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Gemini 2.5 Flash: Uma Nova Era para o Serviço Público?
Nos últimos anos, o avanço das tecnologias de inteligência artificial tem impactado diversas áreas, e o lançamento de modelos como o Gemini 2.5 Flash gera discussões relevantes sobre suas aplicações no serviço público. Como servidor público com mais de 16 anos de experiência, vejo a importância de avaliarmos ferramentas como essa, que prometem ser poderosas e acessíveis, batendo concorrentes robustos como o GPT 4.5 e outros.
A proposta do Gemini 2.5 Flash de ser “poderoso e mais barato” não deve passar despercebida. Modelos mais econômicos podem permitir que órgãos públicos adotem tecnologias avançadas sem comprometer orçamentos limitados, ao mesmo tempo em que buscam eficiência e inovação. A questão central é: como podemos integrar tais soluções para promover resultados melhores para a sociedade?
Um exemplo prático é a implementação de chatbots mais inteligentes que, auxiliados por modelos como o Gemini, poderiam otimizar o atendimento ao cidadão, tornando-o mais ágil e eficiente. Além disso, a análise de dados em larga escala, facilitada por essa nova tecnologia, pode ajudar na tomada de decisões mais embasadas, promovendo políticas públicas que atendam de forma mais eficaz à população.
Entretanto, a adoção de novos modelos deve ser feita com cautela. É essencial refletir sobre as implicações éticas e a necessidade de capacitação dos servidores para o uso desta tecnologia. Precisamos pensar em estratégias que não apenas implementem a IA, mas também garantam que o foco permaneça em melhorar a vida do cidadão.
Finalmente, a discussão sobre os avanços em IA, como o Gemini 2.5 Flash, deve estimular um diálogo contínuo entre os profissionais do serviço público. A troca de experiências e a busca por melhores práticas são fundamentais para que possamos aproveitar todo o potencial tecnológico em benefício da sociedade. Como podemos, efetivamente, transformar essa ferramenta em um motor de melhorias no serviço público? Essa é uma reflexão que todos devemos fazer.
Aprenda tudo sobre automações do n8n, typebot, google workspace, IA, chatGPT entre outras ferramentas indispensáeis no momento atual para aumentar a sua produtividade e eficiência.
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#Gemini #Flash #POWERFUL #CHEAPEST #Model #BEATS #GPT #Deepseek #Sonnet #Fully #Tested
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In india it's totally free
I recently discovered that the Gemini 2.5 Pro is weaker than the deepseek in terms of networking searches for knowledge summaries, I asked Gemini for a comparison of the two aerial photographers, and also gave the official website product description page, and the Gemini actually said that its knowledge base was from 2023, while the deepseek quickly gave an answer.
I don't get it how to make and run apps on AI Studio.
Please consider using time codes
very nice
Pro preview is pretty pricey, I started to use deepseek v3.1 more for coding, google is smart for covering this range. The competition is so fierce, its more interesting than the superbowl was this year 😅
Is there API access for this? What is the model name? I want to try this on Roo code.
I think most of you guys really missed the best part about 2.5 Flash here:
It's a Thinking model that roughly generates responses at the same speed as the 2.0 Flash model; Thinking doesn't just mean "better responses," or rather isn't the most important foundational mark behind why all types of people would use it.. thinking enables it to have contextual awareness.
This means it doesn't lose track. (Or at least not often)
This model is actually a phenomenally important step to the bridging point of having an AI assistant that performs systematically at the same level as a human in conversation. Once they learn to optimally use the base non-thinking/immediate generations as filler for the beginning of a response to buy itself time to think something out, and then apply the "Thinking" constructional methods, we will have effectively recreated 1:1 in technology the human ability of using constructional praxis; the ability for a model to cohesively stay on topic, and use theoretical information to such an extent that it can properly innovate and respond at the same natural level as a human in both speed and performance/appealancy.
This is truly extraordinary. It'll only be a matter of time before the developers at Google reach this conclusion of the next steps as well, if they haven't already been putting in practice these theoretical combinations in closed work-spaces. May is going to be an absolutely crazy month. Y'all think we've seen progress until AI literally crosses the bounds of something "pushing benchmarks" to literally stretching outside of technological uses. Once every day people integrate this naturally sociologically… that's when the real fun begins.
YES, this is what I have been waiting for. Thank you for giving me the update 😊
Anthropic needs to drop a cheap and good coding model to keep up I think
Gemini 2.5 Flash: Real-time AI without the hefty price tag? Developers, this is major!
Hey what are you using to preview your code in?
So it's fantastic compared to the last generation of models, but also totally outclassed by o4 mini, though o4 mini is far more expensive and you can't budget the thinking.
4:12 looks really quite good and considering the speed 😮
I am better than gemini 2.5 flash as I did the last prompt correct before gemini 😂
Bro, I need a free or cheap AI tool that works locally to write intermediate level code. better if it has its own app. I need it like this, otherwise 1M artificial intelligence is useless. I don't want to install it on the computer to say hello, it will work locally.
You are the first to report on this! Damn that was fast
they can make my 2gb video to 40mb, now they starting do it to ai…
I wonder if they are running them at a loss so they can collect massive amounts of data, and then use that to generate augmented synthetic datasets
Now, Anthropic is the only one left to release a cheap model, but I doubt that will happen.
YESSIRR NEW GOOGLE MODEL 🔥🔥
Is it better or worse than 2.5 pro?
I am getting tired of all this buzz. I am yet to be able to actually use ai models for coding. I end up spending more time prompting and explaining to AI what it should do, then fixing it myself. And they're basic things like Python syntax errors and stuff that Ai should be able to "understand" by now. These models are very good at copy/pasting content they've been trained on. They can code basic crap. But when it comes to actually coding, they're pretty much useless because they do not have any reference points. And that's the problem. They cannot actually code, which is a huge problem, because that is their selling point.
Is it really better than o4 mini high?
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