YouTube has always presented itself as a vast library of human experience: tutorials, vlogs, explainers, music, children’s stories, news. But in 2025–2026, this library rapidly developed an extension that resembles a vending machine for text and images: press a button — get a video. This wave is increasingly being called AI slop, or “neuroslop”: content that looks like a video “about something,” but is in fact assembled from templates, repetitions, and crude but effective attention-holding tricks. It isn’t necessarily malicious. It’s simply abundant, cheap, and surprisingly sticky.
Author: Dzmitry Korsak
Dzmitry Korsak
Experienced journalist and editor with over 25 years in the field. His work focuses on medical technologies, social issues, and innovation. He values an evidence-based approach, thorough work with primary sources, and the ability to communicate complex topics in a clear and accessible way.
Canadian biotech company Providence Therapeutics has announced its support for the PaedNEO-VAX clinical study — a program testing personalized mRNA vaccines for children and teens with the most severe, treatment-resistant brain tumors. The project is set to launch in Australia in March 2026, and organizers say patient enrollment will run through a network of 7–8 pediatric hospitals and clinics across several states.
Pfizer has released mid-stage (Phase 2b) VESPER-3 results: its experimental drug PF’3944 (previously known as MET-097i and brought into Pfizer via the Metsera deal) helped people with obesity or overweight lose up to 12.3% of body weight (placebo-adjusted) by week 28. The headline feature is the dosing schedule: patients started with weekly injections during dose escalation, then switched to a once-monthly maintenance shot. Pfizer says there was no clear weight-loss “plateau” by week 28, and the trial continues through week 64.
Inflation, exchange rates, sanctions, market panics—we dream of “calculating” all this in the era of big data. But in the case of any major economic crisis, the chain of human reactions (how officials, businesses, and consumers behave) is so unique and sometimes illogical that it breaks any model. In this interview, we’ll break down what AI can already do in economics and where it still “stumbles” over real life.
AI in pharma and life sciences is an easy “sell,” yet delivering real value remains a formidable challenge. Progress is most often hampered by closed data, weak data sharing, and inflated expectations. In this interview with Marcin Wawryszczuk (PhD, MBA) — Head of AI at Andersen and an AI researcher — we discuss how data platforms are becoming the bottleneck, whether it is possible to distinguish a viable project from a mere demo, and why, in production, resilience to drift and explainability of results outweigh impressive metrics.
The genre of the LLM interview emerged the moment the first model was released to the public. Since then, “artificial intelligence” has been asked to prophesy the future, debate the philosophical nature of being, or simply engage in heart-to-hearts. This creates the illusion of conversation with a sentient being — a phenomenon that simultaneously frightens, astonishes, and inspires awe. Yet, we have never encountered an interview where the AI is addressed honestly, with its mask of humanity stripped away.
Recently, an article titled “How the AI ‘bubble’ compares to history” was published in the Financial Times; its author, Jonathan Vincent, reminds us of economic crises…
Artificial intelligence has rapidly become a working tool in companies, government administration, education, and everyday services within just a few years. As AI becomes more…
AI remote patient monitoring seeks to address a longstanding and complex challenge in medicine: translating chaotic streams of health data into a comprehensible and standardized format. This capability empowers medical professionals to prioritize effectively and respond to challenges in a timely manner. The primary “superpower” of AI is transforming a thousand signals, ex. heart rate spikes, into a single, actionable notification: “Pay attention, there is a problem!”
Today, AI is simultaneously a religion and an irritant: some hope that humanity has gotten its hands on a tool for explosive development; for others, the very disclaimer “made by artificial intelligence” already causes irritation. People worry that LLM will take jobs away from millions and, in the longer run, will become a superintelligence that will enslave humanity. And more and more often we hear that multibillion-dollar infusions into the industry are inflating a bubble that will soon burst.