AI
Matt Ross and
AI
Quanta interviewed 19 current and former NLP researchers to tell that story. From experts to students, tenured academics to startup founders, they describe a series of moments — dawning realizations, elated encounters and at least one “existential crisis” — that changed their world. And ours.
John Pavlus • When ChatGPT Broke an Entire Field: An Oral History | Quanta Magazine
Byron is my AI writing partner — powered by ChatGPT, shaped by a 7-page writing profile we built together. He doesn’t write for me, but with me. When I lose a thread or stall on phrasing, Byron offers possibilities — paths I might not have seen. Between my neural implants and Byron’s digital guidance, I now collaborate with two adaptive systems:... See more
For my 80th birthday I bought myself a new brain
I lost my mom to Parkinson’s this year, so this hit a nerve. My mom never would have done this sort of thing, but as the saying goes, this is the worst it will ever be. I hope I live disease-free long enough to see some significant treatment advancements for neurodegenerative diseases.
This is particularly important because there are already indications that many people who often interact with chatbots attribute consciousness to these systems. At the same time, the consensus among experts is that current AI systems are not conscious.
Wanja Wiese • Consciousness in AI: Distinguishing Reality from Simulation - Neuroscience News
Is the code any good? I don’t know. Who cares? Nobody looks at it anyway. AI produces a result, and results are what matter, and if you’re waiting for quality to factor significantly into that equation, I’ve got some bad news about the last 40 years of professional software development for you.
Michael Tsai - Blog - Greg Knauss Is Losing Himself
The share of human-agent and agent-agent interactions in the economy will increase over time, with agents engaging in price negotiation, placing orders from one another, coordinating supply and demand, and even rating each other to assign trustworthiness scores.
Faster Horses
Second, TA teaches us to never overlook the simplest solutions. There are a lot of complicated methods to automatically find augmentation policies, but the simplest method was so-far overlooked , even though it performs comparably or better
Devansh • TrivialAugment: The next evolution in Data Augmentation [Breakdowns]
