This is image based, not text based. It’s very useful for a number of applications!
I think your usecase is extremely promising assuming it results in better quality output than just running a modern object detector. Another usecase I don’t have bandwidth for, but would likely be very marketable, is similar to what you’re saying but to allow the use of traditional algos like sift or surf across modalities.
Sure, my team and I created “style transfer” GANs to help people better understand particular data in light of other data (the latter of which is usually easier to understand but not always available in practice). It ended up getting strongly positive feedback from large stakeholders, we secured a large contract to deploy, and deployed / maintain it as a SaaS. I even got a patent for the work! I’m sorry I can’t be too much more specific. But, it’s also partially why I may come across as slightly annoyed with the presentation here — HuggingFace is 100% something with functionality I would have preferred to leverage versus my team needing to handle modeling, training, building, releasing, deploying, SLAs, etc. And I would love to support them. But all the presentations being rudimentary with poor UX makes it difficult for me to use them to convince people of this fact, so it’s harder for me to get buy in from finance than it might otherwise be if HF released polished, well thought out demos.
As an aside. I do not personally feel the future of generative modeling is in generative art or creating new Pokémon or things like that, categories which broadly seem like neat tricks without real world usefulness or at least adoption.
I am super familiar with the generative modeling space, have designed them and deployed to real prod, and I will say you’re right that generative modeling results can be hit or miss. But, I was more referring to the page layout, its unreliability (seemed like the author was live debugging in this thread?), poor UX (seems like people can’t easily figure out the page), etc. rather than anything about the model itself (though tbh I also don’t find Pokémon GAN Number 10,000 compelling as a topic). Fundamentally though you do have to always consider results from the latest papers with some baseline skepticism.
I am a big fan of hugging face, but whenever these examples come up, they always seem to be half baked and don’t quite work well, and are not compelling. I think it would behoove them to polish these a little more, in my opinion.
I saw this earlier, and while I’ve been using git for many years, I think this graphic made me understand git less. Maybe because most of my usage is committing and resetting things and not doing the more wacky git commands?
I absolutely love it. Tried it for a few days on vacation because the resort had a few, then started doing it at my work gym, then bought one. I was an athlete in high school and college and now in my 30s I’ve tried all kinds of aerobic fitness equipment over the years. It is the most immersive and exciting piece of fitness equipment I’ve ever used, and singularly the only one that has been able to keep my attention as a real option to train versus going outside and running or cycling. I have also heard very similar stories from colleagues.
I think the people calling it a dumb treadmill or saying it can be replaced by YouTube and a used exercise bike are clueless.
I used to work as a waiter when I was in my first summer out of high school. The calculus was similar there. When it was busy the tables turned as soon as the person got up, so I would often not emphasize dessert. The added $15 on the check from dessert increased my tip a couple dollars, but regular desserts could cause me to lose 1-2 full turns of my section over the course of the evening, so with a four table section of everyone for dessert, I might lose 8 tables total, and if the average tip was $20, I’d lose $160 minus the extra $16 in tip gained from everyone having dessert. Point is, I much preferred quick turns over small per capita increases in per table tips.
In non rush times though where tables didn’t get filled when people left, it made a lot more sense to play up dessert.
This sure is a lot of text, but I have no idea the context of what’s going on and haven’t heard any sort of controversy (though this seems related to _some_ controversy). I’m a little surprised they don’t lead in some of the intro paragraphs with some explanation of what’s going on here for those who aren’t privy to the tech controversy of the week.
This is true with pihole. PiHole is one of my favorite pieces of software and true to this post opening a website off my home network can result in a horrible, ad-ridden experience. But installing PiHole seems to make a number of sites not work, or for example my devices stop updating because they can’t phone home the update server, and it’s difficult to describe to third parties how to address that. All good on my network, but it did take a little targeted whitelisting effort.
Have you ever seen those signs on the back of dump trucks on the highway that state something like, “Stay Back: Truck Driver Not Responsible for Cracked Windshields”?
The other poster roundly dispatched your comment about using a “crypto credit card” so I’ll defer commentary on that.
On the others: the crux of my argument was adoption and usage, with the implication that cryptocurrency was better for the usecase than traditional methods. Of course you can shoehorn a blockchain or “the chain” into any usecase, just like I can use C to write a frontend service, but it doesn’t make sense because C isn’t the best or even a good tool for the job. I can buy bananas and put them on the blockchain, doesn’t mean there is any reason to do so aside from pumping up any cryptocurrency holdings I might have, perhaps BananaCoin or BananaICO or Gorilla NFTs, which I just invented right now.
In the end your pithy comments aren’t going to convince me to start shoehorning blockchain into my day to day transactions — as much as I might long for a decentralized currency — and my fact-based analyses aren’t going to convince someone who has a financial or psychological interest in bitcoins or cryptocurrency or NFTs to abandon them. I suggest we just agree to disagree.
This is really interesting. Copying to the scratch container is powerful and I’ve used it a lot, regularly, but occasionally something comes up where I need to use a more fully featured base to support things. One other downside I’ve encountered with Scratch is no shell so doing docker exec or kubectl exec doesn’t work. Does anyone know a good solution to this problem?
I assumed making money was your metric, but if the metric is “change in currency from fiat to digital” I would argue that after nearly fifteen years of little adoption for mainstream, lack of ability to use cryptocurrency for anything but black market goods and super niche products, and what seems like an utter chaotic ecosystem dominated by con artists, cryptocurrencies are a pretty abject failure on that metric as well.
It doesn’t seem obvious that people who didn’t put money into cryptocurrencies were wrong. Even if you happened to through sheer luck buy low, sell high during one of the pops, that doesn’t mean everyone else was wrong any more than saying someone else was wrong for not playing roulette and selecting the right ending slot.
I’m dealing with this infinite loop chatbot with Verizon right now haha. My number port to become a Verizon customer was supposed to take 4-24 hours. Ten days later still nothing. Chatbot asks me for topics to help with, put in my number but it’s not a Verizon number (it’s mid port) so they recommend I register, I try to register and I cannot because my number isn’t a Verizon number, so back to the chatbot about my problem, they need me to login for further help, but I can’t login without a Verizon number… ad infinitum. It’s maddening and have tried several times to get on the phone with a customer service human being, but after 90 minutes on hold several times nothing.
So I’m in this weird limbo that I think could be solved by a customer rep chat in minutes.
Just an example of automated chatbots being only programmed for a couple common situations and not things like, “I’m a pseudo Verizon customer who is receiving bills but has no phone number with Verizon.”
I started using a tool called Obsidian and making tasks for myself in todo list form interspaced into daily notes, it has worked so far for the last few months and I am able to prioritize better.
One particular incantation of this is I had something complex I wanted to create with a lot of dependencies and steps. I created a kanban style ticket board for myself and was very successful, essentially distilling todo lists into a scoped ticket, via obsidian. I was honestly a little blown away by the whole thing.
Basically the whole thing is integrated into Obsidian as plugins that I fold into my daily calendar and routine. Take notes in meetings or anytime I think of something, and in the middle of notes add a checkbox which gets populated on a master to do list tied to my calendar.
I think your usecase is extremely promising assuming it results in better quality output than just running a modern object detector. Another usecase I don’t have bandwidth for, but would likely be very marketable, is similar to what you’re saying but to allow the use of traditional algos like sift or surf across modalities.