A chatbot powered by reams of data from the internet has passed exams at a US law school after writing essays on topics ranging from constitutional law to taxation and torts.
ChatGPT from OpenAI, a US company that this week got a massive injection of cash from Microsoft, uses artificial intelligence (AI) to generate streams of text from simple prompts.
The results have been so good that educators have warned it could lead to widespread cheating and even signal the end of traditional classroom teaching methods.
Inspired by sea cucumbers, engineers have designed miniature robots that rapidly and reversibly shift between liquid and solid states. On top of being able to shape-shift, the robots are magnetic and can conduct electricity. The researchers put the robots through an obstacle course of mobility and shape-morphing tests in a study publishing January 25 in the journal Matter.
Where traditional robots are hard-bodied and stiff, “soft” robots have the opposite problem; they are flexible but weak, and their movements are difficult to control. “Giving robots the ability to switch between liquid and solid states endows them with more functionality,” says Chengfeng Pan (@ChengfengPan), an engineer at The Chinese University of Hong Kong who led the study.
The team created the new phase-shifting material—dubbed a “magnetoactive solid-liquid phase transitional machine”—by embedding magnetic particles in gallium, a metal with a very low melting point (29.8 °C).
Shutterstock is cooperating with OpenAI. Now the stock database is releasing a platform for the AI generation of images.
In October, Shutterstock and OpenAI partnered to integrate DALL-E 2 into the company’s creative tools. Today, Shutterstock released the AI image generation platform. It is available to all users and the images generated can be used under license.
According to Shutterstock, the tool was developed with an “ethical approach and uses a library of assets that authentically represent the world we live in. Shutterstock also recognizes the artists’ contributions to the generative content by paying royalties for the intellectual property used to develop the models and for the ongoing licensing of the content.”
A new technological development by Tel Aviv University has made it possible for a robot to smell using a biological sensor. The sensor sends electrical signals as a response to the presence of a nearby odor, which the robot can detect and interpret.
In this new study, the researchers successfully connected the biological sensor to an electronic system and, using a machine learning algorithm, were able to identify odors with a level of sensitivity 10,000 times higher than that of a commonly used electronic device. The researchers believe that in light of the success of their research, this technology may also be used in the future to identify explosives, drugs, diseases, and more.
The biological and technological breakthrough was led by doctoral student Neta Shvil of Tel Aviv University’s Sagol School of Neuroscience, Dr. Ben Maoz of the Fleischman Faculty of Engineering and the Sagol School of Neuroscience, and Prof. Yossi Yovel and Prof. Amir Ayali of the School of Zoology and the Sagol School of Neuroscience. The results of the study were published in Biosensors and Bioelectronics.
Machine learning can analyse how the signals from Wi-Fi transmitters are disrupted by human bodies to reveal what position people are sitting, standing or lying in.
Year 2012 The dwave quantum computers could essentially host the entire internet with low cost and even photonic room temperature quantum computers could eventually host the internet for even cheaper even down to pennies. Also if starling had casimir energy generators and casimir propulsion systems it could be even free for satellite operation costs with full automation we could essentially have low cost of pennies for the full system operation. At least some ideas for future operation costs.
This question was originally answered by Greg Price on Quora.
The public perceives OpenAI’s ChatGPT as revolutionary, but the same techniques are being used and the same kind of work is going on at many research labs, says the deep learning pioneer.
The concept of emergence is controversial to some — for example Eliezer Yudkowski, who favors reductionism, wrote a critique at Less Wrong (see link below). Do reductionists often dismiss emergence?
Talking points: EMERGENCE & REDUCTION, CONFUSION REGARDING EMERGENCE, LARGE SCALE NEUROSCIENCE PROJECTS, EMERGENCE AS A WAY OF EXPLAINING AWAY COMPLEXITY, IS CONSCIOUSNESS AN EMERGENT EFFECT? EMERGENCE & ARTIFICIAL INTELLIGENCE
The Attack of the Aliens from Vector Space: Steps Toward a Complex Systems Theory of Categorization and Similarity: http://www.goertzel.org/papers/catpap.html (Emergence & Compression) Extract: “The important concept of emergent pattern is defined: a pattern emerges between two entities if it is present in the combination of the two entities, but not in either of the entities separately. And the structural complexity of an entity is defined as the “total amount” of pattern in it. If the Metapattern is accepted, then these two concepts become essential to any analysis of biological reality.
We turn from these abstractions to a concrete biological example: the mammalian immune system. The theory of clonal selection states that immune systems evolve by natural selection; using the computer simulations of Alan Perelson, Rob deBoer and their colleagues as a guide, we inquire as to the exact nature of this evolution.
Researchers have developed a robot that brings speed, agility and reproducibility to laboratory-scale coin cell batteries.
Until now, laboratories studying battery technology have had to choose between the freedom to iterate and optimise battery chemistry by manually assembling each individual cell, and the reproducibility and speed of large-scale production. AutoBass (Automated battery assembly system), the first laboratory-scale coin cell assembly robot of its kind, is designed to bridge this gap.
Developed by a team from Helmholtz Institute Ulm and Karlsruhe Institute of Technology in Germany, AutoBass promises to improve characterisation of coin cell batteries and promote reproducibility by photographing each individual cell at key points in the assembly process. It produces batches of 64 cells a day.
