New calculations suggest that the event horizons will eventually “decohere” quantum possibilities—even those that are far away.
AI is spreading beyond the tech giants into all aspects of life and work. One of its most impactful roles will be to help nuclear medicine save the lives of many thousands of cancer patients.
Microsoft is determined to thrust “AI” into all of its products at the moment and Microsoft Designer is no exception. This supposedly AI-driven service — currently in preview — is meant to create stunning social media posts, flyers etc. from your written prompts alone. Sadly, it’s about as intelligent as a Big Mac.
This is sort-of fine for a two-for one drinks offer:
This is, at best, conceptual:
Microsoft Designer has a very similar interface and set of features as Adobe Express, which I’ve used regularly to create social media posts, posters and other materials other the past couple of years.
A lightweight, customized mouse delivering maximum comfort and peak performance that fits snugly into your palm and your palm alone.
In this day and age, where we spend hours hunched over a computer, there is a case for everything being ergonomic.
Into this niche steps Formify, a team based out of Toronto with the belief that individualized design should be accessible to everyone.
No human intervention is required.
A research team led by Yan Zeng, a scientist at the Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab), has built a new material research laboratory where robots do the work and artificial intelligence (AI) can make routine decisions. This allows work to be conducted around the clock, thereby accelerating the pace of research.
Research facilities and instrumentation have come a long way over the years, but the nature of research remains the same. At the center of each experiment is a human doing the measurements, making sense of data, and deciding the next steps to be taken. At the A-Lab set up at Berkeley, the researchers led by Zeng want to break the current pace of research by using robotics and AI.
A recent study has suggested that transcriptomes may be the best method for classifying different types of brain disease.
OpenAI’s ChatGPT successor GPT-4 is showing signs of artificial general intelligence, claims a Microsoft study.
A central pillar of cosmology — the universe is the same everywhere and in all directions — is surviving a storm of possible evidence against it.
When we look at something, the different properties of the image are processed in different brain regions. But how does our brain make a coherent image out of such a fragmented representation? A new review by Pieter Roelfsema sheds light on two existing hypotheses in the field.
When we open our eyes, we immediately see what is there. The efficiency of our vision is a remarkable achievement of evolution. The introspective ease with which we perceive our visual surroundings masks the sophisticated machinery in our brain that supports visual perception. The image that we see is rapidly analyzed by a complex hierarchy of cortical and subcortical brain regions.
Neurons in low level brain regions extract basic features such as line orientation, depth and the color of local image elements. They send the information to several mid-level brain areas. Neurons in these areas code for other features, such as motion direction, color and shape fragments.
Do you remember learning to drive a car? You probably fumbled around for the controls, checked every mirror multiple times, made sure your foot was on the brake pedal, then ever-so-slowly rolled your car forward.
Fast forward to now and you’re probably driving places and thinking, “how did I even get here? I don’t remember the drive”. The task of driving, which used to take a lot of mental energy and concentration, has now become subconscious, automatic—habitual.
But how—and why—do you go from concentrating on a task to making it automatic?