0asa

Father, Innovation Engineer @EVSequipment, previously Data Scientist @Kensuio, E-Marketing Tools Manager @diagenode, cofounder @AntibodyAdviser.

[0asa @0asa]

@topazlabs

[Santiago @svpino]

OpenAI, Anthropic, et al. scraped my website, my videos, my codebases, and all of the content I've published online.

They used years of *my* work to train *their* models. Now, they claim this is "their data" and accuse others of "stealing" it.

It's really hard for me to empathize with them about this.

It's also hard to understand how they can claim moral superiority concerning the censuring of models.

Both the GPT model series and Claude are totally nerfed and ideologically biased!

Here I am, once more, rooting for free, open-science, and open-source models to be the last ones standing.

[sacha lewin @SachaLewin]

Thrilled to announce my first paper, "Dynamic NeRFs for Soccer Scenes", which was accepted at the MMSports 2023 workshop (@ ACM Multimedia)!

It features a part of my master's thesis work, in which I explore the use of dynamic NeRFs for the task of reconstructing soccer replays.

[AK @_akhaliq]

Dynamic NeRFs for Soccer Scenes

paper page: https://t.co/1A6XcjdnCO

The long-standing problem of novel view synthesis has many applications, notably in sports broadcasting. Photorealistic novel view synthesis of soccer actions, in particular, is of enormous interest to the broadcast industry. Yet only a few industrial solutions have been proposed, and even fewer that achieve near-broadcast quality of the synthetic replays. Except for their setup of multiple static cameras around the playfield, the best proprietary systems disclose close to no information about their inner workings. Leveraging multiple static cameras for such a task indeed presents a challenge rarely tackled in the literature, for a lack of public datasets: the reconstruction of a large-scale, mostly static environment, with small, fast-moving elements. Recently, the emergence of neural radiance fields has induced stunning progress in many novel view synthesis applications, leveraging deep learning principles to produce photorealistic results in the most challenging settings. In this work, we investigate the feasibility of basing a solution to the task on dynamic NeRFs, i.e., neural models purposed to reconstruct general dynamic content. We compose synthetic soccer environments and conduct multiple experiments using them, identifying key components that help reconstruct soccer scenes with dynamic NeRFs. We show that, although this approach cannot fully meet the quality requirements for the target application, it suggests promising avenues toward a cost-efficient, automatic solution. We also make our work dataset and code publicly available, with the goal to encourage further efforts from the research community on the task of novel view synthesis for dynamic soccer scenes

[0asa @0asa]

@joerybicki

[0asa @0asa]

AssistiveTouch, magic at your fingertips! Quickly and easily interact with your Apple Watch without touching the display. Double tap your index finger and thumb to… turn an accessibility feature into a major update! #AppleEvent

[0asa @0asa]

@joerybicki Not possible, you have to wait till October and to buy the Ultra 2. The thing you are talking about is for disabled people only.

[0asa @0asa]

In case you need more ideas:
- "The Art of Withholding Knowledge: How Paywalls Keep Science Exclusive"
- "From Ivory Tower to Paywall Fortress: How Science Became an Exclusive Club"
- "Paywalls: Because Who Needs Collaboration and Progress When You Can Monetize Information?"

[0asa @0asa]

Hey @Nature, why not consider this title for your next article: "Exploring the Expensive Paywall between Scientific Research and the Public"?
https://t.co/O0q2qDRuTV

[0asa @0asa]

@Laurenceborgs C'est un véritable accomplissement, j'ai tenu tout ce temps à lire des tas de conneries et à regarder des tas de gifs... Je pense ajouter cet exploit sur mon profil LinkedIn, que penses-tu ?

[0asa @0asa]

Vous souvenez-vous quand vous avez rejoint Twitter ? Moi, oui ! #MonAnniversaireTwitter

[0asa @0asa]

@zqmlk @Apple Yup, same here. Yet, everything is green: https://t.co/jS0G2Qq2Vt

[0asa @0asa]

Researchers can select a metric to either create or remove an emergent ability. Therefore, emergent abilities may not be a fundamental property of a model family for a specific task, but rather a result of the researcher’s choices! Wait… what?

https://t.co/5WNPAJee4x

[EVS Broadcast Equipment @EVSEquipment]

Our AI-powered super slow-motion service just got a major upgrade with the ability to deploy on-prem, which means we've reduced the turnaround time to approximately five seconds!

👉 Read our press release: https://t.co/SzYL8JAFLx

#EVSforLive #nab #nab2023 #nab100 #ai

[Daniel Colin James @dcwj]

Raycast is blowing my mind. It's the 20% of macOS I didn't realize was missing. It's everything I wanted Alfred to be. It's clearly made by people obsessed with nailing the details. It's been 2 days and I can't remember how I used my computer before it.

[Eric Wallace @Eric_Wallace_]

Models such as Stable Diffusion are trained on copyrighted, trademarked, private, and sensitive images.

Yet, our new paper shows that diffusion models memorize images from their training data and emit them at generation time.

Paper: https://t.co/LQuTtAskJ9

👇[1/9]

[0asa @0asa]

@tanayj What’s the point?

[0asa @0asa]

Stop Calling Everything AI!
https://t.co/N5TqQzAGie

[AI Breakfast @AiBreakfast]

🤯 Full body tracking now possible using only WiFi signals

A deep neural network maps the phase and amplitude of WiFi signals to UV coordinates within 24 human regions

The model can estimate the dense pose of multiple subjects by utilizing WiFi signals as the only input

🧵

[DHH @dhh]

We spent $3,201,564.24 on cloud in 2022 at @37signals, mostly AWS. $907,837.83 on S3. $473,196.30 on RDS. $519,959.60 on OpenSearch. $123,852.30 on Elasticache. This is with long commits (S3 for 4 years!!), reserved instances, etc. Just obscene. Will publish full accounting soon.