For most aspects my opinions don't change. But on coding, it has changed a lot. Two years ago I would just dismiss at the possibility that llm could write up a simple function. Now it has proven me wrong.
Readit Newsdrzzhan commented on Ask HN: Has your opinion on AI changed over the past year? · Posted by u/atleastoptimal
drzzhan commented on Show HN: Draw a fish and watch it swim with the others drawafish.com... · Posted by u/hallak
This is so fun. I wonder if there is a similar page for other animals,
I don't know if "AI agrees" is reliable enough to count. Do you have a particular scientific article that you based on? And what are your example? Your post is mostly describing without concrete example so I can't follow.
An open model that is competitive to commercial models is a big deal if true. I hope someday I can find a way to run such high performance model locally on my laptop.
every thing you said is false or plain exaggeration.
DOGE are not random people, they are government employees using government owned laptops to do audit on the orders of the President (DOGE is a renamed US Department of Digital Services).
Just because they analyze the data, journalists assume something nefarious going on, without the actual knowledge of actual risks:
Based on what they do, they only need read-only access to the General ledger transactions. I highly doubt they have access to modify COBOL programs on Treasury mainframes, but rather just operate off of read-only replicas/backups to read and analyze the data.
there are no risks to the Tresury system in this scenario.
There is an article said that a DOGE member had write access as well (See [1]). But it was quickly changed back to read only. So there was a risk, but I can only hope nothing happened.
[1] https://www.foxnews.com/politics/treasury-mistakenly-gave-mu...
every thing you said is false or plain exaggeration.
DOGE are not random people, they are government employees using government owned laptops to do audit on the orders of the President (DOGE is a renamed US Department of Digital Services).
Just because they analyze the data, journalists assume something nefarious going on, without the actual knowledge of actual risks:
Based on what they do, they only need read-only access to the General ledger transactions. I highly doubt they have access to modify COBOL programs on Treasury mainframes, but rather just operate off of read-only replicas/backups to read and analyze the data.
there are no risks to the Tresury system in this scenario.
I think there is an article said that a DOGE member has write access as well.
drzzhan commented on Ask HN: Are AI dev tools lowering the barrier to entry for creating software? · Posted by u/joe8756438
Every summer, my community pool has a cardboard regatta. Kids can use as much duct tape as they want to waterproof a cardboard box and paddle it 25 yards to the other side. Half of the vessels sink within a length or two and the kids have to swim to the edge of the pool. There’s no age limit, and last year a grown man entered a fully engineered catamaran design that beat all the others handily. The secret was using way more duct tape than anybody else.
AI dev tools are that catamaran. They’ll get you across the pool; you might even get half a mile from shore, but there you are, in the middle of the lake, sitting on cardboard and duct tape, wishing you knew how to swim.
The best analogy I've ever seen. Thank you for sharing!
drzzhan commented on AI pioneer Fei-Fei Li has a vision for computer vision spectrum.ieee.org/fei-fei... · Posted by u/samizdis
I might be rude for this comment, but can anyone explain what did Fei-Fei Li accomplish in AI to be considered a pioneer?
I read her autobiography and I still do not understand. The only thing she did was create the ImageNet dataset, by paying Amazon Mechanical Turk. Am I missing something? I don’t understand how is she in the same breathe as Cunn, Goodfellow, Hinton, even Karpathy?
ImageNet dataset is the main thing AFAIK. But even so I find Dr. Li's contribution big enough. For a context, datasets for computer vision at her time were mostly small, so nn was rarely considered a good method for CV. Not until AlexNet won the challenge, and the world changes after that. I remember many people initially scoffed at ImageNet, arguing that the dataset was flawed and that a “bad” method like NN (AlexNet) could only win because of those flaws. Simply saying “paying” is an understatement because we also need to account for the academic politics of her time.
A little fun fact, even if most research papers nowadays try to propose new dataset, if we take imagenet and pretrain the backbone, we usually end up with a very strong baseline.
Btw, not sure why you think Karpathy has a bigger impact than Fei-Fei Li. I can't think what he is doing that is actually changing the playing field.
drzzhan commented on LaTeX Style Guide for EE 364B [pdf] (2014) web.stanford.edu/class/ee... · Posted by u/walterbell
A very good and solid guide.
drzzhan commented on Facing the Facts to Keep Our Biometrics Secure nist.gov/blogs/taking-mea... · Posted by u/bookofjoe
When I was a college student, I attended a conference regarding IoT. I still remember a developer of a face ID software for a safe box was so sure that their technology was secure because Apple deployed face ID on iPhone. Then a few days later, an article about fooling iPhone's face ID with a printed paper with the victim's face got published.