Love it. Wonder if it's viable for citizen journalism in warzones and areas of civil unrest, with the larger size of photos (and short videos), given the inherently slow transfer rates and battery life implications of going thru multiple hops before Internet-exiting the area that's otherwise Internet-offline. What's the back-of-the-envelope math here on viable bandwidth?
Wifi obviously has higher bandwidth, but I guess it isn't viable as a mesh, or is there any trick with turning on/off hotspots on phones dynamically that'd make it viable? (Afaik older phones made you pick between being a hotspot or being a regular wifi client, but at least some newer ones seem to allow both simultaneously.)
I'm definitely hoping for a future with wider support for C2PA (content credentials on images) on phone cameras to make these photos power citizen journalism. So far Samsung S25 and Pixel 10 support C2PA in the camera hardware: need other phone makers (especially Apple) to get on board already... if you're an iPhone user, please help yell at Apple support etc!
Aside: I registered a domain and plan to build a citizen journalism news feed for such photos (and uncut videos). I see it as the antidote to Instagram et al's feeds that're full of AI slop (and plenty of fakery even before AI-generated imagery got big). And it's essential to truth, democracy and ultimately (maybe I'm too idealistic here) peace. Aside to the aside: wish some of us techies banded together to build "peace tech" as a new sector in tech, DM if interested in brainstorming or working together.
Sounds like antirez, simonw, et al are still advocating reviewing the code output of these agents for now. But presumably soon (within months?) the agents will be good enough such that line-by-line review will no longer be necessary, or humanly possible as we crank the agents up to 11.
But then how will we review each PR enough to have confidence in it?
How will we understand the overall codebase too after it gets much bigger?
Are there any better tools here other than just asking LLMs to summarize code, or flag risky code... any good "code reader" tools (like code editors but focused on this reading task)?
Most car manufacturers made this mistake because they started mimicking the then leader for innovation (and customer satisfaction), Tesla, too much.
General cautionary tale: just coz a company is successful, doesn't mean it's doing _everything_ right. Plenty of folks who love their Teslas would prefer a few more buttons (and door handles on the inside, etc) if given the choice. Could say similar things about some choices Apple made.
1. What Tesla did right was put a big screen in the center of the car, and then actually think about the UX, and how to improve the software to avoid having to fiddle every other minute with controls on the screen (e.g. climate control is usually amazing, I rarely touch the temperature). What other companies did was just put the screen and slap on sub-par software without much regard for UX, so of course it sucks, even if you have the big screen.
2. Yes, I'd have loved a couple extra buttons, perhaps programmable. My main gripe for instance is/was the air re-circulation (used to live in a country with lots of tunnels), but I'm sure others would have liked some other button. I'd have been very happy to have 3-4 software-programmable buttons for the most used functions.
> I would disagree with that. You do not need a big flashing distract-o-tron in the middle of the dashboard.
Except my car's screen is not distracting: I set it up for my destination, I give it a glance when needed for navigation, and I basically don't touch it until I'm done driving, because (second part of the previous comment) the UX is so well done that I don't have to. Worst case, voice control works well enough for e.g. changing playlists and songs or changing destination mid-trip.
> Cars should have exactly zero screens.
People have been attaching tomtoms and mobiles to the windscreen for the past 30 years anyway to solve exactly the same problem (navigation), and they were always inferior solutions to a well done integrated screen: detaching on a bump, leaving forever-smudges, having to update all maps offline, removable meaning easier to steal, limited functionality, ..... So I disagree. I'd rather have governing bodies evolve to take screen UX into account at regulation: most cars with screens couldn't have been sold.
The display dims adequately , and is far less distracting than competitors , who usually have multiple displays and flashing lights. Especially luxury brands who do the above and have "bejeweled" decorative LEDs all over the cockpit.
Tesla has the most subdued interior of every brand on the market.
sure, I would prefer 90s interfaces if I had the choice, but given the products on the Market , Tesla's attentiveness to the driver experience ( low LCD brightness, moderate contrast UI, reducing demand on the driver) exceeds all competitors by a large margin : better than luxuries, better than German cars.
Even leaving the big distracting floodlight in the the middle of the dash out of it, I don't like Teslas because I don't think an 80 grand car should feel like a 30 grand car.
If they want to sell cars at that price they need to not feel like a base-spec Skoda.
It's not (just) imitation/fashion/aesthetics. Shoving everything into a display allows manufacturers to:
* compress and de-risk production timelines because changes can be made in software instead of requiring retooling/replacing parts.
* reduce cost; the cost of a display is basically required by legislation requiring back-up cameras. Add in a few settings or map view and it has to be a touch screen. Consolidating everything else into a part you are already mandated to included reduces cost.
* meet customer reqirements; Except at the very bottom end of the market, customers expect cars to have space to display a map and be able to use music streaming services. Carplay/android auto also is a requirement for some users.
"Almost anyone can prompt an LLM to generate a thousand-line patch and submit it for code review. That’s no longer valuable. What’s valuable is contributing code that is proven to work."
I'd go further: what's valuable is code review. So review the AI agent's code yourself first, ensuring not only that it's proven to work, but also that it's good quality (across various dimensions but most importantly in maintainability in future). If you're already overwhelmed by that thousand-line patch, try to create a hundred-line patch that accomplishes the same task.
I expect code review tools to also rapidly change, as lines of code written per person dramatically increase. Any good new tools already?
