buzzscale
Joined 13 years ago
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160
Submissions
21
Member since
Feb 8
Recent submissions
Comment · 3 years ago
Comment · 3 years ago
Fascinating. Seems like similar issue risk management issue to silicon valley bank where they didn't account for a jump in interest rates and increase in inflation.
Comment · 3 years ago
That doesn't make any sense though. What benefit would DOJ get from getting the IP address of everyone who downloaded ytp-dlp? They aren't the enforcement arm of google's terms of service, which is a civil matter.
Even if they were, and the DOJ was going for a dragnet operation to go after tools that could potentially infringe terms of service of big corporations, they would go after every tool and every fork. Not just 1 package. But again, what court would allow such action and why?
If I was in the DOJ and was investigating a malicious package uploaded to PyPI, I would ask for the IP's of the downloaders to see if the uploaders dun goofed and downloaded their package shortly after uploading off VPN. Or to find out if any major corporations were impacted by downloading the malicious package and to inform them.
Comment · 3 years ago
Dolly 2.0 is fully open, Apache License and the tuning dataset is employee generated:
https://www.databricks.com/blog/2023/04/12/dolly-first-open-...
Comment · 3 years ago
Databricks Employee here. Contact your Databricks account team, particularly your Account Executive, they can help articulate this to your IT team.
There was a thread on reddit about this:
https://www.reddit.com/r/dataengineering/comments/121mm5c/ma...
Comment · 3 years ago
This is one of the reasons Databricks created Dolly, a slim LLM that unlocks the magic of ChatGPT. A homegrown LLM that can tap into/query the datasets of all the data in an organizations Data Lakehouse will be hugely powerful.
I am working with customers that are looking to train a homegrown LLM that they host and have blocked access to ChatGPT.
https://www.datanami.com/2023/03/24/databricks-bucks-the-her...
Comment · 5 years ago
Millennial home ownership lags sharply behind previous generatons. He's not saying that we have feudalism. He's arguing that is the direction the world is heading with increasing inequality. This video does a good job of explaining his views:
https://youtu.be/ZXP8gH0wddE?t=386
I particularly like his point about why homes have risen from 2-3x wages to 20-30x wages, this was a question I had always pondered about and could never find a good explanation for. The GINI data you posted is interesting but ends at 2018 and if I had to guess the pandemic has only worsened inequality. Asset prices such as homes have risen sharply putting them out of reach for many families.
Edit:
Looks like has worsened signficantly:
The United States’ Gini coefficient is .484, the highest it’s been in 50 years according to the U.S. Census Bureau. The U.S. has the highest Gini coefficient among the G7 nations. The top 1% of earners in the United States earn about 40 times more than the bottom 90% of earners.
https://worldpopulationreview.com/country-rankings/income-in...
Comment · 5 years ago
“My grand, macro thesis is that real interest rates have to stay low, and that’s because the rich have all the wealth and like saving,” he reflected. “Now, no matter how hard you work, how smart you are, if you come from the ‘wrong’ family you’ll probably never own property. That is feudalism. We’re going back into a world of aristocracy. Capitalism’s over.”
Comment · 5 years ago
Thats where Databricks comes in though, you can implement row/column based security on your data on cloud object storage and use it for all your downstream use cases (Not just BI/SQL but AI/ML without piping data over JDBC/ODBC).
Comment · 12 years ago
Care to share details on the technical implementation? What do you have powering the backend?
https://www.mit.edu/people/dpolicar/writing/prose/text/think...