Lifeboat Foundation

An “out there” theory inspired the development of the Dark Matter Radio, a device that could explain the mysterious matter that makes up 85 percent of the mass of our universe.

Scientists have used advanced imaging techniques to identify brain activity and regions linked to cognitive motor dissociation (CMD), or ‘hidden consciousness’. CMD is a state in which a person appears comatose and unresponsive while inwardly showing signs of conscious brain activity.

The findings, reported by a team from Columbia University in the US, may help doctors more easily identify CMD in the future, and better tailor treatments for people who can understand what’s being said to them but can’t respond to it.

CMD happens in around 15–25 percent of people with brain injuries from head trauma, brain hemorrhage, or cardiac arrest. In these patients, something breaks between the instructions coming from the brain and the muscles needed to carry those instructions out.

The largest ever study of the genetics of the brain – encompassing some 36,000 brain scans – has identified more than 4,000 genetic variants linked to brain structure. The results of the study, led by researchers at the University of Cambridge, are published in Nature Genetics today.

So, the bad AI has been arriving. On purpose. It reminds me of when hackers once or a few times checked traffic lights to both green and caused accidents resulting in human harm. That’s sad that such great tools are misused.

ChatGPT has become popular, influencing how people work and what they may find online. Many people, even those who haven’t tried it, are intrigued by the potential of AI chatbots. The prevalence of generative AI models has altered the nature of potential dangers. Evidence of FraudGPT’s emergence can now be seen in recent threads on the Dark Web Forum. Cybercriminals have investigated ways to profit from this trend.

The researchers at Netenrich have uncovered a promising new artificial intelligence tool called “FraudGPT.” This AI bot was built specifically for malicious activities, including sending spear phishing emails, developing cracking tools, doing carding, etc. The product may be purchased on numerous Dark Web marketplaces and the Telegram app.

Continue reading “Meet FraudGPT: The Dark Side Twin of ChatGPT” »

Don’t know what to cook today? Ask an AI chef now.

This post is also available in: עברית (Hebrew)

Two autonomous “robotaxi” companies in San Francisco received the green light to start increasing their operations in the city, after previously facing limits on when or where they could charge for rides.

The promise of driverless car services transforming transport has been very slow to develop since they first came into the public eye over a decade ago, having been faced with technology glitches, safety fears, and high-profile accidents involving vehicles.

Recycling options and technology are slowly emerging as millions of tons of solar panels reach their end of life, threatening to fill landfills.

Artificial Intelligence will gift us with more benefits and advantages than any other invention or discovery in history. On that, everyone agrees.

But it will also require more skills and mastery than anything else. It will place that onus not just on each of us, but also on those in leadership positions who will have to see to their individual transformations and to the transformations of their organizations.

In my previous post (Forbes.com — 8/10/23) I discussed 11 skills necessary for the AI user. In consultation with six respected colleagues, we compiled a sweeping overview of the skill set we’ll all to be effective AI users. No tech involved in that list, just user skills.

A fundamental goal in the field of sensory neuroscience is to understand the complex mechanisms that underlie the neural code responsible for processing natural visual scenes. In neuroscience, a fundamental yet unresolved question is how neural circuits are developed in natural settings by the interaction of multiple cell types. The eyes have evolved to communicate information about natural visual scenes using a wide range of interneurons, which is crucial for transmitting visual information to the brain.

Retina’s functioning is largely based on research into how it reacts to artificial stimuli like flashing lights and noise. These might not accurately represent how the retina interprets actual visual data. The complexity of how these more than 50 different types of interneurons contribute to retinal processing has yet to be fully understood despite the fact that different computations have been detected using such methods. In a recent research paper, a group of researchers has made a significant advancement by showing that a three-layer network model is capable of predicting retinal responses to natural sceneries with amazing precision, almost exceeding the bounds of experimental data. The researchers wanted to understand how the brain processes natural visual scenes, so they focussed on the retina, which is part of the eye that sends signals to the brain.

This model’s interpretability, i.e., the ability to comprehend and examine its internal organization, is one of its key characteristics. There is a strong correlation between the responses of interneurons that were directly included in the model and those that were separately recorded. This suggests that the model captures significant aspects of the retinal interneuron activity. It successfully reproduces a wide range of motion analysis, adaptability, and predictive coding phenomena when they are just trained on natural scenes. On the other hand, models trained on white noise cannot reproduce the same set of events, supporting the idea that examining natural sceneries is necessary to comprehend natural visual processing.