Dr_Arch_Ana_Cocho

Expert in Machine Learning & Adaptive Architecture; Researching how to design with innovative technologies and theories AI based.

[Dr_Arch_Ana_Cocho @EmDeplo]

Glad to share with you the article about #cognition #distributedsystems #architecture & #AI for the 33rd number of the #arquitectonics journal.
Full version here:
https://t.co/UTpo1ZB1oV

[UCL CASA @CASAUCL]

Read a review of @jmichaelbatty's recently published book, The Computable City. The review from @APA_Planning says the book is 'accessible to a broad audience and serves as a particularly valuable reference for scholars'. #JAPAplanning

https://t.co/diUdlhg8Q1

[Yarden Shafir @yarden_shafir]

CrowdStrike effectively bricked windows, Mac and Linux today.

Windows machines won’t boot, and Mac and Linux work is abandoned because all their users are on twitter making memes.

Incredible work.

[Duchess Gemma (MTE) aka Ms Tonks🐟 🇪🇺🇬🇧🕷 @gemmagould]

Right people let’s fucking do this ✊🏻♥️
#RiseUpWiseUpAndVote
#GTTO
#FuckReform
#GeneralElection2024

[José Fernández Sánchez @fernandezsj]

🗓Hoy, Día Mundial del Autismo, recordamos que la diversidad y el valor de las personas con autismo están cerca de nosotros en cada sonrisa, en cada desafío superado.

🔹️Por una sociedad más inclusiva y respetuosa. #AutismoCercaDeTi

[InvestiGal @InvestiGal]

🩵 Rematamos o #FIGaE_2024 en Bruxelas este fin de semana! Grazas a todas as persoas asistentes e poñentes, pola vosa participación e aportacións tan interesantes. E á @axenciaGAIN polo seu apoio e co-organización, así como á @EmbEspBelgica A ciencia galega ten moito que decir!

[Mick W@tson ↙️ @BioMickWatson]

Keeping your academic group funded

[InvestiGal @InvestiGal]

'Habelas,Hailas: investigacións galegas en Europa' falamos de IA,bacterias púrpuras como fonte de proteínas, coanoflaxelados,enx. de tecidos ao estilo Tony Stark,antimateria e agora para finalizar o #FIGaE_2024 o bonus track co director do @IncipitCSIC Felipe Criado.

[Carlos E. Perez @IntuitMachine]

I suspect many AI projects will end up in ruin because its developers are just muddling around getting their dopamine hits from the deluge of micro-events about AI. They focus only on the trees but can't see the forest!

[Re-energising Your Career @career_re]

#AcademicTwitter Your Thesis Committe!😂#phdlife #phdvoice

[Teo_Arquitecto @Teo_Arquitecto]

Lo de "Hasta las pelotas" hay que decirlo mas veces.

[The PhD Place @ThePhDPlace]

I don’t know who needs to hear this but THAT paper doesn’t need to be perfect. It just needs to be finished.

[Daniel Gould, MD, PhD @DJGould94]

Academics be like "there's a lot of confusion about this concept, but it's really quite intuitive. Allow me to explain"

[Oded Rechavi @OdedRechavi]

"We thank the reviewers for their insightful remarks"

[Andrew Ng @AndrewYNg]

The LVM (large vision model) revolution is coming a little after the LLM (large language model) one, and will transform how we process images. But there’s an important difference between LVMs and LLMs:
- Internet text is similar enough to proprietary text documents that an LLM trained on internet text can understand your documents.
- But internet images – such as Instagram pictures – contain a lot of pictures of people, pets, landmarks, and everyday objects. Many practical vision applications (manufacturing, aerial imagery, life sciences, etc.) use images that look nothing like most internet images. So a generic LVM trained on internet images fares poorly at picking out the most salient features of images in many specialized domains.

That’s why domain specific LVMs – ones adapted to images of a particular domain (such as semiconductor manufacturing, or pathology) – do much better. At @LandingAI , by using ~100K unlabeled images to adapt an LVM to a specific domain, we see significantly improved results, for example where only 10-30% as much labeled data is now needed to achieve a certain level of performance.

For companies with large sets of images that look nothing like internet images, I think domain specific LVMs can be a way to unlock considerable value from their data. Dan Maloney and I share more details in the video.

[The Struggling Scientists @TheStrugglingS4]

Close enough 😅

[Oded Rechavi @OdedRechavi]

PhD advisor's response to your detailed 4 pages long email

[Matthias Niessner @MattNiessner]

(1/2)
Check out 𝐌𝐞𝐬𝐡𝐆𝐏𝐓!

MeshGPT generates triangle meshes by autoregressively sampling from a transformer model that produces tokens from a learned geometric vocabulary.

As a result, we obtain clean and compact meshes :)

https://t.co/ynrf0qjYVF
https://t.co/rQe7ipP15t

[DeepLearning.AI @DeepLearningAI]

😌

Original: AI Sciences on Instagram

[José Luis Antúnez @jlantunez]

Esto me vuela la cabeza. Haces una screenshot y te la construye en código. Herramienta gratuita que está en Github https://t.co/yXrXFPWRGv