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Gemini 2.5 Flash

developers.googleblog.com

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Re: Gemini 2.5 Flash

#181

Post by jsnell »

ModernMech wrote: post #162
xbmcuser wrote: post #50

For a non programmer like me google is becoming shockingly good. It is giving working code the first time. I was playing around with it asked it to write code to scrape some data of a website to analyse. I was expecting it to write something that would scrape the data and later I would upload the data to it to analyse. But it actually wrote code that scraped and analysed the data. It was basic categorizing and counti…

I've been continually disappointed. I've been told it's getting exponentially better and we won't be able to keep up with how good they get, but I'm not convinced. I'm using them every single day and I'm never shocked or awed by its competence, but instead continually vexxed that isn't not living up to the hype I keep reading. Case in point: there was a post here recently about implementing a JS algorithm that highli…

Even as a human programmer I don't actually understand your description of the problem well enough to be confident I could correctly guess your intent.

What do you mean by "highlight as you scroll"? I guess you want a single heading highlighted at a time, and it should be somehow depending on the viewport. But even that is ambiguous. Do you want the topmost heading in the viewport? The bottom most? Depending on scroll direction?

This is what I got one-shot from Gemini 2.5 Pro, with my best guess at what you meant: https://gemini.google.com/share/d81c90ab0b9f

It seems pretty good. Handles scrolling via all possible ways, does the highlighting at load too so that the highlighting is in effect for the initial viewport too.

The prompt was "write me some javascript that higlights the topmost heading (h1, h2, etc) in the viewport as the document is scrolled in any way".

So I'm thinking your actual requirements are very different than what you actually wrote. That might explain why you did not have much luck with any LLMs.

Re: Gemini 2.5 Flash

#182

Post by antirez »

deanmoriarty wrote: post #178

Genuine naive question: when it comes to Google HN has generally a negative view of it (pick any random story on Chrome, ads, search, web, working at faang, etc. and this should be obvious from the comments), yet when it comes to AI there is a somewhat notable “cheering effect” for Google to win the AI race that goes beyond a conventional appreciation of a healthy competitive landscape, which may appear as a bit of a…

Maybe because Google is largely responsible, paying for the research, of most of the results we are seeing now. I'm not a Google fan, in the web side, and in their idea of what software engineering is, but they deserve to win the AI race, because right now all the other players provided a lot less than what Google did as public research. Also, with Gemini 2.5 PRO, there was a big hype moment, because the model is of unseen ability.

Re: Gemini 2.5 Flash

#183

Post by swyx »

xnx wrote: post #75
swyx wrote: post #62

Earlier quoted context omitted.

done pretty much inline with the price elo pareto frontier https://x.com/swyx/status/1912959140743586206/photo/1

Love that chart! Am I imagining that I saw a version of that somewhere that even showed how the boundary has moved out over time?

https://x.com/swyx/status/1882933368444309723

https://x.com/swyx/status/1830866865884991999 (scroll up)

Re: Gemini 2.5 Flash

#184

Post by 01100011 »

deanmoriarty wrote: post #178

Genuine naive question: when it comes to Google HN has generally a negative view of it (pick any random story on Chrome, ads, search, web, working at faang, etc. and this should be obvious from the comments), yet when it comes to AI there is a somewhat notable “cheering effect” for Google to win the AI race that goes beyond a conventional appreciation of a healthy competitive landscape, which may appear as a bit of a…

Didn't Google invent the transformer?

I think a lot of us see Google as both an evil advertiser and as an innovator. Google winning AI is sort of nostalgic for those of us who once cheered the "Do No Evil"(now mostly "Do Know Evil") company.

I also like how Google is making quiet progress while other companies take their latest incremental improvement and promote it as hard as they can.

Re: Gemini 2.5 Flash

#185

Post by daemonologist »

behnamoh wrote: post #154
minimaxir wrote: post #139

One hidden note from Gemini 2.5 Flash when diving deep into the documentation: for image inputs, not only can the model be instructed to generated 2D bounding boxes of relevant subjects, but it can also create segmentation masks! https://ai.google.dev/gemini-api/docs/image-understanding#se... At this price point with the Flash model, creating segmentation masks is pretty nifty. The segmentation masks are a bit of a g…

Wait, did they just kill YOLO, at least for time-insensitive tasks?

No, the speed of YOLO/DETR inference makes it cheap as well - probably at least five or six orders of magnitude cheaper.

  Edit: After some experimentation, Gemini also seems to not perform nearly as well as a purpose-tuned detection model.
It'll be interesting to test this capability and see how it evolves though. At some point you might be able use it as a "teacher" to generate training data for new tasks.

