YHK - yet another hacker news clone

I am not so advanced enough as a human being.

I'm worried in their push to catch up on the SOTA front, it's going to lose that natural sounding touch it currently has.

Lately it became load-bearingly-reality-difficult to not only read, but to comprehend the Claude output

On my TODO is try and run all of the analysis pipeline in dense "machine speak" to save on tokens and just let Gemini sort it out at the end.

I've set my documentation sub agent to Gemini and my code agent to Luna

It reminds me of a pedantic grad student.

I can't think of a better general purpose model than 3.8 flash right now. It also writes more naturally than the other big models too.

Ask yourself, how does Google -- a company that famously does everything -- benefit from SWEs outside of Google having access to powerful coding models? They would just be competition.

Famously, Google just eventually discards almost all businesses that don't have the same fire hose of revenue that ads does. Selling coding plans isn't something they are going to want to do.

Google is clearly motivated to make better search and information finding tools and stuff that will ultimately drive users through their existing search/ads/youtube ecosystem. That's really why they're in Android, that's why they do Chrome. Everything else with them is a sideshow.

Google is also full of beancounters obsessed with data centre quota and resourcing. Even massively profitable ads projects have to justify and fight for it. (Source: used to work there).

I can't think of anything less resource & revenue sensible than providing outside parties access to your TPUs for the purpose of letting them write stuff which could just end up competing with you.

Yes, maybe as part of their cloud business, selling token access could be useful money. But I doubt they'd tune it for coding.

I think they’ve made a shrewd move in focusing on search integration and everyday users (Gemini app) vs software power users. They have their corner and nobody is really competing with them, plus it feeds directly into their existing revenue stream.

Google in a sense won (me over) like that. I also expected them to brute force their way into everything and dominate. This is how it played out though. Image generation is great as well, but ChatGPT one is more lenient on copyright and nannying - for example when my kid asks me to "take a photo of him and Sonic". Gemini cops out either because of the kid or Sonic, disappointing us both, but ChatGPT can be.. persuaded.

these are essentially monthly releases, the dated releases that Deepseek and Qwen do make more sense

Google has essentially give up the race for the frontier. The gap is widening very fast. Their strategy appears to be to focus on niche areas like voice, small models for on-device (see their deal with Apple), and specialised models for tasks like search, which are very inference efficient.

My advice is to listen less to brainrot 'influencers' that optimise for engagement through sensationalism.

And they're making money doing it.

Perhaps they don't have the best coding model right now (although 3.8 flash is arguably SOTA at some benchmarks), but is that the be-all and end-all of AI? Only coding matters?

And Gemini is kinda good enough at everything. Never the top, but it is decent at every task, and it is much faster than Kimi K3 and significantly cheaper. Kimi is very focussed on coding, Gemini isn't.

More importantly, it natively understands text, audio and video. If/when we are able to make the jump to robotics, this becomes essential. As you say, Google has a lot of deep background and deep pockets, they are able to make more of a long play. No idea if it will pay off, but it is way to early in the game to count them out.

Do they have a good read on the industry or completely out of touch? Or to put it simply, are they spouting bullshit?

My concern is that some of them arent in the industry or have never been in it.

There's one or two I find more understated but I would love a 2026 SOTA V2V model that speaks clearly but without the artificial personality layered on.

Human interaction/theory of mind relies so much on non-verbal clues for interpreting emotion/intent and so for me having those neurons firing constantly while talking to an LLM just for an emotional no-op is exhausting to put up with for more than a couple minutes.

There's one male voice that would make me assume someone was sarcastically mocking me if I was talking to an actual person because it's just so over the top.

And looks like one can trigger live mode via siri

I once asked it to summarize The Hobbit in Catalan to explain it to my daughter before sleep. I was expecting a lot of mistakes as I see regularly if I ask anything in my native language when using GPT or Claude, but it was surprisingly good. I was going just to kind of skim ahead and retell it my own way, but ended up almost saying it verbatim because it was good already.

She loves Zelda so I asked it to explain the story of Breath of The Wild keeping the original names, and to make it fun, etc.. I was surprised again. I did retell some bits in my own style and taste but it is very convincing.

I haven't tried Catalan on newer models like GTP-6 Astra or Fable tho. We have all these benchmarks based on software development, and AGI, etc.. but it would be cool to have some language benchmarks for different communities.

As I work in english and use them in english, I wonder if using LLMs in a different language to code renders a different result as well. Like, if some of these benchmarks were made in other languages, would the result be similar.

As jy wil, ons kan saam praat op Discord :) maar my Afrikaans is sleg

It makes total sense it’s good at regurgitating the edge cases of language.

Claude does it occasionally but it's a more a soft landing earlier context seems to be compacted, not completely lose the plot.

I just cancelled my pro subscription. I really wanted it to be good but not yet.

This is frustrating because when I discuss AI with laypeople they think it's still incapable of counting the number of Rs in "strawberry." They believe it to be essentially useless and incapable of basic tasks. Which, to be fair, is the case with the free models.

they'll live in my rc for decades

I was like you before, Gemini was the worst model to me.

Then 3.8 came out. At first I was sceptical, but this model *is* able to do useful things ! Complex things.

Of course, it is NOT perfect. But for things like small/medium complex tasks subagents, it's perfect.

Now, is it worth the money vs Astra ? I don't think so. But still my point remain relevant.