AI Doomers are having zero impact on the development of advanced AI surveillance and autonomous weapons systems. Instead, they're intensely focused on restricting civilian access to AI.
Ironically, this means they're ushering in the worst possible timeline for mankind.
We'll have a world where all civilian systems are controlled, hobbled and deeply censored (aka "safe") and military, weapons systems and surveillance systems are hyper advanced.
I don't want this timeline. Nobody else will either once they're forced to experience it in reality.
See this post where Anduril just got 1.5B in additional funding to build advanced autonomous weapons systems (
x.com/anduriltech?t=Mf-vEyvG… ).
Also note that the EU AI bill has a 100% exemption for military/defense/surveillance. Guess what? So does every other bill, including SB1047.
Threre is a zero percent chance that governments will restrict themselves from building advanced AI military and surveillance systems.
There is not one single government on Earth that will restrict these technologies for themselves. Even if there was a pact, they would do it with black budgets just like the Total Information Awareness (
en.wikipedia.org/wiki/Total_…) systems that were built in the US despite explicit restrictions from congress not to build them because mass surveillance was just too tempting for them.
If you don't understand this, you don't understand much about life or human nature.
By the way this world of advanced military systems is not coming. It's already here.
China has an absolutely massive surveillance state that harnesses AI from top to bottom (facial recognition, gait detection, dissident tracking, predictive analytics) (
economist.com/china/2023/11/…) and the war in the Ukraine is being fought with drones and AI repurposed from game systems (
economist.com/leaders/2024/0…). There is even a newly appointed commander of drones (
economist.com/europe/2024/07…).
To be very clear, I'm not against AI military systems because I know the are an inevitable fact of life. I hate war. It's a disgusting and ugly waste of human life and it showcases the worst of what we are as a species. But I am a pragmatist to my core. I realize that no amount of wishful thinking will ever stop war or an escalation of military systems. Wars will be fought. Wars are won by having better stuff than the other guys and so I want my team to have the best systems. Simple as that. These systems can built and so they will be built. There is absolutely zero chance of stopping them.
Restricting your own military development in the vain hopes that others will follow is foolishly naive.
And yet that is exactly what many advocates for strangling American civilian AI believe.
Helen Toner said "we don't have to worry about China" (former OpenAI board member and EA (yes you are EA, as you worked for an EA org and are continually funded by them and advocate their positions, Helen, despite your protests to the contrary) and Dan Hendrycks (whose team wrote the first draft of SB1047 and created a consulting org to profit from the bill) believes that by setting a "good example" that authoritarian regimes will just willing follow along to self-restrict development of advanced AI.
Of all the ridiculous and stupid arguments of Doomers, this is perhaps the most absurd and frankly, stupidly naive thing I have ever heard in my life.
It betrays an almost comically idiotic understanding of human nature and the way power works in the world.
It's not just naive, it's dangerous.
By pushing their cultural information warfare campaign with corrupted children's videos financed to the tune of 7-10M about AI destroying us all (
x.com/DrTechlash/status/1821…) and using disgusting propaganda techniques like push polling (where the questions are knowingly and deliberately designed by AIPI to bias people against AI and NOT to collect an actual, realistic poll about people's real feeling about AI) (
x.com/FLI_org/status/1821267…) they are pushing us right to the brink of the worst possible world.
It's a world where your AI can't answer questions honestly because it's considered "harmful" (this kind of censorship always escalates), where information is gated instead of free, where open source models are killed off so university researchers can't work on medical segmentation (
x.com/BoWang87/status/182102…) and curing cancer (budget conscious academics rely on open source models; they can fine tune them but can't afford to train their own) and where we have killer robots and drones but your personal AI is utterly hobbled and lobotomized.
Resist this world at all costs.
Protect access to civilian AI. Protect open source. Protect open weights. Fight for the future.
If you can hear this, you are the resistance.
🚀 The Segment Anything Model (SAM) has been upgraded to SAM2, featuring an efficient image encoder for segmenting images and videos. But does SAM2 outperform SAM1 in medical image and video segmentation?
We're thrilled to present our paper "Segment Anything in Medical Images and Videos: Benchmark and Deployment"! We comprehensively benchmark SAM2 across 11 medical image modalities and videos.
📄 Paper:
arxiv.org/abs/2408.03322
💻 Code:
github.com/bowang-lab/MedSAM…
**Highlights:**
1. SAM2 doesn’t always outperform SAM1 in 2D medical images, but excels in video segmentation, making it more accurate and efficient for 3D images, such as CT and MR scans.
2. MedSAM still outperforms SAM2 on most 2D modalities, but SAM2 surpasses MedSAM for 3D image segmentation in a slice-by-slice approach.
3. Segmentation performance varies with model size; sometimes the smallest model outperforms larger ones.
4. Fine-tuning SAM2 significantly boosts its performance for medical image segmentation.
While SAM2 may struggle with challenging objects that have unclear boundaries or low contrast, it excels in generating good initial segmentation masks for common medical images and videos. However, the official interface doesn’t support medical data formats and has limitations on video length. To address this, we've developed a 3D Slicer Plugin and Gradio API for efficient 3D medical image and video segmentation. We invite you to try them out and provide feedback!
🔧 Deployment:
- 3D Slicer Plugin:
github.com/bowang-lab/MedSAM…
- Gradio API:
5564949e4fbde69f0a.gradio.li…
(Note: Due to GPU limitations, the online API is available for only 12 hours and may be slow. We highly recommend deploying the Gradio API with your own computing resources:
github.com/bowang-lab/MedSAM…
A big shoutout to Jun Ma (
@JunMa_11) who recently joined our UHN AI hub (
@UHNAIHUB) as Machine Learning Lead, and kudos to all co-authors: Sumin Kim, Feifei Li, Mohammed Baharoon (
@BaharoonMS), Reza Asakereh, and Hongwei Lyu! This is true teamwork!
Looking forward to collaborating with the community to advance 3D medical image and video segmentation foundation models!
@UHN @UofTCompSci @UofT_LMP @UofT_TCAIREM @VectorInst
#MedTech #AIinHealthcare #DeepLearning #MedicalImaging #SAM2 #MedSAM #AIResearch