AI technology is spreading quickly throughout many different industries, and its integration depends on users’ trust and safety concerns. This matter becomes complicated when the algorithms powering AI-based tools are vulnerable to cyberattacks that could have detrimental results.
Dr. David P. Woodruff from Carnegie Mellon University and Dr. Samson Zhou from Texas A&M University are working to strengthen the algorithms used by big data AI models against attacks.
Much like the invigorating passage of a strong cold front, major changes are afoot in the weather forecasting community. And the end game is nothing short of revolutionary: an entirely new way to forecast weather based on artificial intelligence that can run on a desktop computer.
Today’s artificial intelligence systems require one resource more than any other to operate—data. For example, large language models such as ChatGPT voraciously consume data to improve answers to queries. The more and higher quality data, the better their training, and the sharper the results.
Scientists at La Jolla Institute for Immunology (LJI) have developed a new computational method for linking molecular marks on our DNA to gene activity. Their work may help researchers connect genes to the molecular “switches” that turn them on or off.
The Dark Energy Spectroscopic Instrument (DESI) is a robotic instrument and spectrograph mounted on the Mayall Telescope in Kitt Peak, Arizona. The DESI collaboration aims primarily to understand the elusive Dark Energy. This is an energy of unknown source causing the Universe to accelerate in its expansion; this accelerating expansion is not predicted to occur for a universe that is filled with just ordinary matter and radiation (some more detail can be seen in this Astrobite). Since we still know so little about Dark Energy, a large galaxy survey can allow us to explore the history of the expansion of the Universe in more detail. The DESI instrument has 5,000 individual optical fibres controlled by robots that allow it to measure individual spectra of up to 5,000 galaxies in just a mere 20 minutes! Due to this design, and an observing program that optimises targets in the sky based on observing conditions, the survey will measure spectra of up to 35 million galaxies over 5 years. This will allow DESI to perform precise cosmological measurements, as a great volume of space and number of galaxies can be probed, and noise in the data products is reduced. This bite looks at the cosmology results from the collaboration’s analysis of the recently released Year 1 Data (YR1), in particular, via a signal that can be seen in the data known as Baryon Acoustic Oscillations.
DESI tracers
For the cosmological results in this work DESI uses information from various different ‘tracers’ – galaxies that trace the Large Scale Structure of the Universe. These consist of low redshiftbright galaxies (BGS) that are measured when the moon lights the sky (and thus dimmer galaxies are less visible), and higher redshift galaxies measured during the dark time. The dimmer objects include luminous red galaxies (LRGs) which are elliptical galaxies that are extremely bright, emission line galaxies (ELGs) which are younger galaxies with emission line features in their spectra, and quasars (QSOs) which are very distant and bright galaxies that contain active galactic nuclei. The sample used also includes QSOs detected using Lyman-alpha forest measurements, or a method of tracing matter that utilises a series of absorption lines detected due to light from distant QSOs passing through neutral hydrogen in the space between us and the distant galaxies.
A potentially controversial new study suggests that the universe’s expansion may be a mirage.
This new perspective on the universe may also provide answers to the mysteries surrounding dark energy and dark matter, which scientists estimate make up about 95% of all the energy and matter in the universe but are still poorly understood.
I disagree with you Dan Breeden. In my openion AI WILL A BETTER FUTURE FOR HUMAN CIVILIZATION.
Doctors and engineers from Massachusetts General Hospital and MIT are trying to revolutionize cancer detection through an artificial intelligence program called Sybil. Their study found that Sybil could accurately predict whether a person will develop lung cancer in the next year up to 94 percent of the time. NBC News’ Dr. John Torres reports.
A team of New York University researchers has created a new way to visualize crystals by peering inside their structures, akin to having X-ray vision. Their new technique—which they aptly named “Crystal Clear”—combines the use of transparent particles and microscopes with lasers that allow scientists to see each unit that makes up the crystal and to create dynamic three-dimensional models.
עברית (Hebrew)
