The question of how gravity interacts with the quantum world has long perplexed physicists, but a non-quantum theory of space-time could present an answer
This is a ~1 hour 7 minute talk titled “Geometric Framework for Biological Evolution” by Vitaly Vanchurin (http://cosmos.phy.tufts.edu/~vitaly/) given to our Center (https://allencenter.tufts.edu).
As the chart implies, the issue isn’t that the underlying weights of Fable 5 were made fundamentally “dumber”—it’s that Anthropic wrapped the model in an incredibly aggressive, restrictive policy routing architecture to satisfy compliance demands.
According to Anthropic’s documentation and recent technical breakdowns, the “nerf” comes down to a few major bottlenecks:
As developers quickly noticed—and as the BridgeBench data in HMOulJbWYAAw-bf.jpg proves—this “fix” came at a devastating cost to the model’s actual utility, cratering debugging scores by over 60 points.
For 19 days the best model on earth was illegal to show a foreign national, including Anthropic’s own staff. Yesterday Fable 5 came back, with an admitted new classifier, a silent reroute to Opus 4.8, and no proof the weights are the same. Nobody can publish that proof, and the vendor didn’t try. Access used to be gated by price. Now it’s gated by permission, and verified by vibes.
🌌 Holographic theory suggests a profound idea: the universe may store information on its boundary, while the spacetime we experience emerges from that information. In this view, gravity is not only a force between masses.
https://doi.org/10.13140/RG.2.2.17062.
It may also be a macroscopic effect of quantum information, especially entanglement, encoded on a cosmic horizon. 🧠✨
A simple way to express this is:
Horizon information → Entanglement → Spacetime geometry.
To describe how efficiently entanglement becomes geometry, we introduce an entanglement-weight field:
Here, W(x) represents the conversion efficiency from holographic entanglement to gravitational geometry.
This modifies the effective strength of gravity:
Nuttida Rungratsameetaweemana is challenging a story neuroscience has told for decades. According to the conventional account, our eyes collect raw information and relay it through a series of nerves and waystations that lead deep into the brain, eventually reaching the cortex. There, the thinking begins as information is processed and put to use for higher tasks such as reasoning, judgment and decision-making.
Her group’s work is complicating that account. Last year, the team published fMRI scans showing unexpected levels of activity in the earliest visual areas of the cortex, the regions that first receive visual signals. Rather than passively relaying what the eyes take in, those early areas seemed to process the same information differently depending on what the research participant was doing. When asked to sort shapes by one set of rules, a participant’s early visual system behaved one way. When asked to apply a different set of rules to the same shape, it behaved differently.
In a new paper published today in PLOS Biology, Rungratsameetaweemana and her team at Columbia Engineering show how the brain might pull this off. They built a simple neural network that follows many of the rules that govern real brains. Like the brain, their model contained one class of neurons that drive other neurons to fire and another class that suppress firing.
Single-targeted chimeric antigen receptor (CAR) T cells tremendously improve outcomes for patients with relapsed/refractory hematological malignancies and are considered a breakthrough therapy. However, over half of treated patients experience relapse or refractory disease, with antigen escape being one of the main contributing mechanisms. Dual-targeting CAR T-cell therapy is being developed to minimize the risk of relapse or refractory disease. Preclinical and clinical data on five categories of dual-targeting CAR T-cell therapies and approximately fifty studies were summarized to offer insights and support the development of dual-targeting CAR T-cell therapy for hematological malignancies. The clinical efficacy (durability and survival) is validated and the safety profiles of dual-targeting CAR T-cell therapy are acceptable, although there is still room for improvement in the bispecific CAR structure. It is one of the best approaches to optimize the bispecific CAR structure by boosting T-cell transduction efficiency and leveraging evidence from preclinical activity and clinical efficacy.
NASA announced on June 30, 2026, that it is considering sending PROMISE, an engineering test rover built at the Jet Propulsion Laboratory as a stand-in for the Curiosity and Perseverance Mars rovers, to the lunar surface. NASA Administrator Jared Isaacman, announcing the concept alongside a batch of new lunar lander contracts, framed the pitch as a matter of hardware already paid for. “We’ve had years now of experience operating the two rovers on the surface of Mars, and we’ve got this hardware that the taxpayers have invested a lot in,” Isaacman said, according to Space.com. “So the question was posed: what if we send it to the moon?” He introduced the idea with a line borrowed from Yoda: “There is another.”
14 years ago, Steve Mann told me that technology that masters nature is not sustainable.
At the time, that sounded like the poetic caution of a man the media had nicknamed “the cyborg Luddite.” Today it reads like a weather report.
Steve is the person the IEEE named the father of wearable computing. He built the EyeTap decades before Google Glass, invented HDR imaging now sitting in the phone in your pocket, and was called the world’s first cyborg. So when he argues for using less, for choosing which technologies to embrace and which to walk away from, he is not speaking from fear of the machine. He is speaking from a deeper intimacy with it than almost anyone alive.
His core move was to refuse the framing everyone else accepted.
Not more technology. Not less technology. Appropriate technology. Balanced with nature instead of replacing it.
And here is the line that has aged into something close to prophecy: