reading. Did something jump out at you? Share your thoughts in the comments – I love hearing your perspectives. And of course, likes, shares, and follows are always appreciated.
👋🏼 Until next week, fellow AI explorers!
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