Lifeboat Foundation

It was taken by the James Webb space telescope and is one of the clearest images ever produced of the planet.

AI & Machine Learning (ML) Course Online — BlackBelt Plus Program

Certified AI & ML BlackBelt Plus Program is the best data science course online to become a globally recognized data scientist. BlackBelt Plus Program includes 105+ detailed (1:1) mentorship sessions, 36 + assignments, 50+ projects, learning 17 Data Science tools including Python, Pytorch, Tableau, Scikit Learn, Power BI, Numpy, Spark, Dask, Feature Tools, Keras, Matplotlib, Rasa, Pandas, ML Box, Scikits-Image, Amazon SageMaker, Streamlit, AWS, Flask, and other technologies such as Computer Vision, Natural Language Processing, Machine Learning, Artificial Intelligence and Deep Learning.

By Planning in the Latent Space of a Learned World Model. The world model Director builds from pixels allows effective planning in a latent space. To anticipate future model states given future actions, the world model first maps pictures to model states. Director optimizes two policies based on the model states’ anticipated trajectories: Every predetermined number of steps, the management selects a new objective, and the employee learns to accomplish the goals using simple activities. The direction would have a difficult control challenge if they had to choose plans directly in the high-dimensional continuous representation space of the world model. To reduce the size of the discrete codes created by the model states, they instead learn a goal autoencoder. The goal autoencoder then transforms the discrete codes into model states and passes them as goals to the worker after the manager has chosen them.

Deep reinforcement learning advancements have accelerated the study of decision-making in artificial agents. Artificial agents may actively affect their environment by moving a robot arm based on camera inputs or clicking a button in a web browser, in contrast to generative ML models like GPT-3 and Imagen. Although artificial intelligence has the potential to aid humans more and more, existing approaches are limited by the necessity for precise feedback in the form of often given rewards to acquire effective techniques. For instance, even robust computers like AlphaGo are restricted to a certain number of moves before earning their next reward while having access to massive computing resources.

Contrarily, complex activities like preparing a meal necessitate decision-making at all levels, from menu planning to following directions to the shop to buy supplies to properly executing the fine motor skills required at each stage along the way based on high-dimensional sensory inputs. Artificial agents can complete tasks more independently with scarce incentives thanks to hierarchical reinforcement learning (HRL), which automatically breaks down complicated tasks into achievable subgoals. Research on HRL has, however, been difficult because there is no universal answer, and existing approaches rely on manually defined target spaces or subtasks.

A new miracle drug could increase the human lifespan by up to 200 years. Dr. Andrew Steele, a British computational biologist recently published a new book on the longevity of human life. In the book, the doctor argues that it is completely feasible for humans to live beyond our standard 100-year lifespan thanks to a new type of drug.

The Webb Telescope is a new era for astronomy and science. Scientists have no idea what they might discover with Webb. But with five observations taken in just one week of operation, they have already found several cosmic Easter eggs that defy expectations — including a few complete and utter unknowns.

Let’s take a tour through six of the most revelatory and intriguing Easter eggs hidden in the first five James Webb Space Telescope observations.

How many galaxies can you see in this image? Hey, you’re already looking at an exploding star — what more can you want? How about at some galaxies hiding in the chaos?

Circa 2021

NASA, in collaboration with other leading space agencies, aims to send its first human missions to Mars.

Mars is the second smallest planet in our solar system and the fourth planet from the sun. It is a dusty, cold, desert world with a very thin atmosphere. Iron oxide is prevalent in Mars’ surface resulting in its reddish color and its nickname “The Red Planet.” Mars’ name comes from the Roman god of war.

Circa 2020

Researchers say there are good reasons to be optimistic about the future of our oceans.

The bottomless bucket is Karl Marx’s utopian creed: “From each according to his ability, to each according to his needs.” In this idyllic world, everyone works for the good of society, with the fruits of their labor distributed freely — everyone taking what they need, and only what they need. We know how that worked out. When rewards are unrelated to effort, being a slacker is more appealing than being a worker. With more slackers than workers, not nearly enough is produced to satisfy everyone’s needs. A common joke in the Soviet Union was, “They pretend to pay us, and we pretend to work.”

In addition to helping those who in the great lottery of life have drawn blanks, governments should adopt myriad policies that expand the economic pie, including education, infrastructure, and the enforcement of laws and contracts. Public safety, national defense, dealing with externalities are also important. There are many legitimate government activities and there are inevitably tradeoffs. Governing a country is completely different from playing a simple, rigged distribution game.

I love computers. I use them every day — not just for word processing but for mathematical calculations, statistical analyses, and Monte Carlo simulations that would literally take me several lifetimes to do by hand. Computers have benefited and entertained all of us. However, AI is nowhere near ready to rule the world because computer algorithms do not have the intelligence, wisdom, or commonsense required to make rational decisions.

Wearable displacement sensors—which are attached to a human body, detect movements in real time and convert them into electrical signals—are currently being actively studied. However, research on tensile-capable displacement sensors has many limitations, such as low tensile properties and complex manufacturing processes.

If a displacement sensor that can be easily manufactured with high sensitivity and tensile properties is developed, it can be attached to a human body, allowing large movements of joints or fingers to be used in various applications such as AR and VR. A research team led by Sung-Hoon Ahn, mechanical engineering professor at Seoul National University, has developed a piezoelectric strain sensor with high sensitivity and high stretchability based on kirigami design cutting.

In this research, a stretchable piezoelectric displacement sensor was manufactured and its performance was evaluated by applying the kirigami structure to a film-type piezoelectric material. Various sensing characteristics were shown according to the kirigami pattern, and higher sensitivity and tensile properties were shown compared to existing technologies. Wireless haptic gloves using VR technology were produced using the developed sensor, and a piano could be played successfully using them.