Isn't training material the biggest problem for truly open source LLMs (such that could compete with top tier models)? The computation part can be solved with money, but compiling a comprehensive training set that could be freely shared and free of copyright issues is pretty much impossible.
I wonder if we could gamify and democratise it somehow, like fold-at-home and wikipedia...
I've been training a teeny specialised model to run in a browser on a phone to detect harmonium notes played in a song (harmonium turns out is a pita, another story for another day), getting good labelled data is _all_ of the hard work.
That being said, maybe for cheap inference, using a big model to train something ultra-suited for the task at hand might be how we could handle local inference; thinking language specific models.
You don't need to have fully copyright-unencumbered datasets to build Open Source AI, as that (as you say) would be impossible. https://opensource.org/ai
Do we need to bring Keybase[1] "back"? The original idea, mapping your social media presence to certain encryption keys.
In the future it will be increasingly difficult to prove in online context that you are not a bot. Being able to show that your social media (HN, GitHub, etc) presence goes way back would be an option.
"yes, there were regressions in some use cases of rsync in the 3.4.3 release. I quite deliberately tried to err on the side of fixing security issues for that release, and there were some valid (but unusual) use cases that got caught up in the changes"
Not sure if this is the future I want, but I've always thought the main idea of smart glasses is to automatically bring up information that is relevant in your current context. One part of this is to recognize who you are staring at.
I have some vague recollection of a sketch where the user walks around and gets popups and ads in his glasses and later removes them to discover there is a calm city life around him. Was that Black Mirror?
"By integrating Ookla’s data products, including Speedtest®, Downdetector®, Ekahau®, and RootMetrics®, Accenture will help Communications Service Providers (CSPs), hyperscalers, and enterprises optimize the mission-critical Wi-Fi and 5G networks that power their digital core. [...] Ookla’s data platform is anchored by more than 250 million consumer-initiated tests per month, complemented by controlled drive, walk, and embedded testing options"[1]
Is there some legal reason to scatter announcements with that many ® symbols, or do they just do it for style reasons / because they think it makes the announcement look more impressive?
i'm guessing that part of accenture's consulting business is helping people navigate the trademark registration process. so they've got to hype up the ®.
You missed the point of the article, which is that DACH places more importance on Compliance, Security and Stability. Those are the first questions first and foremost, and because they are expensive questions, you have to charge more than <€1000/month.
"Only $99 to add 5G Backup to any UniFI network" and "Fully unlocked for any compatible carrier with SIM and eSIM support". Wonder if there's some catch?
It’s likely because the quick thought is that auth is just user table with hashed password.
Then when you really start thinking about it, the list of requirements grows.
Of course it’s still totally doable for an average developer, but takes time and mistakes can be catastrophic. And maybe the time is better spent developing stuff that differentiates you from others.
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