bigdipper

Well said.

What’s even more astonishing is the nonchalance with which this BS is being published, let alone spewed by a CIO who clearly has used ChatGPT to generate some buzz and justify the next round of layoffs due to AI.

UHC uses AI for 1000 use cases and meanwhile is getting sued for inaccurate adjudication of cases using AI.

Does replacing unqualified medical case specialists with AI seem to be the right use case?

https://www.statnews.com/2025/02/13/lawsuit-unitedhealth-art...

Thanks. I'll take a look at it; hadn't heard about middleman.

One of the challenges is that it's 7 million rows of data - each translating to one HTML page.

Let me add some color to the speculation here, I worked under Ballmer for sometime leading a product.

Ballmer was a math genius, he was also a spreadsheet whiz and knew as much as a CFO did at anytime. His memory was that of a thousand elephants, and could recite forecasts, actuals and numbers for multiple years in one go.

Microsoft played in the enterprise space, and Ballmer was a marketing genius when it came to enterprise positioning. I credit him with driving the attach revenue concept within the enterprise. Companies that bought Windows, bought office, bought Exchange server, bough maintenance and more.

Even more, he was a relationship marketing genius. He had a photographic memory and remembered names of people he would meet once and recall entire conversations after months/years. And this was globally, he took the company global in a very aggressive way.

He rewarded people, both Bill and Steve weren't stingy about doling out stock - unlike Jobs. This kept a strong talent pool of A players at Microsoft.

He had a strong penchant for the enterprise and where he started faltering was when the Internet started maturing and consumer experiences started converging with the enterprise.

Nevertheless, this man took Microsoft from $15B to $70B in revenue and you can't belittle that.

Data was from random volunteers, and at that moment in time over 10% of the U.S. employee base. I say size was statistically significant not quality of data because there were senior engineers who had been with the company for 15+ years and would skew the datasets. We had lots of demographic data too. Can you guess which race and gender won?

We did a similar thing at Microsost a few years ago. We discovered that it was not just the gender, but also your race mattered. A lot of us (south East Asians) were paid a lot less at the same engineering levels and there was a disparity in the bonus payouts too. The data was not insignificant, and we got to a statistically significant size really quick at some engineering levels (senior and principal).

This is a smart move (ignoring their half assed attempts earlier in their lives).

1. Vertical integration with merchants that sell on amazon and their own websites 2. Encourage merchants to inventory, and fulfill and transact via amazon 3. Enable a Global marketplace for their merchants 4. Next step, subscriptions and data.

But it all hinges on execution...

Is there a study to show

A) How many founders of YC's funded companies were native English speakers vs the rest of the population? B) Does the size of the round correlate to whether they are native English speakers or not?

My theory to test - the more you look like the people judging you, the likelier you are to succeed. It's statistically possible to show this pretty easily.

If there is astringent correlation, get a tall blonde, who can speak well to present to YC next time!