Bruce Schneier just called our survey on threats of machine generated text "a solid grounding amongst all of the hype."
Read it here:
https://t.co/lfqnQ7tNHk
@TheCinesthetic Subspecies II wins this for me.
The beheaded villain simply pops his head back on, stands up, and resumes chasing the heroes -- now played by completely different actors.
Truly a masterpiece.
@RealAlbanianPat Large numbers of uninformed people overreacting to new info is basically a selling feature for a prediction market.
Polymarket isn't trustable, but for other reasons.
@shauseth reminds me of the early days of Tesla autopilot when people would ignore every warning, find a way to let go of the wheel, and trust it with their lives.
granted the branding "autopilot" created an expectation there
@shauseth vibe coding has very fixable problems to be honest. problem is that people are willing to trust AI systems 100% when they're nowhere near mature enough to justify it.
🇨🇦 healthcare system is stuck in the last century.
In ON, doctors send 150M faxes (faxes!) a year. 1 in 10 go to the wrong person. People die everyday because their records are unavailable.
Your health records should be available instantly to you and any doctor that needs it.
@molly0xFFF Increasing user counts (and thus market cap) makes this much worse. Once there's enough money at stake, the economic incentives become incredibly dangerous.
To support innovation in computer vision, we’re making DINOv2 available under the Apache 2.0 license + releasing a collection of DINOv2-based dense prediction models for semantic image segmentation and monocular depth estimation.
Try our updated demo ➡️ https://t.co/ctwiBFWS4W
Mother of all LLM jailbreaks: Automatically constructing adversarial prompts using OSS model (Vicuna) weights that work against ChatGPT, Bard, Claude, and Llama 2
Screenshots: Demo of response without/with jailbreak suffix
Linked thread from lead author has details/PDF