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Proactive AI for Superintelligent Agents

What if AI stopped waiting for you to tell it what to do—and started working ahead?

We’re moving past the era of typing prompts into chatbots and waiting around. AI is undergoing a massive shift from passive assistant to proactive teammate. Here is what that looks like: 👇

From Waiting Around to Working Ahead: The Evolution of Proactive AI https://research.google/pubs/proactive-ai-for-superintelligent-agents/

For a long time, interacting with artificial intelligence has felt a bit like talking to an incredibly smart, but intensely passive, digital assistant. You type a prompt, it gives you an answer, and then it sits in absolute silence until you talk to it again. It has no memory of what you did five minutes ago unless you remind it, no clock ticking in its head, and no ambition to do anything on its own.

The cutting edge of AI research is shifting past this “reactive” model. Instead of waiting for human commands, the next generation of AI is designed to be proactive—acting more like a diligent human coworker who anticipates needs, monitors environments, and handles tasks behind the scenes.

Here is what that shift looks like:

1. The Three Tiers of AI Evolution.

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Your Eyes Could Reveal How Fast You’re Aging, Study of Nearly 30,000 Scans Suggests

We celebrate our birthdays on the same date each year, but alongside our chronological age – the number of years we’ve been alive – we also have a biological age that reflects how quickly our bodies are succumbing to wear and tear.

Working out someone’s biological age is more difficult than counting backward to a date of birth, though we are getting better at it.

Knowing this information can help in a variety of ways when it comes to health, including spotting serious problems earlier on.

Novel gene rejuvenation therapy preserves cell identity while reversing age

Every organ and tissue progressively loses function and integrity as it ages. In fact, researchers have identified “hallmarks of aging” that not only present specific processes impacted by age, but are also thought of as levers that, if successfully targeted, could help turn back the aging clock and result in tissue rejuvenation.

In 2006, Shinya Yamanaka’s Nobel prize-winning discovery that the over-expression of four genes, the “Yamanaka factors,” can reprogram most mature cell types back to an undifferentiated, pluripotent ground state was a milestone in aging research. Interestingly, when expressed only in short bursts, the Yamanaka factors can also partially reprogram old cells back to a more youthful state, reversing multiple hallmarks of aging while maintaining their specialized functions. This and other insights showed that aging does not need to be a one-way street and that aging cells retain a latent capacity for rejuvenation.

Unfortunately, the therapeutic use of Yamanaka factors is causing concern for some researchers because their overexpression also raises the risk of cancer formation. Researchers have therefore been hunting other factors for rejuvenating aging tissues in safer and more controllable ways. However, “in reprogramming, there is a fundamental tradeoff between rejuvenation and cell identity; achieving one without losing the other requires walking a fine line,” said Alex Plesa, Ph.D., the first co-author on a study presenting a new potential avenue to solving this challenge.

Building the tools behind genome editing breakthroughs

Genome editing is producing transformative therapies, yet there are still major challenges around delivery, access and understanding. In 2017, St. Jude Children’s Research Hospital in Memphis, Tennessee, established The Center for Advanced Genome Engineering (CAGE), to equip researchers with cutting-edge tools, advance the development of editing technologies, and democratize access to genome engineering expertise.

CAGE director Shondra Pruett-Miller discusses the centre’s role in advancing genome editing and bringing emerging therapies closer to patients, from groundbreaking treatments for sickle cell disease and paediatric cancers, to the responsibility of making safe and cost-effective treatments accessible to all.

God’s Number is 20

The Rubik’s Cube is one of the most iconic mathematical puzzles ever invented, created by Hungarian architect Ernő Rubik in 1974.

A standard 3×3×3 cube has-1 possible configurations — roughly 43 quintillion!

And here’s the remarkable mathematical result: every reachable configuration can be solved in 20 moves or fewer, provided a 180° face turn counts as one move.

Proven in 2010, this result is known as God’s Number.

A simple-looking puzzle. More than 43 quintillion configurations. And a mathematically proven upper limit on the number of moves needed to solve any of them.

Reference: [God’s Number Is 20 —]//www.cube20.org/)

Continue reading “God’s Number is 20” | >

New Electrical Test Can Help Identify Signs of Extraterrestrial Life in Space

If there is extraterrestrial life out there, it’s certainly done a great job of staying hidden so far (at least as far as the official scientific consensus goes).

International researchers led by a team from the University of Osaka in Japan have now developed a new electrical technique for spotting signs of life outside of Earth’s atmosphere – and it promises to be simpler than current approaches to alien detection.

The method focuses on amino acids, the building blocks of proteins, and details have been published in Nature Communications.

ACE Emerges as Potential Biomarker for Treatment-Resistant Schizophrenia

“This study provides some evidence that genetic alterations in the gene for ACE affect the level of the protein it makes, which in turn may influence the biology of psychosis, particularly in patients whose symptoms do not respond adequately to standard treatments,” says Kun Yang, Ph.D., assistant professor of psychiatry and behavioral sciences at Johns Hopkins Medicine.

Psychotic disorders, including schizophrenia, are currently diagnosed primarily through evaluation and assessment of symptoms and behaviors, including hallucinations, delusions and disordered thinking. Sawa says there are currently no objective biological blood or other tests that can determine which people with psychoses are likely to develop treatment resistance. Identifying biological differences associated with treatment resistance could help researchers develop more precise approaches to diagnosis and treatment, including the identification of new drug targets.

For the study, researchers analyzed data from 200 participants, including 78 healthy controls and 122 people with early-stage psychosis. Among the participants with psychosis, 31 had treatment-resistant psychosis and 91 did not. The researchers measured ACE protein levels in blood and cerebrospinal fluid, examined ACE enzymatic activity and analyzed genetic data related to schizophrenia risk. They found that ACE protein levels were significantly lower in both cerebrospinal fluid and blood among people with early-stage psychosis compared with healthy controls.

Volumetric discordance between ¹⁸F-FET-PET/MRI and MRI-based radiotherapy target volumes in high-grade glioma: a prospective pilot study (FETSMaRT)

High-grade gliomas carry a poor prognosis, and MRI-based radiotherapy (RT) planning may inadequately capture metabolically active tumor infiltration. ¹⁸F-fluoroethyl-tyrosine (FET) PET provides superior tumor delineation, yet prospective North American evidence supporting integration with RT planning remains limited.

FETSMaRT enrolled 30 patients with WHO grade 3 or 4 high-grade glioma receiving post-operative RT. FET-PET/MRI was acquired before RT with the radiation oncologist blinded to PET, enabling retrospective quantification of discordance between MRI-based and FET-PET/MRI-derived gross tumor (GTV), clinical target (CTV), and planning target (PTV) volumes. In the glioblastoma subgroup (n = 23), Kaplan–Meier and Cox analyses related GTV and CTV discordance to time to progression.

Median age was 60 years; 77% had glioblastoma and 60% MGMT promoter methylation. GTV discordance occurred in 17/30 patients (56.7%) and CTV discordance in 15/30 (50.0%). FET-PET/MRI-derived volumes significantly exceeded MRI-based volumes for GTV (43.6 vs. 38.6 cc; p 0.0001), CTV (119.2 vs. 110.8 cc; p = 0.0045), and PTV (171.1 vs. 159.6 cc; p = 0.0003). Larger GTV∆ and CTV∆ change values were associated with numerically shorter median time to progression, but neither association was statistically significant. Radiation treatment failures were predominantly central (60.0%).