The scientist, conservationist and UN Messenger of Peace Jane Goodall dedicated her life to safeguarding nature and its inhabitants.
Her extraordinary legacy will continue to inspire our collective efforts for peace, sustainability and harmony with the environmentThe scientist, conservationist and UN Messenger of Peace Jane Goodall dedicated her life to safeguarding nature and its inhabitants.
Her extraordinary legacy will continue to inspire our collective efforts for peace, sustainability and harmony with the environmentThe scientist, conservationist and UN Messenger of Peace Jane Goodall dedicated her life to safeguarding nature and its inhabitants.
Her extraordinary legacy will continue to inspire our collective efforts for peace, sustainability and harmony with the environmentThe scientist, conservationist and UN Messenger of Peace Jane Goodall dedicated her life to safeguarding nature and its inhabitants.
Her extraordinary legacy will continue to inspire our collective efforts for peace, sustainability and harmony with the environmentThe scientist, conservationist and UN Messenger of Peace Jane Goodall dedicated her life to safeguarding nature and its inhabitants.
Her extraordinary legacy will continue to inspire our collective efforts for peace, sustainability and harmony with the environment.
"Hay hombres que luchan un dia y son buenos. Hay otros que luchan un año y son mejores. Hay quienes luchan muchos años y son muy buenos. Pero hay los que luchan toda la vida: esos son los imprescindibles."
The Trump administration’s decision to repatriate the USAID’s overseas workforce has thrust the global agency’s staff into chaos, as workers scramble to uproot their lives and brace for what they fear will be a shutdown of all U.S. aid missions in 30 days. https://t.co/uL3SoKColR
EMBO Postdoctoral Fellowships support internationally mobile postdoctoral researchers in Europe and around the world. Apply here (next cut-off date is 14 February):
https://t.co/MchFNj6TsE
#ResearchFunding#LifeSciences
More than 40 percent of #postdocs leave academia. Those who landed a coveted faculty position were more likely to have had a highly cited paper, changed their research topic between their #PhD and postdoc, or moved abroad after receiving their doctorate. https://t.co/SkU2JVisuu @PNASNews -> https://t.co/GZKmXombKN #ScienceCareer
@kacikprens@melihkavukcu1 Yıllardır, ben de o masadaymış gibi hissetmişimdir sizi dinlerken. Sanki bir dostumu kaybetmişim gibi sarsıldım açılışta. Artık nasıl bir benimsemekse bu... 🥺🥹 (Sabırlar diliyorum @melihkavukcu1. Anılarda yaşasın dostunuz!)
BREAKING NEWS
The Royal Swedish Academy of Sciences has decided to award the 2024 #NobelPrize in Chemistry with one half to David Baker “for computational protein design” and the other half jointly to Demis Hassabis and John M. Jumper “for protein structure prediction.”
📢📢 Calling female scientists! Through the Elisabeth Bauser Postdoctoral Fellowship, we are offering fully-funded postdoctoral contracts. 👩🏽🔬👩🏿🔬👩🔬 Learn more at https://t.co/wmzoqwmegE
1st year PhD student showing up at the 8 am panel with 25 expertly crafted slides, 57 backup slides, and print-outs prepared four weeks in advance
vs
Tenured professor giving the keynote with two slides of mood pictures clicked together in the hotel lobby 15 minutes earlier
We aim to unleash the full potential of cycling in the EU.
Our Declaration recognises cycling as one of the most sustainable, accessible and inclusive, low-cost and healthy forms of transport and recreation
Read our full declaration:
https://t.co/PHGcv0EBUe
Publishing negative results is good for science
My latest Editorial for @MicrobioSoc Access Microbiology, as part of their Negative Results collection.
https://t.co/4ExLDDPFwA
Let me clear a *huge* misunderstanding here.
The generation of mostly realistic-looking videos from prompts *does not* indicate that a system understands the physical world.
Generation is very different from causal prediction from a world model.
The space of plausible videos is very large, and a video generation system merely needs to produce *one* sample to succeed.
The space of plausible continuations of a real video is *much* smaller, and generating a representative chunk of those is a much harder task, particularly when conditioned on an action.
Furthermore, generating those continuations would be not only expensive but totally pointless.
It's much more desirable to generate *abstract representations* of those continuations that eliminate details in the scene that are irrelevant to any action we might want to take.
That is the whole point behind the JEPA (Joint Embedding Predictive Architecture), which is *not generative* and makes predictions in representation space.
Our work on VICReg, I-JEPA, V-JEPA, and the works of others show that Joint Embedding architectures produce much better representations of visual inputs than generative architectures that reconstruct pixels (such as Variational AE, Masked AE, Denoising AE, etc).
When using the learned representations as inputs to a supervised head trained on downstream tasks (without fine tuning the backbone), Joint Embedding beats generative.
See the results table from the V-JEPA blog post or paper:
https://t.co/mfLvtvk8jj