It’s not. But the assumption that humans will agree on AGI alignment before building AGI is inherently flawed. A brief study of human history (or indeed a study AI history) should make that clear.
RESEARCH
-
Hermes Discussion with Nous Research CTO
By
–
Bummer, am talking about Hermes with the CTO of @NousResearch then. Will join after if you are till running.
-
DISCO: AI-Designed Enzyme Engineering via Diffusion Co-design
By
–
Going from a beautiful idea to successful wet lab experiments is the dream cycle of every scientist.
— Kirill Neklyudov (@k_neklyudov) 8 avril 2026
This is exactly what DISCO does but at insane, inhuman scale. Given numerous chemical constraints including binding targets and off-targets, it generates proposals for wet-lab… https://t.co/c7TbU3xUhpGoing from a beautiful idea to successful wet lab experiments is the dream cycle of every scientist. This is exactly what DISCO does but at insane, inhuman scale. Given numerous chemical constraints including binding targets and off-targets, it generates proposals for wet-lab testing at unprecedented throughput. For @martoskreto, @AlexanderTong7, and me, it also means bringing Feynman-Kac Correctors from idea stage to a successful practical technique! Jarrid Rector-Brooks (@jarridrb) What if AI could invent enzymes that nature hasn’t seen? 👩🔬🧑🔬 Introducing 🪩 DISCO: Diffusion for Sequence-structure CO-design 14 rounds of directed evolution and over a year of wet lab work. That's what it took to engineer an enzyme for selective C(sp³)–H insertion, one of the most challenging transformations in organic chemistry. DISCO surpasses this with a single plate. No pre-specified catalytic residues, no template, no theozyme, no inverse folding, just joint diffusion over protein sequence and structure. 📝 Blog: disco-design.github.io/ 📄 Paper: arxiv.org/abs/2604.05181 💻 Code: github.com/DISCO-design/DISC… — https://nitter.net/jarridrb/status/2041893841301860542#m
-

Domino enables reproducible AI workflows for bioengineering collaboration
By
–
In this demo, we show how Domino enables cross-lab collaboration, reproducible AI workflows, and end-to-end experiment tracking to accelerate bioengineering at scale. Watch to see how leading research teams are building biology on demand: https://
hubs.ly/Q04b41SG0 -
Teaching Critical Thinking in the Age of AI
By
–
Teaching Critical Thinking in the Age of AI #AI #AIio #AIInnovation #ML #DataScience #Futureofwork @lexfridman @sama @kaifulee @ID_AA_Carmack @karpathy @2morrowknight @ylecun ow.ly/nzMe30sUVAn
-

Anthropic Had Mythos Internally Since February 2024
By
–
ANTHROPIC HAD MYTHOS INTERNALLY SINCE FEB 24
-
Newton the Magician: Science as Pattern Recognition
By
–
Keynes acquired Newton's private papers and was shocked at what he found. @michael_nielsen reads the key passage in the essay Keynes published afterwards:
— Dwarkesh Patel (@dwarkesh_sp) 8 avril 2026
"Newton was not the first of the age of reason. He was the last of the magicians, the last great mind which looked out on… pic.twitter.com/ACoanqEckbKeynes acquired Newton's private papers and was shocked at what he found. @michael_nielsen reads the key passage in the essay Keynes published afterwards: "Newton was not the first of the age of reason. He was the last of the magicians, the last great mind which looked out on the visible and intellectual world with the same eyes as those who began to build our intellectual inheritance rather less than 10,000 years ago." And as Michael jokes, what are these great scientists actually doing? Writing down squiggles on a page based on observations and these mysterious cosmic connections, then using it to accomplish miracles. Launching rockets, creating atomic bombs. "That's exactly what magicians do." Keynes was shocked to find that Newton's alchemy and theology used the same methods as his physics: "There was extreme method in his madness. All his unpublished works on esoteric and theological matters are marked by careful learning, accurate method and extreme sobriety of statement. They are just as sane as the Principia, if their whole matter and purpose were not magical. They were nearly all composed during the same twenty-five years of his mathematical studies."
-
AI Companions: Short-term Comfort, Long-term Risk for Lonely Users
By
–
#AI companions can comfort lonely users but may deepen distress over time
— Ronald van Loon (@Ronald_vanLoon) 8 avril 2026
by Aalto University @TechXplore_com
Learn more: https://t.co/4U6LpqTo2b#ArtificialIntelligence #MachineLearning #ML #DL pic.twitter.com/EPCji97wij#AI companions can comfort lonely users but may deepen distress over time by Aalto University @TechXplore_com Learn more: bit.ly/3OjC7pm #ArtificialIntelligence #MachineLearning #ML #DL
-
Guided vulnerability detection differs from autonomous discovery
By
–
It's very cool work, but it's not 1:1. The report shows that they basically lead the models to the right spot for them to do the work. It's more "is this a vulnerability?" than "find a vulnerability". Mythos had to find it from scratch, these were told where it was.
-
AI Performance Drift and Human Oversight in Future Systems
By
–
Yeah, it's interesting how it drifts and gets lazy over time. Even with an amazing memory and rule set. I guess there still is a role for humans in the future. "Keep your lazy AIs working hard." 🙂