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The AIs of 2026 Will be Wild!

What if the AIs of 2026 don’t just assist humans—but outthink, outcreate, and outpace them? This video breaks down why experts are calling the next wave of artificial intelligence “wild,” unpredictable, and unlike anything we’ve seen before.

From autonomous AI agents that can run businesses to models that learn continuously without retraining, 2026 is shaping up to be the year AI crosses invisible psychological and technological lines. We explore the breakthroughs most people aren’t paying attention to—and why they matter more than flashy demos.

You’ll discover how AI reasoning, memory, creativity, and decision-making are evolving fast, and why this shift could quietly redefine work, power, and human relevance. These aren’t sci-fi concepts anymore—they’re already being tested behind closed doors.

This video also reveals the hidden risks, ethical tensions, and control problems emerging as AI systems become less tool-like and more independent. By the end, you’ll understand why 2026 may be remembered as the year AI stopped feeling artificial.

What will AI be capable of in 2026? Why are experts worried about next-generation AI? How will AI change jobs and creativity? Are autonomous AI agents dangerous? Is AI evolving faster than humans can adapt?

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The Fine-Tuning Argument is Terrible — Sean Carroll

Watch the full episode on Substack: https://open.substack.com/pub/alexoconnor/p/sean-carroll-wha…nt=overlay.

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Sean Carroll is a theoretical physicist and professor of natural philosophy at Johns Hopkins University.

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Experimental Therapy Targets Cancer’s Bodyguards, Turning Foe to Friend to Eliminate Tumors

Researchers at Mount Sinai have developed a novel immunotherapy strategy that targets the tumor microenvironment (TME) to overcome immune suppression in metastatic cancers. Addressing the protective role of tumor-associated macrophages (TAMs), which often shield malignancies and facilitate growth, the team engineered chimeric antigen receptor (CAR) T-cells to specifically recognize and target these stromal cells. Functioning as a “Trojan horse,” these modified T-cells not only engage macrophages but also release immune-activating molecules that reprogram the TME, converting immunosuppressive macrophages into anti-tumor effectors. In preclinical models of metastatic lung and ovarian cancer, this approach yielded significant therapeutic efficacy, resulting in extended survival and the complete eradication of tumors in some subjects. By transforming the tumor’s protective infrastructure into a mechanism of its destruction, this strategy offers a promising, potentially pan-cancer modality for treating solid tumors resistant to conventional immunotherapies.

Scientists at the Icahn School of Medicine at Mount Sinai have developed an experimental immunotherapy that takes an unconventional approach to metastatic cancer: instead of going after cancer cells directly, it targets the cells that protect them.

T he study, published in the January 22 online issue of Cancer Cell, a Cell Press Journal [DOI 10.1016/j.ccell.2025.12.021], was conducted in aggressive preclinical models of metastatic ovarian and lung cancer. It points to a new strategy for treating advanced-stage solid tumors.

In a strategy modeled after the famed Trojan horse, the treatment enters the tumors by targeting cells called macrophages that guard the cancer cells, disarms these protectors, and opens up the tumor’s gates for the immune system to enter and wipe out the cancer cells.

New algae system cuts building’s energy cost by absorbing indoor heat

Microalgae‑based architecture could soon come to Western Australia.

A team from Murdoch University is working on a project to integrate microalgae-filled photobioreactors into everyday structures like houses, apartments, mining dongas, and urban designs.

If adapted, it could improve energy efficiency and environmental health.

Shapeshifting materials could power next generation of soft robots

McGill University engineers have developed new ultra-thin materials that can be programmed to move, fold and reshape themselves, much like animated origami. They open the door to softer, safer and more adaptable robots that could be used in medical tools that gently move inside the body, wearable devices that change shape on the skin or smart packaging that reacts to its environment.

The research, jointly led by the laboratories of Hamid Akbarzadeh in the Department of Bioresource Engineering and Marta Cerruti in the Department of Mining and Material Engineering, shows how simple, paper-like sheets made from folded graphene oxide (GO) can be turned into tiny devices that walk, twist, flip and sense their own motion. Two related studies demonstrate how these materials can be made at scale, programmed to change shape and controlled either by humidity or magnetic fields.

The studies are published in Materials Horizons and Advanced Science.

Abstract: Caught in the crossfire: cardiac complications of cancer therapy

In this Review, Emilio Hirsch discuss the mechanisms and therapeutic strategies for cardiotoxicity caused by chemotherapy, targeted agents, and immune modulators.

1Department of Molecular Biotechnology and Health Sciences, Molecular Biotechnology Center “Guido Tarone”, University of Torino, Torino, Italy.

2University of Arizona College of Medicine, Tucson, Arizona, USA.

Address correspondence to: Emilio Hirsch or Alessandra Ghigo, Via Nizza 52, 10126, Turin, Italy. Phone: 39.011.670.6425; Email: [email protected] (EH). Phone: 39.011.670.6335; Email: [email protected] (AG). Or to: Hossein Ardehali, 3,838 North Campbell Avenue, Building 2, Tucson, Arizona 85,719, USA. Phone: 520.626.6453; Email: [email protected].

Computational model discovers new types of neurons hidden in decade-old dataset

“We saw some peculiar brain activity in the model,” Miller says. “There was a group of neurons that predicted the wrong answer, yet they kept getting stronger as the model learned. So we went back to the original macaque data, and the same signal was there, hiding in plain sight. It wasn’t a quirk of the model — the monkeys’ brains were doing it too. Even as their performance improved, both the real and simulated brains maintained a reserve of neurons that continued to predict the incorrect answer.”

The new work, published in Nature Communications, puts a name to these overlooked signals: incongruent neurons, or ICNs, and explores theories as to why a primate brain might want to keep alternate options in mind, even if they’re not the right ones at the moment.

Beyond identifying a previously unrecognized class of neurons involved in learning, the study shows that the model behaves like a brain and generates realistic brain activity, even without being trained on neural data. The findings could have major implications for testing potential neurological drugs and for using computational models to investigate how cognition emerges and functions.

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