Re: Gemini 2.5 Flash

#186

Post by sethkim »

statements wrote: post #41
arnaudsm wrote: post #6

Gemini flash models have the least hype, but in my experience in production have the best bang for the buck and multimodal tooling. Google is silently winning the AI race.

Absolutely agree. Granted, it is task dependent. But when it comes to classification and attribute extraction, I've been using 2.0 Flash with huge access across massive datasets. It would not be even viable cost wise with other models.

How "huge" are these datasets? Did you build your own tooling to accomplish this?

Re: Gemini 2.5 Flash

#187

Post by 16bytes »

jay_kyburz wrote: post #103
spruce_tips wrote: post #27

Earlier quoted context omitted.

i have a high volume task i wrote an eval for and was pleasantly surprised at 2.0 flash's cost to value ratio especially compared to gpt4.1-mini/nano accuracy | input price | output price Gemini Flash 2.0 Lite: 67% | $0.075 | $0.30 Gemini Flash 2.0: 93% | $0.10 | $0.40 GPT-4.1-mini: 93% | $0.40 | $1.60 GPT-4.1-nano: 43% | $0.10 | $0.40 excited to to try out 2.5 flash

Can I ask a serious question. What task are you writing where its ok to get 7% error rate. I can't get my head around how this can be used.

There are tons of AI/ML use-cases where 7% is acceptable.

Historically speaking, if you had a 15% word error rate in speech recognition, it would generally be considered useful. 7% would be performing well, and Typically, your error rate just needs to be below the usefulness threshold and in many cases the cost of errors is pretty small.

Re: Gemini 2.5 Flash

#188

Post by pkaye »

deanmoriarty wrote: post #178

Genuine naive question: when it comes to Google HN has generally a negative view of it (pick any random story on Chrome, ads, search, web, working at faang, etc. and this should be obvious from the comments), yet when it comes to AI there is a somewhat notable “cheering effect” for Google to win the AI race that goes beyond a conventional appreciation of a healthy competitive landscape, which may appear as a bit of a…

I think for a while some people felt the Google AI models are worse but now its getting much better. On the other hand Google has their own hardware so they can drive down the costs of using the models so it keeps pressure on Open AI do remain cost competitive. Then you have Anthropic which has very good models but is very expensive. But I've heard they are working with Amazon to build a data center with Amazons custom AI chips so maybe they can bring down their costs. In the end all these companies will need a good model and lower cost hardware to succeed.

Re: Gemini 2.5 Flash

#189

Post by zoogeny »

mdp2021 wrote: post #177
mmaunder wrote: post #158

Earlier quoted context omitted.

Note sure why their comment was downvoted. Google the names. Hassabis runs DeepMind at Google which makes Gemini and he's quite brilliant and has an unbelievable track record. Buffet investing in teams points out that there are smart people out there that think good leadership is a good predictor of future success.

Zoogeny got downvoted? I did not do that. His comments deserved more details anyway (at the level of those kindly provided). > Google the names Was that a wink about the submission (a milestone from Google)? Read Zoogeny's delightful reply and see whether it can compare a search engine result (not to mention that I asked for Zoogeny's insight, not for trivia). And as a listener to Buffet and Munger, I can surely say…

I wouldn't worry about downvotes, it isn't possible on HN to downvote direct replies to your message (unlike reddit), so you cannot be accused of downvoting me unless you did so using an alt.

Some people see tech like they see sports teams and they vote for their tribe without considering any other reason. I'm not shy stating my opinion even when it may invite these kinds of responses.

I do think it is important for people to "do their own research" and not take one man's opinion as fact. I recommend people watch a few videos of Hassabis, there are many, and judge his character and intelligence for themselves. They may find they don't vibe with him and genuinely prefer Altman.

Re: Gemini 2.5 Flash

#190

Post by qwertox »

cjohnson318 wrote: post #164
zoogeny wrote: post #131

Google making Gemini 2.5 Pro (Experimental) free was a big deal. I haven't tried the more expensive OpenAI models so I can't even compare, only to the free models I have used of theirs in the past. Gemini 2.5 Pro is so much of a step up (IME) that I've become sold on Google's models in general. It not only is smarter than me on most of the subjects I engage with it, it also isn't completely obsequious. The model push…

Yeah, my wife pays for ChatGPT, but Gemini is fine enough for me.

Just be aware that if you don't add a key (and set up billing) youre granting Google the right to train on your data. To have persons read them and decide how to use them for training.
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