Model deprecation can trigger costly AI migrations. Learn what enterprise buyers should negotiate on notice periods, support, and vendor contracts.
Get the latest international news and world events from around the world.
The helical model — our solar system is a vortex
How our solar system moves through space. This is a non-conventional view of our solar system that is different from the standard ‘flat’ diagrams. We travel, never return to the same spot again. Helical motion, how the planets move through space.
Respect my copyright and do not re-upload.
Like the music? https://djsadhu.bandcamp.com/
Please consider becoming a Patron to support my work: / djsadhu.
Thanks to the community for providing translations!
New version: Solar System 2.0: • Solar System 2.0 — the helical model.
Full story and philosophy: http://www.djsadhu.com/research/solar… 2 is here: • The helical model — our Galaxy is a vortex Information & research: http://www.djsadhu.com/the-helical-mo… Music: https://djsadhu.bandcamp.com/album/dj… French subtitles provided by the Resonance Project Greek subtitles provided by vasoula2908 Download the sound track: http://www.djsadhu.com/audio-video/vo… (FOR PERSONAL USE ONLY) No, this was not made with Universe Sandbox, but with 3DsMax. Yes, I messed up two orbits.
PART 2 is here: • The helical model — our Galaxy is a vortex.
Information & research: http://www.djsadhu.com/the-helical-mo…
Music: https://djsadhu.bandcamp.com/album/dj…
French subtitles provided by the Resonance Project.
Greek subtitles provided by vasoula2908
Download the sound track: http://www.djsadhu.com/audio-video/vo… (FOR PERSONAL USE ONLY)
No, this was not made with Universe Sandbox, but with 3DsMax.
Yes, I messed up two orbits.
The Extended Language Network: Language-Responsive Brain Areas Whose Contributions to Language Remain To Be Discovered
Despite ample evidence for functional specialization in the brains of humans (Kanwisher, 2010) and nonhuman animals (Tsao et al., 2006), some continue to argue against the idea of stable structure in the brain, emphasizing the distributed, dynamic, and interactive nature of cognitive processes, including language (Pessoa, 2022; Forkel and Hagoort, 2024; Drijvers et al., 2025). Deep engagement with this debate is beyond the scope of this article, but two points are worth clarifying. First, the fact that many areas—sometimes in distant parts of the brain—are engaged by language comprehension does not imply that the “entire brain” supports this function. Although the extended language network spans almost every major component of the brain, within each component, language regions occupy a small fraction of brain tissue. Second, linguistic inputs can unquestionably engage many brain regions beyond those that specifically support language processing: vivid descriptions of faces or scenes can engage category-selective visual areas, a story about a misunderstanding can engage the Theory of Mind network, and a horror story can engage the amygdala (see Casto, et al., 2025b for discussion). However, all these brain regions can also be engaged by nonlinguistic inputs. The ability of a brain region to be engaged by language does not make it a “language region” any more than its ability to be engaged by visual inputs makes it a “visual region.” Furthermore, the fact that the language network needs to interact with other brain areas does not undermine its functional distinctness from those areas and its special role in language processing. As long as different components within the language network interact more strongly with one another than with other networks—for which ample evidence exists (Blank et al., 2014; Braga et al., 2020; Du et al., 2024, 2025; Shain and Fedorenko, 2025)—the language network and other cognitive networks can be treated as meaningfully distinct objects of study (Simon, 1962).
For completeness and ease of comparison with past studies, we explored the possibility of using standard anatomical atlases to constrain individual fROIs (rather than the parcels derived from a group-level representation of brain activity; Fedorenko et al., 2010; Julian et al., 2012). Examining individual activation maps (or maps derived from functional connectivity patterns: Braga et al., 2020; Du et al., 2024, 2025; Shain and Fedorenko, 2025) against standardized brain parcellations reveals two issues. First, individual topographies often do not align with the boundaries of the atlas areas: a contiguous functional region may get broken up by a boundary or—for finer-grained atlases—may get assigned to different atlas areas across individuals because of interindividual topographic variability (see Fig. S5B for examples). For studies focusing on a particular functional network, we therefore recommend functional parcels over anatomical/multimodal atlases.
Sixteen AI-designed viruses offer a new route against drug-resistant bacteria
In a world first, scientists led by a team from Stanford University have created 16 viable viruses that do not exist in nature and were designed by AI. Their experiment, which is published in Science, could help in the fight against superbugs by allowing researchers to design customized viruses to kill drug-resistant bacteria. Thomas Inglesby and Moritz S. Hanke have published a Perspective piece on the work and its implications in the same edition of the journal.
