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Miguel🏴

@miguel-pinturinhas.bsky.social

1.5K followers 2.8K following 1.6K posts

Todas as Tags e representações e links do meu trabalho foram retiradas temporariamente, no momento to fazendo um troço, depois que eu acabar vou poder voltar a fazer o que eu quero.
Minha Linda Namorada: @lowasreborn.bsky.social

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Reposted by Miguel🏴

Remmelt 🛑

@artificialbodies.net

It’s weird how I trusted Ed Zitron to mean well (despite the disingenuous promotion of ideas I noticed sometimes) because he told me didn’t like Gary in part because of his attacks on you.

This is just shit:

"GOT A REALLY unique one here," the email began. It was Zitron, and in August 2024 he was pitching a journalist on an EZPR client: Fulcra Dynamics, a company that collects your information, including health data, and then connects it to LLM models like ChatGPT, allowing you to "talk" to your own data, ask it questions about your workouts or the ETA of an Instacart order. Fulcra is backed by the Winklevoss twins. While some Al skeptics could see it as the sort of predatory crap that, with any luck, could be sued into the ether before everyone's biometrics get leaked on X.com, Zitron in his email expressed no such qualms about Fulcra or its leadership.
"These guys rock," he wrote of the company's founders. "I will stake my rep on them."

October 28, 2025 at 4:49 AM

Reposted by Miguel🏴

Hedrick

@hedrickart.bsky.social

Thanks fo the opportunity?
What i like to draw?
CUTE GIRLS 🤭

Tags :
@midnightisded.bsky.social @dylanmacri.bsky.social @ayuumiko.bsky.social @cheekycatbat.bsky.social

Lexie, my story's MC with long pink hair tied in a ponytail and teal eyes with white pupils. She's wearing a form-fitting, light blue and white jumpsuit with gold accents, which she is unzipping, revealing a significant portion of her chest. The background depict a locker room, with some metal wardrobes behind her.

Himari, a cute human-bird character with glasses and wings, holding the top part of her pan.

Castorice from honkai star rail, looking to the left, hand joined

A girl with short black hairs, brown eyes, a black bikini and a see-through shirt, easting an Ice cream. She's in the water, Thigh-high, and she also has a straw hat.
In her left hand, a tiny crab is holding a love letter, and he has some hearts around him.

October 8, 2025 at 3:42 PM

Miguel🏴

@miguel-pinturinhas.bsky.social

Veja bem IA tem diversas aplicações úteis enquanto ferramenta, mas usar esse troço nas aplicações atuais é danosos demais num geral, mesmo seres unicelulares são muito complexos comparados a computadores.
www.youtube.com/watch?v=E8oI...
www.sci.news/biology/slim...

October 8, 2025 at 3:43 PM

Miguel🏴

@miguel-pinturinhas.bsky.social

Os modelos tem cerca de 4000 "dimensões" pra "simular" o processo de decisão de seres vivos, mas ainda é só uma "gigantesca arvore de decisões" eles usam diversas técnicas pra aproximar, mas ainda sim é um mapa matemático de pixels, o que tiver dentro desses "pixels não autorizados" vai ser cortado.

5Artificial intelligence, machine learning, and deep learning
Engine wasn’t meant as a general-purpose computer when it was designed in the
1830s and 1840s, because the concept of general-purpose computation was yet to be
invented. It was merely meant as a way to use mechanical operations to automate cer-
tain computations from the field of mathematical analysis—hence, the name Analyti-
cal Engine. In 1843, Ada Lovelace remarked on the invention, “The Analytical Engine
has no pretensions whatever to originate anything. It can do whatever we know how to
order it to perform.… Its province is to assist us in making available what we’re
already acquainted with.”
This remark was later quoted by AI pioneer Alan Turing as “Lady Lovelace’s objection” in his landmark 1950 paper “Computing Machinery and Intelligence,” 1 which
introduced the Turing test as well as key concepts that would come to shape AI. Turing
was quoting Ada Lovelace while pondering whether general-purpose computers could
be capable of learning and originality, and he came to the conclusion that they could.
Machine learning arises from this question: could a computer go beyond “what we
know how to order it to perform” and learn on its own how to perform a specified task?
Could a computer surprise us? Rather than programmers crafting data-processing
rules by hand, could a computer automatically learn these rules by looking at data?
This question opens the door to a new programming paradigm. In classical programming, the paradigm of symbolic AI, humans input rules (a program) and data to
be processed according to these rules, and out come answers (see figure 1.2). With
machine learning, humans input data as well as the answers expected from the data,
and out come the rules. These rules can then be applied to new data to produce original answers

A machine-learning system is trained rather than explicitly programmed. It’s presented with many examples relevant to a task, and it finds statistical structure in these examples that eventually allows the system to come up with rules for automating the task.
For instance, if you wished to automate the task of tagging your vacation pictures, you could present a machine-learning system with many examples of pictures already tagged by humans, and the system would learn statistical rules for associating specific pictures to specific tags.

Deep Learning with Python

FRANÇOIS CHOLLET

October 8, 2025 at 3:43 PM

Miguel🏴

@miguel-pinturinhas.bsky.social

Isso é uma limitação do próprio funcionamento desses modelos, eles pegam padrões vetoriais em imagens e ligam eles matematicamente dentro de um plano cartesiano a tokens e os tokens geram uma saída especifica, não da pra arrumar, é a versão mais tonha do conectivismo.
philpapers.org/rec/GUEAMO-2