> iv. Your use of the SAM Materials will not involve or encourage others to reverse engineer, decompile or discover the underlying components of the SAM Materials.
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We've seen b before. React was controversially released with a similar clause and ultimately Facebook dropped it and used a standard open source license. Their lawyers really love this idea for some reason.
Do their lawyers love the idea? Hard to say. My guess is, Zuck really likes the idea, so he keeps directing them and their chief counsel to try stuff like this.
It's almost as if having a CEO of a company placed beyond the control of the corporate board is a bad thing.
I'm no fan of Facebook or its social effects but I can't deny the wonderful downstream effect of their open source.
Popular microscopy models like Cellpose[0] have leaned heavily on the cornucopia of open and SOTA power. I have no doubt thousands of biologists have benefitted from the capabilities these models bring. I think it was unthinkable just 5 years ago that a single biologist with just a laptop could do mass-segmentation at this kind of fidelity.
Then there's Napari and it's plugin ecosystem[1] that wouldn't exist without the Chan Zuckerberg Initiative. Again, I'm not trying to glaze them but as someone in the biotech/microscopy space I can't understate how often I use and benefit from their open source.
React is more of a plague than a wonderful downstream effect or mixed bag. It’s essentially cemented Js as the way to build a website even if you don’t need the complexity. It is the leader in brain dead Js evangelism.
Credit where credit is due, though: ReactJS became #1 on its merits.
...yes, Redux (not React) deserves to be #1, but Redux isn't a complete, all-under-one-roof framework the way React is; but regardless of that: The Redux/React approach is just fundamentally a better design than what we had before: stateful-controls/widgets and two-way data-binding.
If you'd like to relive how UI devs suffered throughout the 1990s, 2000s, and most of the 2010s I invite you to try making a native Windows 11 desktop UI using WinUI3 using the MVVM (anti-) pattern: nothing but mutable objects of indeterminable state getting caught in infinite-loops or unbound recursion due to INotifyPropertyChanged - and Microsoft is still pretending that's the "right" way to build a UI.
Sorry am ranting on about something I have very little control over; it's just frustating.
The scoop: X-ray imaging of various strictures for scientific purposes produces colossal reams of data, previously hard to analyze. Meta provides machine analysis, both segmentation and classification, using unsupervised learning models.
> a fully reconstructed, semantically labeled 3D volume delivered back to the scientist physically standing at the beamline [x-ray] instrument, ready for interpretation while the experiment is still running. Total turnaround: approximately 15 minutes.
To Grok's credit I think it's fairly good as a creative writing tool because it can be very "spontaneous" and it naturally seems to use an informal style. It also lacks a lot of the words and phrasing Claude and OpenAI get hyper-fixated on.
IDK if this is emergent from being trained on an endless trough of Twitter shitposts but compared to how stiff the rest are, I consider it a feature. I wouldn't use it for anything important though, heh.
Even that is kind tbh. The company is so poorly run and the leader so controversial that it makes it irresponsible to build anything serious that relies on their products. Other than the rocket part of the business, everything else under the SpaceX umbrella is a nonstarter.
Starlink arguably is not the rocket part and its the most profitable piece, it held together the rocket side of SpaceX and he expanded research and development.
> And I think OpenAI has solved more open math/ stats/ CS problems.
Still surprises me that OpenAI seems to lead in this one weird niche, I wonder what causes GPT to be able to routinely pull this off, there was one instance where some random 18 year old broke some mathematical question without knowing more than high school math if I remember correctly, all because of GPT.
> Claude often makes better looking interfaces and designs
How do you even qualify this? Either by "Well, when you're not specifying anything about it in the prompt" and then it almost doesn't matter at all, or by what actually goes into the prompt, then again it doesn't matter at all what model you use, more about the person driving it.
AI model inspects hundreds of thousands of scientific images. A job that previously took an expert roughly a month can now be completed in around 15 minutes.
Gonna need to have a talk with LLNL. I'm sure they didn't choose the name, but seems a tad leaning in to use the name of tech from Star Trek meant to produce untold abundance that instead became an unintentional doomsday device.
I used to work with images representing scans of brain tissue - for a full brain visualization at one horizontal slice terabytes was a common measure and the resolution of those images wasn't even particularly detailed - all the full resolution stuff was taken of tiny sub-sections of interest. This was also two decades ago - so I'm sure they've upped their game.
My company does whole-brain scans of mice on a Zeiss Z.1. Lower resolutions are typically in the low hundreds of GB. Higher-resolutions and multichannel staining can get you in the TB range. When a typical client is doing 10's of brains it definitely adds up. But even for us (and I consider us a smaller operation) we aren't output PB's. So I'd consider the above claim still pretty impressive.
Yeah - our multi TB scan from two decades ago was a dolphin brain image which is a fair bit larger than mouse - and it was a stained sample that ended up being used as our demo image frequently because the contrast dyes set well and resulted in a very pretty visual overall.
I didn't meant to say that PBs of image data is common place - we had no image that approached that size - but people outside the domain of microscope scan results might be unfamiliar with just how chonky these image files would get traditionally.
I think a big thing that the enterprise comparison misses is that this is petabytes worth of dense data that has to be put through fairly heavy processing (some of which is currently custom for the specific experiment) and studied by a human.
It isn't just a giant database of small files and metadata blindly feeding a recommender system.
Several petabytes is definitely a staggering amount of data in that context of being analyzed by human eyes to extract some scientific value.
I'm not sure exactly which enterprises you have in mind, but sure: quantities which can be expressed as "a year's worth fits on my desk" should not be described as "staggering", and 10 PB of hard drives will (just about) fit on my desk.
The LHC, on the other hand, that generates a petabyte a second and has to throw most of it away for obvious reasons:
As a former proposal specialist (B2B, B2G, non DoD) I looked into the Genesis Mission procurement site and process.
Unless someone can correct me, the total amount of grant monies is $280,000,000 or so.
It became obvious that it’s not worth my time to engage in the “mission” as they call it, even if I could benefit some worthwhile causes.
That’s a pittance and pretty insulting to the purported benefit of funding scientific endeavors. I’m not even attempting to be political here. $280 Million versus $XX Billion for warfighting is a seriously gross misallocation of public monies, IMHO.
Total lackluster reporting on the scale and scope of the actual numbers, but not surprising.
This is a really weird comparison. The Chan Zuckerberg foundation is nowhere involved with any war. All they’re doing is making money available for research. In which universe is $280m not enough?
On its own it’s a huge pile of money. If you read the Genesis RFP though, you see that 280M being divided up into a large number of distinct thrust areas (26 top level topics, and multiple subtopics under each). So for each area of work, that 280M gets reduced to just a few $M. That may seem like a lot, but when you consider the cost (eg, including non-academic partners since Genesis strongly biased towards collaborative proposals that include some subset of industry, national labs, and academics) and the expectations of what can be delivered in the time allotted for each award, the picture looks far less rosy.
Really fascinating writeup — I particularly appreciated how they didn't hesitate to delve into the load bearing design choices — the implications are staggering.