tbh I also use google AI tools frequently. It’s convenient (search bar is top of my window), and extremely fast at generation. For quick Qs, opening a chat bot and changing the default reasoning from my coding settings, switching from Work to Chat, etc etc, is too much of a faff.
I ended up adding -ai to every search in the browser level to turn this crap off. I couldn't find a way to disable it otherwise. I did it after it hallucinated the world cup games schedule which made my friend send wrong events to everyone after he "looked it up". Can't stop this from him, but at least this honest mistake won't happen to me.
Surely there's an extension for whatever browser you are using?
Firefox: https://addons.mozilla.org/en-US/firefox/addon/hide-google-ai-overviews/
Chromium: https://chromewebstore.google.com/detail/hide-google-ai-overviews/neibhohkbmfjninidnaoacabkjonbahn
Safari: Seems there are none
Google Search's AI has gotten... better. But it's still frequently spouting as much made up shit as I expected from LLMs not doing their research a couple years ago.
Just this morning I looked up what time today's Nintendo Direct livestream is. It correctly told me it's today at 7am PT (confirmed from actual link sources). It then tried to get smart and tell me what that would be in my city's timezone and it was an hour off (possibly because I'm in a timezone without daylight savings)
Yes it's definitely not SOTA, and is worse than all the chatbots I use. But it's correct frequently enough that the convenience + speed does it for me.
Many VCs also dislike these examples, I believe. I'm doubtful this is what they're being pitched.
As for public releases: I wonder if it's because these examples are easy to relate to. Many websites are just a long tail of industry or use-case specific stuff. What's valuable to me probably means nothing to you. This is unlikely to resonate with people-wit-large (and LLMs are marketed broadly) or requires the reader to think (and marketing that requires thinking is bad these days).
Second, it's arguably a good litmus test. If it still can't do the worn out examples of plane tickets and shopping, which would be a good assumption since we've been demo'd these use-cases for 2 years at this point, then ...
I recall them saying they use models to write CUDA kernels and whatnot. Makes sense, and unsurprising that models are good at writing code.
But I think calling this “automating AI research” is misleading. I’m not sure there’s evidence yet that they do creative research work. Even in mathematics, but they are finding counter-examples by intelligent brute-forcing. Not to downplay the results, as they are incredible, but this is one very specific kind of proof and not the most creative type, which arguably requires generalisation.
In essence. But if you have a chain PR1 > PR2 > PR3, and PR1 gets merged, all the others (ime) seem to not cleanly rebase on main. They end up with conflicts that require manual fixing. I've not really figured out why, tbh. It'd also be nice to see a coherent link in the UI between PR1, PR2, PR3.
GitHub's PR workflow doesn't nicely support being able to review individual commits, realise which comments are associated with which commits, etc. Or shipping individual commits to main, while working on some others (unless you allow cherry-picking and direct push to main). Or amending a certain commit with respect to feedback and seeing a diff from the previous patch of that commit to the next.
If GitHub's unit of change were a diff, and not a branch, then that would work pretty well.
have you tried pyor.review? it is actually just github but with better UI, and you get a commits rail that makes it easy to switch between commits on the fly
I think it's telling how long it took GitHub to release a v1 of this feature. Folks have wanted this for a long time. Graphite came along and did it years ago (and I'm sure they pondered whether GitHub would do this).
And the v1 is also a bit... basic, and buggy. And I'm surprised there's not clear documentation for agents (given using GitHub stacked PRs CLI won't be in models' training data yet).
It does feel like GitHub hasn't been great at shipping new features for a few years now. Nonetheless, I'm glad to see this rolling out. Once polished, it's going to be exciting to use.
This feature was brought up amongst GitHub for years, possibly even a decade. And it was something that they didn't want.
It was new leadership back in October that decided to build this, so it took them 9 months or so. To be clear, I am not saying this is a long amount of time, they had a LOT of work to do to get it to this point, just being clear about timelines.
Because it's not losing money on each token? Aside from most global people using American inference providers to run the models, I suspect the cloud inference products of the Chinese labs are profitable, at least on the inference costs (ie: not including model training, salaries, etc).
Pretty sure they are making money since on OpenRouter, there are other providers for DeepSeek V4 flash that are charging even less than DeepSeek themselves (eg DeepInfra and Digital Ocean).
That doesn't mean they're making money. Other providers could just be doing it more efficiently. DeepSeek is trying to make its model optimized for Hauwei chips instead of NVIDIA so it has its own constraints
That says little. Those providers could also be losing money trying to gain marketshare. There is a high amount of speculation in the space and it won’t be apparent for awhile who has a lasting business.
Probably just the US. But the US could do what EU has done with e.g. GDPR, Digital Services Act, USB-C regs, where they force any company trading in their region to follow those regulations for domestic customers.
And basically any AI company has to sell to US companies or consumers. That'd probs be sufficient to force them to use US models.
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