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Descubra o Fabric: O Framework de IA Open Source que Pode Transformar o Serviço Público
No contexto atual, a implementação de tecnologias inovadoras é essencial para o avanço e a eficiência no serviço público. O Fabric, um framework de inteligência artificial open source, surge como uma ferramenta poderosa para automatizar processos e, assim, potencializar o atendimento à sociedade. Em meus 16 anos de experiência no serviço público, percebo que a automação pode ser uma aliada valiosa na busca por maior eficiência e transparência.
O Fabric não apenas facilita a automação de tarefas rotineiras, mas também promove uma análise de dados mais profunda, permitindo que os servidores públicos tomem decisões fundamentadas. Imagine a possibilidade de otimizar o tempo gasto em atividades administrativas, direcionando esse esforço para ações que impactem positivamente a comunidade.
Além de tornar os processos mais ágeis, a implementação de soluções como o Fabric pode contribuir para a redução da burocracia, melhorando a experiência do cidadão ao acessar serviços públicos. No entanto, é crucial que a adoção dessas tecnologias ocorra de forma responsável e colaborativa, envolvendo todos os stakeholders para garantir que os resultados atendam às reais necessidades da população.
Convido todos os servidores públicos a refletirem sobre como o Fabric e outras tecnologias emergentes podem ser integradas em suas rotinas de trabalho. A inovação não é apenas uma tendência, mas uma necessidade urgente para melhorarmos continuamente o nosso serviço e, consequentemente, a vida da sociedade que servimos. Vamos juntos explorar essas possibilidades e construir um futuro mais eficiente e acessível para todos.
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.
Vamos juntos dominar o espaço dos novos profissionais do futuro!!!
#Fabric #Opensource #Framework #Automate #Life
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which backend is he using to make this work? OpenAI, Anthropic, Claude, Local?
A horrible name if trying to search for it
side note, doesnt appear to work with podcast episodes which have CC disabled unfortunately.
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It's important to understand this is essentially highly refined snake oil (though I don't directly fault Daniel Miessler / @unsupervised-learning or @intheworldofai for getting caught up in the hype). Rather than be impressed by this, we need to critique it more deeply and see it as another of the growing number of demonstrations of the problematic and fundamental limits of GPT / LLM-based approaches, and that the current round of generative-AI approaches using GPT-LLM's have plateaued.
We're essentially in a driverless car, outside the training park limits, going nowhere. And like the unfulfilled promise of current driverless car systems as a general technology for use in any given human environment, GPT-LLM's for solving any generalised human problem are nonsensical pipe dreams. We need fundamental breakthroughs to escape the confines of brute-force, big-data crunching find significant paths forward.
That's not to say GPT-LLM's are useless – I think they have some utility as a component part of forming output from other systems: they have potential as a subsystem as part of a more general networked AI system. However they are largely useless in doing much more than structuring logical language outputs – and we're collectively wasting significant amounts of time and money in trying to get GPT-LLM systems to "understand".
Here are a couple of examples to ponder:
As @ErikdeBruijn noted, it's quite hilarious that the example video (1:01) that is used to demonstrate AI-generated "wisdom" (3:09) is focused in large part on dealing with "the importance of detail", "the importance of deep reading", "the value of re-reading books" and the "subtlety of experience". The guidance in the video is to engage more deeply using our own human faculties. It's notable that this important aspect is lost in the clinical output from Fabric.
Secondly, it's equally amusing that in reviewing the summary of the intent / context of the example YouTube video that is shown in its description (1:01) ABSOLUTELY NONE of that context appears to be brought forward into the "wisdom" that is generated by Fabric. We're told nothing about Riva Tez, why she is of interest, her background, nor anything about credentials, why we should value what she says, etc.
These are FUNDAMANENTAL aspects of turning data to information to knowledge to wisdom – and they are completely missing from the data output produced by this Fabric extract_wisdom example. Furthermore, the very framing of "extract_wisdom" itself shows a significant misunderstanding of what wisdom is. At best, we might be able to argue this is extracting "information" – very arguably "knowledge".
And these are the fundamental problems of GPT-LLM's. No amount of source data and no reasonable amount of prompt engineering can resolve the contextual problems that are self-evident to humans in the obvious failings of these tools.
In the absence of access to structured knowledge and governing world-models / domain-models to set logical boundaries and guard rails that would help carry "knowledge" or "wisdom", with no anchoring models for establishing fact or truth within a given domain, these tools are at best extremely clever fortune tellers, impressive automata, next-level slot machines.
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It's in Go now
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This is amazing, thank you
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Does this AI undestand engilsh only lang?
West is not dying bro lmao
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man this person is my hero
thank you man
I just did pretty much the same thing with the video summarizer gpt on chat gpt4o and it was far simpler…
at 7:35
instead of using pipx install
use pipx install fabric
Skimming through some of the transcription summary and seeing a lot of interesting… concepts, also a repetition between Ideas and Facts. Facts being a section that doesn't express actual explicitly factual information. O.o
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your voice audio is so low,
Okay, Another tool called Fabric
/me summarizes a video that talks about decreasing attention spans… 😅
What is the difference using ChatGpt?
I thought this was about Minecraft mods for a second
People. There is a Yandex Browser, it translates and voices the video + can retell it.😎
Youtube transcript worked but only for english
Good idea, but unfortunately those Llm API are not free.
it seems to be semantic chunking
Ok, so its just chatgpt on CLI. Meh
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Yo….
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find_logical_fallacies and find_hidden_message, my favorites….
Was that before or after the Geneva Convention? Wow😅, nuclear war just might be around the corner…. 🤦🏽♂️