srajabi
Joined 14 years ago
Karma
221
Submissions
34
Member since
Feb 5
Software Dev in ML/Analytics out of YVR
View on Hacker NewsRecent submissions
Comment · 1 year ago
What about DiskANN? https://milvus.io/docs/disk_index.md
Comment · 2 years ago
https://archive.is/L0BdY
Summary:
* Spotify’s Layoff Impact: CEO Daniel Ek was surprised by the significant operational challenges following the layoff of 1,500 employees.
* Financial Performance: Despite achieving record profits of €168 million and revenue growth, Spotify missed its targets for profitability and user growth.
* Investor Reaction: Shares increased by over 8% after the earnings report, reflecting investor confidence.
* Long-Term Strategy: Despite short-term issues, Spotify believes the layoffs were necessary for long-term profitability.
Comment · 2 years ago
Does this mean you get additional documentation then the example in the blog? Or is that $99 for the bad documentation?
Comment · 2 years ago
Is this down?
Comment · 2 years ago
I constantly do this OpenAI/OpenAPI typo
Comment · 3 years ago
Looks like they've been in use since 1972 and in use in Healthcare specifically since 1995.
Comment · 3 years ago
No abstractions turns to spaghetti
Too many abstractions turns to spaghetti
I don't think the answer is one or the other at all like the blog post is implying. I think his previous conclusion of a threshold makes more sense. Perhaps though they have chosen the wrong abstractions and hence the confusion
Comment · 3 years ago
A little hard to understand why this is cool, but if I understand correctly:
1. Lucene is trying to get Approximate Nearest Neighbours (ANN) search working for semantic search purposes: https://issues.apache.org/jira/browse/LUCENE-9004 https://github.com/apache/lucene/issues/10047
2. The Panama Vector API allows CPU's that support it to accelerate vector operations: https://openjdk.org/jeps/438
So this allows fast ANN on Lucene for semantic search!
How did people do this before Lucene supported it? Only through entirely different tools?
Comment · 3 years ago
"This work is part of the third pillar of our approach to alignment research: we want to automate the alignment research work itself. A promising aspect of this approach is that it scales with the pace of AI development. As future models become increasingly intelligent and helpful as assistants, we will find better explanations."
On first look this is genius but it seems pretty tautological in a way. How do we know if the explainer is good?... Kinda leads to thinking about who watches the watchers...
Comment · 3 years ago
Wow this does so well on text! The original model struggled a lot, it's impressive to see how far they've come.
Comment · 3 years ago
Can't seem to click "I Agree" and try it out. Anyone have a work around?
Edit: The answer was patience
Comment · 3 years ago
It's not a defense. If you want to fix the fact that a lot of tech jobs are bullshit, FAANG or otherwise. You have to fix that phenomenon in all work sectors, because it's not a uniquely big tech created problem.
Comment · 3 years ago
Most jobs are bullshit jobs https://en.wikipedia.org/wiki/Bullshit_Jobs the phenomenon is not unique to tech.
How many finance workers on wall street do you think provide direct value to society?
Comment · 3 years ago
This is all fluff with very little substance, OpenAI wow'ed the whole world with ChatGPT and all Google can do is post a half-baked fluff piece that they're releasing something "soon"
Comment · 3 years ago
It's cool you're on here and I'm sure I speak for many people in saying I really appreciate your video series and comments like the above!
Thank you!