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Update from November 9, 2023:
During a Q&A session at OpenAI’s developer conference, Altman reiterated that GPT-5 is not yet concrete. OpenAI still has “a lot” of things to figure out before it can train a model it calls GPT-5, Altman said.
Continue reading “OpenAI’s Altman says today’s AI will be ‘quaint’ by next year, talks GPT-5” »
Boston Dynamics Starting from the technological building blocks of Atlas, Stretch has the mobility, power, and intelligence to automate warehousing’s toughest tasks. See how we went from initial idea to a product delivering value in the real world.
A combined team of biomedical researchers from Novartis Institutes for Biomedical Research and Microsoft Research AI4Science has made inroads into teaching AI systems how to find new medicines. In their study, reported in the journal Nature Communications, the group used feedback from chemists in the field to provide intuition guidelines for an AI model.
Finding new medicines is a notoriously difficult and laborious task. The process for finding new therapies typically involves experts in a variety of fields working on different parts of the problem. Doctors and other medical researchers, for example, must first uncover the roots of a given illness to find its cause. Chemists or other medical researchers must then find a chemical that might reverse the problem or stop it from happening in the first place.
Both parts of the process take time and effort. In this new project, the research team sought to determine whether AI applications might make the second part easier.
When you think of empty space, you almost certainly imagine a vacuum in which nothing interesting can ever happen. However, if we zoom in to tiny length scales where quantum effects start to become important, it turns out that what you thought was empty is actually filled at all times with a seething mass of electromagnetic activity, as virtual photons flicker in and out of existence. This unexpected phenomenon is known as the vacuum fluctuation field. However, because these fluctuations of light energy are so small and fleeting in time, it is difficult to find ways for matter to interact with them, especially within a single, integrated device.
In a study published this month in Nano Letters (“Electrical Detection of Ultrastrong Coherent Interaction between Terahertz Fields and Electrons Using Quantum Point Contacts”), researchers from the Institute of Industrial Science, The University of Tokyo succeeded in fabricating a single nanoscale hybrid system for doing exactly this. In their design, a quantum point contact connects a single on-chip split-ring resonator with a two-dimensional electron system.
Quantum Hall edge channels at the quantum point contact. (Image: University of Tokyo)
A method developed at the University of Duisburg-Essen makes it possible to read data from noisy signals. Theoretical physicists and their experimental colleagues have published their findings in the current issue of Physical Review Research. The method they describe could also be significant for quantum computers.
You know it from the car radio: The weaker the signal, the more disturbing the noise. This is even more true for laboratory measurements. Researchers from the Collaborative Research Center 1,242 and the Center for Nanointegration (CENIDE) at the University of Duisburg-Essen (UDE) have now described a method for extracting data from noise.
What is a bit in a conventional computer, i.e., state 1 (current on) or state 0 (current off), is taken over in the quantum computer by the quantum bits, or qubits for short. To do this, they need defined and distinguishable states, but they can overlap at the same time and therefore enable many times the computing power of a current computer. This means they could also be used where today’s supercomputers are overtaxed, for example in searching extremely large databases.
Sometimes, going ‘deeper’ doesn’t reveal the answers you seek. By viewing more Universe with better precision, ESA’s Euclid mission shines.
Summary: New study on mice decision-making reveals that choice is not a singular moment but a reflection of the brain’s preexisting state.
The research, using Buridan’s Assay, suggests that the mice’s brain constantly broadcasts its goal, even before options are available, with patterns of neuron activity predicting choice.
Hunger and thirst don’t directly drive behavior; instead, they modulate the brain’s goal-setting, with an element of randomness causing switches between needs, ensuring both are met over time.
The aviation industry could be on the cusp of a revolution, following recent tests of a new purely electric jet engine that packs the same punch as its traditional fossil fuel-burning cousins.
Canadian-based company Duxion Motors recently celebrated a significant milestone with the successful ground test of its eJet Motor – the world’s first rim-driven jet propulsion motor.
The eJet motor, an electric jet engine, represents a significant leap in electric aviation, utilizing permanent magnet technology to deliver unprecedented power-to-weight ratios within a compact design. Duxion’s approach could revolutionize the industry, offering scalable efficiency suited to larger aircraft, hybrid cooling for enhanced power density and reliability, and a flexible design that can be tailored to various airframes.
