Lifeboat Foundation

Industrial condition monitoring sensors collect data that facilitates intelligent decisions via machine learning or AI to predict machine failures and increase productivity.

So why not break the AI apart?

In a new study published in PNAS, the team took a page from cognitive neuroscience and built a modular AI agent.

The idea is seemingly simple. Rather than a monolithic AI—a single network that encompasses the entire “self”—the team constructed a modular agent, each part with its own “motivation” and goals but commanding a single “body.” Like a democratic society, the AI system argues within itself to decide on the best response, where the action most likely to yield the largest winning outcome guides its next step.

Other commentators, though, were not convinced. Noam Chomsky, a professor of linguistics, dismissed ChatGPT as “hi-tech plagiarism”.

For years, I was relaxed about the prospect of AI’s impact on human existence and our environment. That’s because I always thought of it as a guide or adviser to humans. But the prospect of AIs taking decisions – exerting executive control – is another matter. And it’s one that is now being seriously entertained.

One of the key reasons we shouldn’t let AI have executive power is that it entirely lacks emotion, which is crucial for decision-making. Without emotion, empathy and a moral compass, you have created the perfect psychopath. The resulting system may be highly intelligent, but it will lack the human emotional core that enables it to measure the potentially devastating emotional consequences of an otherwise rational decision.

Technological advancements like autonomous driving and computer vision are driving a surge in demand for computational power. Optical computing, with its high throughput, energy efficiency, and low latency, has garnered considerable attention from academia and industry. However, current optical computing chips face limitations in power consumption and size, which hinders the scalability of optical computing networks.

Thanks to the rise of nonvolatile integrated photonics, optical computing devices can achieve in-memory computing while operating with zero static power consumption. Phase-change materials (PCMs) have emerged as promising candidates for achieving photonic memory and nonvolatile neuromorphic photonic chips. PCMs offer high refractive index contrast between different states and reversible transitions, making them ideal for large-scale nonvolatile optical computing chips.

While the promise of nonvolatile integrated optical computing chips is tantalizing, it comes with its share of challenges. The need for frequent and rapid switching, essential for online training, is a hurdle that researchers are determined to overcome. Forging a path towards quick and efficient training is a vital step on the journey to unleash the full potential of photonic computing chips.

Two days after AIM said that it’s time for OpenAI to launch GPT-5, the company filed a trademark application for “GPT-5” with the United States Patent and Trademark Office (USPTO) on July 18. This move suggests the potential development of a new version of their language model. The news was shared by trademark attorney Josh Gerben on Twitter on July 31.

The trademark application says that GPT-5 is related to computer software for generating human speech and text, as well as for natural language processing, generation, understanding, and analysis. It is speculated to be the next powerful version of OpenAI’s generative chatbot, following the previous release of GPT-4 in March.

Despite the trademark application, there is no confirmation of immediate development for GPT-5. While it is likely that OpenAI has plans for an advanced language model in the future, the primary purpose of the trademark filing might be to secure the name “GPT-5” and prevent unauthorised use by others.

Micron just unveiled specs for its new high-bandwidth memory for AI, which appears to one-up the fastest HBM on the market.

As ive said before we should at least attempt to reverse engineer brains of: mice, lab rats, crows, octupi, pigs, chimps, and end on the… human brain. it would be messy and expensive, and animal activsts would be runnin around it.

Lurking just below the surface of these concerns is the question of machine consciousness. Even if there is “nobody home” inside today’s AIs, some researchers wonder if they may one day exhibit a glimmer of consciousness—or more. If that happens, it will raise a slew of moral and ethical concerns, says Jonathan Birch, a professor of philosophy at the London School of Economics and Political Science.

As AI technology leaps forward, ethical questions sparked by human-AI interactions have taken on new urgency. “We don’t know whether to bring them into our moral circle, or exclude them,” said Birch. “We don’t know what the consequences will be. And I take that seriously as a genuine risk that we should start talking about. Not really because I think ChatGPT is in that category, but because I don’t know what’s going to happen in the next 10 or 20 years.”

Continue reading “How Studying Animal Sentience Could Help Solve the Ethical Puzzle of Sentient AI” »

A Long Island man who was paralyzed in a diving accident has regained motion and feeling in his body after a breakthrough, machine learning-based surgery that successfully “connected a computer to his brain” through microelectrode implants.

Now, the successful case of Massapequa’s Keith Thomas, 45, is being heralded throughout the medical world as a “pioneer” case for AI-infused surgeries to treat or cure impassible illnesses like blindness, deafness, ALS, seizures, cerebral palsy and Parkinson’s, experts at Manhasset’s Feinstein Institutes for Medical Research boast.

“This is the first time a paralyzed person is regaining movement and sensation by having their brain, body and spinal cord electronically linked together,” Chad Bouton, a professor at Feinstein’s Institute of Bioelectronic Medicine, told The Post.

There’s a lot of talk about the potential for artificial intelligence in medicine, but few researchers have shown through well-designed clinical trials that it could be a boon for doctors, health care providers and patients.

Now, researchers at Stanford Medicine have conducted one such trial; they tested an artificial intelligence algorithm used to evaluate heart function. The algorithm, they found, improves evaluations of heart function from echocardiograms — movies of the beating heart, filmed with ultrasound waves, that show how efficiently it pumps blood.

“This blinded, randomized clinical trial is, to our knowledge, one of the first to evaluate the performance of an artificial intelligence algorithm in medicine. We showed that AI can help improve accuracy and speed of echocardiogram readings,” said James Zou, PhD, assistant professor of biomedical data science and co-senior author on the study. “This is important because heart disease is the leading cause of death in the world. There are over 10 million echocardiograms done each year in the U.S., and AI has the potential to add precision to how they are interpreted.”