Wyoming is the least populous U.S. state, with around 590,000 people, and currently exports two-thirds of its generated energy.
Category: robotics/AI – Page 173
Amazon has invested in «Netflix with AI» — streaming, which allows viewers to generate their own series
Fable, a San Francisco-based startup, has created a new streaming service called Showrunner, which is touted as «Netflix with AI». Its main feature is that viewers can create scenes or entire episodes for TV shows from scratch — using simple text prompts for artificial intelligence. The idea may seem dubious, but a tech giant like Amazon believed in the project’s potential and invested an undisclosed amount in Fable and the development of streaming.
Showrunner currently operates in closed alpha version with 10,000 users (another 100,000 are on the waiting list) and offers two original «shows» — storyworlds with characters that users can direct into different narrative arcs.
The first, titled «Exit Valley», is described as a «Family Guy-style television comedy set in Sim-Francisco, poking fun at artificial intelligence leaders Sam Altman, Elon Musk, and others». Second, «Everything Is Fine», in which a husband and wife have a big fight while going to Ikea, and then are transported to a world where they are actually divorced and have to find each other.
Microsoft Releases List of Jobs Most and Least Likely to Be Replaced by AI
Researchers at Microsoft tried to determine which precise jobs are most and least likely to be replaced by generative AI — and the results are bad news for anyone currently enjoying the perks of a cushy desk job.
As detailed in a yet-to-be-peer-reviewed paper, the Microsoft team analyzed a “dataset of 200k anonymized and privacy-scrubbed conversations between users and Microsoft Bing Copilot,” and found that the occupations most likely to be made obsolete by the tech involve “providing information and assistance, writing, teaching, and advising.”
The team used the data to come up with an “AI applicability score,” an effort to quantify just how vulnerable each given occupation is, taking into consideration how often AI is already being used there and how successful those efforts have been.
Memories Go Where?
How does your brain decide where to store a brand-new piece of information—like a new face, word, or concept? In this video, we’ll explore a working neural circuit that demonstrates how cortical columns could be allocated dynamically and efficiently—using real spikes, real timing, and biologically realistic learning rules. Instead of vague theories or abstract algorithms, we’ll show a testable mechanism that selects the first available cortical column in just 5 milliseconds, highlighting the incredible speed and parallelism of the brain. This is a crucial first step in building intelligence from the ground up—one circuit at a time.
Useful links:
The Future AI Society: https://futureaisociety.org.
The Brain Simulator III (UKS) project: https://github.com/FutureAIGuru/BrainSimIII
The Brain Simulator II (Neural Simulator) project: https://github.com/FutureAIGuru/BrainSimII
Overview Video: https://youtu.be/W2uauk2bFjs.
More Details Video: https://youtu.be/6po1rMFZkik.
How the UKS Learns Video: https://youtu.be/Rv0lrem3lVs.
Synthetic data boosts gait analysis: AI trained on simulations rivals existing models
Gait assessment is critical for diagnosing and monitoring neurological disorders, yet current clinical standards remain largely subjective and qualitative. Recent advances in AI have enabled more quantitative and accessible gait analysis using widely available sensors such as smartphone cameras.
However, most existing AI models are designed for specific patient populations and sensor configurations, primarily due to the scarcity of diverse clinical datasets—a constraint often driven by privacy concerns. As a result, these models tend to underperform when applied to populations or settings not well represented in the training data, limiting their broader clinical applicability.
In a study published in Nature Communications, researchers from IBM Research, the Cleveland Clinic, and the University of Tsukuba propose a novel framework to overcome this limitation. Their approach involves generating synthetic gait data using generative AI trained on physics-based musculoskeletal simulations.
State of the art in fault-tolerant quantum computing
This report reviews the construction and potential use of FTQC (Fault Tolerant Quantum Computing) computers to reliably perform complex calculations by overcoming the problems posed by the errors and noise inherent in quantum systems.
After recalling the reality of the quantum advantage and its needs, the report describes the use of error-correcting codes in the design of FTQCi computers. It then reports on the progress of the five most advanced physical technologies in the world for building such computers and the obstacles they will have to face in order to achieve the transition to scale necessary for the execution of useful applications. Finally, it discusses the technical and economic environment for quantum computers, how their performance can be compared and evaluated, and their future coexistence with other computing technologies (3D silicon, AI) or with supercomputers.
AI agent autonomously solves complex cybersecurity challenges using text-based tools
Artificial intelligence agents—AI systems that can work independently toward specific goals without constant human guidance—have demonstrated strong capabilities in software development and web navigation. Their effectiveness in cybersecurity has remained limited, however.
That may soon change, thanks to a research team from NYU Tandon School of Engineering, NYU Abu Dhabi and other universities that developed an AI agent capable of autonomously solving complex cybersecurity challenges.
The system, called EnIGMA, was presented this month at the International Conference on Machine Learning (ICML) 2025 in Vancouver, Canada.