kjw

For example, here's another article from MarketWatch citing this same research note -- https://www.marketwatch.com/story/the-research-note-thats-ra...

Leads me to lend more credence to the news even though OP is linking Bloomberg.

"The Internal Revenue Service's (IRS) legacy IT environment includes applications, software, and hardware, which are outdated but still critical to day-to-day operations. Specifically, GAO's analysis showed that about 33 percent of the applications, 23 percent of the software instances in use, and 8 percent of hardware assets were considered legacy. This includes applications ranging from 25 to 64 years in age, as well as software up to 15 versions behind the current version. As GAO has previously noted, and IRS has acknowledged, these legacy assets will continue to contribute to security risks, unmet mission needs, staffing issues, and increased costs."

This is not true. Snowflake has done just that - it has continuously improved performance resulting in reduced credit consumption and revenue from customers on a unit compute/storage basis. And it has negatively impacted their revenues and stock price. Snowflake's incentive is to strengthen their competitive position and to hopefully generate more long-term revenue from their customers.

The CFO forecasted a $97 million dollar short fall when guiding for 2022 revenue resulting from product improvements. Snowflake stock dropped immediately after.

See Q4 transcript -- https://www.fool.com/earnings/call-transcripts/2022/03/02/sn...

"Similarly, phased throughout this year, we are rolling out platform improvements within our cloud deployments. No two customers are the same, but our initial testing has shown performance improvements ranging on average from 10% to 20%. We have assumed an approximately $97 million revenue impact in our full-year forecast, but there is still uncertainty around the full impact these improvements can have. While these efforts negatively impact our revenue in the near term, over time, they lead customers to deploy more workloads to Snowflake due to the improved economics."

Also see the Bloomberg article -- https://www.bloomberg.com/news/articles/2022-03-02/snowflake....

"Snowflake Inc., a software company that helps businesses organize data in the cloud, dropped the most ever in a single day Thursday after projecting that annual product sales growth would slow from its previous triple-digit-percentage pace.

Executives said improvements to the company’s data storage and analysis products will let customers get the same results by spending less, which will hurt revenue in the short term, but attract more clients in the future.

“The full-year impact of that next year is quite significant,” Chief Executive Officer Frank Slootman said on a conference call Wednesday after the results were released. But “when customers see their performance per credit get cheaper, they realize they can do other things cheaper in Snowflake and they move more data into us to run more queries.”"

This reminds me of the explosion of "big data" tech, which feels like it started exploding in 2010 and peaked maybe five years later.

If ML follows a similar cycle, then in perhaps five years, most tools will have receded into obscurity but a few frameworks and approaches will become dominant. Big stakes and justifies the prevalence and investment in OSS.

Comparison of "big data" and "machine learning" in Google Trends -- https://trends.google.com/trends/explore?date=all&geo=US&q=b...

(Part 1 posted yesterday; thanks HN.)