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So the author recycled 10 pounds of plastic, but used 8.5 pounds of glue to do so (184 sticks at 0.74 oz which seems to be average for glue sticks).
Cool project, but that ratio seems very ineffective. Especially since there is a realistic chance this ends up in landfill within some decades anyway.
We've been running YOLO for a number of years (since v5) on soccer videos. None of the recent iterations have been significantly better, with v26 scoring worse then v9 and v11 on our tasks. Makes me wonder why this version is being pushed by roboflow and ultralytics.
We happened to be in Borsh beach around a week or so ago, and that will be a tourist wreck in 2 years. Multiple working sites, 70% of the beach already claimed by beds.
Quite laid-back in May / start of June, but I do not want to be there in the high season.
Very interesting idea, I hope you can progress this into a well working, proven application.
I tried to do something very similar a year or 2 ago, more directed towards meditation. (Ie as a helper that uses breath to detect a wandering mind). A microphone in itself wasn't sufficient in my case, and detection was quite hard. I ended up using wired earbuds with microphones.
Nice focus as well, less scoring and more signal. All the best in your project!
This seems exactly not what you want. If fully invested in this, you never have the freedom to switch tools, ie go to a different team chat solution. The benefits of having these apps in one UI / ecosystem are relatively small: files - teamchat makes sense, but todo-email, kanban-recpies doesn't add any value.
Like samdixon mentions with ClickUp, the downside is quite large UX wise: you'd be constantly switching context witin dobase. Having 10 pinned tabs for all your tools is very convenient, checking a todo while working on an email in dobase feels messy.
This is sort of what their first sentence states? Except your line implies that they are fast in training and inference, they imply they are focusing on inference and are dropping training speed for it.
It's a nice opening as it is imo
And here I am, feeling slightly ashamed at taking 1 or 2 flights a year. These "commute" statistics are staggering.
Cost wise it does not seem very effective. .5 token / sec (the optimized one) is 3600 tokens an hour, which costs about 200-300 watts for an active 3090+system. Running 3600 tokens on open router @.4$ for llama 3.1 (3.3 costs less), is about $0,00144. That money buys you about 2-3 watts (in the Netherlands).
Great achievement for privacy inference nonetheless.
Which seems weird, it's very technical. Monolith design, relationship types, I've never met an HR person who wondered about those kinds of things
Surprising how badly Jetbrains implemented AI. Apparently to such an extent that even after multiple years of LLM's someone felt confident enough to build a company that can do better.
This looks really neat, interesting technical writeup as well!
Cool social experiment. It's interesting how narrow the scope of all top voted PRs are: change this or that detail in the voting (daily, count down votes etc), or make it more efficient (rust).
I wonder if this has the potential to build a "community" that will take this into a completely different direction, or if it will neatly stay within the initial boundaries.
Is the dependancy on Cloudflare worth the saved time in infrastructure? Getting a big bare metal and deploying a docker should go a long way.
This implementation sounds fully dependant on a service that Zed has little to say about.
Smart 11 | React Native Software Engineer | Netherlands (Breda) / Remote | Part or Full time | smart11.ai
Smart11 helps soccer players to become more intelligent on the field. We're a small team of 3 engineers and are looking for a react native developer to continue development on our mobile app.
Our soccer learning methods rely heavily on video (and a touch of vision AI) to help players learn from their own actions on the field. The app is crucial in that process, and used hundreds of hours a week by clubs and pro players alike. Your work might directly contribute to the improvement of soccer players around the world!
We're a productive, balanced team, and are looking for someone with a builder mentality. Apply at connect [at] smart11.ai, or send me a PM (I'm the CTO). If you're interested but are only experienced in related techniques, please do get in touch, we like to invest in the right people!
Thanks for the suggestion, I missed that!
Super easy? Getting that setup for the first time from zero knowledge will probably take a few days. And that's before understanding all the intricacies like your AWS bill, the hidden costs of cloud, properly securing IAM and setting up your VPC etc etc
Which is peanuts compared to the 350 million that the VCs invested. You're totally right, but I think the internal financial pressure is higher.
I'm using it for a 10.000+ multisite installation (quite simple personal blogs), and even though it has it quirks it works quite well. Almost nothing is best in class and a slight pain to get it working, but the sheer size of the ecosystem is still it's biggest plus. In general every problem or feature you can imagine already exists or is easy to bolt on.
This is a bit too much of an apples vs oranges. Use cases for PHP (easy to develop, maintain websites) are different from those for Go and Rust.
Obviously, PHP came from a place of great inconsistency, and the remains are still there, including the popularity to rant on it. PHP is getting significantly better though, and while a long one, I hugely prefer this route over something more abrupt like python 2-3. The first 3 or so points are valid, but annoyances at best. For the points about closures, statements, inline classes etc., they are just features from other languages that aren't in PHP.
I think they do. Given the damage that leaked keys can do (especially in the Bitcoin mining area) it must be an expensive problem for them.
Exactly. Like so many popular non-fiction books these days, there's about 15 pages of content fluffed up with 200 pages of anecdotes to be able to sell it as a book.
http://nonint.com/ has some interesting posts about how he build a custom server to house 8 GPU's (3090's in this case). You're right that that will set you back more than $1000, though I was only referring to the GPU's themselves.
You might be interested in http://nonint.com/. He made a number of quite detailed blogposts on his 2 gpu machines (both 8x 3090's), including racks, power delivery etc
Reading the timeline at the bottom makes this seem like a very frustrating process, it took multiple nudges and over a year for Valve to even start fixing. I can't imagine putting in this much work and getting such a lackluster response.
Some people use second hand P40 GPUs, which go for around 200-300$. Combine 3 of them with SLI and you've got 72GB of VRAM for less then $1000
At some point it becomes a serious tradeoff. It will definitely excel in finding niche solutions, in bringing up that one mechanism that's rarely used but very relevant in some case. It cannot say "I don't know" and will start babbeling instead, but if you know the downsides the upsides can be significant
Cloudflare bot protection adds a slight delay (as in seconds) at best, and completely blocks users like the parent comment at worst. It costs no money, but isn't free either.
Probably a URL and title and perhaps a bit of readable content would be enough for chatgpt 3 to classify the page type.
There was a show HN here a couple of days ago that used chatgpt to create a scraper based on a webpage. Hook the 2 together and you are basically there!
The difference between your search query and theirs is clearly the level of expertise. Chatgpt has a great use case when you get started on a new subject; even with a very cluncky description it can point you into the core concepts of any field. Instead of reading 10 papers with are somewhat related but not what you are looking for, you can spend 3 minutes writing clumsy prompts and that's about it :)
I'd even argue that if you are given a bunch of code of which 20% is incorrect, it's going to take more than 20% time to fix that. If you've written 100%, you know what the code is doing, what kind of data the variables are supposed to hold etc. In the 80-20% case you've got to build the internal model, test the code, reason and think about it, all of which you would have done during writing.
There are so many nuances to these kinds of statistics (same as the github copilot claims) that they give me a little marketing nausea every time they are claimed as truth.
You are quite right, it's something I've been considering for a long time as well. The cold start problem however is so large, that it has to be an open protocol supported by many of the biggest companies for it to have even a slim chance of succeeding. I admire your attempt, though I'd imagine it to be a very steep and long climb.