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Beyond Agentic AI: The Emergence Of Cognitive AI Ecosystems
In the next decade, AI will likely undergo more significant changes than only becoming more independent; it will also grow more cognitive. AI systems will act as interconnected ecosystems that are capable of contextual awareness, cooperative reasoning, ongoing learning, and adaptive decision-making in almost every facet of society, rather than isolated applications.
Large language models of today are remarkable due to their ability to produce and anticipate information. Persistent memory, multimodal perception, long-term planning, causal reasoning, and self-directed learning within strictly regulated bounds will probably be characteristics of the AI of 2036. Similar to biological neural networks, millions of specialized AI agents will work together to create dynamic intelligence fabrics that continuously optimize national defense, manufacturing, transportation, financial markets, healthcare delivery, and energy grids.
The line between workforce and software will become increasingly hazy. Hundreds of thousands of AI agents working continuously alongside human employees may be employed by organizations as digital workforces. A customized constellation of AI advisers, researchers, legal assistants, financial analysts, engineers, and cybersecurity specialists working around the clock could be present for every knowledge worker. This shift signifies the emergence of an entirely new digital labor force in addition to automation.
Scientists Used Post-Mortem Brain Tissue to Control a Robot
Further reading.
Thumbnail image credit: Paper cited in video.
Unsupervised sensory-motor associative learning by human brain explant in-a-dish enables movement imitation by robot.
https://www.researchsquare.com/articl…
The lab.
Not alive. but not dea: disembodied human brains used for drug testing.
https://www.science.org/content/artic…
#science #brain #technology #news #explained
Imagination is not escapism, it brings us closer to reality
Einstein called imagination “more important than knowledge,” yet we increasingly treat it as a childhood pastime we outgrow. Philosopher of mind Amy Kind argues that it’s something far more practical: the skill we draw on to make our hardest decisions, read the people around us, and work out who we want to become. Like any skill, it weakens without use — and we’re using it less. Reading for pleasure has nearly halved in two decades, fewer parents play with their children each day, and we increasingly hand our creative work to machines. If we don’t make time to exercise it, we’ll lose the capacity to conceive of things being other than they are, and risk being trapped in the present, unable to imagine a different future, let alone build one.
In recent years, amidst the hustle and bustle of contemporary life, people are devoting considerably less time to imaginative activities. Significantly fewer people are reading for pleasure today compared to 20 years ago, and in just the last decade, significantly fewer parents are making time to play with their children on a daily basis than used to be the case.
This neglect of imagination has been accelerated by the increasing reliance on generative AI tools in both personal contexts and professional contexts. In one recent survey, more than 50% of adults reported interacting with AI tool at least several times a week for personal purposes, often for learning, entertainment, or supporting their children’s education. In another study on business uses of AI, more than half of firms surveyed reported using AI in the creation of new products and services and, more generally, in their at innovation projects. With each passing day, we seem to be increasingly more willing—and perhaps even eager—to outsource our creative and imaginative efforts to machines.
Researchers Discovered Your Brain Really Can Sync Up With Someone Else’s. Here’s How It Works
If you’ve ever been riding a wave of creativity that feels like your brain and someone else’s have been Bluetooth-synced and are now finishing each other’s sentences, both instinctively knowing where the song/screenplay/woodworking project or whatever you’re building should go, then you’ve experienced what scientists call brain synchrony.
As described by a team of researchers publishing their findings as a press release on Eureka Alert, originally published in Trends in Cognitive Sciences, it’s a real phenomenon that’s been observed in laboratories and real-world settings. Now, researchers say it isn’t just measurable, but it can actually be strengthened.
Researchers reviewed a decade of studies involving thousands of people, from regular everyday students to professional artists. Using portable EEG headsets, researchers found that when people are genuinely engaged with one another, their brainwave activity begins to align. Even more interesting, when participants received real-time feedback showing how synchronized they were, that alignment often became even stronger.
Hybrid AI model cuts financial forecasting error across stocks and crypto
A hybrid artificial intelligence model that combines two well-established deep learning techniques has improved the accuracy of financial market forecasts across major stock indices and so-called cryptocurrency, according to work in the International Journal of Reasoning-based Intelligent Systems.
The researchers designed the model, CLSTM-HN, to address a long-standing problem in financial forecasting: balancing the detection of short-term market movements with the recognition of longer-term trends. The researchers tested the system on publicly available data and achieved a forecasting error 15% to 20% lower than that of conventional long-short-term memory (LSTM) models. They also saw an improvement in the accuracy of predicting whether prices would rise or fall by 10% to 14%.
Financial markets are difficult to predict because prices are volatile, noisy and subject to sudden structural shifts. Traditional statistical approaches often rely on assumptions about market behavior that break down during periods of instability.
New, improved method to find and isolate the strongest cancer-fighting immune cells
A new platform developed by researchers at the University of Texas MD Anderson Cancer Center quickly finds and isolates rare, tumor-reactive immune cells that are especially good at recognizing and attacking cancer cells, even without knowing which tumor targets are recognized by the immune cells. This approach addresses a major bottleneck in immunotherapy development and could accelerate the creation of personalized treatments.
The platform, called ATTACH (Assessment of T cells Tethered to Antigen Class I Histocompatibility), identifies the strongest interactions between T cells and cancer-specific proteins, isolating only the most effective, tumor-reactive T cells for further study and therapeutic use.
The study, published today in the Journal for ImmunoTherapy of Cancer, was led by Alexandre Reuben, Ph.D., assistant professor of Thoracic/Head and Neck Medical Oncology, and Amanda Montoya, senior research assistant in the Reuben lab.