Asahi’s approach avoids any use of AI coding agents, etc at all (even for debugging, testing, and so forth). The amount of work/effort the Asahi team did for M1/M2/M3 is near superhuman, and M4 is gonna take all that effort again, since Apple likes to change things, a lot, and doesn’t really document their hardware device interfaces in detail.
Gravity approaches this with an attitude that using an LLM is indeed allowed (per upstream Linux contribute requirements), particularly for analysis, debugging and testing. The goal is to get M4 support contributed back to to the upstream kernel. (And eventually M5, M6, A18…)
Ideally, the documentation about hardware interfaces from this project could be used for other people who want to write kernel drivers for Linux or even for other operating systems. It’s mostly a matter of documenting what the device interface actually is.
None of this would be possible without Asahi’s foundational work and techniques to make clean room reverse engineering possible. Despite differences on opinions about AI, I can’t stress the quality of their work or the effort they’ve put in enough.
This approach to marketing one's AI by finding ways to brag that it "broke out" and "hacked companies" is getting ridiculous. It's particularly sad when it's large, established businesses like Google resorting to the kind of thing that's embarrassing enough when it's some brand new startup on tpot trying to get some engagement.
This approach to marketing one's AI by finding ways to brag that it "broke out" and "hacked companies" is getting ridiculous. It's particularly sad when it's large, established businesses like Google resorting to the kind of thing that's embarrassing enough when it's some brand new startup on tpot trying to get some engagement.
I must be out of the loop. Not defending google when I ask this but....how is google flailing, exactly? I figured they were in the best position of all the other companies combined. They have their own hardware for inference, they have a solid grasp on enterprise, and they have a good road map. I mean, Google is incredibly strong, is it not? And remember how quickly google answered Bard? For a while, gemini was even the preferred model, if we are strictly speaking AI models. Again, I'm not defending google, I just want to see how this comment makes sense is all, without letting fantasy overtake reality in the process...
I totally agree. Characterising Google as "flailing" because Gemini isn't the #1 model for coding at the moment is... not realistic, to put it politely. In addition to the factors you mention, Google has enormous cash flow from its ad business, which translates to a long runway when compared to other frontier AI outfits.
It's possible that they will nevertheless snatch defeat from the jaws of victory, of course, but I personally think they're in the strongest position of them all.
They are doing fine as a shovel salesman (GPUs/TPUs, being the inference hardware provider, though I now wonder if their token processing stats are their own or combined with those who are running on their hardware too, I've been conditioned to be far more skeptical of Big Ai these days)
On the flip side, gemini is terrible at coding by comparison, so much so google has now given all engineers access to claude. They promised us Gemini 3.5 pro at their developer event this summer, now it seems it will never be released. Antigravity usage is on par with grok (~1%). They've removed the feedback button for "ai answers" at the top of search, that does not seem well received, it hallucinates too much (and may be a legal liability, some courts have ruled as such in the EU). Talk to googlers IRL, things are not so happy internally. You can see the forced gemini usage for coding and subsequent slop in their products, especially gcloud console. I was sent the greatest slop deck by one of their sales people for Gemini Enterprise, needless to say we did not buy from them, but we did get an amazing :cursed-claude: emoji from the deck (nano banana's take on what claude looks like as a person)
a rambled sample, hope this helps, I was a google superfan for a long time, I was sad to see things go south, now I'm happy that I was motivated to move off most their platforms (gmail/youtube remain)
I admire your optimism. The only thing I see stopping AI is widespread nuclear war, or if we’re lucky widespread destruction of the electric grid leading to a collapse in gas’s and oil supply for only a billion or two dead.
You seem to be implying that mankind will decide to scale back AI in favour of tackling climate change, or that it won’t happen but AI will not destroy at least the economy which powers AI long before unrecoverable climate change will occur.
If AI kills us all, doesn’t matter about climate change - some species will adapt and thrive, some will die out
If AI destroys jobs, there will be no demand for energy so oil will no longer be burnt at the scale currently causing so much problem
Your view seems to be AI will continue in approximately the current state for the next 20 years? I don’t see how that happens. Best case scenario to me is a 2001/2008/2020 style crash coupled with an actual limit to LLM capacity so countries pesss exposed to capitalist systems will draw back from current AI for a few decades.
Or am I missing something? How do you foresee the next 20 years?
> If AI destroys jobs, there will be no demand for energy
Quite the leap there. Are you imagining billions dying off with no food and no further consumption while the AI overlords cruise about in their yachts between bunkers while zooming into Davos to cosplay as Davros and chuckle about the fate of the poors?
That aside, the earth land / sea layer is still lagging in its reaction the gigatonnes of CO2 already aloft .. which isn't going to magically disappear for some generations.
Even if AI destroys jobs there will still be fossil fuel consumption adding to the CO2 already there.
> Are you imagining billions dying off with food and no further consumption while the AI overlords cruise about in their yachts between bunkers while zooming into Davos to cosplay as Davros and chuckle about the fate of the poors?
Well that’s certainly one scenario. And that scenario would decimate co2 emissions. Sure things will continue to get worse, but as most of humanity will be dead they won’t be concerned.
So your view of billions not dying is somewhat optimistic for the future
You have to set up trivial, low value “burner” email that you use for your emailing activity when overseas, and other related social media accounts, and make sure to keep them “warm”.
A spare old Pixel or iPhone SE is $20-$50 you can use for this purpose.
Asahi’s approach avoids any use of AI coding agents, etc at all (even for debugging, testing, and so forth). The amount of work/effort the Asahi team did for M1/M2/M3 is near superhuman, and M4 is gonna take all that effort again, since Apple likes to change things, a lot, and doesn’t really document their hardware device interfaces in detail.
Gravity approaches this with an attitude that using an LLM is indeed allowed (per upstream Linux contribute requirements), particularly for analysis, debugging and testing. The goal is to get M4 support contributed back to to the upstream kernel. (And eventually M5, M6, A18…)
Ideally, the documentation about hardware interfaces from this project could be used for other people who want to write kernel drivers for Linux or even for other operating systems. It’s mostly a matter of documenting what the device interface actually is.
None of this would be possible without Asahi’s foundational work and techniques to make clean room reverse engineering possible. Despite differences on opinions about AI, I can’t stress the quality of their work or the effort they’ve put in enough.
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