Artificial intelligence is already helping to speed up drug discovery by analyzing massive genetic data sets, predicting protein shapes and identifying potential medicines. But in this research, the team wanted to see if AI could go a step further by creating an entire functioning genome based on a natural virus template.
Atomic view of Alzheimer’s disease peptide could inform new drugs
One of the hallmarks of Alzheimer’s disease is the accumulation of a peptide in the brain known as amyloid beta. A new study published in Nature Communications on July 22 has uncovered the atomic structure of the peptide in its harmful form.
Amyloid beta is a naturally occurring peptide that exists in healthy brains. But in Alzheimer’s disease, these peptides clump together abnormally and form large plaques. Scientists have known about the association between these plaques and Alzheimer’s disease for over a century, but whether this buildup is actually damaging the brain or simply a byproduct of the disease has been hotly debated.
There is also an intermediate state of amyloid beta that exists between the healthy peptides and the large plaques. Emerging evidence suggests that it is these intermediates—so-called “oligomeric” amyloid beta—that drive damage to the brain, but their structure has remained unknown. Now, a team of researchers at Yale School of Medicine has characterized this intermediate form for the first time.
Soluble signals released by neighboring cells direct how the human kidney is built
A human kidney is built once, before birth, and the rules guiding its construction have been largely inferred from animal models. Researchers at Penn Medicine have now read those rules directly in human tissue. They found that developing cells are steered by soluble signals released by their neighbors—and identified insulin-like growth factor 2 (IGF2) as a key signal that sustains the kidney’s stem-like cells.
Their study is published in Nature Genetics and was conducted by the Penn-CHOP Kidney Innovation Center, a research collaboration between the Perelman School of Medicine and Children’s Hospital of Philadelphia, working with bioengineers from Penn’s School of Engineering and Applied Science and the Institute for Regenerative Medicine.
How well a kidney is built before birth matters for the rest of a person’s life. Healthy people are born with anywhere from 200,000 to 2 million nephrons—the microscopic filtering units that clear waste from the blood—and no more are made after birth. A low nephron endowment carries a higher lifetime risk of high blood pressure and chronic kidney disease, and severe disruptions of kidney formation are the leading cause of chronic kidney disease in children.
Novel radioligand therapy proven superior for metastatic prostate cancer patients
A novel prostate cancer treatment—225 Ac-PSMA-617 radioligand therapy—has been shown to increase the progression free survival (PFS) and overall survival (OS) of metastatic castration-resistant prostate cancer (mCRPC) patients, according to research published by The Journal of Nuclear Medicine. Ninety-one percent of patients experienced a greater than 50% reduction of their initial PSA (prostate specific antigen) value after treatment with 225 Ac-PSMA-617, resulting in a PFS of 22 months and an OS not yet reached at the conclusion of the study.
While the five-year survival rate of localized prostate cancer is nearly 100%, for mCRPC patients it is only 30%. Clinical studies have demonstrated the efficacy and safety of several therapies, including 177 Lu-PSMA in the post-androgen deprivation therapy (ADT) setting in patients with mCRPC. Additional therapies, such as 225 Ac-PSMA-617, are often considered once the disease begins to progress again.
“Previous research has shown a remarkable therapeutic efficacy of 225 Ac-PSMA-617 in heavily pre-treated mCRPC patients, as demonstrated by the initial work from Kratochwil et al. from Germany,” said Mike Sathekge, professor and head of the Nuclear Medicine Department at the University of Pretoria and Steve Biko Academic Hospital in Pretoria, South Africa. “In this study we sought to compare 225 Ac-PSMA-617 to other common post-ADT treatments, such as chemotherapy, enzalutamide, and abiraterone acetate or docetaxel, administered in a comparable setting.”
Could a new approach to AI finally deliver artificial general intelligence?
AI chatbots can describe reality in words, but don’t truly understand cause and effect in the real world. Now, a fresh kind of machine intelligence that does just that is emerging
Is the Singularity a Religion? Why AI Needs a NeoRomanticism
Karl Marx knew the future. Not suspected it. Knew it. The revolution was inevitable, and history had a timetable.
Silicon Valley talks the same way now.
Technology has a direction, the exponential is its engine, and the singularity is its destination. You can slow the train, they say, but you cannot stop it.
I spent seventeen years and 300+ interviews taking that story seriously. I was a believer. In 2006 it blew my mind, and I built half a life on it.
Today I am the skeptic. And I have finally written down exactly why I turned.
Because when you strip the singularity down to its engine, it is not a forecast at all. It is a religion, and I can show you the receipts, using Ray Kurzweil’s own diagram to do it.
This is not an attack from the outside. It is a confession from someone who used to preach it.