End of an era: video (with broadband Internet penetration) was the best tool we had for 15+ years. But LLMs are now good enough, including in image+infographic generation and factuality (especially when grounding resources are provided... which is where human experts still matter). I think video is now better only for learning physical hands-on skills... and those videos tend to be on YouTube rather than on Udemy or Coursera.
Coursera's model will still survive for a while, given people's desire for branded credentials (university degree credits or company-branded certificates)... until the university bubble bursts too in a 10+ years. Start of trend: https://www.nbcnews.com/politics/politics-news/poll-dramatic...
A bit of a plug: we tried building a consumer business, with a learning experience built atop these LLMs: https://uphop.ai/learn . Still offered for free to consumers, but we're now succeeding much better on B2B ("you either die a consumer business or live long enough to become B2B" was v true for us).
LLMs are not remotely good enough to use as a learning tool. They still make shit up a ton of the time, and you can only catch it if you already know the material (so, not useful for learning). They probably never will be useful for learning, since even after all this time hallucinations are still just as bad as they ever were.
Have you tried them with providing a grounding resource, e.g. attaching a file to ChatGPT or NotebookLM? Yes need some human expert to create (or curate) that grounding resource in the first place, but LLMs handle the rest well: presenting info in different ways and paces, interacting with the learner like a tutor, etc.
Glad to see big improvement in the SimpleQA Verified benchmark (28->69%), which is meant to measure factuality (built-in, i.e. without adding grounding resources). That's one benchmark where all models seemed to have low scores until recently. Can't wait to see a model go over 90%... then will be years till the competition is over number of 9s in such a factuality benchmark, but that'd be glorious.
Yes, that's very good because it's my main use case for Flash; queries depending on world knowledge. Not science or engineering problems, but think you'd ask someone that has a really broad knowledge about things and can give quick and straightforward answers.
Big knowledge cutoff jump from Sep 2024 to Aug 2025. How'd they pull that off for a small point release, which presumably hasn't done a fresh pre-training over the web?
Did they figure out how to do more incremental knowledge updates somehow? If yes that'd be a huge change to these releases going forward. I'd appreciate the freshness that comes with that (without having to rely on web search as a RAG tool, which isn't as deeply intelligent, as is game-able by SEO).
With Gemini 3, my only disappointment was 0 change in knowledge cutoff relative to 2.5's (Jan 2025).
It's all about the chip economics. I don't know how the _manufacturing cost_ of Google's TPUs compares to Nvidia's GPUs, for inference of equivalent token throughput.
But at the moment Nvidia's 75-80% gross margin is slowly killing its customers like OpenAI. Eventually Nvidia will drop its margins, because non-0 profit from OpenAI is better than the 0 it'll be if OpenAI doesn't survive. Will be interesting to see if, say, 1/3 the chip cost would make OpenAI gross margin profitable... numbers bandied in this thread of $20B revenue with $115B cost imply they need 1/6 the chip cost, but I doubt those numbers are right (hard to get accurate $ numbers for a private company for the benefit of us arm-chair commenters).
Yes, from the first principles perspective this AI thingy is just about running electricity through some wires printed on silicon by a Taiwanese company using a Dutch machine. Which means, up until the Taiwanese you have plenty of room to cut margins up until that point the costs are mostly greed based. That is Nvidia is asking for the highest price the customer can pay and they have quite a way to the cost that define their min price. Which means AI companies can actually keep getting better deals until the devices delivered to them are priced close to TSMCs bulk wafer printing prices.
"complementing the Neural Accelerators in the CPU and GPU" seems to be a misprint; I don't believe they have the accelerators in the CPU too.
Still super interesting architecture with accelerators in each GPU core _and_ a dedicated neural engine. Any links to software documentation for how to leverage both together, or when to leverage one vs the other?
Plug for our https://uphop.ai/app : it's for adult learning / corporate training. We break down a desired job skill into small chunks, and engage the user with practice & give nuanced feedback. And of course like chatbots make it easy for user to ask more questions or go on tangents.
Would appreciate feedback!
There's a bit of overlap with Learn Your Way I guess. I'm not sure users need to toggle between alternate formats of the same instruction though. Instead the instruction itself should be as multi-modal as possible, and offer flexibility to ask questions... which even gemini.google.com offers so I'm not sure this is a net improvement over that.
Wifi obviously has higher bandwidth, but I guess it isn't viable as a mesh, or is there any trick with turning on/off hotspots on phones dynamically that'd make it viable? (Afaik older phones made you pick between being a hotspot or being a regular wifi client, but at least some newer ones seem to allow both simultaneously.)
I'm definitely hoping for a future with wider support for C2PA (content credentials on images) on phone cameras to make these photos power citizen journalism. So far Samsung S25 and Pixel 10 support C2PA in the camera hardware: need other phone makers (especially Apple) to get on board already... if you're an iPhone user, please help yell at Apple support etc!
Aside: I registered a domain and plan to build a citizen journalism news feed for such photos (and uncut videos). I see it as the antidote to Instagram et al's feeds that're full of AI slop (and plenty of fakery even before AI-generated imagery got big). And it's essential to truth, democracy and ultimately (maybe I'm too idealistic here) peace. Aside to the aside: wish some of us techies banded together to build "peace tech" as a new sector in tech, DM if interested in brainstorming or working together.