The amount of roadblocks Google is putting up for GrapheneOS is just ridiculous. None of their decisions make any sense, from the delayed source patches upstream, to the embargos, attestation issues, etc. Google simply regrets android being open source.
I hope people remember this when advocating for chromium. Just because it is open source doesn't mean they don't control it. We need to start the long process of hard forking now or turn to alternatives like Firefox as a new foundation.
> Google simply regrets android being open source.
Android wouldn't be what it is if it wasn't open source. With all the work from outside Google. The same is true chrome.
But they won't learn that on their own. They are breaking the deals. So we move. We force their hand
A lot of people in the comments say that the supposedly better examples in the article are still “horrible” because they can tell they’re AI and point to things that the AI did “wrong” and a human artist would do better.
That may be true if you’re working with a top of the line artist, but in my experience the average freelance designer online is significantly worse than AI. I’ve worked with dozens of budget friendly designers on Fiverr and consistently get way worse results than I’ve gotten from AI models. Will a great human designer produce better output than an AI? Maybe, but a small local event or business probably won’t have the budget to hire them or know where to find them. It’s cheaper, faster and easier to use AI to generate something that’s good enough for their purposes.
People also point out all the little flaws in the “good” examples and cite them as obvious tells that they were AI generated. I think it would be interesting to see if people could reliably distinguish between AI generated flyers and human made flyers. Sure, sometimes it’s obvious like when the AI adds those weird, cartoony people. But if the model is told not to create designs like that and stick to the styles used in the second half of the article, I expect people would have a much harder time distinguishing the human designs from the AI designs.
It’s a tale as old as time — people don’t understand that marketing and branding are just as important, if not more so, than the product. Jev is exceptionally-well branded. Anyone can look at the webpage and understand it, and the implications, instantly.
OPs “marketing” is a single post on Reddit titled “ Predicting sales conversion probability from conversations using pure Reinforcement Learning”. Can you understand what that means? I can’t, and I consider myself reasonably technical. Is it obvious it has the same implications as Jev? Again, no idea. And it was just a single post on a subreddit that I don’t even browse! I see people on this thread saying “Jev is just BERT”. Sure, and Dropbox is just a ftp account mounted with curlftpfs!
I do feel bad for the author for finding something cool and being unable to brand it. But the full definition of “product” INCLUDES being able to coherently communicate it. In some sense the branding is just as much the “breakthrough” as the model.
The biggest problem that I have with most AI posters is that they are too busy, you have to look for information instead of seeing it popping right away.
Amateurs posters of before AI didn't have this problem. White background, the important info in big letters, maybe one clipart or to. So I'm not talking about how pro artists could make a better job, but even the small local non-profit used to produce better posters. Not in the sense of "better looking", but in the sense that they were more readable.
At least the examples of this blog are more readable than what we usually see.
* Different brain regions have different functions: ancient knowledge.
* Different regions contain distinct cell types and molecular programs: also well established.
* Anterior and posterior brain structures may trace back to fundamentally separate progenitor lineages that were independently specified very early in evolution and development: that's the interesting new result.
The headline should have been: "Human forebrain and hindbrain arise from distinct embryonic progenitor lineages" - not that we have "two organs" in the brain.
You use a bunch of technical-sounding words here to make it sound like you understand. But to be clear, nobody understands why the evolved weights of a NN make the decisions that they do.
Almost nothing is understood about the actual representations used for nontrivial concepts, decision algorithms, etc.
If you look at the field of mechanistic interpretability, compared to “GOFAI” like learned decision trees, an LLM is completely opaque.
I think the main gripe that people had with Jev and Typesafe was the language used when they launched. To me personally it seemed like a parody/con/shady at first.
"Breakthrough", "our research went in another direction" , "Two years in stealth", "System One thinking model", "Jev can't hallucinate", "RLCD","We are doing very cool stuff, but we will have to hire you to tell you", - these are some of the things that they said on their website on the launch blog.
I had used versions of bert to achieve the same functionality years ago. But to me it seems like they were able to trick the VCs with "can't hallucinate" etc.
To the above author, kudos for sharing your work and making it open. Something like this shouldn't be closed in the first place when it has been available for so many years
It’s not complicated - the default style signals low effort. Why should I get excited about the village fete if the organizers put in the barest minimum of effort?
But there’s another reason it drives people crazy - it’s low effort trying to present as high effort. If the sign was simple Comic Sans then it would at least be charmingly honest.
I find it kinda funny that even "smartest", most capable models often have a very hard time going beyond surface-level, top-of-mind associations, when faced with creative tasks.
Of course, a "Japanese Minimal Poster" has a sakura and a stylized flag of Japan, duh
A human designer would probably think that "Japan -> sakura" and "Japan -> Japanese flag" are way too obvious, too banal, too stereotypical, and, most importantly too boring. And then they would probably sit for a while and try to think of something fresher and less clichéd.
But AI has absolutely no problem with going with the cheesiest, most overused trope.
Hi! I'm the proprietor of onionfutures.com. I'm actually not a member of UChicago for Our Futures and came up with the idea independently, but we've since connected and they handle our Chicago deliveries.
I played around with Jev last night and did it for classification tasks that I used Gemini 2.5 flash lite with.
It’s a bit faster and bit cheaper, but this is compared to LLM. The consistency was nice to see, BUT, as someone who trained NLP models prior to LLMs, it’s just BERT with more data. I can see why people would want ready made one shot classifier, and I can see the value of sending multiple classifier in one call, but I wouldn’t call it breakthrough. And I believe many labs will replicate it in no time and might have it as part of their harness.
I see it as a wake up call for the tech community to go back to basics for most tasks instead of relying solely on generic LLMs.
The fact that it took this long to add such a basic feature is a disgrace. I’m not even remotely satisfied. Bailed on Claude ages ago. Rolling Codex, Gemini, and Qwen3.8 30B. The only way I’m going back to Anthropic is if they drop and Culture Series mind.
The people behind this are a real (if silly) student organization at UChicago and Northwestern campaigning for the legalization of onion futures trading. Sometimes they will aggressively hand out free onions to passerby on campus. It's quite entertaining.
I think they're fully aware of this. They just don't care, because the goal of "get market share super high" has been reached, so now they have no need for it to continue being open.
I don't disagree about what that means we should do; I just don't think we should assume they're being naive here. It's like writing a program to play chess; you should select your move assuming the opponent is smart and will make the optimal counterplay rather than assuming weakness, and then if they end up being less smart than that, you're still in a good place.
From TFA: "Eric Schwitzgebel writes that . . . There’s a huge cognitive difference between nodding along while reading something and actually productively generating a text. Two reasons: First, once the text is on the page, it’s easy to passively let the approximate word suffice, rather than thinking about word choice in the same effortful, active way we do when generating prose de novo. Second, as I suggested above, I doubt that human beings, even experts, have a good sense of all the factors that shape word choice -- everything they’re being sensitive to. You would have phrased it slightly differently, and even if you don’t know that, or why, a different signal is sent and received."
This is the best articulation I've seen of why simply reviewing and copy-editing does not provide remotely the same value as writing from scratch. I spent a considerable amount of time over the past two weeks reviewing and improving a work document that was the output of an LLM. Given the number of people involved and the final level of effort, I'm firmly convinced that writing it manually would have been faster and resulted in a higher quality product. Getting the wording right matters.
* Google drop "real" Android source-code updates to OEMs _and_ the public every half.
* But they ship four Pixel updates, including documentation + SDKs.
* Now they added new APIs in a Pixel-only update.
* Google also drop security update backports to "trusted" OEMs monthly (which GrapheneOS have had access to for years).
So, there are now Pixel-exclusive app features on the Pixel SDK version which isn't available to OEMs - but, it's highly unlikely any app developer would actually depend on these new APIs, since Pixel marketshare is tiny to begin with. This in essence just makes Pixels a weird beta-testing device for what will come out a quarter later to "normal" devices, which is sort of an odd business decision, but also a weird thing to get really mad about, in my opinion (I do see what GrapheneOS are trying to do, with having OEMs saber-rattle about not getting features on the same cadence as Pixels, it just doesn't resonate very loudly for me).
However, the API headline seems to bury a deeper lede; in the thread, GrapheneOS also claim that the quarterly Pixel releases contain security content which is not appearing in the monthly backports. This is quite bad and very sloppy if true, since the Pixel releases can easily be patch-diffed and exploits backed out of them. I'd be interested in seeing this enumerated in more depth.
Is a new vibe-coded landing page for a 5-year old product really worthy of being on the front page nowadays? There should at least be a [2021] in the title.
I’m reminded of that famous debate between Poincaré and Hilbert at the International Congress of Mathematicians in Paris in 1900. It was then that everyone decided to follow Hilbert’s path, and proof came to be valued more than intuition. I think modern math at school and at applied university kind of lost this intuitive part.
I try to teach my students that mathematics is, first and foremost, a very precise language of communication. It’s sometimes amusing to ask those who don’t like math to do without it entirely, just to see how much harder it becomes to describe the things around them.
Second thing I tell them, formulas are the essence of mechanisms in their purest form. And in this form, they’re much easier to grasp and mentally manipulate. It always amused me, after taking a mechanics course, to imagine that for any formula, you could visualize a mechanism or process that implements it.
And third thing, I suppose, the ability to verify one’s own statements as proof. Although, of course, mathematicians would probably tear me apart here for my heresy:sorry, I’m not a mathematician, but an engineer. You can make mistakes by using incorrect assumptions, but at some point, analysis itself will show you that you were mistaken. There’s a wonderful book, How to Prove It by Daniel Velleman, which provides an introduction to proof for the uninitiated like me. I really enjoyed it.
I love StarCraft. I started playing it right from the beginning, most of my friends right now are from that era. I literally met people that have spread to almost every continent when I was in my early teens. We played at internet cafes and did not have access to the internet, that was priced differently...
I miss those days so much.
Everybody was from a different background back then, and nobody was anything other than a guy that plays StaCraft at the cybercafe... And now, we are in our 40's and I know Math teachers, history teachers, oil rig operators, software programmers, professional gamers, lawyers and more... hahah So crazy to think about it... and I know them, we talk, what a world.
I'm not sure that Claude's "Realigned the shape of the load-bearing ownership gate to reduce the blast radius of the design contract; confirmed, not assumed" is more meaningful than "fix".
Use AI to write things for you to read that you wish someone else had written. ‘Give me a summary of the research on this topic’; ‘Write a report on this data to help me make a decision’. ‘Take this transcript of a meeting and write me the email it could have been’.
Don’t use AI to write things that you are producing for someone else to consume.
There's an amazing viral twitter thread where someone claimed a real Monet painting was an AI generated imitation, and it got an avalanche of comments from people who claimed it was an obvious fake and a poor imitation at that.
It's not tracking a real thing as much as people would like to think.
You can just do what my university did, hire a small shell firm with 3 employees to hold all your data, and when it got hacked they just went bankrupt and we switched to a new shell firm with similar form and function.
Minimizes money usage and does not require any security investments
> They identified two different brain progenitor cells. One, which expresses a gene called Otx2, is destined to become the forebrain and midbrain. The other, which expresses a gene called Gbx2, is committed to forming the hindbrain. They showed that these two cell populations never overlap; they are mutually exclusive from the earliest stages of development.
Very cool. Never thought the brain could have two completely different ancestors
